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Population PK modelling and simulation based on fluoxetine and norfluoxetine concentrations in milk: a milk concentration-based prediction model.

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Tanoshima, Reo; Bournissen, Facundo Garcia; Tanigawara, Yusuke; Kristensen, Judith H; Taddio, Anna; Ilett, Kenneth F; Begg, Evan J; Wallach, Izhar; Ito, Shinya

2014-10-01

Population pharmacokinetic (pop PK) modelling can be used for PK assessment of drugs in breast milk. However, complex mechanistic modelling of a parent and an active metabolite using both blood and milk samples is challenging. We aimed to develop a simple predictive pop PK model for milk concentration-time profiles of a parent and a metabolite, using data on fluoxetine (FX) and its active metabolite, norfluoxetine (NFX), in milk. Using a previously published data set of drug concentrations in milk from 25 women treated with FX, a pop PK model predictive of milk concentration-time profiles of FX and NFX was developed. Simulation was performed with the model to generate FX and NFX concentration-time profiles in milk of 1000 mothers. This milk concentration-based pop PK model was compared with the previously validated plasma/milk concentration-based pop PK model of FX. Milk FX and NFX concentration-time profiles were described reasonably well by a one compartment model with a FX-to-NFX conversion coefficient. Median values of the simulated relative infant dose on a weight basis (sRID: weight-adjusted daily doses of FX and NFX through breastmilk to the infant, expressed as a fraction of therapeutic FX daily dose per body weight) were 0.028 for FX and 0.029 for NFX. The FX sRID estimates were consistent with those of the plasma/milk-based pop PK model. A predictive pop PK model based on only milk concentrations can be developed for simultaneous estimation of milk concentration-time profiles of a parent (FX) and an active metabolite (NFX). © 2014 The British Pharmacological Society.
Ratio-based vs. model-based methods to correct for urinary creatinine concentrations.

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Jain, Ram B

2016-08-01

Creatinine-corrected urinary analyte concentration is usually computed as the ratio of the observed level of analyte concentration divided by the observed level of the urinary creatinine concentration (UCR). This ratio-based method is flawed since it implicitly assumes that hydration is the only factor that affects urinary creatinine concentrations. On the contrary, it has been shown in the literature, that age, gender, race/ethnicity, and other factors also affect UCR. Consequently, an optimal method to correct for UCR should correct for hydration as well as other factors like age, gender, and race/ethnicity that affect UCR. Model-based creatinine correction in which observed UCRs are used as an independent variable in regression models has been proposed. This study was conducted to evaluate the performance of ratio-based and model-based creatinine correction methods when the effects of gender, age, and race/ethnicity are evaluated one factor at a time for selected urinary analytes and metabolites. It was observed that ratio-based method leads to statistically significant pairwise differences, for example, between males and females or between non-Hispanic whites (NHW) and non-Hispanic blacks (NHB), more often than the model-based method. However, depending upon the analyte of interest, the reverse is also possible. The estimated ratios of geometric means (GM), for example, male to female or NHW to NHB, were also compared for the two methods. When estimated UCRs were higher for the group (for example, males) in the numerator of this ratio, these ratios were higher for the model-based method, for example, male to female ratio of GMs. When estimated UCR were lower for the group (for example, NHW) in the numerator of this ratio, these ratios were higher for the ratio-based method, for example, NHW to NHB ratio of GMs. Model-based method is the method of choice if all factors that affect UCR are to be accounted for.
Ammonia concentration modeling based on retained gas sampler data

International Nuclear Information System (INIS)

Terrones, G.; Palmer, B.J.; Cuta, J.M.

1997-09-01

The vertical ammonia concentration distributions determined by the retained gas sampler (RGS) apparatus were modeled for double-shell tanks (DSTs) AW-101, AN-103, AN-104, and AN-105 and single-shell tanks (SSTs) A-101, S-106, and U-103. One the vertical transport of ammonia in the tanks were used for the modeling. Transport in the non-convective settled solids and floating solids layers is assumed to occur primarily via some type of diffusion process, while transport in the convective liquid layers is incorporated into the model via mass transfer coefficients based on empirical correlations. Mass transfer between the top of the waste and the tank headspace and the effects of ventilation of the headspace are also included in the models. The resulting models contain a large number of parameters, but many of them can be determined from known properties of the waste configuration or can be estimated within reasonable bounds from data on the waste samples themselves. The models are used to extract effective diffusion coefficients for transport in the nonconvective layers based on the measured values of ammonia from the RGS apparatus. The modeling indicates that the higher concentrations of ammonia seen in bubbles trapped inside the waste relative to the ammonia concentrations in the tank headspace can be explained by a combination of slow transport of ammonia via diffusion in the nonconvective layers and ventilation of the tank headspace by either passive or active means. Slow transport by diffusion causes a higher concentration of ammonia to build up deep within the waste until the concentration gradients between the interior and top of the waste are sufficient to allow ammonia to escape at the same rate at which it is being generated in the waste
Model methodology for estimating pesticide concentration extremes based on sparse monitoring data

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Vecchia, Aldo V.

2018-03-22

This report describes a new methodology for using sparse (weekly or less frequent observations) and potentially highly censored pesticide monitoring data to simulate daily pesticide concentrations and associated quantities used for acute and chronic exposure assessments, such as the annual maximum daily concentration. The new methodology is based on a statistical model that expresses log-transformed daily pesticide concentration in terms of a seasonal wave, flow-related variability, long-term trend, and serially correlated errors. Methods are described for estimating the model parameters, generating conditional simulations of daily pesticide concentration given sparse (weekly or less frequent) and potentially highly censored observations, and estimating concentration extremes based on the conditional simulations. The model can be applied to datasets with as few as 3 years of record, as few as 30 total observations, and as few as 10 uncensored observations. The model was applied to atrazine, carbaryl, chlorpyrifos, and fipronil data for U.S. Geological Survey pesticide sampling sites with sufficient data for applying the model. A total of 112 sites were analyzed for atrazine, 38 for carbaryl, 34 for chlorpyrifos, and 33 for fipronil. The results are summarized in this report; and, R functions, described in this report and provided in an accompanying model archive, can be used to fit the model parameters and generate conditional simulations of daily concentrations for use in investigations involving pesticide exposure risk and uncertainty.
MODELLING OF CONCENTRATION LIMITS BASED ON NEURAL NETWORKS.

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A. L. Osipov

2017-02-01

Full Text Available We study the forecasting model with the concentration limits is-the use of neural network technology. The software for the implementation of these models. It is shown that the efficiency of the system in the experimental material.
Modelling of marine base cation emissions, concentrations and deposition in the UK

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M. Werner

2011-02-01

Full Text Available Base cations exert a large impact on various geochemical and geophysical processes both in the atmosphere and at the Earth surface. One of the essential roles of these compounds is impact on surface pH causing an increase in alkalinity and neutralizing the effects of acidity generated by sulphur and nitrogen deposition. During recent years anthropogenic emissions of base cations in the UK have decreased substantially, by about 70%, 78%, 75% and 48% for Na⁺, Mg²⁺, Ca²⁺ and K⁺, respectively, over the period 1990–2006. For the island regions, such as the UK, the main source of base cation particles is the aerosol produced from the sea surface. Here, the sea salt aerosol (SSA emissions are calculated with parameterisations proposed by Mårtensson et al. (2003 for ultra fine particles, Monahan et al. (1986 for fine particles and Smith and Harisson (1998 for coarse particles continuously with a 0.1 μm size step using WRF-modelled wind speed data at a 5 km × 5 km grid square resolution with a 3 h time step for two selected years 2003 and 2006. SSA production has been converted into base cation emissions, with the assumption that the chemical composition of the particle emitted from the sea surface is equal to the chemical composition of sea water, and used as input data in the Fine Resolution Atmospheric Multi-pollutant Exchange Model (FRAME. FRAME model annual mean concentrations and total wet deposition at a 5 km × 5 km grid resolution, are compared with concentrations in air and wet deposition from the National Monitoring Network and measurements based estimates of UK deposition budget. The correlation coefficient for wet deposition achieves high values (R = 0.8 for Na⁺ and Mg²⁺, whereas for Ca²⁺ the correlation is poor (R < 0.3. Base cation concentrations are also represented well, with some overestimations on the west coast and underestimations in the
Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

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Yeganeh, B.; Motlagh, M. Shafie Pour; Rashidi, Y.; Kamalan, H.

2012-08-01

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS-SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS-SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65-85% for hybrid PLS-SVM model respectively. Also it was found that the hybrid PLS-SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS-SVM model.
TK Modeler version 1.0, a Microsoft® Excel®-based modeling software for the prediction of diurnal blood/plasma concentration for toxicokinetic use.

Science.gov (United States)

McCoy, Alene T; Bartels, Michael J; Rick, David L; Saghir, Shakil A

2012-07-01

TK Modeler 1.0 is a Microsoft® Excel®-based pharmacokinetic (PK) modeling program created to aid in the design of toxicokinetic (TK) studies. TK Modeler 1.0 predicts the diurnal blood/plasma concentrations of a test material after single, multiple bolus or dietary dosing using known PK information. Fluctuations in blood/plasma concentrations based on test material kinetics are calculated using one- or two-compartment PK model equations and the principle of superposition. This information can be utilized for the determination of appropriate dosing regimens based on reaching a specific desired C(max), maintaining steady-state blood/plasma concentrations, or other exposure target. This program can also aid in the selection of sampling times for accurate calculation of AUC(24h) (diurnal area under the blood concentration time curve) using sparse-sampling methodologies (one, two or three samples). This paper describes the construction, use and validation of TK Modeler. TK Modeler accurately predicted blood/plasma concentrations of test materials and provided optimal sampling times for the calculation of AUC(24h) with improved accuracy using sparse-sampling methods. TK Modeler is therefore a validated, unique and simple modeling program that can aid in the design of toxicokinetic studies. Copyright © 2012 Elsevier Inc. All rights reserved.
Application Study of Comprehensive Forecasting Model Based on Entropy Weighting Method on Trend of PM2.5 Concentration in Guangzhou, China

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Liu, Dong-jun; Li, Li

2015-01-01

For the issue of haze-fog, PM2.5 is the main influence factor of haze-fog pollution in China. The trend of PM2.5 concentration was analyzed from a qualitative point of view based on mathematical models and simulation in this study. The comprehensive forecasting model (CFM) was developed based on the combination forecasting ideas. Autoregressive Integrated Moving Average Model (ARIMA), Artificial Neural Networks (ANNs) model and Exponential Smoothing Method (ESM) were used to predict the time series data of PM2.5 concentration. The results of the comprehensive forecasting model were obtained by combining the results of three methods based on the weights from the Entropy Weighting Method. The trend of PM2.5 concentration in Guangzhou China was quantitatively forecasted based on the comprehensive forecasting model. The results were compared with those of three single models, and PM2.5 concentration values in the next ten days were predicted. The comprehensive forecasting model balanced the deviation of each single prediction method, and had better applicability. It broadens a new prediction method for the air quality forecasting field. PMID:26110332
Prediction of Dissolved Gas Concentrations in Transformer Oil Based on the KPCA-FFOA-GRNN Model

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Jun Lin

2018-01-01

Full Text Available The purpose of analyzing the dissolved gas in transformer oil is to determine the transformer’s operating status and is an important basis for fault diagnosis. Accurate prediction of the concentration of dissolved gas in oil can provide an important reference for the evaluation of the state of the transformer. A combined predicting model is proposed based on kernel principal component analysis (KPCA and a generalized regression neural network (GRNN using an improved fruit fly optimization algorithm (FFOA to select the smooth factor. Firstly, based on the idea of using the dissolved gas ratio of oil to diagnose the transformer fault, gas concentration ratios are also used as characteristic parameters. Secondly, the main parameters are selected from the feature parameters using the KPCA method, and the GRNN is then used to predict the gas concentration in the transformer oil. In the training process of the network, the FFOA is used to select the smooth factor of the neural network. Through a concrete example, it is shown that the method proposed in this paper has better data fitting ability and more accurate prediction ability compared with the support vector machine (SVM and gray model (GM methods.
Food chain model to predict westslope cutthroat trout ovary selenium concentrations from water concentrations in the Elk Valley, BC

International Nuclear Information System (INIS)

Orr, P.; Wiramanaden, C.; Franklin, W.; Fraser, C.

2010-01-01

The 5 coal mines operated by Teck Coal Ltd. in British Columbia's Elk River watershed release selenium during weathering of mine waste rock. Since 1966, several field studies have been conducted in which selenium concentrations in biota were measured. They revealed that tissue concentrations are higher in aquatic biota sampled in lentic compared to lotic habitats of the watershed with similar water selenium concentrations. Two food chain models were developed based on the available data. The models described dietary selenium accumulation in the ovaries of lotic versus lentic westslope cutthroat trout (WCT), a valued aquatic resource in the Elk River system. The following 3 trophic transfer relationships were characterized for each model: (1) water to base of the food web, (2) base of the food web to benthic invertebrates, and (3) benthic invertebrates to WCT ovaries. The lotic and lentic models combined the resulting equations for each trophic transfer relationships to predict WCT ovary concentrations from water concentrations. The models were in very good agreement with the available data, despite fish movement and the fact that composite benthic invertebrate sample data were only an approximation of the feeding preferences of individual fish. Based on the observed rates of increase in water selenium concentrations throughout the watershed, the models predicted very small/slow increases in WCT ovary concentrations with time.
Post-dialysis urea concentration: comparison between one- compartment model and two-compartment model

International Nuclear Information System (INIS)

Tamrin, N S Ahmad; Ibrahim, N

2014-01-01

The reduction of the urea concentration in blood can be numerically projected by using one-compartment model and two-compartment model with no variation in body fluid. This study aims to compare the simulated values of post-dialysis urea concentration for both models with the clinical data obtained from the hospital. The clinical assessment of adequacy of a treatment is based on the value of Kt/V. Further, direct calculation using clinical data and one-compartment model are presented in the form of ratio. It is found that the ratios of postdialysis urea concentration simulated using two-compartment model are higher compared to the ratios of post-dialysis urea concentration using one-compartment model. In addition, most values of post-dialysis urea concentration simulated using two-compartment model are much closer to the clinical data compared to values simulated using one-compartment model. Kt/V values calculated directly using clinical data are found to be higher than Kt/V values derived from one-compartment model
A model to secure a stable iodine concentration in milk

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Gisken Trøan

2015-12-01

Full Text Available Background: Dairy products account for approximately 60% of the iodine intake in the Norwegian population. The iodine concentration in cow's milk varies considerably, depending on feeding practices, season, and amount of iodine and rapeseed products in cow fodder. The variation in iodine in milk affects the risk of iodine deficiency or excess in the population. Objective: The first goal of this study was to develop a model to predict the iodine concentration in milk based on the concentration of iodine and rapeseed or glucosinolate in feed, as a tool to securing stable iodine concentration in milk. A second aim was to estimate the impact of different iodine levels in milk on iodine nutrition in the Norwegian population. Design: Two models were developed on the basis of results from eight published and two unpublished studies from the past 20 years. The models were based on different iodine concentrations in the fodder combined with either glucosinolate (Model 1 or rapeseed cake/meal (Model 2. To illustrate the impact of different iodine concentrations in milk on iodine intake, we simulated the iodine contribution from dairy products in different population groups based on food intake data in the most recent dietary surveys in Norway. Results: The models developed could predict iodine concentration in milk. Cross-validation showed good fit and confirmed the explanatory power of the models. Our calculations showed that dairy products with current iodine level in milk (200 µg/kg cover 68, 49, 108 and 56% of the daily iodine requirements for men, women, 2-year-old children, and pregnant women, respectively. Conclusions: Securing a stable level of iodine in milk by adjusting iodine concentration in different cow feeds is thus important for preventing excess intake in small children and iodine deficiency in pregnant and non-pregnant women.
Uncertainties in neural network model based on carbon dioxide concentration for occupancy estimation

Energy Technology Data Exchange (ETDEWEB)

Alam, Azimil Gani; Rahman, Haolia; Kim, Jung-Kyung; Han, Hwataik [Kookmin University, Seoul (Korea, Republic of)

2017-05-15

Demand control ventilation is employed to save energy by adjusting airflow rate according to the ventilation load of a building. This paper investigates a method for occupancy estimation by using a dynamic neural network model based on carbon dioxide concentration in an occupied zone. The method can be applied to most commercial and residential buildings where human effluents to be ventilated. An indoor simulation program CONTAMW is used to generate indoor CO{sub 2} data corresponding to various occupancy schedules and airflow patterns to train neural network models. Coefficients of variation are obtained depending on the complexities of the physical parameters as well as the system parameters of neural networks, such as the numbers of hidden neurons and tapped delay lines. We intend to identify the uncertainties caused by the model parameters themselves, by excluding uncertainties in input data inherent in measurement. Our results show estimation accuracy is highly influenced by the frequency of occupancy variation but not significantly influenced by fluctuation in the airflow rate. Furthermore, we discuss the applicability and validity of the present method based on passive environmental conditions for estimating occupancy in a room from the viewpoint of demand control ventilation applications.
Site effect classification based on microtremor data analysis using concentration-area fractal model

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Adib, A.; Afzal, P.; Heydarzadeh, K.

2014-07-01

The aim of this study is to classify the site effect using concentration-area (C-A) fractal model in Meybod city, Central Iran, based on microtremor data analysis. Log-log plots of the frequency, amplification and vulnerability index (k-g) indicate a multifractal nature for the parameters in the area. The results obtained from the C-A fractal modeling reveal that proper soil types are located around the central city. The results derived via the fractal modeling were utilized to improve the Nogoshi's classification results in the Meybod city. The resulted categories are: (1) hard soil and weak rock with frequency of 6.2 to 8 Hz, (2) stiff soil with frequency of about 4.9 to 6.2 Hz, (3) moderately soft soil with the frequency of 2.4 to 4.9 Hz, and (4) soft soil with the frequency lower than 2.4 Hz.
An isotherm-based thermodynamic model of multicomponent aqueous solutions, applicable over the entire concentration range.

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Dutcher, Cari S; Ge, Xinlei; Wexler, Anthony S; Clegg, Simon L

2013-04-18

In previous studies (Dutcher et al. J. Phys. Chem. C 2011, 115, 16474-16487; 2012, 116, 1850-1864), we derived equations for the Gibbs energy, solvent and solute activities, and solute concentrations in multicomponent liquid mixtures, based upon expressions for adsorption isotherms that include arbitrary numbers of hydration layers on each solute. In this work, the long-range electrostatic interactions that dominate in dilute solutions are added to the Gibbs energy expression, thus extending the range of concentrations for which the model can be used from pure liquid solute(s) to infinite dilution in the solvent, water. An equation for the conversion of the reference state for solute activity coefficients to infinite dilution in water has been derived. A number of simplifications are identified, notably the equivalence of the sorption site parameters r and the stoichiometric coefficients of the solutes, resulting in a reduction in the number of model parameters. Solute concentrations in mixtures conform to a modified Zdanovskii-Stokes-Robinson mixing rule, and solute activity coefficients to a modified McKay-Perring relation, when the effects of the long-range (Debye-Hückel) term in the equations are taken into account. Practical applications of the equations to osmotic and activity coefficients of pure aqueous electrolyte solutions and mixtures show both satisfactory accuracy from low to high concentrations, together with a thermodynamically reasonable extrapolation (beyond the range of measurements) to extreme concentration and to the pure liquid solute(s).
Modeled atmospheric radon concentrations from uranium mines

Energy Technology Data Exchange (ETDEWEB)

Droppo, J.G.

1985-04-01

Uranium mining and milling operations result in the release of radon from numerous sources of various types and strengths. The US Environmental Protection Agency (EPA) under the Clean Air Act, is assessing the health impact of air emissions of radon from underground uranium mines. In this case, the radon emissions may impact workers and residents in the mine vicinity. To aid in this assessment, the EPA needs to know how mine releases can affect the radon concentrations at populated locations. To obtain this type of information, Pacific Northwest Laboratory used the radon emissions, release characteristics and local meterological conditions for a number of mines to model incremental radon concentrations. Long-term, average, incremental radon concentrations were computed based on the best available information on release rates, plume rise parameters, number and locations of vents, and local dispersion climatology. Calculations are made for a model mine, individual mines, and multiple mines. Our approach was to start with a general case and then consider specific cases for comparison. A model underground uranium mine was used to provide definition of the order of magnitude of typical impacts. Then computations were made for specific mines using the best mine-specific information available for each mine. These case study results are expressed as predicted incremental radon concentration contours plotted on maps with local population data from a previous study. Finally, the effect of possible overlap of radon releases from nearby mines was studied by calculating cumulative radon concentrations for multiple mines in a region with many mines. The dispersion model, modeling assumptions, data sources, computational procedures, and results are documented in this report. 7 refs., 27 figs., 18 tabs.
Modeled atmospheric radon concentrations from uranium mines

International Nuclear Information System (INIS)

Droppo, J.G.

1985-04-01

Uranium mining and milling operations result in the release of radon from numerous sources of various types and strengths. The US Environmental Protection Agency (EPA) under the Clean Air Act, is assessing the health impact of air emissions of radon from underground uranium mines. In this case, the radon emissions may impact workers and residents in the mine vicinity. To aid in this assessment, the EPA needs to know how mine releases can affect the radon concentrations at populated locations. To obtain this type of information, Pacific Northwest Laboratory used the radon emissions, release characteristics and local meterological conditions for a number of mines to model incremental radon concentrations. Long-term, average, incremental radon concentrations were computed based on the best available information on release rates, plume rise parameters, number and locations of vents, and local dispersion climatology. Calculations are made for a model mine, individual mines, and multiple mines. Our approach was to start with a general case and then consider specific cases for comparison. A model underground uranium mine was used to provide definition of the order of magnitude of typical impacts. Then computations were made for specific mines using the best mine-specific information available for each mine. These case study results are expressed as predicted incremental radon concentration contours plotted on maps with local population data from a previous study. Finally, the effect of possible overlap of radon releases from nearby mines was studied by calculating cumulative radon concentrations for multiple mines in a region with many mines. The dispersion model, modeling assumptions, data sources, computational procedures, and results are documented in this report. 7 refs., 27 figs., 18 tabs
Development and evaluation of a regression-based model to predict cesium-137 concentration ratios for saltwater fish

International Nuclear Information System (INIS)

Pinder, John E.; Rowan, David J.; Smith, Jim T.

2016-01-01

Data from published studies and World Wide Web sources were combined to develop a regression model to predict "1"3"7Cs concentration ratios for saltwater fish. Predictions were developed from 1) numeric trophic levels computed primarily from random resampling of known food items and 2) K concentrations in the saltwater for 65 samplings from 41 different species from both the Atlantic and Pacific Oceans. A number of different models were initially developed and evaluated for accuracy which was assessed as the ratios of independently measured concentration ratios to those predicted by the model. In contrast to freshwater systems, were K concentrations are highly variable and are an important factor in affecting fish concentration ratios, the less variable K concentrations in saltwater were relatively unimportant in affecting concentration ratios. As a result, the simplest model, which used only trophic level as a predictor, had comparable accuracies to more complex models that also included K concentrations. A test of model accuracy involving comparisons of 56 published concentration ratios from 51 species of marine fish to those predicted by the model indicated that 52 of the predicted concentration ratios were within a factor of 2 of the observed concentration ratios. - Highlights: • We developed a model to predict concentration ratios (C_r) for saltwater fish. • The model requires only a single input variable to predict C_r. • That variable is a mean numeric trophic level available at (fishbase.org). • The K concentrations in seawater were not an important predictor variable. • The median-to observed ratio for 56 independently measured C_r was 0.83.
State-of-the-art report on the theoretical modeling of interfacial area concentration

International Nuclear Information System (INIS)

Lee, Won Jae; Euh, Dong Jin

1998-03-01

Classical approaches based on experimental correlations and the mechanistic approaches based on the interfacial area concentration were reviewed. The study focuses on the state-of-the-art researches based on the mechanistic modeling of the interfacial area concentration. The investigation is performed by classifying the mechanistic modeling approaches into those using the number density transport equations supported with a simple algebraic relation for obtaining interfacial area concentration and those using the direct interfacial area transport equations. The modeling approaches are subdivided into one group and multi-group models. The state-of-the-art source terms of transport equations are also investigated for their applicability and limitations. (author). 62 refs., 6 tabs., 49 figs

Site effect classification based on microtremor data analysis using a concentration-area fractal model

Science.gov (United States)

Adib, A.; Afzal, P.; Heydarzadeh, K.

2015-01-01

The aim of this study is to classify the site effect using concentration-area (C-A) fractal model in Meybod city, central Iran, based on microtremor data analysis. Log-log plots of the frequency, amplification and vulnerability index (k-g) indicate a multifractal nature for the parameters in the area. The results obtained from the C-A fractal modelling reveal that proper soil types are located around the central city. The results derived via the fractal modelling were utilized to improve the Nogoshi and Igarashi (1970, 1971) classification results in the Meybod city. The resulting categories are: (1) hard soil and weak rock with frequency of 6.2 to 8 Hz, (2) stiff soil with frequency of about 4.9 to 6.2 Hz, (3) moderately soft soil with the frequency of 2.4 to 4.9 Hz, and (4) soft soil with the frequency lower than 2.4 Hz.
Diffusion dynamics and concentration of toxic materials from quantum dots-based nanotechnologies: an agent-based modeling simulation framework

Energy Technology Data Exchange (ETDEWEB)

Agusdinata, Datu Buyung, E-mail: bagusdinata@niu.edu; Amouie, Mahbod [Northern Illinois University, Department of Industrial & Systems Engineering and Environment, Sustainability, & Energy Institute (United States); Xu, Tao [Northern Illinois University, Department of Chemistry and Biochemistry (United States)

2015-01-15

Due to their favorable electrical and optical properties, quantum dots (QDs) nanostructures have found numerous applications including nanomedicine and photovoltaic cells. However, increased future production, use, and disposal of engineered QD products also raise concerns about their potential environmental impacts. The objective of this work is to establish a modeling framework for predicting the diffusion dynamics and concentration of toxic materials released from Trioctylphosphine oxide-capped CdSe. To this end, an agent-based model simulation with reaction kinetics and Brownian motion dynamics was developed. Reaction kinetics is used to model the stability of surface capping agent particularly due to oxidation process. The diffusion of toxic Cd{sup 2+} ions in aquatic environment was simulated using an adapted Brownian motion algorithm. A calibrated parameter to reflect sensitivity to reaction rate is proposed. The model output demonstrates the stochastic spatial distribution of toxic Cd{sup 2+} ions under different values of proxy environmental factor parameters. With the only chemistry considered was oxidation, the simulation was able to replicate Cd{sup 2+} ion release from Thiol-capped QDs in aerated water. The agent-based method is the first to be developed in the QDs application domain. It adds both simplicity of the solubility and rate of release of Cd{sup 2+} ions and complexity of tracking of individual atoms of Cd at the same time.
Diffusion dynamics and concentration of toxic materials from quantum dots-based nanotechnologies: an agent-based modeling simulation framework

International Nuclear Information System (INIS)

Agusdinata, Datu Buyung; Amouie, Mahbod; Xu, Tao

2015-01-01

Due to their favorable electrical and optical properties, quantum dots (QDs) nanostructures have found numerous applications including nanomedicine and photovoltaic cells. However, increased future production, use, and disposal of engineered QD products also raise concerns about their potential environmental impacts. The objective of this work is to establish a modeling framework for predicting the diffusion dynamics and concentration of toxic materials released from Trioctylphosphine oxide-capped CdSe. To this end, an agent-based model simulation with reaction kinetics and Brownian motion dynamics was developed. Reaction kinetics is used to model the stability of surface capping agent particularly due to oxidation process. The diffusion of toxic Cd 2+ ions in aquatic environment was simulated using an adapted Brownian motion algorithm. A calibrated parameter to reflect sensitivity to reaction rate is proposed. The model output demonstrates the stochastic spatial distribution of toxic Cd 2+ ions under different values of proxy environmental factor parameters. With the only chemistry considered was oxidation, the simulation was able to replicate Cd 2+ ion release from Thiol-capped QDs in aerated water. The agent-based method is the first to be developed in the QDs application domain. It adds both simplicity of the solubility and rate of release of Cd 2+ ions and complexity of tracking of individual atoms of Cd at the same time
Modeling and prototyping of a flux concentrator for positron capture

International Nuclear Information System (INIS)

Liu, W.; Gai, W.; Wang, H.; Wong, T.

2008-01-01

An adiabatic matching device (AMD) generates a tapered high-strength magnetic field to capture positrons emitted from a positron target to a downstream accelerating structure. The AMD is a key component of a positron source and represents a technical challenge. The International Linear Collider collaboration is proposing to employ a pulsed, normal-conducting, flux-concentrator to generate a 5 Tesla initial magnetic field. The flux-concentrator structure itself and the interactions between the flux-concentrator and the external power supply circuits give rise to a nontrivial system. In this paper, we present a recently developed equivalent circuit model for a flux concentrator, along with the characteristics of a prototype fabricated for validating the model. Using the model, we can obtain the transient response of the pulsed magnetic field and the field profile. Calculations based on the model and the results of measurements made on the prototype are in good agreement.
Modeling sediment concentration of rill flow

Science.gov (United States)

Yang, Daming; Gao, Peiling; Zhao, Yadong; Zhang, Yuhang; Liu, Xiaoyuan; Zhang, Qingwen

2018-06-01

Accurate estimation of sediment concentration is essential to establish physically-based erosion models. The objectives of this study were to evaluate the effects of flow discharge (Q), slope gradient (S), flow velocity (V), shear stress (τ), stream power (ω) and unit stream power (U) on sediment concentration. Laboratory experiments were conducted using a 10 × 0.1 m rill flume under four flow discharges (2, 4, 8 and 16 L min-1), and five slope gradients (5°, 10°, 15°, 20° and 25°). The results showed that the measured sediment concentration varied from 87.08 to 620.80 kg m-3 with a mean value of 343.13 kg m-3. Sediment concentration increased as a power function with flow discharge and slope gradient, with R2 = 0.975 and NSE = 0.945. The sediment concentration was more sensitive to slope gradient than to flow discharge. The sediment concentration was well predicted by unit stream power (R2 = 0.937, NSE = 0.865), whereas less satisfactorily by flow velocity (R2 = 0.470, NSE = 0.539) and stream power (R2 = 0.773, NSE = 0.732). In addition, using the equations to simulate the measured sediment concentration of other studies, the result further indicated that slope gradient, flow discharge and unit stream power were good predictors of sediment concentration. In general, slope gradient, flow discharge and unit stream power seem to be the preferred predictors for estimating sediment concentration.
A Concentrator Photovoltaic System Based on a Combination of Prism-Compound Parabolic Concentrators

Directory of Open Access Journals (Sweden)

Ngoc Hai Vu

2016-08-01

Full Text Available We present a cost-effective concentrating photovoltaic system composed of a prism and a compound parabolic concentrator (P-CPC. In this approach, the primary collector consists of a prism, a solid compound parabolic concentrator (CPC, and a slab waveguide. The prism, which is placed on the input aperture of CPC, directs the incoming sunlight beam to be parallel with the main axes of parabolic rims of CPC. Then, the sunlight is reflected at the parabolic rims and concentrated at the focal point of these parabolas. A slab waveguide is coupled at the output aperture of the CPC to collect focused sunlight beams and to guide them to the solar cell. The optical system was modeled and simulated with commercial ray tracing software (LightTools™. Simulation results show that the optical efficiency of a P-CPC can achieve up to 89%. when the concentration ratio of the P-CPC is fixed at 50. We also determine an optimal geometric structure of P-CPC based on simulation. Because of the simplicity of the P-CPC structure, a lower-cost mass production process is possible. A simulation based on optimal structure of P-CPC was performed and the results also shown that P-CPC has high angular tolerance for input sunlight. The high tolerance of the input angle of sunlight allows P-CPC solar concentrator utilize a single sun tracking system instead of a highly precise dual suntracking system as cost effective solution.
COMPLEX OF NUMERICAL MODELS FOR COMPUTATION OF AIR ION CONCENTRATION IN PREMISES

Directory of Open Access Journals (Sweden)

M. M. Biliaiev

2016-04-01

Full Text Available Purpose. The article highlights the question about creation the complex numerical models in order to calculate the ions concentration fields in premises of various purpose and in work areas. Developed complex should take into account the main physical factors influencing the formation of the concentration field of ions, that is, aerodynamics of air jets in the room, presence of furniture, equipment, placement of ventilation holes, ventilation mode, location of ionization sources, transfer of ions under the electric field effect, other factors, determining the intensity and shape of the field of concentration of ions. In addition, complex of numerical models has to ensure conducting of the express calculation of the ions concentration in the premises, allowing quick sorting of possible variants and enabling «enlarged» evaluation of air ions concentration in the premises. Methodology. The complex numerical models to calculate air ion regime in the premises is developed. CFD numerical model is based on the use of aerodynamics, electrostatics and mass transfer equations, and takes into account the effect of air flows caused by the ventilation operation, diffusion, electric field effects, as well as the interaction of different polarities ions with each other and with the dust particles. The proposed balance model for computation of air ion regime indoors allows operative calculating the ions concentration field considering pulsed operation of the ionizer. Findings. The calculated data are received, on the basis of which one can estimate the ions concentration anywhere in the premises with artificial air ionization. An example of calculating the negative ions concentration on the basis of the CFD numerical model in the premises with reengineering transformations is given. On the basis of the developed balance model the air ions concentration in the room volume was calculated. Originality. Results of the air ion regime computation in premise, which
MLP based models to predict PM10, O3 concentrations, in Sines industrial area

Science.gov (United States)

Durao, R.; Pereira, M. J.

2012-04-01

Sines is an important Portuguese industrial area located southwest cost of Portugal with important nearby protected natural areas. The main economical activities are related with this industrial area, the deep-water port, petrochemical and thermo-electric industry. Nevertheless, tourism is also an important economic activity especially in summer time with potential to grow. The aim of this study is to develop prediction models of pollutant concentration categories (e.g. low concentration and high concentration) in order to provide early warnings to the competent authorities who are responsible for the air quality management. The knowledge in advanced of pollutant high concentrations occurrence will allow the implementation of mitigation actions and the release of precautionary alerts to population. The regional air quality monitoring network consists in three monitoring stations where a set of pollutants' concentrations are registered on a continuous basis. From this set stands out the tropospheric ozone (O3) and particulate matter (PM10) due to the high concentrations occurring in the region and their adverse effects on human health. Moreover, the major industrial plants of the region monitor SO2, NO2 and particles emitted flows at the principal chimneys (point sources), also on a continuous basis,. Therefore Artificial neuronal networks (ANN) were the applied methodology to predict next day pollutant concentrations; due to the ANNs structure they have the ability to capture the non-linear relationships between predictor variables. Hence the first step of this study was to apply multivariate exploratory techniques to select the best predictor variables. The classification trees methodology (CART) was revealed to be the most appropriate in this case.. Results shown that pollutants atmospheric concentrations are mainly dependent on industrial emissions and a complex combination of meteorological factors and the time of the year. In the second step, the Multi
A dynamic model to calculate cadmium concentrations in bovine tissues from basic soil characteristics

International Nuclear Information System (INIS)

Waegeneers, Nadia; Ruttens, Ann; De Temmerman, Ludwig

2011-01-01

A chain model was developed to calculate the flow of cadmium from soil, drinking water and feed towards bovine tissues. The data used for model development were tissue Cd concentrations of 57 bovines and Cd concentrations in soil, feed and drinking water, sampled at the farms were the bovines were reared. Validation of the model occurred with a second set of measured tissue Cd concentrations of 93 bovines of which age and farm location were known. The exposure part of the chain model consists of two parts: (1) a soil-plant transfer model, deriving cadmium concentrations in feed from basic soil characteristics (pH and organic matter content) and soil Cd concentrations, and (2) bovine intake calculations, based on typical feed and water consumption patterns for cattle and Cd concentrations in feed and drinking water. The output of the exposure model is an animal-specific average daily Cd intake, which is then taken forward to a kinetic uptake model in which time-dependent Cd concentrations in bovine tissues are calculated. The chain model was able to account for 65%, 42% and 32% of the variation in observed kidney, liver and meat Cd concentrations in the validation study. - Research highlights: → Cadmium transfer from soil, drinking water and feed to bovine tissues was modeled. → The model was based on 57 bovines and corresponding feed and soil Cd concentrations. → The model was validated with an independent data set of 93 bovines. → The model explained 65% of variation in kidney Cd in the validation study.
Sorption kinetics and microbial biodegradation activity of hydrophobic chemicals in sewage sludge: Model and measurements based on free concentrations

NARCIS (Netherlands)

Artola-Garicano, E.; Borkent, I.; Damen, K.; Jager, T.; Vaes, W.H.J.

2003-01-01

In the current study, a new method is introduced with which the rate-limiting factor of biodegradation processes of hydrophobic chemicals in organic and aqueous systems can be determined. The novelty of this approach lies in the combination of a free concentration-based kinetic model with
Modeling of surface dust concentrations using neural networks and kriging

Science.gov (United States)

Buevich, Alexander G.; Medvedev, Alexander N.; Sergeev, Alexander P.; Tarasov, Dmitry A.; Shichkin, Andrey V.; Sergeeva, Marina V.; Atanasova, T. B.

2016-12-01

Creating models which are able to accurately predict the distribution of pollutants based on a limited set of input data is an important task in environmental studies. In the paper two neural approaches: (multilayer perceptron (MLP)) and generalized regression neural network (GRNN)), and two geostatistical approaches: (kriging and cokriging), are using for modeling and forecasting of dust concentrations in snow cover. The area of study is under the influence of dust emissions from a copper quarry and a several industrial companies. The comparison of two mentioned approaches is conducted. Three indices are used as the indicators of the models accuracy: the mean absolute error (MAE), root mean square error (RMSE) and relative root mean square error (RRMSE). Models based on artificial neural networks (ANN) have shown better accuracy. When considering all indices, the most precision model was the GRNN, which uses as input parameters for modeling the coordinates of sampling points and the distance to the probable emissions source. The results of work confirm that trained ANN may be more suitable tool for modeling of dust concentrations in snow cover.
Generic Modelling of Faecal Indicator Organism Concentrations in the UK

Directory of Open Access Journals (Sweden)

Carl M. Stapleton

2011-06-01

Full Text Available To meet European Water Framework Directive requirements, data are needed on faecal indicator organism (FIO concentrations in rivers to enable the more heavily polluted to be targeted for remedial action. Due to the paucity of FIO data for the UK, especially under high-flow hydrograph event conditions, there is an urgent need by the policy community for generic models that can accurately predict FIO concentrations, thus informing integrated catchment management programmes. This paper reports the development of regression models to predict base- and high-flow faecal coliform (FC and enterococci (EN concentrations for 153 monitoring points across 14 UK catchments, using land cover, population (human and livestock density and other variables that may affect FIO source strength, transport and die-off. Statistically significant models were developed for both FC and EN, with greater explained variance achieved in the high-flow models. Both land cover and, in particular, population variables are significant predictors of FIO concentrations, with r2 maxima for EN of 0.571 and 0.624, respectively. It is argued that the resulting models can be applied, with confidence, to other UK catchments, both to predict FIO concentrations in unmonitored watercourses and evaluate the likely impact of different land use/stocking level and human population change scenarios.
Influence of ventilation strategies on indoor radon concentrations based on a semiempirical model for Florida-style houses

International Nuclear Information System (INIS)

Hintenlang, D.E.; Al-Ahmady, K.K.

1994-01-01

Measurements in a full-scale experimental facility are used to benchmark a semiempirical model for predicting indoor radon concentrations for Florida-style houses built using slab-on-grade construction. The model is developed to provide time-averaged indoor radon concentrations from quantitative relationships between the time-dependent radon entry and elimination mechanisms that have been demonstrated to be important for this style of residential construction. The model successfully predicts indoor radon concentrations in the research structure for several pressure and ventilation conditions. Parametric studies using the model illustrate how different ventilation strategies affect indoor radon concentrations. It is demonstrated that increasing house ventilation rates by increasing the effective leakage area of the house shell does not reduce indoor radon concentrations as effectively as increasing house ventilation rates by controlled duct ventilation associated with the heating, ventilating, and air conditioning system. The latter strategy provides the potential to minimize indoor radon concentrations while providing positive control over the quality of infiltration air. 9 refs., 5 figs
Modelling concentrations of decamethylcyclopentasiloxane in two UK rivers using LF2000-WQX

International Nuclear Information System (INIS)

Price, Oliver R.; Williams, Richard J.; Zhang, Zhong; Egmond, Roger van

2010-01-01

Current regulatory environmental exposure assessments for decamethylcyclopentasiloxane (D 5 ), used in a range of personal care products, are based on a number of erroneous assumptions. Using an estimated D 5 flux to waste water of 11.6 mg cap -1 d -1 , a 95.2% removal rate in Sewage Treatment Plants (STP) and a dilution factor of 10 results in modelled surface water concentrations that are up to an order of magnitude higher than concentrations observed downstream of STPs in two UK rivers. A GIS-based water quality model (LF2000-WQX) was used to predict concentrations of D 5 in two UK rivers. Assuming the STP removal rate is reasonable, a waste water flux of 2.4 mg cap -1 d -1 is needed in order to obtain a reasonable match between predicted and observed in-river concentrations. This flux is consistent with measured effluent concentrations. The results highlight major uncertainties in estimating chemical emission rates for volatile chemicals used in personal care products and suggest that measured concentrations in waste water are needed to refine exposure assessments. - Surface water modelling of decamethylcyclopentasiloxane.
Modelling concentrations of decamethylcyclopentasiloxane in two UK rivers using LF2000-WQX

Energy Technology Data Exchange (ETDEWEB)

Price, Oliver R., E-mail: oliver.price@unilever.co [Safety and Environmental Assurance Centre (SEAC), Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ (United Kingdom); Williams, Richard J.; Zhang, Zhong [Centre for Ecology and Hydrology, Crowmarsh Gifford, Wallingford, Oxfordshire OX10 8BB (United Kingdom); Egmond, Roger van [Safety and Environmental Assurance Centre (SEAC), Unilever, Colworth Science Park, Sharnbrook, Bedfordshire MK44 1LQ (United Kingdom)

2010-02-15

Current regulatory environmental exposure assessments for decamethylcyclopentasiloxane (D{sub 5}), used in a range of personal care products, are based on a number of erroneous assumptions. Using an estimated D{sub 5} flux to waste water of 11.6 mg cap{sup -1} d{sup -1}, a 95.2% removal rate in Sewage Treatment Plants (STP) and a dilution factor of 10 results in modelled surface water concentrations that are up to an order of magnitude higher than concentrations observed downstream of STPs in two UK rivers. A GIS-based water quality model (LF2000-WQX) was used to predict concentrations of D{sub 5} in two UK rivers. Assuming the STP removal rate is reasonable, a waste water flux of 2.4 mg cap{sup -1} d{sup -1} is needed in order to obtain a reasonable match between predicted and observed in-river concentrations. This flux is consistent with measured effluent concentrations. The results highlight major uncertainties in estimating chemical emission rates for volatile chemicals used in personal care products and suggest that measured concentrations in waste water are needed to refine exposure assessments. - Surface water modelling of decamethylcyclopentasiloxane.
Scientific white paper on concentration-QTc modeling.

Science.gov (United States)

Garnett, Christine; Bonate, Peter L; Dang, Qianyu; Ferber, Georg; Huang, Dalong; Liu, Jiang; Mehrotra, Devan; Riley, Steve; Sager, Philip; Tornoe, Christoffer; Wang, Yaning

2018-06-01

The International Council for Harmonisation revised the E14 guideline through the questions and answers process to allow concentration-QTc (C-QTc) modeling to be used as the primary analysis for assessing the QTc interval prolongation risk of new drugs. A well-designed and conducted QTc assessment based on C-QTc modeling in early phase 1 studies can be an alternative approach to a thorough QT study for some drugs to reliably exclude clinically relevant QTc effects. This white paper provides recommendations on how to plan and conduct a definitive QTc assessment of a drug using C-QTc modeling in early phase clinical pharmacology and thorough QT studies. Topics included are: important study design features in a phase 1 study; modeling objectives and approach; exploratory plots; the pre-specified linear mixed effects model; general principles for model development and evaluation; and expectations for modeling analysis plans and reports. The recommendations are based on current best modeling practices, scientific literature and personal experiences of the authors. These recommendations are expected to evolve as their implementation during drug development provides additional data and with advances in analytical methodology.
An electrical circuit model for simulation of indoor radon concentration.

Science.gov (United States)

Musavi Nasab, S M; Negarestani, A

2013-01-01

In this study, a new model based on electric circuit theory was introduced to simulate the behaviour of indoor radon concentration. In this model, a voltage source simulates radon generation in walls, conductivity simulates migration through walls and voltage across a capacitor simulates radon concentration in a room. This simulation considers migration of radon through walls by diffusion mechanism in one-dimensional geometry. Data reported in a typical Greek house were employed to examine the application of this technique of simulation to the behaviour of radon.
A Three-Dimensional Radiation Transfer Model to Evaluate Performance of Compound Parabolic Concentrator-Based Photovoltaic Systems

Directory of Open Access Journals (Sweden)

Jingjing Tang

2018-04-01

Full Text Available In the past, two-dimensional radiation transfer models (2-D models were widely used to investigate the optical performance of linear compound parabolic concentrators (CPCs, in which the radiation transfer on the cross-section of CPC troughs is considered. However, the photovoltaic efficiency of solar cells depends on the real incidence angle instead of the projection incidence angle, thus 2-D models can’t reasonably evaluate the photovoltaic performance of CPC-based photovoltaic systems (CPVs. In this work, three-dimensional radiation transfer (3-D model within CPC-θa/θe, the CPC with a maximum exit angle θe for radiation within its acceptance angle (θa, is investigated by means of vector algebra, solar geometry and imaging principle of plane mirror, and effects of geometry of CPV-θa/θe on its annual electricity generation are studied. Analysis shows that, as compared to similar photovoltaic (PV panels, the use of CPCs makes the incident angle of solar rays on solar cells increase thus lowers the photovoltaic conversion efficiency of solar cells. Calculations show that, 2-D models can reasonably predict the optical performance of CPVs, but such models always overestimate the photovoltaic performance of CPVs, and even can’t predict the variation trend of annual power output of CPV-θa/θe with θe. Results show that, for full CPV-θa/θe with a given θa, the annual power output increases with θe first and then comes to a halt as θe > 83°, whereas for truncated CPV-θa/θe with a given geometric concentration (Ct, the annual power output decreases with θe.
Linear stochastic models for forecasting daily maxima and hourly concentrations of air pollutants

Energy Technology Data Exchange (ETDEWEB)

McCollister, G M; Wilson, K R

1975-04-01

Two related time series models were developed to forecast concentrations of various air pollutants and tested on carbon monoxide and oxidant data for the Los Angeles basin. One model forecasts daily maximum concentrations of a particular pollutant using only past daily maximum values of that pollutant as input. The other model forecasts 1 hr average concentrations using only the past hourly average values. Both are significantly more accurate than persistence, i.e., forecasting for tomorrow what occurred today (or yesterday). Model forecasts for 1972 of the daily instantaneous maxima for total oxidant made using only past pollutant concentration data are more accurate than those made by the Los Angeles APCD using meteorological input as well as pollutant concentrations. Although none of these models forecast as accurately as might be desired for a health warning system, the relative success of simple time series models, even though based solely on pollutant concentration, suggests that models incorporating meteorological data and using either multi-dimensional times series or pattern recognition techniques should be tested.
Numerical modelling of concentrated leak erosion during Hole Erosion Tests

OpenAIRE

Mercier, F.; Bonelli, S.; Golay, F.; Anselmet, F.; Philippe, P.; Borghi, R.

2015-01-01

This study focuses on the numerical modelling of concentrated leak erosion of a cohesive soil by a turbulent flow in axisymmetrical geometry, with application to the Hole Erosion Test (HET). The numerical model is based on adaptive remeshing of the water/soil interface to ensure accurate description of the mechanical phenomena occurring near the soil/water interface. The erosion law governing the interface motion is based on two erosion parameters: the critical shear stress and the erosion co...

Prediction of indoor radon concentration based on residence location and construction

International Nuclear Information System (INIS)

Maekelaeinen, I.; Voutilainen, A.; Castren, O.

1992-01-01

We have constructed a model for assessing indoor radon concentrations in houses where measurements cannot be performed. It has been used in an epidemiological study and to determine the radon potential of new building sites. The model is based on data from about 10,000 buildings. Integrated radon measurements were made during the cold season in all the houses; their geographic coordinates were also known. The 2-mo measurement results were corrected to annual average concentrations. Construction data were collected from questionnaires completed by residents; geological data were determined from geological maps. Data were classified according to geographical, geological, and construction factors. In order to describe different radon production levels, the country was divided into four zones. We assumed that the factors were multiplicative, and a linear concentration-prediction model was used. The most significant factor in determining radon concentration was the geographical region, followed by soil type, year of construction, and type of foundation. The predicted indoor radon concentrations given by the model varied from 50 to 440 Bq m -3 . The lower figure represents a house with a basement, built in the 1950s on clay soil, in the region with the lowest radon concentration levels. The higher value represents a house with a concrete slab in contact with the ground, built in the 1980s, on gravel, in the region with the highest average radon concentration
Carbon Monoxide Emission and Concentration Models for Chiang Mai Urban Area

Institute of Scientific and Technical Information of China (English)

无

2006-01-01

An emission inventory containing emissions from traffic and other sources was complied. Based on the analysis, Carbon Monoxide (CO) emissions from traffic play a very important role in CO levels in Chiang Mai area. Analysis showed that CO emissions from traffic during rush hours contributed approximately 90% of total CO emissions. Regional Atmospheric Modeling System (RAMS) was applied to simulate wind fields and temperatures in the Chiang Mai area, and eight cases were selected to study annual variations in wind fields and temperatures. Model results can reflect major features of wind fields and diurnal variations in temperatures. For evaluating the model performance, model results were compared with observed wind speed, wind direction and temperature, which were monitored at a meteorological tower. Comparison showed that model results are in good agreement with observations, and the model captured many of the observed features. HYbrid Particle And Concentration Transport model (HYPACT) was used to simulate CO concentration in the Chiang Mai area. Model results generally agree well with observed CO concentrations at the air quality monitoring stations, and can explain observed CO diurnal variations.
Electrodiffusive model for astrocytic and neuronal ion concentration dynamics.

Directory of Open Access Journals (Sweden)

Geir Halnes

Full Text Available The cable equation is a proper framework for modeling electrical neural signalling that takes place at a timescale at which the ionic concentrations vary little. However, in neural tissue there are also key dynamic processes that occur at longer timescales. For example, endured periods of intense neural signaling may cause the local extracellular K(+-concentration to increase by several millimolars. The clearance of this excess K(+ depends partly on diffusion in the extracellular space, partly on local uptake by astrocytes, and partly on intracellular transport (spatial buffering within astrocytes. These processes, that take place at the time scale of seconds, demand a mathematical description able to account for the spatiotemporal variations in ion concentrations as well as the subsequent effects of these variations on the membrane potential. Here, we present a general electrodiffusive formalism for modeling of ion concentration dynamics in a one-dimensional geometry, including both the intra- and extracellular domains. Based on the Nernst-Planck equations, this formalism ensures that the membrane potential and ion concentrations are in consistency, it ensures global particle/charge conservation and it accounts for diffusion and concentration dependent variations in resistivity. We apply the formalism to a model of astrocytes exchanging ions with the extracellular space. The simulations show that K(+-removal from high-concentration regions is driven by a local depolarization of the astrocyte membrane, which concertedly (i increases the local astrocytic uptake of K(+, (ii suppresses extracellular transport of K(+, (iii increases axial transport of K(+ within astrocytes, and (iv facilitates astrocytic relase of K(+ in regions where the extracellular concentration is low. Together, these mechanisms seem to provide a robust regulatory scheme for shielding the extracellular space from excess K(+.
Hybrid ATDL-gamma distribution model for predicting area source acid gas concentrations

Energy Technology Data Exchange (ETDEWEB)

Jakeman, A J; Taylor, J A

1985-01-01

An air quality model is developed to predict the distribution of concentrations of acid gas in an urban airshed. The model is hybrid in character, combining reliable features of a deterministic ATDL-based model with statistical distributional approaches. The gamma distribution was identified from a range of distributional models as the best model. The paper shows that the assumptions of a previous hybrid model may be relaxed and presents a methodology for characterizing the uncertainty associated with model predictions. Results are demonstrated for the 98-percentile predictions of 24-h average data over annual periods at six monitoring sites. This percentile relates to the World Health Organization goal for acid gas concentrations.
Mathematical modeling of atmospheric fine particle-associated primary organic compound concentrations

Science.gov (United States)

Rogge, Wolfgang F.; Hildemann, Lynn M.; Mazurek, Monica A.; Cass, Glen R.; Simoneit, Bernd R. T.

1996-08-01

An atmospheric transport model has been used to explore the relationship between source emissions and ambient air quality for individual particle phase organic compounds present in primary aerosol source emissions. An inventory of fine particulate organic compound emissions was assembled for the Los Angeles area in the year 1982. Sources characterized included noncatalyst- and catalyst-equipped autos, diesel trucks, paved road dust, tire wear, brake lining dust, meat cooking operations, industrial oil-fired boilers, roofing tar pots, natural gas combustion in residential homes, cigarette smoke, fireplaces burning oak and pine wood, and plant leaf abrasion products. These primary fine particle source emissions were supplied to a computer-based model that simulates atmospheric transport, dispersion, and dry deposition based on the time series of hourly wind observations and mixing depths. Monthly average fine particle organic compound concentrations that would prevail if the primary organic aerosol were transported without chemical reaction were computed for more than 100 organic compounds within an 80 km × 80 km modeling area centered over Los Angeles. The monthly average compound concentrations predicted by the transport model were compared to atmospheric measurements made at monitoring sites within the study area during 1982. The predicted seasonal variation and absolute values of the concentrations of the more stable compounds are found to be in reasonable agreement with the ambient observations. While model predictions for the higher molecular weight polycyclic aromatic hydrocarbons (PAH) are in agreement with ambient observations, lower molecular weight PAH show much higher predicted than measured atmospheric concentrations in the particle phase, indicating atmospheric decay by chemical reactions or evaporation from the particle phase. The atmospheric concentrations of dicarboxylic acids and aromatic polycarboxylic acids greatly exceed the contributions that
Retrieve Aerosol Concentration Based On Surface Model and Distribution of Concentration of PM2.5 ——A Case Study of Beijing

Science.gov (United States)

Cui, H.

2017-12-01

As China's economy continues to grow, urbanization continues to advance, along with growth in all areas to pollutant emissions in the air industry, air quality also continued to deteriorate. Aerosol concentrations as a measure of air quality of the most important part of are more and more people's attention. Traditional monitoring stations measuring aerosol concentration method is accurate, but time-consuming and can't be done simultaneously measure a large area, can only rely on data from several monitoring sites to predict the concentration of the panorama. Remote Sensing Technology retrieves aerosol concentrations being by virtue of their efficient, fast advantages gradually into sight. In this paper, by the method of surface model to start with the physical processes of atmospheric transport, innovative aerosol concentration coefficient proposed to replace the traditional aerosol concentrations, pushed to a set of retrieval of aerosol concentration coefficient method, enabling fast and efficient Get accurate air pollution target area. At the same paper also monitoring data for PM2.5 in Beijing were analyzed from different angles, from the perspective of the data summarized in Beijing PM2.5 concentration of time, space, geographical distribution and concentration of PM2.5 and explored the relationship between aerosol concentration coefficient and concentration of PM2.5.
Modelling NO2 concentrations at the street level in the GAINS integrated assessment model: projections under current legislation

Science.gov (United States)

Kiesewetter, G.; Borken-Kleefeld, J.; Schöpp, W.; Heyes, C.; Thunis, P.; Bessagnet, B.; Terrenoire, E.; Gsella, A.; Amann, M.

2014-01-01

NO2 concentrations at the street level are a major concern for urban air quality in Europe and have been regulated under the EU Thematic Strategy on Air Pollution. Despite the legal requirements, limit values are exceeded at many monitoring stations with little or no improvement in recent years. In order to assess the effects of future emission control regulations on roadside NO2 concentrations, a downscaling module has been implemented in the GAINS integrated assessment model. The module follows a hybrid approach based on atmospheric dispersion calculations and observations from the AirBase European air quality database that are used to estimate site-specific parameters. Pollutant concentrations at every monitoring site with sufficient data coverage are disaggregated into contributions from regional background, urban increment, and local roadside increment. The future evolution of each contribution is assessed with a model of the appropriate scale: 28 × 28 km grid based on the EMEP Model for the regional background, 7 × 7 km urban increment based on the CHIMERE Chemistry Transport Model, and a chemical box model for the roadside increment. Thus, different emission scenarios and control options for long-range transport as well as regional and local emissions can be analysed. Observed concentrations and historical trends are well captured, in particular the differing NO2 and total NOx = NO + NO2 trends. Altogether, more than 1950 air quality monitoring stations in the EU are covered by the model, including more than 400 traffic stations and 70% of the critical stations. Together with its well-established bottom-up emission and dispersion calculation scheme, GAINS is thus able to bridge the scales from European-wide policies to impacts in street canyons. As an application of the model, we assess the evolution of attainment of NO2 limit values under current legislation until 2030. Strong improvements are expected with the introduction of the Euro 6 emission standard
Modeling of the Critical Micelle Concentration (CMC) of Nonionic Surfactants with an Extended Group-Contribution Method

DEFF Research Database (Denmark)

Mattei, Michele; Kontogeorgis, Georgios; Gani, Rafiqul

2013-01-01

, those compounds that exhibit larger correlation errors (based only on first- and second-order groups) are assigned to more detailed molecular descriptions, so that better correlations of critical micelle concentrations are obtained. The group parameter estimation has been performed using a data set......A group-contribution (GC) property prediction model for estimating the critical micelle concentration (CMC) of nonionic surfactants in water at 25 °C is presented. The model is based on the Marrero and Gani GC method. A systematic analysis of the model performance against experimental data...... concentration, and in particular, the quantitative structure−property relationship models, the developed GC model provides an accurate correlation and allows for an easier and faster application in computer-aided molecular design techniques facilitating chemical process and product design....
Network modeling of PM10 concentration in Malaysia

Science.gov (United States)

Supian, Muhammad Nazirul Aiman Abu; Bakar, Sakhinah Abu; Razak, Fatimah Abdul

2017-08-01

Air pollution is not a new phenomenon in Malaysia. The Department of Environment (DOE) monitors the country's ambient air quality through a network of 51 stations. The air quality is measured using the Air Pollution Index (API) which is mainly recorded based on the concentration of particulate matter, PM10 readings. The Continuous Air Quality Monitoring (CAQM) stations are located in various places across the country. In this study, a network model of air quality based on PM10 concen tration for selected CAQM stations in Malaysia has been developed. The model is built using a graph formulation, G = (V, E) where vertex, V is a set of CAQM stations and edges, E is a set of correlation values for each pair of vertices. The network measurements such as degree distributions, closeness centrality, and betweenness centrality are computed to analyse the behaviour of the network. As a result, a rank of CAQM stations has been produced based on their centrality characteristics.
Models and data to predict radionuclide concentrations in river basin systems

International Nuclear Information System (INIS)

Fleming, G.; Rufai, G.G.

1990-01-01

Radioactive contamination of land may result from the detonation of nuclear weapons or nuclear accidents, such as Chernobyl. The deposition of fallout on soil and/or plants, and subsequent erosion by rainsplash and overland flow, could introduce radioactive isotopes into the water and soil resources of the environment. A model to simulate the transport and deposition of concentrated pollutants and radionuclides within the river basin is proposed. The proposed model is built on an existing Strathclyde River Basin Model, (SRBM), which has the potential to simulate runoff and erosion and the distribution of eroded soil particle sizes. An algorithm of the processes of concentration of pollutants and radionuclides can be developed based on the current understanding of the process of radionuclide attachment to soil particles. (author)
Development and evaluation of a regression-based model to predict cesium concentration ratios for freshwater fish

International Nuclear Information System (INIS)

Pinder, John E.; Rowan, David J.; Rasmussen, Joseph B.; Smith, Jim T.; Hinton, Thomas G.; Whicker, F.W.

2014-01-01

Data from published studies and World Wide Web sources were combined to produce and test a regression model to predict Cs concentration ratios for freshwater fish species. The accuracies of predicted concentration ratios, which were computed using 1) species trophic levels obtained from random resampling of known food items and 2) K concentrations in the water for 207 fish from 44 species and 43 locations, were tested against independent observations of ratios for 57 fish from 17 species from 25 locations. Accuracy was assessed as the percent of observed to predicted ratios within factors of 2 or 3. Conservatism, expressed as the lack of under prediction, was assessed as the percent of observed to predicted ratios that were less than 2 or less than 3. The model's median observed to predicted ratio was 1.26, which was not significantly different from 1, and 50% of the ratios were between 0.73 and 1.85. The percentages of ratios within factors of 2 or 3 were 67 and 82%, respectively. The percentages of ratios that were <2 or <3 were 79 and 88%, respectively. An example for Perca fluviatilis demonstrated that increased prediction accuracy could be obtained when more detailed knowledge of diet was available to estimate trophic level. - Highlights: • We developed a model to predict Cs concentration ratios for freshwater fish species. • The model uses only two variables to predict a species CR for any location. • One variable is the K concentration in the freshwater. • The other is a species mean trophic level measure easily obtained from (fishbase.org). • The median observed to predicted ratio for 57 independent test cases was 1.26
Use of a Simple GIS-Based Model in Mapping the Atmospheric Concentration of γ-HCH in Europe

Directory of Open Access Journals (Sweden)

Pilar Vizcaino

2014-10-01

Full Text Available The state-of-the-art of atmospheric contaminant transport modeling provides accurate estimation of chemical concentrations. However, existing complex models, sophisticated in terms of process description and potentially highly accurate, may entail expensive setups and require very detailed input data. In contexts where detailed predictions are not needed (e.g., for regulatory risk assessment or life cycle impact assessment of chemicals, simple models allowing quick evaluation of contaminants may be preferable. The goal of this paper is to illustrate and critically discuss the use of a simple equation proposed by Pistocchi and Galmarini (2010, which can be implemented through basic GIS functions, to predict atmospheric concentrations of lindane (γ-HCH in Europe from both local and remote sources. Concentrations were computed for 1995 and 2005 assuming different modes of use of lindane and consequently different spatial patterns of emissions. Results were compared with those from the well-established MSCE-POP model (2005 developed within EMEP (European Monitoring and Evaluation Programme, and with available monitoring data, showing acceptable correspondence in terms of the orders of magnitude and spatial distribution of concentrations, especially when the background effect of emissions from extracontinental sources, estimated using the same equation, is added to European emissions.
Modelling of the concentration-time relationship based on global diffusion-charge transfer parameters in a flow-by reactor with a 3D electrode

International Nuclear Information System (INIS)

Nava, J.L.; Sosa, E.; Carreno, G.; Ponce-de-Leon, C.; Oropeza, M.T.

2006-01-01

A concentration versus time relationship model based on the isothermal diffusion-charge transfer mechanism was developed for a flow-by reactor with a three-dimensional (3D) reticulated vitreous carbon (RVC) electrode. The relationship was based on the effectiveness factor (η) which lead to the simulation of the concentration decay at different electrode polarisation conditions, i.e. -0.1, -0.3 and -0.59 V versus SCE; the charge transfer process was used for the former and mix and a mass transport control was used for the latter. Charge transfer and mass transport parameters were estimated from experimental data using Electrochemical Impedance Spectroscopy (EIS) and Linear Voltammetry (LV) techniques, respectively
Modelling of the concentration-time relationship based on global diffusion-charge transfer parameters in a flow-by reactor with a 3D electrode

Energy Technology Data Exchange (ETDEWEB)

Nava, J.L. [Universidad Autonoma Metropolitana-Iztapalapa, Departamento de Quimica, Av. San Rafael Atlixco 186, A.P. 55-534, C.P. 09340, Mexico D.F. (Mexico); Sosa, E. [Instituto Mexicano del Petroleo, Programa de Investigacion en Ingenieria Molecular, Eje Central 152, C.P. 07730, Mexico D.F. (Mexico); Carreno, G. [Universidad de Guanajuato, Facultad de Ingenieria en Geomatica e Hidraulica, Av. Juarez 77, C.P. 36000, Guanajuato, Gto. (Mexico); Ponce-de-Leon, C. [Electrochemical Engineering Group, School of Engineering Sciences, University of Southampton, Highfield, Southampton SO17 1BJ (United Kingdom)]. E-mail: capla@soton.ac.uk; Oropeza, M.T. [Centro de Graduados e Investigacion del Instituto Tecnologico de Tijuana, Blvd. Industrial, s/n, C.P. 22500, Tijuana B.C. (Mexico)

2006-05-25

A concentration versus time relationship model based on the isothermal diffusion-charge transfer mechanism was developed for a flow-by reactor with a three-dimensional (3D) reticulated vitreous carbon (RVC) electrode. The relationship was based on the effectiveness factor ({eta}) which lead to the simulation of the concentration decay at different electrode polarisation conditions, i.e. -0.1, -0.3 and -0.59 V versus SCE; the charge transfer process was used for the former and mix and a mass transport control was used for the latter. Charge transfer and mass transport parameters were estimated from experimental data using Electrochemical Impedance Spectroscopy (EIS) and Linear Voltammetry (LV) techniques, respectively.
Predicting long-term average concentrations of traffic-related air pollutants using GIS-based information

Science.gov (United States)

Hochadel, Matthias; Heinrich, Joachim; Gehring, Ulrike; Morgenstern, Verena; Kuhlbusch, Thomas; Link, Elke; Wichmann, H.-Erich; Krämer, Ursula

Global regression models were developed to estimate individual levels of long-term exposure to traffic-related air pollutants. The models are based on data of a one-year measurement programme including geographic data on traffic and population densities. This investigation is part of a cohort study on the impact of traffic-related air pollution on respiratory health, conducted at the westerly end of the Ruhr-area in North-Rhine Westphalia, Germany. Concentrations of NO 2, fine particle mass (PM 2.5) and filter absorbance of PM 2.5 as a marker for soot were measured at 40 sites spread throughout the study region. Fourteen-day samples were taken between March 2002 and March 2003 for each season and site. Annual average concentrations for the sites were determined after adjustment for temporal variation. Information on traffic counts in major roads, building densities and community population figures were collected in a geographical information system (GIS). This information was used to calculate different potential traffic-based predictors: (a) daily traffic flow and maximum traffic intensity of buffers with radii from 50 to 10 000 m and (b) distances to main roads and highways. NO 2 concentration and PM 2.5 absorbance were strongly correlated with the traffic-based variables. Linear regression prediction models, which involved predictors with radii of 50 to 1000 m, were developed for the Wesel region where most of the cohort members lived. They reached a model fit ( R2) of 0.81 and 0.65 for NO 2 and PM 2.5 absorbance, respectively. Regression models for the whole area required larger spatial scales and reached R2=0.90 and 0.82. Comparison of predicted values with NO 2 measurements at independent public monitoring stations showed a satisfactory association ( r=0.66). PM 2.5 concentration, however, was only slightly correlated and thus poorly predictable by traffic-based variables ( rGIS-based regression models offer a promising approach to assess individual levels of
An improved geographically weighted regression model for PM2.5 concentration estimation in large areas

Science.gov (United States)

Zhai, Liang; Li, Shuang; Zou, Bin; Sang, Huiyong; Fang, Xin; Xu, Shan

2018-05-01

Considering the spatial non-stationary contributions of environment variables to PM2.5 variations, the geographically weighted regression (GWR) modeling method has been using to estimate PM2.5 concentrations widely. However, most of the GWR models in reported studies so far were established based on the screened predictors through pretreatment correlation analysis, and this process might cause the omissions of factors really driving PM2.5 variations. This study therefore developed a best subsets regression (BSR) enhanced principal component analysis-GWR (PCA-GWR) modeling approach to estimate PM2.5 concentration by fully considering all the potential variables' contributions simultaneously. The performance comparison experiment between PCA-GWR and regular GWR was conducted in the Beijing-Tianjin-Hebei (BTH) region over a one-year-period. Results indicated that the PCA-GWR modeling outperforms the regular GWR modeling with obvious higher model fitting- and cross-validation based adjusted R2 and lower RMSE. Meanwhile, the distribution map of PM2.5 concentration from PCA-GWR modeling also clearly depicts more spatial variation details in contrast to the one from regular GWR modeling. It can be concluded that the BSR enhanced PCA-GWR modeling could be a reliable way for effective air pollution concentration estimation in the coming future by involving all the potential predictor variables' contributions to PM2.5 variations.
Spatio-temporal Analysis of suspended sediment Concentration in the Yongjiang Estuary Based on GOCI

Science.gov (United States)

Kang, Yanyan; Dong, Chuan

2018-01-01

The concentration and spatio-temporal variation of suspended sediment concentration in the estuary area are of great significance to the nearshore engineering, port construction and coastal evolution. Based on multi-period GOCI images and corresponding measured suspended sediment concentration (SSC) data, three inversion models (the linear regression model, the power exponent model and the neural network model) were established after rapid atmospheric correction. The results show that the absolute error of the three models is 0.20, 0.16 and 0.10kg/m3 respectively, and the relative errors are 38%, 23% and 18% respectively. The accuracy of the neural network (8-17-17-1) is the best. The SSC distribution diagrams in an ebb and flow cycle are obtained using this ANN model. The results show that with Yongjiang estuary for segmentation, the high concentration area is located in the north and the lower is in the south around Jintang Island deeper water area. When the tide rises, the water flow disturbs a large amount of sediment, and then the sediment concentration increases and high area high concentrations water body moves along the SE-NW. When the tide falls, flow rate decreases and the sediment concentration decreases. However, with the falling tide, the concentration of suspended sediment in the northern sea areas gradually increases, and is higher than 1kg/m3, and gradually moves along the NW-SE until to the estuary.
Riparian zone controls on base cation concentrations in boreal streams

Science.gov (United States)

Ledesma, J. L. J.; Grabs, T.; Futter, M. N.; Bishop, K. H.; Laudon, H.; Köhler, S. J.

2013-01-01

Forest riparian zones are a major in control of surface water quality. Base cation (BC) concentrations, fluxes, and cycling in the riparian zone merit attention because of increasing concern of negative consequences for re-acidification of surface waters from future climate and forest harvesting scenarios. We present a two-year study of BC and silica (Si) flow-weighted concentrations from 13 riparian zones and 14 streams in a boreal catchment in northern Sweden. The Riparian Flow-Concentration Integration Model (RIM) was used to estimate riparian zone flow-weighted concentrations and tested to predict the stream flow-weighted concentrations. Spatial variation in BC and Si concentrations as well as in flow-weighted concentrations was related to differences in Quaternary deposits, with the largest contribution from lower lying silty sediments and the lowest contribution from wetland areas higher up in the catchment. Temporal stability in the concentrations of most elements, a remarkably stable Mg / Ca ratio in the soil water and a homogeneous mineralogy suggest that the stable patterns found in the riparian zones are a result of distinct mineralogical upslope groundwater signals integrating the chemical signals of biological and chemical weathering. Stream water Mg / Ca ratio indicates that the signal is subsequently maintained in the streams. RIM gave good predictions of Ca, Mg, and Na flow-weighted concentrations in headwater streams. The difficulty in modelling K and Si suggests a stronger biogeochemical influence on these elements. The observed chemical dilution effect with flow in the streams was related to variation in groundwater levels and element concentration profiles in the riparian zones. This study provides a first step toward specific investigations of the vulnerability of riparian zones to changes induced by forest management or climate change, with focus on BC or other compounds.
A Twitter-based survey on marijuana concentrate use.

Science.gov (United States)

Daniulaityte, Raminta; Zatreh, Mussa Y; Lamy, Francois R; Nahhas, Ramzi W; Martins, Silvia S; Sheth, Amit; Carlson, Robert G

2018-04-11

The purpose of this paper is to analyze characteristics of marijuana concentrate users, describe patterns and reasons of use, and identify factors associated with daily use of concentrates among U.S.-based cannabis users recruited via a Twitter-based online survey. An anonymous Web-based survey was conducted in June 2017 with 687 U.S.-based cannabis users recruited via Twitter-based ads. The survey included questions about state of residence, socio-demographic characteristics, and cannabis use including marijuana concentrates. Multiple logistic regression analyses were conducted to identify characteristics associated with lifetime and daily use of marijuana concentrates. Almost 60% of respondents were male, 86% were white, and the mean age was 43.0 years. About 48% reported marijuana concentrate use. After adjusting for multiple testing, significant predictors of concentrate use included: living in "recreational" (AOR = 2.04; adj. p = .042) or "medical, less restrictive" (AOR = 1.74; adj. p = .030) states, being younger (AOR = 0.97, adj. p = .008), and daily herbal cannabis use (AOR = 2.57, adj. p = .008). Out of 329 marijuana concentrate users, about 13% (n = 44) reported daily/near daily use. Significant predictors of daily concentrate use included: living in recreational states (AOR = 3.59, adj. p = .020) and using concentrates for therapeutic purposes (AOR = 4.34, adj. p = .020). Living in states with more liberal marijuana policies is associated with greater likelihood of marijuana concentrate use and with more frequent use. Characteristics of daily users, in particular, patterns of therapeutic use warrant further research with community-recruited samples. Copyright © 2018 Elsevier B.V. All rights reserved.
Modelling anaerobic digestion of concentrated black water and faecal matter in accumulation system

NARCIS (Netherlands)

Elmitwalli, T.; Zeeman, G.; Otterpohl, R.

2011-01-01

A dynamic mathematical model based on anaerobic digestion model no. 1 (ADM1) was developed for accumulation (AC) system treating concentrated black water and faecal matter at different temperatures. The AC system was investigated for the treatment of waste(water) produced from the following systems:

Modeling the concentration-dependent permeation modes of the KcsA potassium ion channel.

Science.gov (United States)

Nelson, Peter Hugo

2003-12-01

The potassium channel from Streptomyces lividans (KcsA) is an integral membrane protein with sequence similarity to all known potassium channels, particularly in the selectivity filter region. A recently proposed model for ion channels containing either n or (n-1) single-file ions in their selectivity filters [P. H. Nelson, J. Chem. Phys. 177, 11396 (2002)] is applied to published KcsA channel K+ permeation data that exhibit a high-affinity process at low concentrations and a low-affinity process at high concentrations [M. LeMasurier et al., J. Gen. Physiol. 118, 303 (2001)]. The kinetic model is shown to provide a reasonable first-order explanation for both the high- and low-concentration permeation modes observed experimentally. The low-concentration mode ([K+]200 mM) has a 200-mV dissociation constant of 1100 mM and a conductance of 500 pS. Based on the permeation model, and x-ray analysis [J. H. Morais-Cabral et al., Nature (London) 414, 37 (2001)], it is suggested that the experimentally observed K+ permeation modes correspond to an n=3 mechanism at high concentrations and an n=2 mechanism at low concentrations. The ratio of the electrical dissociation distances for the high- and low-concentration modes is 3:2, also consistent with the proposed n=3 and n=2 modes. Model predictions for K+ channels that exhibit asymmetric current-voltage (I-V) curves are presented, and further validation of the kinetic model via molecular simulation and experiment is discussed. The qualitatively distinct I-V characteristics exhibited experimentally by Tl+, NH+4, and Rb+ ions at 100 mM concentration can also be explained using the model, but more extensive experimental tests are required for quantitative validation of the model predictions.
Study on calculation models and distribution rules of the radon concentration and its progenies concentration in blind roadway with forced-exhaust ventilation

International Nuclear Information System (INIS)

Ye Yongjun; Wang Liheng; Zhou Xinghuo; Li Xiangyang; Zhong Yongming; Wang Shuyun; Ding Dexin

2014-01-01

The forced-exhaust ventilation is an important way to control the concentration of radon and its progenies in long-distance blind driving roadway. It is of great significance for guiding the design of ventilation and radiation protection to study distribution characteristics of the concentration of radon and its progenies in the wind of roadway adopting the forced-exhaust ventilation. Therefore, according to the decay relationship of radon and its progenies, a simplified mathematical calculation model was built, which relates to the radon activity concentration and the potential alpha concentration of radon progenies. The paper also analyzed the sources of radon and its progenies in the limited space of the blind roadway. Then, based on the turbulence mass transfer theory of ventilation air flow, the paper established mathematical calculation models of distribution characteristics of the radon activity concentration and the potential alpha concentration of radon progenies in blind roadway with forced-exhaust ventilation, respectively. Finally, the paper applied the calculation models to a special blind roadway, and discussed the influence of the ventilation air inflow and the radon exhalation rate of rock wall on the distribution of radon concentration and the potential alpha concentration of radon progenies in the roadway. Meanwhile, some protective measurements were put forward to reduce the radiation dose of worker caused by radon and its progenies in the blind roadway. (authors)
Shape Modeling of a Concentric-tube Continuum Robot

DEFF Research Database (Denmark)

Bai, Shaoping; Xing, Charles Chuhao

2012-01-01

Concentric-tube continuum robots feature with simple and compact structures and have a great potential in medical applications. The paper is concerned with the shape modeling of a type of concentric-tube continuum robot built with a collection of super-elastic NiTiNol tubes. The mechanics...... is modeled on the basis of energy approach for both the in-plane and out-plane cases. The torsional influences on the shape of the concentric-tube robots are considered. An experimental device was build for the model validation. The results of simulation and experiments are included and analyzed....
Bioaerosol collection and concentration for microseparations-based detectors.

Energy Technology Data Exchange (ETDEWEB)

Cummings, Eric B. (Sandia National Laboratories, Livermore, CA); Ellis, C. R. Bowe (Sandia National Laboratories, Livermore, CA); Kanouff, Michael P. (Sandia National Laboratories, Livermore, CA); Rader, Daniel John; Wally, Karl (Sandia National Laboratories, Livermore, CA)

2005-03-01

The ability to detect Weapons of Mass Destruction biological agents rapidly and sensitively is vital to homeland security, spurring development of compact detection systems at Sandia and elsewhere. One such system is Sandia's microseparations-based pChemLab. Many bio-agents are serious health threats even at extremely low concentrations. Therefore, a universal challenge for detection systems is the efficient collection and selective transport of highly diffuse bio-agents against the enormous background of benign particles and species ever present in the ambient environment. We have investigated development of a ''front end'' system for the collection, preconcentration, and selective transport of aerosolized biological agents from dilute (1-10 active particles per liter of air) atmospheric samples, to ultimate concentrations of {approx}20 active particles per microliter of liquid, for interface with microfluidic-based analyses and detection systems. Our approach employs a Sandia-developed aerosol particle-focusing microseparator array to focus size-selected particles into a mating microimpinger array of open microfluidic transport channels. Upon collection (i.e., impingement, submergence, and liquid suspension), microfluidic dielectrophoretic particle concentrators and sorters can be employed to further concentrate and selectively transport bio-agent particles to the sample preparation stages of microfluidic analyses and detection systems. This report documents results in experimental testing, modeling and analysis, component design, and materials fabrication critical to establishing proof-of-principle for this collection ''front end''. Outstanding results have been achieved for the aerodynamic microseparator, and for the post-collection dielectrophoretic concentrator and sorter. Results have been obtained for the microimpinger, too, but issues of particle-trapping by surface tension in liquid surfaces have proven
Aquatic Exposure Predictions of Insecticide Field Concentrations Using a Multimedia Mass-Balance Model.

Science.gov (United States)

Knäbel, Anja; Scheringer, Martin; Stehle, Sebastian; Schulz, Ralf

2016-04-05

Highly complex process-driven mechanistic fate and transport models and multimedia mass balance models can be used for the exposure prediction of pesticides in different environmental compartments. Generally, both types of models differ in spatial and temporal resolution. Process-driven mechanistic fate models are very complex, and calculations are time-intensive. This type of model is currently used within the European regulatory pesticide registration (FOCUS). Multimedia mass-balance models require fewer input parameters to calculate concentration ranges and the partitioning between different environmental media. In this study, we used the fugacity-based small-region model (SRM) to calculate predicted environmental concentrations (PEC) for 466 cases of insecticide field concentrations measured in European surface waters. We were able to show that the PECs of the multimedia model are more protective in comparison to FOCUS. In addition, our results show that the multimedia model results have a higher predictive power to simulate varying field concentrations at a higher level of field relevance. The adaptation of the model scenario to actual field conditions suggests that the performance of the SRM increases when worst-case conditions are replaced by real field data. Therefore, this study shows that a less complex modeling approach than that used in the regulatory risk assessment exhibits a higher level of protectiveness and predictiveness and that there is a need to develop and evaluate new ecologically relevant scenarios in the context of pesticide exposure modeling.
Simplified 2DEG carrier concentration model for composite barrier AlGaN/GaN HEMT

International Nuclear Information System (INIS)

Das, Palash; Biswas, Dhrubes

2014-01-01

The self consistent solution of Schrodinger and Poisson equations is used along with the total charge depletion model and applied with a novel approach of composite AlGaN barrier based HEMT heterostructure. The solution leaded to a completely new analytical model for Fermi energy level vs. 2DEG carrier concentration. This was eventually used to demonstrate a new analytical model for the temperature dependent 2DEG carrier concentration in AlGaN/GaN HEMT
Mathematical Modeling of the Concentrated Energy Flow Effect on Metallic Materials

Directory of Open Access Journals (Sweden)

Sergey Konovalov

2016-12-01

Full Text Available Numerous processes take place in materials under the action of concentrated energy flows. The most important ones include heating together with the temperature misdistribution throughout the depth, probable vaporization on the surface layer, melting to a definite depth, and hydrodynamic flotation; generation of thermo-elastic waves; dissolution of heterogeneous matrix particles; and formation of nanolayers. The heat-based model is presented in an enthalpy statement involving changes in the boundary conditions, which makes it possible to consider melting and vaporization on the material surface. As a result, a linear dependence of penetration depth vs. energy density has been derived. The model of thermo-elastic wave generation is based on the system of equations on the uncoupled one-dimensional problem of dynamic thermo-elasticity for a layer with the finite thickness. This problem was solved analytically by the symbolic method. It has been revealed for the first time that the generated stress pulse comprises tension and compression zones, which are caused by increases and decreases in temperature on the boundary. The dissolution of alloying elements is modeled on the example of a titanium-carbon system in the process of electron beam action. The mathematical model is proposed to describe it, and a procedure is suggested to solve the problem of carbon distribution in titanium carbide and liquid titanium-carbide solution in terms of the state diagram and temperature changes caused by phase transitions. Carbon concentration vs. spatial values were calculated for various points of time at diverse initial temperatures of the cell. The dependence of carbon particle dissolution on initial temperature and radius of the particle were derived. A hydrodynamic model based on the evolution of Kelvin-Helmholtz instability in shear viscous flows has been proposed to specify the formation of nanostructures in materials subjected to the action of concentrated
Land-use regression panel models of NO2 concentrations in Seoul, Korea

Science.gov (United States)

Kim, Youngkook; Guldmann, Jean-Michel

2015-04-01

Transportation and land-use activities are major air pollution contributors. Since their shares of emissions vary across space and time, so do air pollution concentrations. Despite these variations, panel data have rarely been used in land-use regression (LUR) modeling of air pollution. In addition, the complex interactions between traffic flows, land uses, and meteorological variables, have not been satisfactorily investigated in LUR models. The purpose of this research is to develop and estimate nitrogen dioxide (NO2) panel models based on the LUR framework with data for Seoul, Korea, accounting for the impacts of these variables, and their interactions with spatial and temporal dummy variables. The panel data vary over several scales: daily (24 h), seasonally (4), and spatially (34 intra-urban measurement locations). To enhance model explanatory power, wind direction and distance decay effects are accounted for. The results show that vehicle-kilometers-traveled (VKT) and solar radiation have statistically strong positive and negative impacts on NO2 concentrations across the four seasonal models. In addition, there are significant interactions with the dummy variables, pointing to VKT and solar radiation effects on NO2 concentrations that vary with time and intra-urban location. The results also show that residential, commercial, and industrial land uses, and wind speed, temperature, and humidity, all impact NO2 concentrations. The R2 vary between 0.95 and 0.98.
A GIS-based groundwater travel time model to evaluate stream nitrate concentration reductions from land use change

Science.gov (United States)

Schilling, K.E.; Wolter, C.F.

2007-01-01

Excessive nitrate-nitrogen (nitrate) loss from agricultural watersheds is an environmental concern. A common conservation practice to improve stream water quality is to retire vulnerable row croplands to grass. In this paper, a groundwater travel time model based on a geographic information system (GIS) analysis of readily available soil and topographic variables was used to evaluate the time needed to observe stream nitrate concentration reductions from conversion of row crop land to native prairie in Walnut Creek watershed, Iowa. Average linear groundwater velocity in 5-m cells was estimated by overlaying GIS layers of soil permeability, land slope (surrogates for hydraulic conductivity and gradient, respectively) and porosity. Cells were summed backwards from the stream network to watershed divide to develop a travel time distribution map. Results suggested that groundwater from half of the land planted in prairie has reached the stream network during the 10 years of ongoing water quality monitoring. The mean travel time for the watershed was estimated to be 10.1 years, consistent with results from a simple analytical model. The proportion of land in the watershed and subbasins with prairie groundwater reaching the stream (10-22%) was similar to the measured reduction of stream nitrate (11-36%). Results provide encouragement that additional nitrate reductions in Walnut Creek are probable in the future as reduced nitrate groundwater from distal locations discharges to the stream network in the coming years. The high spatial resolution of the model (5-m cells) and its simplicity may make it potentially applicable for land managers interested in communicating lag time issues to the public, particularly related to nitrate concentration reductions over time. ?? 2007 Springer-Verlag.
PET measurement of FK506 concentration in a monkey model of stroke

International Nuclear Information System (INIS)

Murakami, Yoshihiro; Takamatsu, Hiroyuki; Noda, Akihiro; Osoda, Kazuhiko; Nishimura, Shintaro

2007-01-01

Introduction: The immunosuppressive agent FK506 (tacrolimus) has neuroprotective properties in an experimental model of cerebral ischemia. To improve the accuracy of clinical studies in acute stroke, a clinical dose setting should be based on the brain concentration, but not on the blood concentration of agents in humans. We have already established a measurement method using PET for FK506 concentration in the normal monkey brain, which could be applicable for human study; however, under ischemic conditions, in this study, we aimed to examine the brain concentration of FK506 in a monkey model of stroke. Methods: Studies were performed on six male cynomolgus monkeys (Macaca fascicularis) and a middle cerebral artery (MCA) occlusion model was used. Regional cerebral blood flow (rCBF) was measured by an intravenous injection of [ 15 O]H 2 O 165 min after MCA occlusion. FK506 (0.1 mg/kg) containing [ 11 C]FK506 was intravenously injected into the monkeys 180 min after MCA occlusion, and dynamic PET images were acquired for 30 min after administration. FK506 concentrations in the brain were calculated in moles per liter (M) units using the specific activity of injected FK506. Results: MCA occlusion produced ischemia, confirmed by rCBF measurement before the administration of [ 11 C]FK506. Fifteen minutes after FK506 (0.1 mg/kg) administration, the concentrations in the contralateral and ipsilateral cortex were 22.4±6.4 and 19.7±4.0 ng/g, respectively. Conclusion: We successfully measured the brain concentration of FK506 in a monkey model of stroke. The difference between the contralateral and ipsilateral concentrations of FK506 was not significant. This characteristic that FK506 readily penetrates ischemic tissue as well as normal tissue might explain the neuroprotective effect of FK506 in the ischemic brain and is suitable for the treatment of stroke patients
Comparison of marine dispersion model predictions with environmental radionuclide concentrations

International Nuclear Information System (INIS)

Johnson, C.E.; McKay, W.A.

1988-01-01

The comparison of marine dispersion model results with measurements is an essential part of model development and testing. The results from two residual flow models are compared with seawater concentrations, and in one case with concentrations measured in marine molluscs. For areas with short turnover times, seawater concentrations respond rapidly to variations in discharge rate and marine currents. These variations are difficult to model, and comparison with concentrations in marine animals provides an alternative and complementary technique for model validation with the advantages that the measurements reflect the mean conditions and frequently form a useful time series. (author)
Quick Estimation Model for the Concentration of Indoor Airborne Culturable Bacteria: An Application of Machine Learning

Directory of Open Access Journals (Sweden)

Zhijian Liu

2017-07-01

Full Text Available Indoor airborne culturable bacteria are sometimes harmful to human health. Therefore, a quick estimation of their concentration is particularly necessary. However, measuring the indoor microorganism concentration (e.g., bacteria usually requires a large amount of time, economic cost, and manpower. In this paper, we aim to provide a quick solution: using knowledge-based machine learning to provide quick estimation of the concentration of indoor airborne culturable bacteria only with the inputs of several measurable indoor environmental indicators, including: indoor particulate matter (PM2.5 and PM10, temperature, relative humidity, and CO2 concentration. Our results show that a general regression neural network (GRNN model can sufficiently provide a quick and decent estimation based on the model training and testing using an experimental database with 249 data groups.
Background Concentrations for Use in the Operational Street Pollution Model (OSPM)

DEFF Research Database (Denmark)

Jensen, S. S.

A background model has been developed for application in the Operational Street Pollution Model (OSPM) in context of long-term exposure modelling. The back ground model is based on a semi-empirical method founded on a few monitor stations that estimates standardised one hour time-series of urban...... and rural back ground concentrations of NO2, NOx, O3 and CO for different geographic regions in Denmark. The annual mean of selected monitor stations is used as a reference year and the development in estimated traffic emissions as an index is used to establish a historic trend. As an exception ozone trends...
Modeling and design of energy concentrating laser weld joints

Energy Technology Data Exchange (ETDEWEB)

Milewski, J.O. [Los Alamos National Lab., NM (United States); Sklar, E. [OptiCad Corp., Santa Fe, NM (United States)

1997-04-01

The application of lasers for welding and joining has increased steadily over the past decade with the advent of high powered industrial laser systems. Attributes such as high energy density and precise focusing allow high speed processing of precision assemblies. Other characteristics of the process such as poor coupling of energy due to highly reflective materials and instabilities associated with deep penetration keyhole mode welding remain as process limitations and challenges to be overcome. Reflective loss of laser energy impinging on metal surfaces can in some cases exceed ninety five percent, thus making the process extremely inefficient. Enhanced coupling of the laser beam can occur when high energy densities approach the vaporization point of the materials and form a keyhole feature which can trap laser energy and enhance melting and process efficiency. The extreme temperature, pressure and fluid flow dynamics of the keyhole make control of the process difficult in this melting regime. The authors design and model weld joints which through reflective propagation and concentration of the laser beam energy significantly enhance the melting process and weld morphology. A three dimensional computer based geometric optical model is used to describe the key laser parameters and joint geometry. Ray tracing is used to compute the location and intensity of energy absorption within the weld joint. Comparison with experimentation shows good correlation of energy concentration within the model to actual weld profiles. The effect of energy concentration within various joint geometry is described. This method for extending the design of the laser system to include the weld joint allows the evaluation and selection of laser parameters such as lens and focal position for process optimization. The design of narrow gap joints which function as energy concentrators is described. The enhanced laser welding of aluminum without keyhole formation has been demonstrated.
Specific activity and concentration model applied to 137Cs movement in a eutrophic lake

International Nuclear Information System (INIS)

Vanderploeg, H.A.; Booth, R.S.; Clark, F.H.

1976-01-01

A linear systems-analysis model which simulates time-dependent dynamics of specific activity and concentration of radiocesium in lake ecosystems was applied to a shallow, eutrophic lake that had received a pulse input of 137 Cs. Best estimates of transfer coefficients for abiotic compartments (sediment, interstitial water and lake water) and the macrophyte compartment which controlled the mass balance of cesium in water were determined by ''tuning'' our initial estimates of the transfer coefficients to observed data on 137 Cs concentrations and contents of these compartments. In most cases, the optimized transfer coefficients for the abiotic compartments were not greatly different from our independently derived initial estimates, and the simulations for optimized coefficients were close to those based on initial estimates. The 137 Cs concentrations in water as predicted by the optimized transfer coefficients were then used to calculate 137 Cs kinetics in biota other than macrophytes. In general, model simulations were close to concentrations observed in the biota. The agreement between 137 Cs concentrations and simulations in bottom invertebrates supported our assumption that bottom sediments are not a major source of Cs to the biota. Our specific activity and concentration model was compared to the radionuclide content model, the model used in terrestrial ecosystems. For biotic components of aquatic ecosystems, values of α/sub ij/, the transfer coefficients of our model, are easily estimated from turnover rates of radiocesium in individual organisms in the laboratory
Communication: Modeling electrolyte mixtures with concentration dependent dielectric permittivity

Science.gov (United States)

Chen, Hsieh; Panagiotopoulos, Athanassios Z.

2018-01-01

We report a new implicit-solvent simulation model for electrolyte mixtures based on the concept of concentration dependent dielectric permittivity. A combining rule is found to predict the dielectric permittivity of electrolyte mixtures based on the experimentally measured dielectric permittivity for pure electrolytes as well as the mole fractions of the electrolytes in mixtures. Using grand canonical Monte Carlo simulations, we demonstrate that this approach allows us to accurately reproduce the mean ionic activity coefficients of NaCl in NaCl-CaCl2 mixtures at ionic strengths up to I = 3M. These results are important for thermodynamic studies of geologically relevant brines and physiological fluids.
Maximum solid concentrations of coal water slurries predicted by neural network models

Energy Technology Data Exchange (ETDEWEB)

Cheng, Jun; Li, Yanchang; Zhou, Junhu; Liu, Jianzhong; Cen, Kefa

2010-12-15

The nonlinear back-propagation (BP) neural network models were developed to predict the maximum solid concentration of coal water slurry (CWS) which is a substitute for oil fuel, based on physicochemical properties of 37 typical Chinese coals. The Levenberg-Marquardt algorithm was used to train five BP neural network models with different input factors. The data pretreatment method, learning rate and hidden neuron number were optimized by training models. It is found that the Hardgrove grindability index (HGI), moisture and coalification degree of parent coal are 3 indispensable factors for the prediction of CWS maximum solid concentration. Each BP neural network model gives a more accurate prediction result than the traditional polynomial regression equation. The BP neural network model with 3 input factors of HGI, moisture and oxygen/carbon ratio gives the smallest mean absolute error of 0.40%, which is much lower than that of 1.15% given by the traditional polynomial regression equation. (author)
COMPUTER MODELING OF STRUCTURAL - CONCENTRATION CHARACTERISTICS OF BUILDING COMPOSITE MATERIALS

Directory of Open Access Journals (Sweden)

I. I. Zaripova

2015-09-01

Full Text Available In the article the computer modeling of structural and concentration characteristics of the building composite material on the basis of the theory of the package. The main provisions of the algorithmon the basis of which it was possible to get the package with a significant number of packaged elements, making it more representative in comparison with existing analogues modeling. We describe the modeled area related areas, the presence of which determines the possibility of a percolation process, which in turn makes it possible to study and management of individual properties of the composite material of construction. As an example of the construction of a composite material is considered concrete that does not exclude the possibility of using algorithms and modeling results of similar studies for composite matrix type (matrix of the same material and distributed in a certain way by volume particles of another substance. Based on modeling results can be manufactured parts and construction elementsfor various purposes with improved technical characteristics (by controlling the concentration composition substance.
Model for calculating the boron concentration in PWR type reactors

International Nuclear Information System (INIS)

Reis Martins Junior, L.L. dos; Vanni, E.A.

1986-01-01

A PWR boron concentration model has been developed for use with RETRAN code. The concentration model calculates the boron mass balance in the primary circuit as the injected boron mixes and is transported through the same circuit. RETRAN control blocks are used to calculate the boron concentration in fluid volumes during steady-state and transient conditions. The boron reactivity worth is obtained from the core concentration and used in RETRAN point kinetics model. A FSAR type analysis of a Steam Line Break Accident in Angra I plant was selected to test the model and the results obtained indicate a sucessfull performance. (Author) [pt
Experimental validation of a heat transfer model for concentrating photovoltaic system

International Nuclear Information System (INIS)

Sendhil Kumar, Natarajan; Matty, Katz; Rita, Ebner; Simon, Weingaertner; Ortrun, Aßländer; Alex, Cole; Roland, Wertz; Tim, Giesen; Tapas Kumar, Mallick

2012-01-01

In this paper, a three dimensional heat transfer model is presented for a novel concentrating photovoltaic design for Active Solar Panel Initiative System (ASPIS). The concentration ratio of two systems (early and integrated prototype) are 5× and 10× respectively, designed for roof-top integrated Photovoltaic systems. ANSYS 12.1, CFX package was effectively used to predict the temperatures of the components of the both ASPIS systems at various boundary conditions. The predicted component temperatures of an early prototype were compared with experimental results of ASPIS, which were carried out in Solecta – Israel and at the Austrian Institute of Technology (AIT) – Austria. It was observed that the solar cell and lens temperature prediction shows good agreement with Solecta measurements. The minimum and maximum deviation of 3.8% and 17.9% were observed between numerical and Solecta measurements and the maximum deviations of 16.9% were observed between modeling and AIT measurements. Thus, the developed validated thermal model enables to predict the component temperatures for concentrating photovoltaic systems. - Highlights: ► Experimentally validated heat transfer model for concentrating Photovoltaic system developed. ► Predictions of solar cell temperatures for parallactic tracking CPV system for roof integration. ► The ASPIS module contains 2 mm wide 216 solar cells manufactured based on SATURN technology. ► A solar cell temperature of 44 °C was predicted for solar radiation intensity was 1000 W/m 2 and ambient temperature was 20 °C. ► Average deviation was 6% and enabled to predict temperature of any CPV system.

Modelling 99Tc concentrations in Fucus vesiculosus from the north-east Irish Sea

International Nuclear Information System (INIS)

Nawakowski, Claire; Nicholson, Michael D.; John Kershaw, Peter; Leonard, Kinson S.

2004-01-01

In 1994 there were substantial increases in the quantity of 99 Tc discharged into the north-east Irish Sea from BNFL Sellafield (UK), concomitant with improvements in waste treatment procedures. As a consequence, the concentration of 99 Tc observed in seawater and biota samples, taken from the Irish Sea coastline, increased significantly. Elevated concentrations were also reported in Dutch, Danish, Norwegian, Swedish and Arctic waters in subsequent years. In the present study a simple numerical model was developed and applied to time-series data of 99 Tc concentrations in the brown seaweed Fucus vesiculosus, collected from three UK sites in the vicinity of Sellafield (St. Bees, Heysham, Port William). The model considered site-specific scaling effects, lag times, previous discharge history and potential seasonal variation in uptake. In general, there was a good fit between predicted and observed concentrations, but the degree of uncertainty varied inversely with the frequency of sampling. We did not observe a significant seasonal variation. The modelled lag times to the three sites were consistent with transport times based on observations of the water column distribution of 99 Tc. The model was applied to a variety of discharge scenarios, reflecting current discussion on the future management of 99 Tc releases. Concentrations in Fucus reached asymptotic values in 3-10 years, depending on the scenario and sampling site under consideration
Alumina Concentration Detection Based on the Kernel Extreme Learning Machine.

Science.gov (United States)

Zhang, Sen; Zhang, Tao; Yin, Yixin; Xiao, Wendong

2017-09-01

The concentration of alumina in the electrolyte is of great significance during the production of aluminum. The amount of the alumina concentration may lead to unbalanced material distribution and low production efficiency and affect the stability of the aluminum reduction cell and current efficiency. The existing methods cannot meet the needs for online measurement because industrial aluminum electrolysis has the characteristics of high temperature, strong magnetic field, coupled parameters, and high nonlinearity. Currently, there are no sensors or equipment that can detect the alumina concentration on line. Most companies acquire the alumina concentration from the electrolyte samples which are analyzed through an X-ray fluorescence spectrometer. To solve the problem, the paper proposes a soft sensing model based on a kernel extreme learning machine algorithm that takes the kernel function into the extreme learning machine. K-fold cross validation is used to estimate the generalization error. The proposed soft sensing algorithm can detect alumina concentration by the electrical signals such as voltages and currents of the anode rods. The predicted results show that the proposed approach can give more accurate estimations of alumina concentration with faster learning speed compared with the other methods such as the basic ELM, BP, and SVM.
A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

Science.gov (United States)

Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

2016-06-01

To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.
Physiologically based pharmacokinetic modeling of human exposure to perfluorooctanoic acid suggests historical non drinking-water exposures are important for predicting current serum concentrations.

Science.gov (United States)

Worley, Rachel Rogers; Yang, Xiaoxia; Fisher, Jeffrey

2017-09-01

Manufacturing of perfluorooctanoic acid (PFOA), a synthetic chemical with a long half-life in humans, peaked between 1970 and 2002, and has since diminished. In the United States, PFOA is detected in the blood of >99% of people tested, but serum concentrations have decreased since 1999. Much is known about exposure to PFOA in drinking water; however, the impact of non-drinking water PFOA exposure on serum PFOA concentrations is not well characterized. The objective of this research is to apply physiologically based pharmacokinetic (PBPK) modeling and Monte Carlo analysis to evaluate the impact of historic non-drinking water PFOA exposure on serum PFOA concentrations. In vitro to in vivo extrapolation was utilized to inform descriptions of PFOA transport in the kidney. Monte Carlo simulations were incorporated to evaluate factors that account for the large inter-individual variability of serum PFOA concentrations measured in individuals from North Alabama in 2010 and 2016, and the Mid-Ohio River Valley between 2005 and 2008. Predicted serum PFOA concentrations were within two-fold of experimental data. With incorporation of Monte Carlo simulations, the model successfully tracked the large variability of serum PFOA concentrations measured in populations from the Mid-Ohio River Valley. Simulation of exposure in a population of 45 adults from North Alabama successfully predicted 98% of individual serum PFOA concentrations measured in 2010 and 2016, respectively, when non-drinking water ingestion of PFOA exposure was included. Variation in serum PFOA concentrations may be due to inter-individual variability in the disposition of PFOA and potentially elevated historical non-drinking water exposures. Published by Elsevier Inc.
Concentrations of the UV filter ethylhexyl methoxycinnamate in the aquatic compartment: a comparison of modelled concentrations for Swiss surface waters with empirical monitoring data.

Science.gov (United States)

Straub, Jürg Oliver

2002-05-10

UV filters in sunscreens and cosmetics protect the skin from damage through UV radiation. Many tonnes per year of UV filters are being used in Europe and will be present, at least seasonally, in detectable concentrations in surface waters similar to common pharmaceutically active substances. Predicted environmental concentrations (PECs) of ethylhexyl methoxycinnamate (EHMC; CAS 5466-77-3) were extrapolated for Switzerland, taking into consideration substance-specific environmental fate data and marketing estimates, by crude worst-case reckoning and by applying two environmental models (Mackay Level III; USES 3.0), both configured for Swiss hydrological and area data. By worst-case reckoning the summer PEC is 70.8-81.3 ng/l while for the remaining 8 months of the year the PEC is 13.1-15.1 ng/l. The Level III model results in concentrations of 2.4 ng/l during the summer and 0.44 ng/l during the rest of the year, while the USES 3.0 model gives an average PEC for the whole year of 7.6 ng/l. Pooling summer monitoring data (90 single analyses) from the River Rhine below Basel in the year 1997 (Water Protection Board of Basel) and from Lakes Zurich and Hüttner in 1998 (Poiger et al., in preparation) allowed a derivation of a probabilistic median concentration of 4.6 ng/l, a 95th-percentile concentration of 18.6 ng/l and a 99th-percentile concentration of 33.5 ng/l. The 6-fold range from the median value to the maximum calls for caution in interpreting published monitoring concentrations. Comparison of modelled PECs with realistic median concentrations shows that crude reckoning overestimates actual concentrations by a factor of about 10, probably through insufficient consideration of (further) degradation of EHMC in sewage works, surface waters, sediments or river banks. Both computer models, in contrast, are within the same order of magnitude as the actual summer concentrations. Based on the available data, both these environmental fate and distribution models give
Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

Science.gov (United States)

Aksoy, A.; Yuzugullu, O.

2017-12-01

Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.
Modelling Black Carbon concentrations in two busy street canyons in Brussels using CANSBC

Science.gov (United States)

Brasseur, O.; Declerck, P.; Heene, B.; Vanderstraeten, P.

2015-01-01

This paper focused on modelling Black Carbon (BC) concentrations in two busy street canyons, the Crown and Belliard Street in Brussels. The used original Operational Street Pollution Model was adapted to BC by eliminating the chemical module and is noted here as CANSBC. Model validations were performed using temporal BC data from the fixed measurement network in Brussels. Subsequently, BC emissions were adjusted so that simulated BC concentrations equalled the observed ones, averaged over the whole period of simulation. Direct validations were performed for the Crown Street, while BC model calculations for the Belliard Street were validated indirectly using the linear relationship between BC and NOx. Concerning the Crown Street, simulated and observed half-hourly BC concentrations correlated well (r = 0.74) for the period from July 1st, 2011 till June 30th, 2013. In particular, CANSBC performed very well to simulate the monthly and diurnal evolutions of averaged BC concentrations, as well as the difference between weekdays and weekends. This means that the model correctly handled the meteorological conditions as well as the variation in traffic emissions. Considering dispersion, it should however be noted that BC concentrations are better simulated under stable than under unstable conditions. Even if the correlation on half-hourly NOx concentrations was slightly lower (r = 0.60) than the one of BC, indirect validations of CANSBC for the Belliard Street yielded comparable results and conclusions as described above for the Crown Street. Based on our results, it can be stated that CANSBC is suitable to accurately simulate BC concentrations in the street canyons of Brussels, under the following conditions: (i) accurate vehicle counting data is available to correctly estimate traffic emissions, and (ii) vehicle speeds are measured in order to improve emission estimates and to take into account the impact of the turbulence generated by moving vehicles on the local
Modelling CO concentrations under free-flowing and congested traffic conditions in Ireland

Energy Technology Data Exchange (ETDEWEB)

Broderick, B; Budd, U; Misstear, B [Dept. of Civil, Structural and Environmental Engineering, Trinity Coll. Dublin (Ireland); Ceburnis, D; Jennings, S G [Dept. of Experimental Physics, National Univ. of Ireland, Galway (Ireland)

2004-07-01

The assessment and management of air quality is required under the EU Air Quality Framework Directive and its Daughter Directives (CEC, 1996, 1999, 2000) which specify the limits for certain pollutants, including carbon monoxide (CO). Air quality modelling is used to predict the future impact of road improvements, often as part of an Environmental Impact Assessment. The U.S. National Commission on Air Quality found in 1981 that such models may typically overpredict or underpredict actual concentrations by a factor of two. Even twenty years later the U.K. Department of the Environment Transport and the Regions (UK DETR, 2001) concurred that ''If the prediction of an annual mean concentration lies within {+-}50% of the measurement, a user would not consider that the model has behaved badly.'' The Daughter Directive (CEC, 2000) concerned with CO allows 50% uncertainty in modelling of the eight-hour average concentration. An assessment of CALINE4 was performed for two contrasting sites: a free-flowing motorway and a periodically-congested roundabout. Air quality was continuously monitored over a one-year period at both sites. The data collected was compared with model predictions based on local and regional meteorological data, site geometry and traffic volumes. The modelled and monitored results were compared through both graphical and statistical analysis (Broderick B.M. et al., 2003). (orig.)
Estimation of local concentration from measurements of stochastic adsorption dynamics using carbon nanotube-based sensors

International Nuclear Information System (INIS)

Jang, Hong; Lee, Jay H.; Braatz, Richard D.

2016-01-01

This paper proposes a maximum likelihood estimation (MLE) method for estimating time varying local concentration of the target molecule proximate to the sensor from the time profile of monomolecular adsorption and desorption on the surface of the sensor at nanoscale. Recently, several carbon nanotube sensors have been developed that can selectively detect target molecules at a trace concentration level. These sensors use light intensity changes mediated by adsorption or desorption phenomena on their surfaces. The molecular events occurring at trace concentration levels are inherently stochastic, posing a challenge for optimal estimation. The stochastic behavior is modeled by the chemical master equation (CME), composed of a set of ordinary differential equations describing the time evolution of probabilities for the possible adsorption states. Given the significant stochastic nature of the underlying phenomena, rigorous stochastic estimation based on the CME should lead to an improved accuracy over than deterministic estimation formulated based on the continuum model. Motivated by this expectation, we formulate the MLE based on an analytical solution of the relevant CME, both for the constant and the time-varying local concentrations, with the objective of estimating the analyte concentration field in real time from the adsorption readings of the sensor array. The performances of the MLE and the deterministic least squares are compared using data generated by kinetic Monte Carlo (KMC) simulations of the stochastic process. Some future challenges are described for estimating and controlling the concentration field in a distributed domain using the sensor technology.
Population PK/PD model of homocysteine concentrations after high-dose methotrexate treatment in patients with acute lymphoblastic leukemia.

Directory of Open Access Journals (Sweden)

Hauke Rühs

Full Text Available Elevated homocysteine concentrations have been associated with methotrexate-induced neurotoxicity. Based on methotrexate and homocysteine plasma concentrations of 494 children with acute lymphoblastic leukemia treated with high-dose methotrexate in the TOTAL XV study, a pharmacokinetic/pharmacodynamic (PK/PD model was built with NONMEM. Several compartment and indirect response models were investigated. The pharmacokinetic disposition of methotrexate was best described by a two-compartment model. Homocysteine concentrations were included by an indirect response model where methotrexate inhibition of the homocysteine elimination rate was described by an E(max model. The homocysteine baseline level was found to be age-dependent. Simulations revealed that folinate rescue therapy does not affect peak concentrations of homocysteine but leads to a modestly reduced homocysteine exposure. In conclusion, our PK/PD model describes the increase of methotrexate-induced HCY concentrations with satisfactory precision and can be applied to assess the effect of folinate regimens on the HCY concentration-time course.
A concentration correction scheme for Lagrangian particle model and its application in street canyon air dispersion modelling

Energy Technology Data Exchange (ETDEWEB)

Jiyang Xia [Shanghai Jiao Tong University, Shanghai (China). Department of Engineering Mechanics; Leung, D.Y.C. [The University of Hong Kong (Hong Kong). Department of Mechanical Engineering

2001-07-01

Pollutant dispersion in street canyons with various configurations was simulated by discharging a large number of particles into the computation domain after developing a time-dependent wind field. Trajectory of the released particles was predicted using a Lagrangian particle model developed in an earlier study. A concentration correction scheme, based on the concept of 'visibility', was adopted for the Lagrangian particle model to correct the calculated pollutant concentration field in street canyons. The corrected concentrations compared favourably with those from wind tunnel experiments and a linear relationship between the computed concentrations and wind tunnel data were found. The developed model was then applied to four simulations to test for the suitability of the correction scheme and to study pollutant distribution in street canyons with different configurations. For those cases with obstacles presence in the computation domain, the correction scheme gives more reasonable results compared with the one without using it. Different flow regimes are observed in the street canyons, which depend on building configurations. A counter-clockwise rotating vortex may appear in a two-building case with wind flow from left to right, causing lower pollutant concentration at the leeward side of upstream building and higher concentration at the windward side of downstream building. On the other hand, a stable clockwise rotating vortex is formed in the street canyon with multiple identical buildings, resulting in poor natural ventilation in the street canyon. Moreover, particles emitted in the downstream canyon formed by buildings with large height-to-width ratios will be transported to upstream canyons. (author)
The first estimates of global nucleation mode aerosol concentrations based on satellite measurements

Directory of Open Access Journals (Sweden)

M. Kulmala

2011-11-01

Full Text Available Atmospheric aerosols play a key role in the Earth's climate system by scattering and absorbing solar radiation and by acting as cloud condensation nuclei. Satellites are increasingly used to obtain information on properties of aerosol particles with a diameter larger than about 100 nm. However, new aerosol particles formed by nucleation are initially much smaller and grow into the optically active size range on time scales of many hours. In this paper we derive proxies, based on process understanding and ground-based observations, to determine the concentrations of these new particles and their spatial distribution using satellite data. The results are applied to provide seasonal variation of nucleation mode concentration. The proxies describe the concentration of nucleation mode particles over continents. The source rates are related to both regional nucleation and nucleation associated with more restricted sources. The global pattern of nucleation mode particle number concentration predicted by satellite data using our proxies is compared qualitatively against both observations and global model simulations.
Multiphysics modelling and experimental validation of high concentration photovoltaic modules

International Nuclear Information System (INIS)

Theristis, Marios; Fernández, Eduardo F.; Sumner, Mike; O'Donovan, Tadhg S.

2017-01-01

Highlights: • A multiphysics modelling approach for concentrating photovoltaics was developed. • An experimental campaign was conducted to validate the models. • The experimental results were in good agreement with the models. • The multiphysics modelling allows the concentrator’s optimisation. - Abstract: High concentration photovoltaics, equipped with high efficiency multijunction solar cells, have great potential in achieving cost-effective and clean electricity generation at utility scale. Such systems are more complex compared to conventional photovoltaics because of the multiphysics effect that is present. Modelling the power output of such systems is therefore crucial for their further market penetration. Following this line, a multiphysics modelling procedure for high concentration photovoltaics is presented in this work. It combines an open source spectral model, a single diode electrical model and a three-dimensional finite element thermal model. In order to validate the models and the multiphysics modelling procedure against actual data, an outdoor experimental campaign was conducted in Albuquerque, New Mexico using a high concentration photovoltaic monomodule that is thoroughly described in terms of its geometry and materials. The experimental results were in good agreement (within 2.7%) with the predicted maximum power point. This multiphysics approach is relatively more complex when compared to empirical models, but besides the overall performance prediction it can also provide better understanding of the physics involved in the conversion of solar irradiance into electricity. It can therefore be used for the design and optimisation of high concentration photovoltaic modules.
Information modelling and knowledge bases XXV

CERN Document Server

Tokuda, T; Jaakkola, H; Yoshida, N

2014-01-01

Because of our ever increasing use of and reliance on technology and information systems, information modelling and knowledge bases continue to be important topics in those academic communities concerned with data handling and computer science. As the information itself becomes more complex, so do the levels of abstraction and the databases themselves. This book is part of the series Information Modelling and Knowledge Bases, which concentrates on a variety of themes in the important domains of conceptual modeling, design and specification of information systems, multimedia information modelin
Modeling of Drift Effects on Solar Tower Concentrated Flux Distributions

Directory of Open Access Journals (Sweden)

Luis O. Lara-Cerecedo

2016-01-01

Full Text Available A novel modeling tool for calculation of central receiver concentrated flux distributions is presented, which takes into account drift effects. This tool is based on a drift model that includes different geometrical error sources in a rigorous manner and on a simple analytic approximation for the individual flux distribution of a heliostat. The model is applied to a group of heliostats of a real field to obtain the resulting flux distribution and its variation along the day. The distributions differ strongly from those obtained assuming the ideal case without drift or a case with a Gaussian tracking error function. The time evolution of peak flux is also calculated to demonstrate the capabilities of the model. The evolution of this parameter also shows strong differences in comparison to the case without drift.
The attenuation of concentrations model: a new method for assessing mercury mobility in sediments

Directory of Open Access Journals (Sweden)

Julio C. Wasserman

2004-02-01

Full Text Available In this work we propose a new approach for the determination of the mobility of mercury in sediments based on spatial distribution of concentrations. We chose the Tainheiros Cove, located in the Todos os Santos Bay, Brazil, as the study area, for it has a history of mercury contamination due to a chloro-alkali plant that was active during 12 years. Twenty-six surface sediment samples were collected from the area and mercury concentrations were measured by cold vapour atomic absorption spectrophotometry. A contour map was constructed from the results, indicating that mercury accumulated in a "hot spot" where concentrations reach more than 1 µg g-1. The model is able to estimate mobility of mercury in the sediments based on the distances between iso-concentration contours that determines an attenuation of concentrations factor. Values of attenuation ranged between 0.0729 (East of the hot spot, indicating higher mobility to 0.7727 (North of the hot spot, indicating lower mobility.
Regression models for explaining and predicting concentrations of organochlorine pesticides in fish from streams in the United States

Science.gov (United States)

Nowell, Lisa H.; Crawford, Charles G.; Gilliom, Robert J.; Nakagaki, Naomi; Stone, Wesley W.; Thelin, Gail; Wolock, David M.

2009-01-01

Empirical regression models were developed for estimating concentrations of dieldrin, total chlordane, and total DDT in whole fish from U.S. streams. Models were based on pesticide concentrations measured in whole fish at 648 stream sites nationwide (1992-2001) as part of the U.S. Geological Survey's National Water Quality Assessment Program. Explanatory variables included fish lipid content, estimates (or surrogates) representing historical agricultural and urban sources, watershed characteristics, and geographic location. Models were developed using Tobit regression methods appropriate for data with censoring. Typically, the models explain approximately 50 to 70% of the variability in pesticide concentrations measured in whole fish. The models were used to predict pesticide concentrations in whole fish for streams nationwide using the U.S. Environmental Protection Agency's River Reach File 1 and to estimate the probability that whole-fish concentrations exceed benchmarks for protection of fish-eating wildlife. Predicted concentrations were highest for dieldrin in the Corn Belt, Texas, and scattered urban areas; for total chlordane in the Corn Belt, Texas, the Southeast, and urbanized Northeast; and for total DDT in the Southeast, Texas, California, and urban areas nationwide. The probability of exceeding wildlife benchmarks for dieldrin and chlordane was predicted to be low for most U.S. streams. The probability of exceeding wildlife benchmarks for total DDT is higher but varies depending on the fish taxon and on the benchmark used. Because the models in the present study are based on fish data collected during the 1990s and organochlorine pesticide residues in the environment continue to decline decades after their uses were discontinued, these models may overestimate present-day pesticide concentrations in fish. ?? 2009 SETAC.
Estimation of time-variable fast flow path chemical concentrations for application in tracer-based hydrograph separation analyses

Science.gov (United States)

Kronholm, Scott C.; Capel, Paul D.

2016-01-01

Mixing models are a commonly used method for hydrograph separation, but can be hindered by the subjective choice of the end-member tracer concentrations. This work tests a new variant of mixing model that uses high-frequency measures of two tracers and streamflow to separate total streamflow into water from slowflow and fastflow sources. The ratio between the concentrations of the two tracers is used to create a time-variable estimate of the concentration of each tracer in the fastflow end-member. Multiple synthetic data sets, and data from two hydrologically diverse streams, are used to test the performance and limitations of the new model (two-tracer ratio-based mixing model: TRaMM). When applied to the synthetic streams under many different scenarios, the TRaMM produces results that were reasonable approximations of the actual values of fastflow discharge (±0.1% of maximum fastflow) and fastflow tracer concentrations (±9.5% and ±16% of maximum fastflow nitrate concentration and specific conductance, respectively). With real stream data, the TRaMM produces high-frequency estimates of slowflow and fastflow discharge that align with expectations for each stream based on their respective hydrologic settings. The use of two tracers with the TRaMM provides an innovative and objective approach for estimating high-frequency fastflow concentrations and contributions of fastflow water to the stream. This provides useful information for tracking chemical movement to streams and allows for better selection and implementation of water quality management strategies.
Retrieving CO concentrations from FT-IR spectra with nonmodeled interferences and fluctuating baselines using PCR model parameters

DEFF Research Database (Denmark)

Bak, J.

2001-01-01

It is demonstrated that good predictions of gas concentrations based on measured spectra can be made even if these spectra contain totally overlapping spectral features from nonidentified and non-modeled interfering compounds and fluctuating baselines. The prediction program (CONTOUR) is based...... solely on principal component regression (PCR) model parameters, CONTOUR consists of two smaller algorithms. The first of these is used to calculate pure component spectra based on the PCR model parameters at different concentrations. In the second algorithm, the calculated pure component spectra...... remains. The assumptions are that the background and analytical signals must be additive and that no accidental match between these signals takes place. The best results are obtained with the use of spectra with a high selectivity. The use of the program is demonstrated hg applying simple single...
Environmental concentrations of engineered nanomaterials: Review of modeling and analytical studies

International Nuclear Information System (INIS)

Gottschalk, Fadri; Sun, TianYin; Nowack, Bernd

2013-01-01

Scientific consensus predicts that the worldwide use of engineered nanomaterials (ENM) leads to their release into the environment. We reviewed the available literature concerning environmental concentrations of six ENMs (TiO 2 , ZnO, Ag, fullerenes, CNT and CeO 2 ) in surface waters, wastewater treatment plant effluents, biosolids, sediments, soils and air. Presently, a dozen modeling studies provide environmental concentrations for ENM and a handful of analytical works can be used as basis for a preliminary validation. There are still major knowledge gaps (e.g. on ENM production, application and release) that affect the modeled values, but over all an agreement on the order of magnitude of the environmental concentrations can be reached. True validation of the modeled values is difficult because trace analytical methods that are specific for ENM detection and quantification are not available. The modeled and measured results are not always comparable due to the different forms and sizes of particles that these two approaches target. -- Highlights: •Modeled environmental concentrations of engineered nanomaterials are reviewed. •Measured environmental concentrations of engineered nanomaterials are reviewed. •Possible validation of modeled data by measurements is critically evaluated. •Different approaches in modeling and measurement methods complicate validation. -- Modeled and measured environmental concentrations of engineered nanomaterials are reviewed and critically discussed

Simplified Entropic Model for the Evaluation of Suspended Load Concentration

Directory of Open Access Journals (Sweden)

Domenica Mirauda

2018-03-01

Full Text Available Suspended sediment concentration is a key aspect in the forecasting of river evolution dynamics, as well as in water quality assessment, evaluation of reservoir impacts, and management of water resources. The estimation of suspended load often relies on empirical models, of which efficiency is limited by their analytic structure or by the need for calibration parameters. The present work deals with a simplified fully-analytical formulation of the so-called entropic model in order to reproduce the vertical distribution of sediment concentration. The simplification consists in the leading order expansion of the generalized spatial coordinate of the entropic velocity profile that, strictly speaking, applies to the near-bed region, but that provides acceptable results also near the free surface. The proposed closed-form solution, which highlights the interplay among channel morphology, stream power, secondary flows, and suspended transport features, allows reducing the needed number of field measurements and, therefore, the time of field activities. Its accuracy and robustness were successfully tested based on the comparison with laboratory data reported in literature.
Characterizing marijuana concentrate users: A web-based survey.

Science.gov (United States)

Daniulaityte, Raminta; Lamy, Francois R; Barratt, Monica; Nahhas, Ramzi W; Martins, Silvia S; Boyer, Edward W; Sheth, Amit; Carlson, Robert G

2017-09-01

The study seeks to characterize marijuana concentrate users, describe reasons and patterns of use, perceived risk, and identify predictors of daily/near daily use. An anonymous web-based survey was conducted (April-June 2016) with 673 US-based cannabis users recruited via the Bluelight.org web-forum and included questions about marijuana concentrate use, other drugs, and socio-demographics. Multivariable logistic regression analyses were conducted to identify characteristics associated with greater odds of lifetime and daily use of marijuana concentrates. About 66% of respondents reported marijuana concentrate use. The sample was 76% male, and 87% white. Marijuana concentrate use was viewed as riskier than flower cannabis. Greater odds of marijuana concentrate use was associated with living in states with "recreational" (AOR=4.91; p=0.001) or "medical, less restrictive" marijuana policies (AOR=1.87; p=0.014), being male (AOR=2.21, p=0.002), younger (AOR=0.95, pmarijuana concentrate users reported daily/near daily use. Greater odds of daily concentrate use was associated with being male (AOR=9.29, p=0.033), using concentrates for therapeutic purposes (AOR=7.61, p=0.001), using vape pens for marijuana concentrate administration (AOR=4.58, p=0.007), and lower perceived risk of marijuana concentrate use (AOR=0.92, p=0.017). Marijuana concentrate use was more common among male, younger and more experienced users, and those living in states with more liberal marijuana policies. Characteristics of daily users, in particular patterns of therapeutic use and utilization of different vaporization devices, warrant further research with community-recruited samples. Copyright © 2017 Elsevier B.V. All rights reserved.
Chemistry resolved kinetic flow modeling of TATB based explosives

Science.gov (United States)

Vitello, Peter; Fried, Laurence E.; William, Howard; Levesque, George; Souers, P. Clark

2012-03-01

Detonation waves in insensitive, TATB-based explosives are believed to have multiple time scale regimes. The initial burn rate of such explosives has a sub-microsecond time scale. However, significant late-time slow release in energy is believed to occur due to diffusion limited growth of carbon. In the intermediate time scale concentrations of product species likely change from being in equilibrium to being kinetic rate controlled. We use the thermo-chemical code CHEETAH linked to an ALE hydrodynamics code to model detonations. We term our model chemistry resolved kinetic flow, since CHEETAH tracks the time dependent concentrations of individual species in the detonation wave and calculates EOS values based on the concentrations. We present here two variants of our new rate model and comparison with hot, ambient, and cold experimental data for PBX 9502.
Compound parabolic concentrator optical fiber tip for FRET-based fluorescent sensors

DEFF Research Database (Denmark)

Hassan, Hafeez Ul; Nielsen, Kristian; Aasmul, Soren

2015-01-01

The Compound Parabolic Concentrator (CPC) optical fiber tip shape has been proposed for intensity based fluorescent sensors working on the principle of FRET (Förster Resonance Energy Transfer). A simple numerical Zemax model has been used to optimize the CPC tip geometry for a step-index multimode...... polymer optical fiber for an excitation and emission wavelength of 550 nm and 650nm, respectively. The model suggests an increase of a factor of 1.6 to 4 in the collected fluorescent power for an ideal CPC tip, as compared to the plane-cut fiber tip for fiber lengths between 5 and 45mm...
Simulating indoor concentrations of NO(2) and PM(2.5) in multifamily housing for use in health-based intervention modeling.

Science.gov (United States)

Fabian, P; Adamkiewicz, G; Levy, J I

2012-02-01

Residents of low-income multifamily housing can have elevated exposures to multiple environmental pollutants known to influence asthma. Simulation models can characterize the health implications of changing indoor concentrations, but quantifying the influence of interventions on concentrations is challenging given complex airflow and source characteristics. In this study, we simulated concentrations in a prototype multifamily building using CONTAM, a multizone airflow and contaminant transport program. Contaminants modeled included PM(2.5) and NO(2) , and parameters included stove use, presence and operability of exhaust fans, smoking, unit level, and building leakiness. We developed regression models to explain variability in CONTAM outputs for individual sources, in a manner that could be utilized in simulation modeling of health outcomes. To evaluate our models, we generated a database of 1000 simulated households with characteristics consistent with Boston public housing developments and residents and compared the predicted levels of NO(2) and PM(2.5) and their correlates with the literature. Our analyses demonstrated that CONTAM outputs could be readily explained by available parameters (R(2) between 0.89 and 0.98 across models), but that one-compartment box models would mischaracterize concentrations and source contributions. Our study quantifies the key drivers for indoor concentrations in multifamily housing and helps to identify opportunities for interventions. Many low-income urban asthmatics live in multifamily housing that may be amenable to ventilation-related interventions such as weatherization or air sealing, wall and ceiling hole repairs, and exhaust fan installation or repair, but such interventions must be designed carefully given their cost and their offsetting effects on energy savings as well as indoor and outdoor pollutants. We developed models to take into account the complex behavior of airflow patterns in multifamily buildings, which can
Predictive geochemical modeling of contaminant concentrations in laboratory columns and in plumes migrating from uranium mill tailings waste impoundments

International Nuclear Information System (INIS)

Peterson, S.R.; Martin, W.J.; Serne, R.J.

1986-04-01

A computer-based conceptual chemical model was applied to predict contaminant concentrations in plumes migrating from a uranium mill tailings waste impoundment. The solids chosen for inclusion in the conceptual model were selected based on reviews of the literature, on ion speciation/solubility calculations performed on the column effluent solutions and on mineralogical characterization of the contacted and uncontacted sediments. The mechanism of adsorption included in the conceptual chemical model was chosen based on results from semiselective extraction experiments and from mineralogical characterization procedures performed on the sediments. This conceptual chemical model was further developed and partially validated in laboratory experiments where assorted acidic uranium mill tailings solutions percolated through various sediments. This document contains the results of a partial field and laboratory validation (i.e., test of coherence) of this chemical model. Macro constituents (e.g., Ca, SO 4 , Al, Fe, and Mn) of the tailings solution were predicted closely by considering their concentrations to be controlled by the precipitation/dissolution of solid phases. Trace elements, however, were generally predicted to be undersaturated with respect to plausible solid phase controls. The concentration of several of the trace elements were closely predicted by considering their concentrations to be controlled by adsorption onto the amorphous iron oxyhydroxides that precipitated
A data base for thermodynamic modeling of +III actinide solubility in concentrated Na-Cl-SO4-CO3-PO4 electrolytes

International Nuclear Information System (INIS)

Novak, C.F.; Crafts, C.C.; Dhooge, N.J.

1995-01-01

The literature contains thermodynamic parameters for describing the chemical behavior of the following: Am(III) in dilute NaHCO 3 media; Nd(III) in dilute to concentrated Na 2 CO 3 and NaHCO 3 media; Pu(III) in dilute to concentrated NaCl media; Nd(III)/Am(III) in dilute to concentrated Na 2 SO 4 media; and Am(III) in NaH 2 PO 4 media. We have combined this information into a thermodynamic data base for the general +III actinide, An(III), using the analogy for chemical behavior of f-elements in the same oxidation state. This internally consistent data base is based on equilibrium thermodynamics and the specific ion interaction activity coefficient formalism of Pitzer. This data base forms the basis for the prediction of potential Am(III) and Pu(III) dissolved concentrations in the concentrated natural brines associated with the Waste Isolation Pilot Plant (WIPP) in Southeastern New Mexico, USA
Corrosion in low dielectric constant Si-O based thin films: Buffer concentration effects

International Nuclear Information System (INIS)

Zeng, F. W.; Lane, M. W.; Gates, S. M.

2014-01-01

Organosilicate glass (OSG) is often used as an interlayer dielectric (ILD) in high performance integrated circuits. OSG is a brittle material and prone to stress-corrosion cracking reminiscent of that observed in bulk glasses. Of particular concern are chemical-mechanical planarization techniques and wet cleans involving solvents commonly encountered in microelectronics fabrication where the organosilicate film is exposed to aqueous environments. Previous work has focused on the effect of pH, surfactant, and peroxide concentration on the subcritical crack growth of these films. However, little or no attention has focused on the effect of the conjugate acid/base concentration in a buffer. Accordingly, this work examines the “strength” of the buffer solution in both acidic and basic environments. The concentration of the buffer components is varied keeping the ratio of acid/base and therefore pH constant. In addition, the pH was varied by altering the acid/base ratio to ascertain any additional effect of pH. Corrosion tests were conducted with double-cantilever beam fracture mechanics specimens and fracture paths were verified with ATR-FTIR. Shifts in the threshold fracture energy, the lowest energy required for bond rupture in the given environment, G TH , were found to shift to lower values as the concentration of the base in the buffer increased. This effect was found to be much larger than the effect of the hydroxide ion concentration in unbuffered solutions. The results are rationalized in terms of the salient chemical bond breaking process occurring at the crack tip and modeled in terms of the chemical potential of the reactive species
Modeling flow for modified concentric cylinder rheometer geometry

Science.gov (United States)

Ekeruche, Karen; Connelly, Kelly; Kavehpour, H. Pirouz

2016-11-01

Rheology experiments on biological fluids can be difficult when samples are limited in volume, sensitive to degradation, and delicate to extract from tissues. A probe-like geometry has been developed to perform shear creep experiments on biological fluids and to use the creep response to characterize fluid material properties. This probe geometry is a modified concentric cylinder setup, where the gap is large and we assume the inner cylinder rotates in an infinite fluid. To validate this assumption we perform shear creep tests with the designed probe on Newtonian and non-Newtonian fluids and vary the outer cylinder container diameter. We have also created a numerical model based on the probe geometry setup to compare with experimental results at different outer cylinder diameters. A creep test is modeled by applying rotation to the inner cylinder and solving for the deformation of the fluid throughout the gap. Steady state viscosity values are calculated from creep compliance curves and compared between experimental and numerical results.
A simple flow-concentration modelling method for integrating water ...

African Journals Online (AJOL)

A simple flow-concentration modelling method for integrating water quality and ... flow requirements are assessed for maintenance low flow, drought low flow ... the instream concentrations of chemical constituents that will arise from different ...
Estimating surface water concentrations of “down-the-drain” chemicals in China using a global model

International Nuclear Information System (INIS)

Whelan, M.J.; Hodges, J.E.N.; Williams, R.J.; Keller, V.D.J.; Price, O.R.; Li, M.

2012-01-01

Predictions of surface water exposure to “down-the-drain” chemicals are presented which employ grid-based spatially-referenced data on average monthly runoff, population density, country-specific per capita domestic water and substance use rates and sewage treatment provision. Water and chemical load are routed through the landscape using flow directions derived from digital elevation data, accounting for in-stream chemical losses using simple first order kinetics. Although the spatial and temporal resolution of the model are relatively coarse, the model still has advantages over spatially inexplicit “unit-world” approaches, which apply arbitrary dilution factors, in terms of predicting the location of exposure hotspots and the statistical distribution of concentrations. The latter can be employed in probabilistic risk assessments. Here the model was applied to predict surface water exposure to “down-the-drain” chemicals in China for different levels of sewage treatment provision. Predicted spatial patterns of concentration were consistent with observed water quality classes for China. - Highlights: ► A global-scale model of “down-the-drain” chemical concentrations is presented. ► The model was used to predict spatial patterns of exposure in China. ► Predictions were consistent with observed water quality classes. ► The model can identify hotspots and statistical distributions of concentrations. - A global-scale model was used to predict spatial patterns of “down-the-drain” chemical concentrations in China. Predictions were consistent with observed water quality classes, demonstrating the potential value of the model.
Model based monitoring of stormwater runoff quality

DEFF Research Database (Denmark)

Birch, Heidi; Vezzaro, Luca; Mikkelsen, Peter Steen

2012-01-01

the information obtained about MPs discharged from the monitored system. A dynamic stormwater quality model was calibrated using MP data collected by volume-proportional and passive sampling in a storm drainage system in the outskirts of Copenhagen (Denmark) and a 10-year rain series was used to find annual...... average and maximum event mean concentrations. Use of this model reduced the uncertainty of predicted annual average concentrations compared to a simple stochastic method based solely on data. The predicted annual average obtained by using passive sampler measurements (one month installation...
Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods.

Science.gov (United States)

Hidalgo, J Ignacio; Colmenar, J Manuel; Kronberger, Gabriel; Winkler, Stephan M; Garnica, Oscar; Lanchares, Juan

2017-08-08

Predicting glucose values on the basis of insulin and food intakes is a difficult task that people with diabetes need to do daily. This is necessary as it is important to maintain glucose levels at appropriate values to avoid not only short-term, but also long-term complications of the illness. Artificial intelligence in general and machine learning techniques in particular have already lead to promising results in modeling and predicting glucose concentrations. In this work, several machine learning techniques are used for the modeling and prediction of glucose concentrations using as inputs the values measured by a continuous monitoring glucose system as well as also previous and estimated future carbohydrate intakes and insulin injections. In particular, we use the following four techniques: genetic programming, random forests, k-nearest neighbors, and grammatical evolution. We propose two new enhanced modeling algorithms for glucose prediction, namely (i) a variant of grammatical evolution which uses an optimized grammar, and (ii) a variant of tree-based genetic programming which uses a three-compartment model for carbohydrate and insulin dynamics. The predictors were trained and tested using data of ten patients from a public hospital in Spain. We analyze our experimental results using the Clarke error grid metric and see that 90% of the forecasts are correct (i.e., Clarke error categories A and B), but still even the best methods produce 5 to 10% of serious errors (category D) and approximately 0.5% of very serious errors (category E). We also propose an enhanced genetic programming algorithm that incorporates a three-compartment model into symbolic regression models to create smoothed time series of the original carbohydrate and insulin time series.
Geo-referenced modelling of metal concentrations in river basins at the catchment scale

Science.gov (United States)

Hüffmeyer, N.; Berlekamp, J.; Klasmeier, J.

2009-04-01

1. Introduction The European Water Framework Directive demands the good ecological and chemical state of surface waters [1]. This implies the reduction of unwanted metal concentrations in surface waters. To define reasonable environmental target values and to develop promising mitigation strategies a detailed exposure assessment is required. This includes the identification of emission sources and the evaluation of their effect on local and regional surface water concentrations. Point source emissions via municipal or industrial wastewater that collect metal loads from a wide variety of applications and products are important anthropogenic pathways into receiving waters. Natural background and historical influences from ore-mining activities may be another important factor. Non-point emissions occur via surface runoff and erosion from drained land area. Besides deposition metals can be deposited by fertilizer application or the use of metal products such as wires or metal fences. Surface water concentrations vary according to the emission strength of sources located nearby and upstream of the considered location. A direct link between specific emission sources and pathways on the one hand and observed concentrations can hardly be established by monitoring alone. Geo-referenced models such as GREAT-ER (Geo-referenced Regional Exposure Assessment Tool for European Rivers) deliver spatially resolved concentrations in a whole river basin and allow for evaluating the causal relationship between specific emissions and resulting concentrations. This study summarizes the results of investigations for the metals zinc and copper in three German catchments. 2. The model GREAT-ER The geo-referenced model GREAT-ER has originally been developed to simulate and assess chemical burden of European river systems from multiple emission sources [2]. Emission loads from private households and rainwater runoff are individually estimated based on average consumption figures, runoff rates
Probability of foliar injury for Acer sp. based on foliar fluoride concentrations.

Science.gov (United States)

McDonough, Andrew M; Dixon, Murray J; Terry, Debbie T; Todd, Aaron K; Luciani, Michael A; Williamson, Michele L; Roszak, Danuta S; Farias, Kim A

2016-12-01

Fluoride is considered one of the most phytotoxic elements to plants, and indicative fluoride injury has been associated over a wide range of foliar fluoride concentrations. The aim of this study was to determine the probability of indicative foliar fluoride injury based on Acer sp. foliar fluoride concentrations using a logistic regression model. Foliage from Acer nedundo, Acer saccharinum, Acer saccharum and Acer platanoides was collected along a distance gradient from three separate brick manufacturing facilities in southern Ontario as part of a long-term monitoring programme between 1995 and 2014. Hydrogen fluoride is the major emission source associated with the manufacturing facilities resulting with highly elevated foliar fluoride close to the facilities and decreasing with distance. Consistent with other studies, indicative fluoride injury was observed over a wide range of foliar concentrations (9.9-480.0 μg F - g -1 ). The logistic regression model was statistically significant for the Acer sp. group, A. negundo and A. saccharinum; consequently, A. negundo being the most sensitive species among the group. In addition, A. saccharum and A. platanoides were not statistically significant within the model. We are unaware of published foliar fluoride values for Acer sp. within Canada, and this research provides policy maker and scientist with probabilities of indicative foliar injury for common urban Acer sp. trees that can help guide decisions about emissions controls. Further research should focus on mechanisms driving indicative fluoride injury over wide ranging foliar fluoride concentrations and help determine foliar fluoride thresholds for damage.
Evaluation of seismic reliability of steel moment resisting frames rehabilitated by concentric braces with probabilistic models

Directory of Open Access Journals (Sweden)

Fateme Rezaei

2017-08-01

Full Text Available Probability of structure failure which has been designed by "deterministic methods" can be more than the one which has been designed in similar situation using probabilistic methods and models considering "uncertainties". The main purpose of this research was to evaluate the seismic reliability of steel moment resisting frames rehabilitated with concentric braces by probabilistic models. To do so, three-story and nine-story steel moment resisting frames were designed based on resistant criteria of Iranian code and then they were rehabilitated based on controlling drift limitations by concentric braces. Probability of frames failure was evaluated by probabilistic models of magnitude, location of earthquake, ground shaking intensity in the area of the structure, probabilistic model of building response (based on maximum lateral roof displacement and probabilistic methods. These frames were analyzed under subcrustal source by sampling probabilistic method "Risk Tools" (RT. Comparing the exceedance probability of building response curves (or selected points on it of the three-story and nine-story model frames (before and after rehabilitation, seismic response of rehabilitated frames, was reduced and their reliability was improved. Also the main effective variables in reducing the probability of frames failure were determined using sensitivity analysis by FORM probabilistic method. The most effective variables reducing the probability of frames failure are in the magnitude model, ground shaking intensity model error and magnitude model error
Using ANN and EPR models to predict carbon monoxide concentrations in urban area of Tabriz

Directory of Open Access Journals (Sweden)

Mohammad Shakerkhatibi

2015-09-01

Full Text Available Background: Forecasting of air pollutants has become a popular topic of environmental research today. For this purpose, the artificial neural network (AAN technique is widely used as a reliable method for forecasting air pollutants in urban areas. On the other hand, the evolutionary polynomial regression (EPR model has recently been used as a forecasting tool in some environmental issues. In this research, we compared the ability of these models to forecast carbon monoxide (CO concentrations in the urban area of Tabriz city. Methods: The dataset of CO concentrations measured at the fixed stations operated by the East Azerbaijan Environmental Office along with meteorological data obtained from the East Azerbaijan Meteorological Bureau from March 2007 to March 2013, were used as input for the ANN and EPR models. Results: Based on the results, the performance of ANN is more reliable in comparison with EPR. Using the ANN model, the correlation coefficient values at all monitoring stations were calculated above 0.85. Conversely, the R2 values for these stations were obtained <0.41 using the EPR model. Conclusion: The EPR model could not overcome the nonlinearities of input data. However, the ANN model displayed more accurate results compared to the EPR. Hence, the ANN models are robust tools for predicting air pollutant concentrations.
Concentration- and flux-based ozone dose–response relationships for five poplar clones grown in North China

International Nuclear Information System (INIS)

Hu, Enzhu; Gao, Feng; Xin, Yue; Jia, Huixia; Li, Kaihui; Hu, Jianjun; Feng, Zhaozhong

2015-01-01

Concentration- and flux-based O_3 dose–response relationships were developed for poplars in China. Stomatal conductance (g_s) of five poplar clones was measured to parameterize a Jarvis-type multiplicative g_s model. The maximum g_s and other model parameters varied between clones. The strongest relationship between stomatal O_3 flux and total biomass was obtained when phytotoxic ozone dose (POD) was integrated using an uptake rate threshold of 7 nmol m"−"2 s"−"1. The R"2 value was similar between flux-based and concentration-based dose–response relationships. Ozone concentrations above 28–36 nmol mol"−"1 contributed to reducing the biomass production of poplar. Critical levels of AOT_4_0 (accumulated O_3 exposure over 40 nmol mol"−"1) and POD_7 in relation to 5% reduction in total biomass for poplar were 12 μmol mol"−"1 h and 3.8 mmol m"−"2, respectively. - Highlights: • A stomatal conductance model was calibrated for poplar clones in China. • The stomatal O_3 flux–response relationship was developed for poplars. • O_3 concentrations > 28–36 nmol mol"−"1 contributed to poplar biomass reduction. • Current ambient O_3 level in most places of China has threatened poplar growth. • Ozone sensitivity of poplar is similar to that of birch/beech. - For the first time, dose–response relationships were developed for risk assessment of O_3 impacts on poplars in China.
Modelling street level PM10 concentrations across Europe: source apportionment and possible futures

Science.gov (United States)

Kiesewetter, G.; Borken-Kleefeld, J.; Schöpp, W.; Heyes, C.; Thunis, P.; Bessagnet, B.; Terrenoire, E.; Fagerli, H.; Nyiri, A.; Amann, M.

2015-02-01

Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80% of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period 2000-2008 to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are
Specific activity and concentration model applied to cesium-137 movement in a eutrophic lake

International Nuclear Information System (INIS)

Vanderploeg, H.A.; Booth, R.S.; Clark, F.H.

1975-01-01

A linear systems-analysis model which simulates time-dependent dynamics of specific activity and concentration of radiocesium in lake ecosystems was applied to a shallow, eutrophic lake that had received a pulse input of 137 Cs. Best estimates of transfer coefficients for abiotic compartments (sediment, interstitial water, and water) and macrophyte compartment which control mass balance of cesium in water were determined by tuning our initial estimates of the transfer coefficients to observed data on 137 Cs concentrations and contents of these compartments. In most cases, the optimized transfer coefficients of the abiotic compartments were not greatly different from our independently-derived initial estimates, and the simulations for optimized coefficients were close to those based on initial estimates. The simulations of 137 Cs concentration in water predicted by the optimized transfer coefficients were used to derive 137 Cs kinetics in biota other than macrophytes. In general, model simulations were close to concentrations observed in the biota. The agreement between 137 Cs concentrations and simulations in bottom invertebrates supported our assumption that bottom sediments are not a major source of Cs to the biota. (U.S.)

Modelling and analysis of ozone concentration by artificial intelligent techniques for estimating air quality

Science.gov (United States)

Taylan, Osman

2017-02-01

High ozone concentration is an important cause of air pollution mainly due to its role in the greenhouse gas emission. Ozone is produced by photochemical processes which contain nitrogen oxides and volatile organic compounds in the lower atmospheric level. Therefore, monitoring and controlling the quality of air in the urban environment is very important due to the public health care. However, air quality prediction is a highly complex and non-linear process; usually several attributes have to be considered. Artificial intelligent (AI) techniques can be employed to monitor and evaluate the ozone concentration level. The aim of this study is to develop an Adaptive Neuro-Fuzzy inference approach (ANFIS) to determine the influence of peripheral factors on air quality and pollution which is an arising problem due to ozone level in Jeddah city. The concentration of ozone level was considered as a factor to predict the Air Quality (AQ) under the atmospheric conditions. Using Air Quality Standards of Saudi Arabia, ozone concentration level was modelled by employing certain factors such as; nitrogen oxide (NOx), atmospheric pressure, temperature, and relative humidity. Hence, an ANFIS model was developed to observe the ozone concentration level and the model performance was assessed by testing data obtained from the monitoring stations established by the General Authority of Meteorology and Environment Protection of Kingdom of Saudi Arabia. The outcomes of ANFIS model were re-assessed by fuzzy quality charts using quality specification and control limits based on US-EPA air quality standards. The results of present study show that the ANFIS model is a comprehensive approach for the estimation and assessment of ozone level and is a reliable approach to produce more genuine outcomes.
Estimation of surface area concentration of workplace incidental nanoparticles based on number and mass concentrations

Science.gov (United States)

Park, J. Y.; Ramachandran, G.; Raynor, P. C.; Kim, S. W.

2011-10-01

Surface area was estimated by three different methods using number and/or mass concentrations obtained from either two or three instruments that are commonly used in the field. The estimated surface area concentrations were compared with reference surface area concentrations (SAREF) calculated from the particle size distributions obtained from a scanning mobility particle sizer and an optical particle counter (OPC). The first estimation method (SAPSD) used particle size distribution measured by a condensation particle counter (CPC) and an OPC. The second method (SAINV1) used an inversion routine based on PM1.0, PM2.5, and number concentrations to reconstruct assumed lognormal size distributions by minimizing the difference between measurements and calculated values. The third method (SAINV2) utilized a simpler inversion method that used PM1.0 and number concentrations to construct a lognormal size distribution with an assumed value of geometric standard deviation. All estimated surface area concentrations were calculated from the reconstructed size distributions. These methods were evaluated using particle measurements obtained in a restaurant, an aluminum die-casting factory, and a diesel engine laboratory. SAPSD was 0.7-1.8 times higher and SAINV1 and SAINV2 were 2.2-8 times higher than SAREF in the restaurant and diesel engine laboratory. In the die casting facility, all estimated surface area concentrations were lower than SAREF. However, the estimated surface area concentration using all three methods had qualitatively similar exposure trends and rankings to those using SAREF within a workplace. This study suggests that surface area concentration estimation based on particle size distribution (SAPSD) is a more accurate and convenient method to estimate surface area concentrations than estimation methods using inversion routines and may be feasible to use for classifying exposure groups and identifying exposure trends.
Estimation of surface area concentration of workplace incidental nanoparticles based on number and mass concentrations

International Nuclear Information System (INIS)

Park, J. Y.; Ramachandran, G.; Raynor, P. C.; Kim, S. W.

2011-01-01

Surface area was estimated by three different methods using number and/or mass concentrations obtained from either two or three instruments that are commonly used in the field. The estimated surface area concentrations were compared with reference surface area concentrations (SA REF ) calculated from the particle size distributions obtained from a scanning mobility particle sizer and an optical particle counter (OPC). The first estimation method (SA PSD ) used particle size distribution measured by a condensation particle counter (CPC) and an OPC. The second method (SA INV1 ) used an inversion routine based on PM1.0, PM2.5, and number concentrations to reconstruct assumed lognormal size distributions by minimizing the difference between measurements and calculated values. The third method (SA INV2 ) utilized a simpler inversion method that used PM1.0 and number concentrations to construct a lognormal size distribution with an assumed value of geometric standard deviation. All estimated surface area concentrations were calculated from the reconstructed size distributions. These methods were evaluated using particle measurements obtained in a restaurant, an aluminum die-casting factory, and a diesel engine laboratory. SA PSD was 0.7–1.8 times higher and SA INV1 and SA INV2 were 2.2–8 times higher than SA REF in the restaurant and diesel engine laboratory. In the die casting facility, all estimated surface area concentrations were lower than SA REF . However, the estimated surface area concentration using all three methods had qualitatively similar exposure trends and rankings to those using SA REF within a workplace. This study suggests that surface area concentration estimation based on particle size distribution (SA PSD ) is a more accurate and convenient method to estimate surface area concentrations than estimation methods using inversion routines and may be feasible to use for classifying exposure groups and identifying exposure trends.
Eigenvector Spatial Filtering Regression Modeling of Ground PM2.5 Concentrations Using Remotely Sensed Data

Directory of Open Access Journals (Sweden)

Jingyi Zhang

2018-06-01

Full Text Available This paper proposes a regression model using the Eigenvector Spatial Filtering (ESF method to estimate ground PM2.5 concentrations. Covariates are derived from remotely sensed data including aerosol optical depth, normal differential vegetation index, surface temperature, air pressure, relative humidity, height of planetary boundary layer and digital elevation model. In addition, cultural variables such as factory densities and road densities are also used in the model. With the Yangtze River Delta region as the study area, we constructed ESF-based Regression (ESFR models at different time scales, using data for the period between December 2015 and November 2016. We found that the ESFR models effectively filtered spatial autocorrelation in the OLS residuals and resulted in increases in the goodness-of-fit metrics as well as reductions in residual standard errors and cross-validation errors, compared to the classic OLS models. The annual ESFR model explained 70% of the variability in PM2.5 concentrations, 16.7% more than the non-spatial OLS model. With the ESFR models, we performed detail analyses on the spatial and temporal distributions of PM2.5 concentrations in the study area. The model predictions are lower than ground observations but match the general trend. The experiment shows that ESFR provides a promising approach to PM2.5 analysis and prediction.
Eigenvector Spatial Filtering Regression Modeling of Ground PM2.5 Concentrations Using Remotely Sensed Data.

Science.gov (United States)

Zhang, Jingyi; Li, Bin; Chen, Yumin; Chen, Meijie; Fang, Tao; Liu, Yongfeng

2018-06-11

This paper proposes a regression model using the Eigenvector Spatial Filtering (ESF) method to estimate ground PM 2.5 concentrations. Covariates are derived from remotely sensed data including aerosol optical depth, normal differential vegetation index, surface temperature, air pressure, relative humidity, height of planetary boundary layer and digital elevation model. In addition, cultural variables such as factory densities and road densities are also used in the model. With the Yangtze River Delta region as the study area, we constructed ESF-based Regression (ESFR) models at different time scales, using data for the period between December 2015 and November 2016. We found that the ESFR models effectively filtered spatial autocorrelation in the OLS residuals and resulted in increases in the goodness-of-fit metrics as well as reductions in residual standard errors and cross-validation errors, compared to the classic OLS models. The annual ESFR model explained 70% of the variability in PM 2.5 concentrations, 16.7% more than the non-spatial OLS model. With the ESFR models, we performed detail analyses on the spatial and temporal distributions of PM 2.5 concentrations in the study area. The model predictions are lower than ground observations but match the general trend. The experiment shows that ESFR provides a promising approach to PM 2.5 analysis and prediction.
Fitting the Probability Distribution Functions to Model Particulate Matter Concentrations

International Nuclear Information System (INIS)

El-Shanshoury, Gh.I.

2017-01-01

The main objective of this study is to identify the best probability distribution and the plotting position formula for modeling the concentrations of Total Suspended Particles (TSP) as well as the Particulate Matter with an aerodynamic diameter<10 μm (PM 10 ). The best distribution provides the estimated probabilities that exceed the threshold limit given by the Egyptian Air Quality Limit value (EAQLV) as well the number of exceedance days is estimated. The standard limits of the EAQLV for TSP and PM 10 concentrations are 24-h average of 230 μg/m 3 and 70 μg/m 3 , respectively. Five frequency distribution functions with seven formula of plotting positions (empirical cumulative distribution functions) are compared to fit the average of daily TSP and PM 10 concentrations in year 2014 for Ain Sokhna city. The Quantile-Quantile plot (Q-Q plot) is used as a method for assessing how closely a data set fits a particular distribution. A proper probability distribution that represents the TSP and PM 10 has been chosen based on the statistical performance indicator values. The results show that Hosking and Wallis plotting position combined with Frechet distribution gave the highest fit for TSP and PM 10 concentrations. Burr distribution with the same plotting position follows Frechet distribution. The exceedance probability and days over the EAQLV are predicted using Frechet distribution. In 2014, the exceedance probability and days for TSP concentrations are 0.052 and 19 days, respectively. Furthermore, the PM 10 concentration is found to exceed the threshold limit by 174 days
Modeling the distribution of colonial species to improve estimation of plankton concentration in ballast water

Science.gov (United States)

Rajakaruna, Harshana; VandenByllaardt, Julie; Kydd, Jocelyn; Bailey, Sarah

2018-03-01

The International Maritime Organization (IMO) has set limits on allowable plankton concentrations in ballast water discharge to minimize aquatic invasions globally. Previous guidance on ballast water sampling and compliance decision thresholds was based on the assumption that probability distributions of plankton are Poisson when spatially homogenous, or negative binomial when heterogeneous. We propose a hierarchical probability model, which incorporates distributions at the level of particles (i.e., discrete individuals plus colonies per unit volume) and also within particles (i.e., individuals per particle) to estimate the average plankton concentration in ballast water. We examined the performance of the models using data for plankton in the size class ≥ 10 μm and test ballast water compliance using the above models.
Probability density function modeling of scalar mixing from concentrated sources in turbulent channel flow

Science.gov (United States)

Bakosi, J.; Franzese, P.; Boybeyi, Z.

2007-11-01

Dispersion of a passive scalar from concentrated sources in fully developed turbulent channel flow is studied with the probability density function (PDF) method. The joint PDF of velocity, turbulent frequency and scalar concentration is represented by a large number of Lagrangian particles. A stochastic near-wall PDF model combines the generalized Langevin model of Haworth and Pope [Phys. Fluids 29, 387 (1986)] with Durbin's [J. Fluid Mech. 249, 465 (1993)] method of elliptic relaxation to provide a mathematically exact treatment of convective and viscous transport with a nonlocal representation of the near-wall Reynolds stress anisotropy. The presence of walls is incorporated through the imposition of no-slip and impermeability conditions on particles without the use of damping or wall-functions. Information on the turbulent time scale is supplied by the gamma-distribution model of van Slooten et al. [Phys. Fluids 10, 246 (1998)]. Two different micromixing models are compared that incorporate the effect of small scale mixing on the transported scalar: the widely used interaction by exchange with the mean and the interaction by exchange with the conditional mean model. Single-point velocity and concentration statistics are compared to direct numerical simulation and experimental data at Reτ=1080 based on the friction velocity and the channel half width. The joint model accurately reproduces a wide variety of conditional and unconditional statistics in both physical and composition space.
Modelling NOX concentrations through CFD-RANS in an urban hot-spot using high resolution traffic emissions and meteorology from a mesoscale model

Science.gov (United States)

Sanchez, Beatriz; Santiago, Jose Luis; Martilli, Alberto; Martin, Fernando; Borge, Rafael; Quaassdorff, Christina; de la Paz, David

2017-08-01

Air quality management requires more detailed studies about air pollution at urban and local scale over long periods of time. This work focuses on obtaining the spatial distribution of NOx concentration averaged over several days in a heavily trafficked urban area in Madrid (Spain) using a computational fluid dynamics (CFD) model. A methodology based on weighted average of CFD simulations is applied computing the time evolution of NOx dispersion as a sequence of steady-state scenarios taking into account the actual atmospheric conditions. The inputs of emissions are estimated from the traffic emission model and the meteorological information used is derived from a mesoscale model. Finally, the computed concentration map correlates well with 72 passive samplers deployed in the research area. This work reveals the potential of using urban mesoscale simulations together with detailed traffic emissions so as to provide accurate maps of pollutant concentration at microscale using CFD simulations.
Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

Science.gov (United States)

Ng, Kar Yong; Awang, Norhashidah

2018-01-06

Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.
MECHANISTIC KINETIC MODELS FOR STEAM REFORMING OF CONCENTRATED CRUDE ETHANOL ON NI/AL2O3 CATALYST

Directory of Open Access Journals (Sweden)

O. A. OLAFADEHAN

2015-05-01

Full Text Available Mechanistic kinetic models were postulated for the catalytic steam reforming of concentrated crude ethanol on a Ni-based commercial catalyst at atmosphere pressure in the temperature range of 673-863 K, and at different catalyst weight to the crude ethanol molar flow rate ratio (in the range 0.9645-9.6451 kg catalyst h/kg mole crude ethanol in a stainless steel packed bed tubular microreactor. The models were based on Langmuir-Hinshelwood-Hougen-Watson (LHHW and Eley-Rideal (ER mechanisms. The optimization routine of Nelder-Mead simplex algorithm was used to estimate the inherent kinetic parameters in the proposed models. The selection of the best kinetic model amongst the rival kinetic models was based on physicochemical, statistical and thermodynamic scrutinies. The rate determining step for the steam reforming of concentrated crude ethanol on Ni/Al2O3 catalyst was found to be surface reaction between chemisorbed CH3O and O when hydrogen and oxygen were adsorbed as monomolecular species on the catalyst surface. Excellent agreement was obtained between the experimental rate of reaction and conversion of crude ethanol, and the simulated results, with ADD% being ±0.46.
Adaptive sensor-based ultra-high accuracy solar concentrator tracker

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Brinkley, Jordyn; Hassanzadeh, Ali

2017-09-01

Conventional solar trackers use information of the sun's position, either by direct sensing or by GPS. Our method uses the shading of the receiver. This, coupled with nonimaging optics design allows us to achieve ultra-high concentration. Incorporating a sensor based shadow tracking method with a two stage concentration solar hybrid parabolic trough allows the system to maintain high concentration with acute accuracy.
In-core LOCA-s: analytical solution for the delayed mixing model for moderator poison concentration

International Nuclear Information System (INIS)

Firla, A.P.

1995-01-01

Solutions to dynamic moderator poison concentration model with delayed mixing under single pressure tube / calandria tube rupture scenario are discussed. Such a model is described by a delay differential equation, and for such equations the standard ways of solution are not directly applicable. In the paper an exact, direct time-domain analytical solution to the delayed mixing model is presented and discussed. The obtained solution has a 'marching' form and is easy to calculate numerically. Results of the numerical calculations based on the analytical solution indicate that for the expected range of mixing times the existing uniform mixing model is a good representation of the moderator poison mixing process for single PT/CT breaks. However, for postulated multi-pipe breaks ( which is very unlikely to occur ) the uniform mixing model is not adequate any more; at the same time an 'approximate' solution based on Laplace transform significantly overpredicts the rate of poison concentration decrease, resulting in excessive increase in the moderator dilution factor. In this situation the true, analytical solution must be used. The analytical solution presented in the paper may also serve as a bench-mark test for the accuracy of the existing poison mixing models. Moreover, because of the existing oscillatory tendency of the solution, special care must be taken in using delay differential models in other applications. (author). 3 refs., 3 tabs., 8 figs
Microfluidic paper-based biomolecule preconcentrator based on ion concentration polarization.

Science.gov (United States)

Han, Sung Il; Hwang, Kyo Seon; Kwak, Rhokyun; Lee, Jeong Hoon

2016-06-21

Microfluidic paper-based analytical devices (μPADs) for molecular detection have great potential in the field of point-of-care diagnostics. Currently, a critical problem being faced by μPADs is improving their detection sensitivity. Various preconcentration processes have been developed, but they still have complicated structures and fabrication processes to integrate into μPADs. To address this issue, we have developed a novel paper-based preconcentrator utilizing ion concentration polarization (ICP) with minimal addition on lateral-flow paper. The cation selective membrane (i.e., Nafion) is patterned on adhesive tape, and this tape is then attached to paper-based channels. When an electric field is applied across the Nafion, ICP is initiated to preconcentrate the biomolecules in the paper channel. Departing from previous paper-based preconcentrators, we maintain steady lateral fluid flow with the separated Nafion layer; as a result, fluorescent dyes and proteins (FITC-albumin and bovine serum albumin) are continuously delivered to the preconcentration zone, achieving high preconcentration performance up to 1000-fold. In addition, we demonstrate that the Nafion-patterned tape can be integrated with various geometries (multiplexed preconcentrator) and platforms (string and polymer microfluidic channel). This work would facilitate integration of various ICP devices, including preconcentrators, pH/concentration modulators, and micro mixers, with steady lateral flows in paper-based platforms.
Numerical modelling of pyrolysis in normal and reduced oxygen concentration

International Nuclear Information System (INIS)

Kacem, Ahmed

2016-01-01

The predictive capability of computational fluid dynamics (CFD) fire models depends on the accuracy with which the source term due to fuel pyrolysis can be determined. The pyrolysis rate is a key parameter controlling fire behavior, which in turn drives the heat feedback from the flame to the fuel surface. In the present study an in-depth pyrolysis model of a semi-transparent solid fuel (here, clear polymethyl methacrylate or PMMA) with spectrally-resolved radiation and a moving gas/solid interface was coupled with the CFD code ISIS of the IRSN which included turbulence, combustion and radiation for the gas phase. A combined genetic algorithm/pyrolysis model was used with Cone Calorimeter data from a pure pyrolysis experiment to estimate a unique set of kinetic parameters for PMMA pyrolysis. In order to validate the coupled model, ambient air flaming experiments were conducted on square slabs of PMMA with side lengths of 10, 20 and 40 cm. From measurements at the center of the slab, it was found that i) for any sample size, the experimental regression rate becomes almost constant with time, and ii) although the radiative and total heat transfers increase significantly with the sample size, the radiative contribution to the total heat flux remains almost constant (∼80%). Coupled model results show a fairly good agreement with the literature and with current measurements of the heat fluxes, gas temperature and regressing surface rate at the center of the slabs. Discrepancies between predicted and measured total pyrolysis rate are observed, which result from the underestimation of the flame heat flux feedback at the edges of the slab, as confirmed by the comparison between predicted and observed topography of burned samples. Predicted flame heights based on a threshold temperature criterion were found to be close to those deduced from the correlation of Heskestad. Finally, in order to predict the pyrolysis of PMMA under reduced ambient oxygen concentration, a two
Prediction of traffic-related nitrogen oxides concentrations using Structural Time-Series models

Science.gov (United States)

Lawson, Anneka Ruth; Ghosh, Bidisha; Broderick, Brian

2011-09-01

Ambient air quality monitoring, modeling and compliance to the standards set by European Union (EU) directives and World Health Organization (WHO) guidelines are required to ensure the protection of human and environmental health. Congested urban areas are most susceptible to traffic-related air pollution which is the most problematic source of air pollution in Ireland. Long-term continuous real-time monitoring of ambient air quality at such urban centers is essential but often not realistic due to financial and operational constraints. Hence, the development of a resource-conservative ambient air quality monitoring technique is essential to ensure compliance with the threshold values set by the standards. As an intelligent and advanced statistical methodology, a Structural Time Series (STS) based approach has been introduced in this paper to develop a parsimonious and computationally simple air quality model. In STS methodology, the different components of a time-series dataset such as the trend, seasonal, cyclical and calendar variations can be modeled separately. To test the effectiveness of the proposed modeling strategy, average hourly concentrations of nitrogen dioxide and nitrogen oxides from a congested urban arterial in Dublin city center were modeled using STS methodology. The prediction error estimates from the developed air quality model indicate that the STS model can be a useful tool in predicting nitrogen dioxide and nitrogen oxides concentrations in urban areas and will be particularly useful in situations where the information on external variables such as meteorology or traffic volume is not available.
Human plasma concentrations of tolbutamide and acetaminophen extrapolated from in vivo animal pharmacokinetics using in vitro human hepatic clearances and simple physiologically based pharmacokinetic modeling for radio-labeled microdose clinical studies

International Nuclear Information System (INIS)

Yamazaki, Hiroshi; Kunikane, Eriko; Nishiyama, Sayako; Murayama, Norie; Shimizu, Makiko; Sugiyama, Yuichi; Chiba, Koji; Ikeda, Toshihiko

2015-01-01

The aim of the current study was to extrapolate the pharmacokinetics of drug substances orally administered in humans from rat pharmacokinetic data using tolbutamide and acetaminophen as model compounds. Adjusted animal biomonitoring equivalents from rat studies based on reported plasma concentrations were scaled to human biomonitoring equivalents using known species allometric scaling factors. In this extrapolation, in vitro metabolic clearance data were obtained using liver preparations. Rates of tolbutamide elimination were roughly similar in rat and human liver microsome experiments, but acetaminophen elimination by rat liver microsomes and cytosolic preparations showed a tendency to be faster than those in humans. Using a simple physiologically based pharmacokinetic (PBPK) model, estimated human plasma concentrations of tolbutamide and acetaminophen were consistent with reported concentrations. Tolbutamide cleared in a roughly similar manner in humans and rats, but medical-dose levels of acetaminophen cleared (dependent on liver metabolism) more slowly from plasma in humans than it did in rats. The data presented here illustrate how pharmacokinetic data in combination with a simple PBPK model can be used to assist evaluations of the pharmacological/toxicological potential of new drug substances and for estimating human radiation exposures from radio-labeled drugs when planning human studies. (author)
Experiment and modeling of low-concentration methane catalytic combustion in a fluidized bed reactor

International Nuclear Information System (INIS)

Yang, Zhongqing; Yang, Peng; Zhang, Li; Guo, Mingnv; Ran, Jingyu

2016-01-01

Highlights: • The catalytic combustion of 0.15~3 vol. % low concentration methane in a fluidized bed was studied. • A mathematical model was proposed on the basis of gas–solid flow theory. • A comparative analysis of the established model with plug flow, mixed flow and K-L models was carried out. • The axial methane profile along fluidized bed was predicted by using the mathematical model. • The bed temperature has greater impact on methane conversion than fluidized velocity. - Abstract: This study undertakes a theoretical analysis and an experimental investigation into the characteristics of low-concentration methane catalytic combustion in a bubbling fluidized bed reactor using 0.5 wt.% Pd/Al_2O_3 as catalytic particles. A mathematical model is established based on gas–solid flow theory and is used to study the effects of bed temperature and fluidized velocity on methane catalytic combustion, and predict the dimensionless methane concentration axial profile in reactor. It is shown that methane conversion increases with bed temperature, but decreases with increasing fluidized velocity. These theoretical results are found to correlate well with the experimental measurement, with a deviation within 5%. A comparative analysis of the developed model with plug flow, mixed flow and K-L models is also carried out, and this further verifies that the established model better reflects the characteristics of low-concentration methane catalytic combustion in a bubbling fluidized bed. Using this reaction model, it was found that the difference in methane conversion between dense and freeboard zones gradually increases with bed temperature; the dense zone reaction levels off at 650 °C, thereby minimizing the difference between the dense and freeboard regions to around 15%. With an increase in bed temperature, the dimensionless methane concentration in the dense zone decreases exponentially, while in the splash zone, it varies from an exponential decay to a slow
Simultaneous pre-concentration and separation on simple paper-based analytical device for protein analysis.

Science.gov (United States)

Niu, Ji-Cheng; Zhou, Ting; Niu, Li-Li; Xie, Zhen-Sheng; Fang, Fang; Yang, Fu-Quan; Wu, Zhi-Yong

2018-02-01

In this work, fast isoelectric focusing (IEF) was successfully implemented on an open paper fluidic channel for simultaneous concentration and separation of proteins from complex matrix. With this simple device, IEF can be finished in 10 min with a resolution of 0.03 pH units and concentration factor of 10, as estimated by color model proteins by smartphone-based colorimetric detection. Fast detection of albumin from human serum and glycated hemoglobin (HBA1c) from blood cell was demonstrated. In addition, off-line identification of the model proteins from the IEF fractions with matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) was also shown. This PAD IEF is potentially useful either for point of care test (POCT) or biomarker analysis as a cost-effective sample pretreatment method.
Modelling acceptance of sunlight in high and low photovoltaic concentration

Energy Technology Data Exchange (ETDEWEB)

Leutz, Ralf, E-mail: ralf.leutz@leopil.com [Leutz Optics and Illumination UG (haftungsbeschränkt), Marburg (Germany)

2014-09-26

A simple model incorporating linear radiation characteristics, along with the optical trains and geometrical concentration ratios of solar concentrators is presented with performance examples for optical trains of HCPV, LCPV and benchmark flat-plate PV.

Modelling acceptance of sunlight in high and low photovoltaic concentration

Science.gov (United States)

Leutz, Ralf

2014-09-01

A simple model incorporating linear radiation characteristics, along with the optical trains and geometrical concentration ratios of solar concentrators is presented with performance examples for optical trains of HCPV, LCPV and benchmark flat-plate PV.
Modelling acceptance of sunlight in high and low photovoltaic concentration

International Nuclear Information System (INIS)

Leutz, Ralf

2014-01-01

A simple model incorporating linear radiation characteristics, along with the optical trains and geometrical concentration ratios of solar concentrators is presented with performance examples for optical trains of HCPV, LCPV and benchmark flat-plate PV
Prediction of Coal Face Gas Concentration by Multi-Scale Selective Ensemble Hybrid Modeling

Directory of Open Access Journals (Sweden)

WU Xiang

2014-06-01

Full Text Available A selective ensemble hybrid modeling prediction method based on wavelet transformation is proposed to improve the fitting and generalization capability of the existing prediction models of the coal face gas concentration, which has a strong stochastic volatility. Mallat algorithm was employed for the multi-scale decomposition and single-scale reconstruction of the gas concentration time series. Then, it predicted every subsequence by sparsely weighted multi unstable ELM(extreme learning machine predictor within method SERELM(sparse ensemble regressors of ELM. At last, it superimposed the predicted values of these models to obtain the predicted values of the original sequence. The proposed method takes advantage of characteristics of multi scale analysis of wavelet transformation, accuracy and fast characteristics of ELM prediction and the generalization ability of L1 regularized selective ensemble learning method. The results show that the forecast accuracy has large increase by using the proposed method. The average relative error is 0.65%, the maximum relative error is 4.16% and the probability of relative error less than 1% reaches 0.785.
A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model

Science.gov (United States)

Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kue-Young; Jun, Seong-Chun; Choung, Sungwook; Yun, Seong-Taek; Oh, Junho; Kim, Hyun-Jun

2017-11-01

In this study, a data-driven method for predicting CO2 leaks and associated concentrations from geological CO2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems.
A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model.

Science.gov (United States)

Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kue-Young; Jun, Seong-Chun; Choung, Sungwook; Yun, Seong-Taek; Oh, Junho; Kim, Hyun-Jun

2017-11-01

In this study, a data-driven method for predicting CO 2 leaks and associated concentrations from geological CO 2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO 2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO 2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO 2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems. Copyright © 2017 Elsevier B.V. All rights reserved.
Modeling of Groundwater Resources Heavy Metals Concentration Using Soft Computing Methods: Application of Different Types of Artificial Neural Networks

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Meysam Alizamir

2017-09-01

Full Text Available Nowadays, groundwater resources play a vital role as a source of drinking water in arid and semiarid regions and forecasting of pollutants content in these resources is very important. Therefore, this study aimed to compare two soft computing methods for modeling Cd, Pb and Zn concentration in groundwater resources of Asadabad Plain, Western Iran. The relative accuracy of several soft computing models, namely multi-layer perceptron (MLP and radial basis function (RBF for forecasting of heavy metals concentration have been investigated. In addition, Levenberg-Marquardt, gradient descent and conjugate gradient training algorithms were utilized for the MLP models. The ANN models for this study were developed using MATLAB R 2014 Software program. The MLP performs better than the other models for heavy metals concentration estimation. The simulation results revealed that MLP model was able to model heavy metals concentration in groundwater resources favorably. It generally is effectively utilized in environmental applications and in the water quality estimations. In addition, out of three algorithms, Levenberg-Marquardt was better than the others were. This study proposed soft computing modeling techniques for the prediction and estimation of heavy metals concentration in groundwater resources of Asadabad Plain. Based on collected data from the plain, MLP and RBF models were developed for each heavy metal. MLP can be utilized effectively in applications of prediction of heavy metals concentration in groundwater resources of Asadabad Plain.
Forecasting methodologies for Ganoderma spore concentration using combined statistical approaches and model evaluations

Science.gov (United States)

Sadyś, Magdalena; Skjøth, Carsten Ambelas; Kennedy, Roy

2016-04-01

High concentration levels of Ganoderma spp. spores were observed in Worcester, UK, during 2006-2010. These basidiospores are known to cause sensitization due to the allergen content and their small dimensions. This enables them to penetrate the lower part of the respiratory tract in humans. Establishment of a link between occurring symptoms of sensitization to Ganoderma spp. and other basidiospores is challenging due to lack of information regarding spore concentration in the air. Hence, aerobiological monitoring should be conducted, and if possible extended with the construction of forecast models. Daily mean concentration of allergenic Ganoderma spp. spores in the atmosphere of Worcester was measured using 7-day volumetric spore sampler through five consecutive years. The relationships between the presence of spores in the air and the weather parameters were examined. Forecast models were constructed for Ganoderma spp. spores using advanced statistical techniques, i.e. multivariate regression trees and artificial neural networks. Dew point temperature along with maximum temperature was the most important factor influencing the presence of spores in the air of Worcester. Based on these two major factors and several others of lesser importance, thresholds for certain levels of fungal spore concentration, i.e. low (0-49 s m-3), moderate (50-99 s m-3), high (100-149 s m-3) and very high (150 < n s m-3), could be designated. Despite some deviation in results obtained by artificial neural networks, authors have achieved a forecasting model, which was accurate (correlation between observed and predicted values varied from r s = 0.57 to r s = 0.68).
Prediction and analysis of near-road concentrations using a reduced-form emission/dispersion model

Directory of Open Access Journals (Sweden)

Kononowech Robert

2010-06-01

Full Text Available Abstract Background Near-road exposures of traffic-related air pollutants have been receiving increased attention due to evidence linking emissions from high-traffic roadways to adverse health outcomes. To date, most epidemiological and risk analyses have utilized simple but crude exposure indicators, most typically proximity measures, such as the distance between freeways and residences, to represent air quality impacts from traffic. This paper derives and analyzes a simplified microscale simulation model designed to predict short- (hourly to long-term (annual average pollutant concentrations near roads. Sensitivity analyses and case studies are used to highlight issues in predicting near-road exposures. Methods Process-based simulation models using a computationally efficient reduced-form response surface structure and a minimum number of inputs integrate the major determinants of air pollution exposures: traffic volume and vehicle emissions, meteorology, and receptor location. We identify the most influential variables and then derive a set of multiplicative submodels that match predictions from "parent" models MOBILE6.2 and CALINE4. The assembled model is applied to two case studies in the Detroit, Michigan area. The first predicts carbon monoxide (CO concentrations at a monitoring site near a freeway. The second predicts CO and PM2.5 concentrations in a dense receptor grid over a 1 km2 area around the intersection of two major roads. We analyze the spatial and temporal patterns of pollutant concentration predictions. Results Predicted CO concentrations showed reasonable agreement with annual average and 24-hour measurements, e.g., 59% of the 24-hr predictions were within a factor of two of observations in the warmer months when CO emissions are more consistent. The highest concentrations of both CO and PM2.5 were predicted to occur near intersections and downwind of major roads during periods of unfavorable meteorology (e.g., low wind
Filtering remotely sensed chlorophyll concentrations in the Red Sea using a space-time covariance model and a Kalman filter

KAUST Repository

Dreano, Denis

2015-04-27

A statistical model is proposed to filter satellite-derived chlorophyll concentration from the Red Sea, and to predict future chlorophyll concentrations. The seasonal trend is first estimated after filling missing chlorophyll data using an Empirical Orthogonal Function (EOF)-based algorithm (Data Interpolation EOF). The anomalies are then modeled as a stationary Gaussian process. A method proposed by Gneiting (2002) is used to construct positive-definite space-time covariance models for this process. After choosing an appropriate statistical model and identifying its parameters, Kriging is applied in the space-time domain to make a one step ahead prediction of the anomalies. The latter serves as the prediction model of a reduced-order Kalman filter, which is applied to assimilate and predict future chlorophyll concentrations. The proposed method decreases the root mean square (RMS) prediction error by about 11% compared with the seasonal average.
Filtering remotely sensed chlorophyll concentrations in the Red Sea using a space-time covariance model and a Kalman filter

KAUST Repository

Dreano, Denis; Mallick, Bani; Hoteit, Ibrahim

2015-01-01

A statistical model is proposed to filter satellite-derived chlorophyll concentration from the Red Sea, and to predict future chlorophyll concentrations. The seasonal trend is first estimated after filling missing chlorophyll data using an Empirical Orthogonal Function (EOF)-based algorithm (Data Interpolation EOF). The anomalies are then modeled as a stationary Gaussian process. A method proposed by Gneiting (2002) is used to construct positive-definite space-time covariance models for this process. After choosing an appropriate statistical model and identifying its parameters, Kriging is applied in the space-time domain to make a one step ahead prediction of the anomalies. The latter serves as the prediction model of a reduced-order Kalman filter, which is applied to assimilate and predict future chlorophyll concentrations. The proposed method decreases the root mean square (RMS) prediction error by about 11% compared with the seasonal average.
Parametric modelling of temporal variations in radon concentrations in homes

International Nuclear Information System (INIS)

Revzan, K.L.; Turk, B.H.; Harrison, J.; Nero, A.V.; Sextro, R.G.

1988-01-01

The 222 Rn concentrations in the living area, the basement, and the undelying soil of a New Jersey home have been measured at half-hour intervals over the course of a year, as have indoor and outdoor temperatures, wind speed and direction, and indoor-outdoor and basement-subslab pressures; in addition, periods of furnace opration have been logged. We generalize and extend an existing radon entry model in order to demonstrate the dependence of the radon concentration on the environmental variales and the extent of furnace use. The model contains parameters which are dependent on geological and structural factors which have not been measured or otherwise determined; statistical methods are used to find the best values of the parameters. The non-linear regression of the model predictions (over time) on the measured living area radon concentrations yields an R/aup 2/ of 0.88. 9 refs., 2 figs
Physical Property Modeling of Concentrated Cesium Eluate Solutions, Part I - Derivation of Models

Energy Technology Data Exchange (ETDEWEB)

Choi, A.S.; Pierce, R. A.; Edwards, T. B.; Calloway, T. B.

2005-09-15

Major analytes projected to be present in the Hanford Waste Treatment Plant cesium ion-exchange eluate solutions were identified from the available analytical data collected during radioactive bench-scale runs, and a test matrix of cesium eluate solutions was designed within the bounding concentrations of those analytes. A computer model simulating the semi-batch evaporation of cesium eluate solutions was run in conjunction with a multi-electrolyte aqueous system database to calculate the physical properties of each test matrix solution concentrated to the target endpoints of 80% and 100% saturation. The calculated physical properties were analyzed statistically and fitted into mathematical expressions for the bulk solubility, density, viscosity, heat capacity and volume reduction factor as a function of temperature and concentration of each major analyte in the eluate feed. The R{sup 2} of the resulting physical property models ranged from 0.89 to 0.99.
Increasing precision of turbidity-based suspended sediment concentration and load estimates.

Science.gov (United States)

Jastram, John D; Zipper, Carl E; Zelazny, Lucian W; Hyer, Kenneth E

2010-01-01

Turbidity is an effective tool for estimating and monitoring suspended sediments in aquatic systems. Turbidity can be measured in situ remotely and at fine temporal scales as a surrogate for suspended sediment concentration (SSC), providing opportunity for a more complete record of SSC than is possible with physical sampling approaches. However, there is variability in turbidity-based SSC estimates and in sediment loadings calculated from those estimates. This study investigated the potential to improve turbidity-based SSC, and by extension the resulting sediment loading estimates, by incorporating hydrologic variables that can be monitored remotely and continuously (typically 15-min intervals) into the SSC estimation procedure. On the Roanoke River in southwestern Virginia, hydrologic stage, turbidity, and other water-quality parameters were monitored with in situ instrumentation; suspended sediments were sampled manually during elevated turbidity events; samples were analyzed for SSC and physical properties including particle-size distribution and organic C content; and rainfall was quantified by geologic source area. The study identified physical properties of the suspended-sediment samples that contribute to SSC estimation variance and hydrologic variables that explained variability of those physical properties. Results indicated that the inclusion of any of the measured physical properties in turbidity-based SSC estimation models reduces unexplained variance. Further, the use of hydrologic variables to represent these physical properties, along with turbidity, resulted in a model, relying solely on data collected remotely and continuously, that estimated SSC with less variance than a conventional turbidity-based univariate model, allowing a more precise estimate of sediment loading, Modeling results are consistent with known mechanisms governing sediment transport in hydrologic systems.
Use of Artificial Neural Network Models to Predict Indicator Organism Concentrations in an Urban Watershed

Science.gov (United States)

Mas, D. M.; Ahlfeld, D. P.

2004-05-01

Forecasting stream water quality is important for numerous aspects of resource protection and management. Fecal coliform and enteroccocus are primary indicator organisms used to assess potential pathogen contamination. Consequently, modeling the occurrence and concentration of fecal coliform and enterococcus is an important tool in watershed management. In addition, analyzing the relationship between model input and predicted indicator organisms is useful for elucidating possible sources of contamination and mechanisms of transport. While many process-based, statistical, and empirical models exist for water quality prediction, artificial neural network (ANN) models are increasingly being used for forecasting of water resources variables because ANNs are often capable of modeling complex systems for which behavioral rules are either unknown or difficult to simulate. The performance of ANNs compared to more established modeling approaches such as multiple linear regression (MLR) remains an importance research question. Data collected the U.S. Geological Survey in the lower Charles River in Massachusetts, USA in 1999-2000 was examined to determine correlation between various water quality constituents and indicator organisms and to explore the relationship between rainfall characteristics and indicator organism concentrations. Using the results of the statistical analysis to guide the selection of explanatory variables, MLR was performed to develop predictive equations for wet weather and dry weather conditions. The results show that the best-performing predictor variables are generally consistent for both indicator organisms considered. In addition, the regression equations show increasing indicator organism concentrations as a function of suspended sediment concentrations and length of time since last precipitation event, suggesting accumulation and wash off as a key mechanism of pathogen transport under wet weather conditions. This research also presents the
Process intensification on membrane-based process for blackcurrant juice concentration

DEFF Research Database (Denmark)

Fjerbæk Søtoft, Lene; Rong, Ben-Guang; Christensen, Knud Villy

Juice concentrate production is a field where process intensification and novel concentration processes need to be implemented. The paper presents a systematic approach for process synthesis based on membrane processes for the concentration of blackcurrant juice, exemplified by the aroma recovery...... using combinations of vacuum membrane distillation and traditional distillation. Furthermore, the paper further suggests a novel method for the combination of nanofiltration, reverse osmosis and membrane distillation for the concentration of the dearomatized juice....
ACCURATE UNIVERSAL MODELS FOR THE MASS ACCRETION HISTORIES AND CONCENTRATIONS OF DARK MATTER HALOS

International Nuclear Information System (INIS)

Zhao, D. H.; Jing, Y. P.; Mo, H. J.; Boerner, G.

2009-01-01

A large amount of observations have constrained cosmological parameters and the initial density fluctuation spectrum to a very high accuracy. However, cosmological parameters change with time and the power index of the power spectrum dramatically varies with mass scale in the so-called concordance ΛCDM cosmology. Thus, any successful model for its structural evolution should work well simultaneously for various cosmological models and different power spectra. We use a large set of high-resolution N-body simulations of a variety of structure formation models (scale-free, standard CDM, open CDM, and ΛCDM) to study the mass accretion histories, the mass and redshift dependence of concentrations, and the concentration evolution histories of dark matter halos. We find that there is significant disagreement between the much-used empirical models in the literature and our simulations. Based on our simulation results, we find that the mass accretion rate of a halo is tightly correlated with a simple function of its mass, the redshift, parameters of the cosmology, and of the initial density fluctuation spectrum, which correctly disentangles the effects of all these factors and halo environments. We also find that the concentration of a halo is strongly correlated with the universe age when its progenitor on the mass accretion history first reaches 4% of its current mass. According to these correlations, we develop new empirical models for both the mass accretion histories and the concentration evolution histories of dark matter halos, and the latter can also be used to predict the mass and redshift dependence of halo concentrations. These models are accurate and universal: the same set of model parameters works well for different cosmological models and for halos of different masses at different redshifts, and in the ΛCDM case the model predictions match the simulation results very well even though halo mass is traced to about 0.0005 times the final mass, when
The concentration of kynurenine in rat model of asthma.

Directory of Open Access Journals (Sweden)

Barbara Mroczko

2008-06-01

Full Text Available Asthma is a chronic inflammatory disease that involves the immune system activation. Evidence is accumulating about the role of kynurenine pathway in the immune system regulation. The kynurenine pathway includes several metabolites of tryptophan, among others kynurenine (KYN. To study the immunological system regulation in asthma a simple and sensitive models of asthma are required. In the present study we induced rat model of asthma using ovalbumin (OVA sensitization followed by challenge with OVA. The development of asthma has been confirmed by plasma total IgE measurement and the histological examination. The concentration of KYN has been determined in plasma, lungs and liver by high-performance liquid chromatography (HPLC. In OVA sensitized rats the concentration of total IgE was statistically significantly increased as compared to VEH sensitized control groups (437.6 +/- 97.7 kU/l vs 159.2 +/- 22.7 kU/l, respectively; p< 0.01. In asthmatic animals, the number of eosinophils, neutrophils and mast cells increased considerably, and epithelial lesion and the increase in airway epithelium goblet cells and edema of bronchial mucosa were present. We did not observe any significant changes in the concentration of KYN in plasma, lungs or liver between studied groups. In conclusion, the concentration of KYN remains unchanged in asthmatic animals as compared to control groups. Further studies using rat model of asthma are warranted to establish the role of kynurenine pathway regulation in asthma.
A Simplified Model to Estimate the Concentration of Inorganic Ions and Heavy Metals in Rivers

Directory of Open Access Journals (Sweden)

Clemêncio Nhantumbo

2016-10-01

Full Text Available This paper presents a model that uses only pH, alkalinity, and temperature to estimate the concentrations of major ions in rivers (Na+, K+, Mg2+, Ca2+, HCO3−, SO42−, Cl−, and NO3− together with the equilibrium concentrations of minor ions and heavy metals (Fe3+, Mn2+, Cd2+, Cu2+, Al3+, Pb2+, and Zn2+. Mining operations have been increasing, which has led to changes in the pollution loads to receiving water systems, meanwhile most developing countries cannot afford water quality monitoring. A possible solution is to implement less resource-demanding monitoring programs, supported by mathematical models that minimize the required sampling and analysis, while still being able to detect water quality changes, thereby allowing implementation of measures to protect the water resources. The present model was developed using existing theories for: (i carbonate equilibrium; (ii total alkalinity; (iii statistics of major ions; (iv solubility of minerals; and (v conductivity of salts in water. The model includes two options to estimate the concentrations of major ions: (1 a generalized method, which employs standard values from a world-wide data base; and (2 a customized method, which requires specific baseline data for the river of interest. The model was tested using data from four monitoring stations in Swedish rivers with satisfactory results.
A novel diagnosis method for a Hall plates-based rotary encoder with a magnetic concentrator.

Science.gov (United States)

Meng, Bumin; Wang, Yaonan; Sun, Wei; Yuan, Xiaofang

2014-07-31

In the last few years, rotary encoders based on two-dimensional complementary metal oxide semiconductors (CMOS) Hall plates with a magnetic concentrator have been developed to measure contactless absolute angle. There are various error factors influencing the measuring accuracy, which are difficult to locate after the assembly of encoder. In this paper, a model-based rapid diagnosis method is presented. Based on an analysis of the error mechanism, an error model is built to compare minimum residual angle error and to quantify the error factors. Additionally, a modified particle swarm optimization (PSO) algorithm is used to reduce the calculated amount. The simulation and experimental results show that this diagnosis method is feasible to quantify the causes of the error and to reduce iteration significantly.
Modeling air concentration over macro roughness conditions by Artificial Intelligence techniques

Science.gov (United States)

Roshni, T.; Pagliara, S.

2018-05-01

Aeration is improved in rivers by the turbulence created in the flow over macro and intermediate roughness conditions. Macro and intermediate roughness flow conditions are generated by flows over block ramps or rock chutes. The measurements are taken in uniform flow region. Efficacy of soft computing methods in modeling hydraulic parameters are not common so far. In this study, modeling efficiencies of MPMR model and FFNN model are found for estimating the air concentration over block ramps under macro roughness conditions. The experimental data are used for training and testing phases. Potential capability of MPMR and FFNN model in estimating air concentration are proved through this study.

Modelling hourly dissolved oxygen concentration (DO) using dynamic evolving neural-fuzzy inference system (DENFIS)-based approach: case study of Klamath River at Miller Island Boat Ramp, OR, USA.

Science.gov (United States)

Heddam, Salim

2014-01-01

In this study, we present application of an artificial intelligence (AI) technique model called dynamic evolving neural-fuzzy inference system (DENFIS) based on an evolving clustering method (ECM), for modelling dissolved oxygen concentration in a river. To demonstrate the forecasting capability of DENFIS, a one year period from 1 January 2009 to 30 December 2009, of hourly experimental water quality data collected by the United States Geological Survey (USGS Station No: 420853121505500) station at Klamath River at Miller Island Boat Ramp, OR, USA, were used for model development. Two DENFIS-based models are presented and compared. The two DENFIS systems are: (1) offline-based system named DENFIS-OF, and (2) online-based system, named DENFIS-ON. The input variables used for the two models are water pH, temperature, specific conductance, and sensor depth. The performances of the models are evaluated using root mean square errors (RMSE), mean absolute error (MAE), Willmott index of agreement (d) and correlation coefficient (CC) statistics. The lowest root mean square error and highest correlation coefficient values were obtained with the DENFIS-ON method. The results obtained with DENFIS models are compared with linear (multiple linear regression, MLR) and nonlinear (multi-layer perceptron neural networks, MLPNN) methods. This study demonstrates that DENFIS-ON investigated herein outperforms all the proposed techniques for DO modelling.
Modified bond model for shear in slabs under concentrated loads

NARCIS (Netherlands)

Lantsoght, E.O.L.; Van der Veen, C.; De Boer, A.

2015-01-01

Slabs subjected to concentrated loads close to supports, as occurring for truck loads on slab bridges, are less studied than beams in shear or slab-column connections in punching. To predict the shear capacity for this case, the Bond Model for concentric punching shear was studied initially.
An algorithm for variational data assimilation of contact concentration measurements for atmospheric chemistry models

Science.gov (United States)

Penenko, Alexey; Penenko, Vladimir

2014-05-01

Contact concentration measurement data assimilation problem is considered for convection-diffusion-reaction models originating from the atmospheric chemistry study. High dimensionality of models imposes strict requirements on the computational efficiency of the algorithms. Data assimilation is carried out within the variation approach on a single time step of the approximated model. A control function is introduced into the source term of the model to provide flexibility for data assimilation. This function is evaluated as the minimum of the target functional that connects its norm to a misfit between measured and model-simulated data. In the case mathematical model acts as a natural Tikhonov regularizer for the ill-posed measurement data inversion problem. This provides flow-dependent and physically-plausible structure of the resulting analysis and reduces a need to calculate model error covariance matrices that are sought within conventional approach to data assimilation. The advantage comes at the cost of the adjoint problem solution. This issue is solved within the frameworks of splitting-based realization of the basic convection-diffusion-reaction model. The model is split with respect to physical processes and spatial variables. A contact measurement data is assimilated on each one-dimensional convection-diffusion splitting stage. In this case a computationally-efficient direct scheme for both direct and adjoint problem solution can be constructed based on the matrix sweep method. Data assimilation (or regularization) parameter that regulates ratio between model and data in the resulting analysis is obtained with Morozov discrepancy principle. For the proper performance the algorithm takes measurement noise estimation. In the case of Gaussian errors the probability that the used Chi-squared-based estimate is the upper one acts as the assimilation parameter. A solution obtained can be used as the initial guess for data assimilation algorithms that assimilate
Planetary boundary layer model for estimating the radionuclides concentration in accidental liberations

International Nuclear Information System (INIS)

Molnary, Leslie de

2002-01-01

A two layer bulk model is used to simulate numerically the time and spatial evolution of concentration of radionuclides in the Planetary Boundary Layer (PBL) for convective and stable conditions. In this model, the closure hypothesis are based on the integrated version of the Turbulent Kinetics Energy equation. This type of model was adopted here because it is numerically simple to be applied operationally in routine and emergency support systems of atmospheric releases at nuclear power plants, and the hypothesis of the efficiency of the vertical mixing seems to be physically reasonable to simulate PBL evolution for high wind conditions and stable conditions in subtropical latitudes regions. In order to validate the model, numerical simulations were carried out with initial and boundary conditions based on vertical profiles of temperatures and horizontal wind speed and direction obtained from tethered balloon soundings, synoptic charts at 850 hPa and surface observations. Comparisons between a 24 hour long numerical simulation and observations indicate that the model is capable of reproduce the diurnal evolution of temperature and horizontal wind during the convective regime. During stable conditions, the slab model was able to simulate the intensity of the surface inversion as a difference between the mixed layer and the surface temperature. The simulated mixed layer height matches with observations during the convective and stable regime. (author)
Nitrogen dioxide concentrations in neighborhoods adjacent to a commercial airport: a land use regression modeling study.

Science.gov (United States)

Adamkiewicz, Gary; Hsu, Hsiao-Hsien; Vallarino, Jose; Melly, Steven J; Spengler, John D; Levy, Jonathan I

2010-11-17

There is growing concern in communities surrounding airports regarding the contribution of various emission sources (such as aircraft and ground support equipment) to nearby ambient concentrations. We used extensive monitoring of nitrogen dioxide (NO2) in neighborhoods surrounding T.F. Green Airport in Warwick, RI, and land-use regression (LUR) modeling techniques to determine the impact of proximity to the airport and local traffic on these concentrations. Palmes diffusion tube samplers were deployed along the airport's fence line and within surrounding neighborhoods for one to two weeks. In total, 644 measurements were collected over three sampling campaigns (October 2007, March 2008 and June 2008) and each sampling location was geocoded. GIS-based variables were created as proxies for local traffic and airport activity. A forward stepwise regression methodology was employed to create general linear models (GLMs) of NO2 variability near the airport. The effect of local meteorology on associations with GIS-based variables was also explored. Higher concentrations of NO2 were seen near the airport terminal, entrance roads to the terminal, and near major roads, with qualitatively consistent spatial patterns between seasons. In our final multivariate model (R2 = 0.32), the local influences of highways and arterial/collector roads were statistically significant, as were local traffic density and distance to the airport terminal (all p GIS variables, and the regression model structure was robust to various model-building approaches. Our study has shown that there are clear local variations in NO2 in the neighborhoods that surround an urban airport, which are spatially consistent across seasons. LUR modeling demonstrated a strong influence of local traffic, except the smallest roads that predominate in residential areas, as well as proximity to the airport terminal.
Analysis of the repaglinide concentration increase produced by gemfibrozil and itraconazole based on the inhibition of the hepatic uptake transporter and metabolic enzymes.

Science.gov (United States)

Kudo, Toshiyuki; Hisaka, Akihiro; Sugiyama, Yuichi; Ito, Kiyomi

2013-02-01

The plasma concentration of repaglinide is reported to increase greatly when given after repeated oral administration of itraconazole and gemfibrozil. The present study analyzed this interaction based on a physiologically based pharmacokinetic (PBPK) model incorporating inhibition of the hepatic uptake transporter and metabolic enzymes involved in repaglinide disposition. Firstly, the plasma concentration profiles of inhibitors (itraconazole, gemfibrozil, and gemfibrozil glucuronide) were reproduced by a PBPK model to obtain their pharmacokinetic parameters. The plasma concentration profiles of repaglinide were then analyzed by a PBPK model, together with those of the inhibitors, assuming a competitive inhibition of CYP3A4 by itraconazole, mechanism-based inhibition of CYP2C8 by gemfibrozil glucuronide, and inhibition of organic anion transporting polypeptide (OATP) 1B1 by gemfibrozil and its glucuronide. The plasma concentration profiles of repaglinide were well reproduced by the PBPK model based on the above assumptions, and the optimized values for the inhibition constants (0.0676 nM for itraconazole against CYP3A4; 14.2 μM for gemfibrozil against OATP1B1; and 5.48 μM for gemfibrozil glucuronide against OATP1B1) and the fraction of repaglinide metabolized by CYP2C8 (0.801) were consistent with the reported values. The validity of the obtained parameters was further confirmed by sensitivity analyses and by reproducing the repaglinide concentration increase produced by concomitant gemfibrozil administration at various timings/doses. The present findings suggested that the reported concentration increase of repaglinide, suggestive of synergistic effects of the coadministered inhibitors, can be quantitatively explained by the simultaneous inhibition of the multiple clearance pathways of repaglinide.
Improved OAM-Based Radar Targets Detection Using Uniform Concentric Circular Arrays

Directory of Open Access Journals (Sweden)

Mingtuan Lin

2016-01-01

Full Text Available Without any relative moves or beam scanning, the novel Orbital-Angular-Momentum- (OAM- based radar targets detection technique using uniform concentric circular arrays (UCCAs shows the azimuthal estimation ability, which provides new perspective for radar system design. However, the main estimation method, that is, Fast Fourier Transform (FFT, under this scheme suffers from low resolution. As a solution, this paper rebuilds the OAM-based radar targets detection model and introduces the multiple signal classification (MUSIC algorithm to improve the resolution for detecting targets within the main lobes. The spatial smoothing technique is proposed to tackle the coherent problem brought by the proposed model. Analytical study and simulation demonstrate the superresolution estimation capacity the MUSIC algorithm can achieve for detecting targets within the main lobes. The performance of the MUSIC algorithm to detect targets not illuminated by the main lobes is further evaluated. Despite the fact that MUSIC algorithm loses the resolution advantage under this case, its estimation is more robust than that of the FFT method. Overall, the proposed MUSIC algorithm for the OAM-based radar system demonstrates the superresolution ability for detecting targets within the main lobes and good robustness for targets out of the main lobes.
[Application of predictive model to estimate concentrations of chemical substances in the work environment].

Science.gov (United States)

Kupczewska-Dobecka, Małgorzata; Czerczak, Sławomir; Jakubowski, Marek; Maciaszek, Piotr; Janasik, Beata

2010-01-01

Based on the Estimation and Assessment of Substance Exposure (EASE) predictive model implemented into the European Union System for the Evaluation of Substances (EUSES 2.1.), the exposure to three chosen organic solvents: toluene, ethyl acetate and acetone was estimated and compared with the results of measurements in workplaces. Prior to validation, the EASE model was pretested using three exposure scenarios. The scenarios differed in the decision tree of pattern of use. Five substances were chosen for the test: 1,4-dioxane tert-methyl-butyl ether, diethylamine, 1,1,1-trichloroethane and bisphenol A. After testing the EASE model, the next step was the validation by estimating the exposure level and comparing it with the results of measurements in the workplace. We used the results of measurements of toluene, ethyl acetate and acetone concentrations in the work environment of a paint and lacquer factory, a shoe factory and a refinery. Three types of exposure scenarios, adaptable to the description of working conditions were chosen to estimate inhalation exposure. Comparison of calculated exposure to toluene, ethyl acetate and acetone with measurements in workplaces showed that model predictions are comparable with the measurement results. Only for low concentration ranges, the measured concentrations were higher than those predicted. EASE is a clear, consistent system, which can be successfully used as an additional component of inhalation exposure estimation. If the measurement data are available, they should be preferred to values estimated from models. In addition to inhalation exposure estimation, the EASE model makes it possible not only to assess exposure-related risk but also to predict workers' dermal exposure.
Modeling microelectrode biosensors: free-flow calibration can substantially underestimate tissue concentrations.

Science.gov (United States)

Newton, Adam J H; Wall, Mark J; Richardson, Magnus J E

2017-03-01

Microelectrode amperometric biosensors are widely used to measure concentrations of analytes in solution and tissue including acetylcholine, adenosine, glucose, and glutamate. A great deal of experimental and modeling effort has been directed at quantifying the response of the biosensors themselves; however, the influence that the macroscopic tissue environment has on biosensor response has not been subjected to the same level of scrutiny. Here we identify an important issue in the way microelectrode biosensors are calibrated that is likely to have led to underestimations of analyte tissue concentrations. Concentration in tissue is typically determined by comparing the biosensor signal to that measured in free-flow calibration conditions. In a free-flow environment the concentration of the analyte at the outer surface of the biosensor can be considered constant. However, in tissue the analyte reaches the biosensor surface by diffusion through the extracellular space. Because the enzymes in the biosensor break down the analyte, a density gradient is set up resulting in a significantly lower concentration of analyte near the biosensor surface. This effect is compounded by the diminished volume fraction (porosity) and reduction in the diffusion coefficient due to obstructions (tortuosity) in tissue. We demonstrate this effect through modeling and experimentally verify our predictions in diffusive environments. NEW & NOTEWORTHY Microelectrode biosensors are typically calibrated in a free-flow environment where the concentrations at the biosensor surface are constant. However, when in tissue, the analyte reaches the biosensor via diffusion and so analyte breakdown by the biosensor results in a concentration gradient and consequently a lower concentration around the biosensor. This effect means that naive free-flow calibration will underestimate tissue concentration. We develop mathematical models to better quantify the discrepancy between the calibration and tissue
Modeling extreme PM10 concentration in Malaysia using generalized extreme value distribution

Science.gov (United States)

Hasan, Husna; Mansor, Nadiah; Salleh, Nur Hanim Mohd

2015-05-01

Extreme PM10 concentration from the Air Pollutant Index (API) at thirteen monitoring stations in Malaysia is modeled using the Generalized Extreme Value (GEV) distribution. The data is blocked into monthly selection period. The Mann-Kendall (MK) test suggests a non-stationary model so two models are considered for the stations with trend. The likelihood ratio test is used to determine the best fitted model and the result shows that only two stations favor the non-stationary model (Model 2) while the other eleven stations favor stationary model (Model 1). The return level of PM10 concentration that is expected to exceed the maximum once within a selected period is obtained.
Developing the remote sensing-based early warning system for monitoring TSS concentrations in Lake Mead.

Science.gov (United States)

Imen, Sanaz; Chang, Ni-Bin; Yang, Y Jeffrey

2015-09-01

Adjustment of the water treatment process to changes in water quality is a focus area for engineers and managers of water treatment plants. The desired and preferred capability depends on timely and quantitative knowledge of water quality monitoring in terms of total suspended solids (TSS) concentrations. This paper presents the development of a suite of nowcasting and forecasting methods by using high-resolution remote-sensing-based monitoring techniques on a daily basis. First, the integrated data fusion and mining (IDFM) technique was applied to develop a near real-time monitoring system for daily nowcasting of the TSS concentrations. Then a nonlinear autoregressive neural network with external input (NARXNET) model was selected and applied for forecasting analysis of the changes in TSS concentrations over time on a rolling basis onward using the IDFM technique. The implementation of such an integrated forecasting and nowcasting approach was assessed by a case study at Lake Mead hosting the water intake for Las Vegas, Nevada, in the water-stressed western U.S. Long-term monthly averaged results showed no simultaneous impact from forest fire events on accelerating the rise of TSS concentration. However, the results showed a probable impact of a decade of drought on increasing TSS concentration in the Colorado River Arm and Overton Arm. Results of the forecasting model highlight the reservoir water level as a significant parameter in predicting TSS in Lake Mead. In addition, the R-squared value of 0.98 and the root mean square error of 0.5 between the observed and predicted TSS values demonstrates the reliability and application potential of this remote sensing-based early warning system in terms of TSS projections at a drinking water intake. Copyright © 2015 Elsevier Ltd. All rights reserved.
Concentric Tube Robot Design and Optimization Based on Task and Anatomical Constraints

Science.gov (United States)

Bergeles, Christos; Gosline, Andrew H.; Vasilyev, Nikolay V.; Codd, Patrick J.; del Nido, Pedro J.; Dupont, Pierre E.

2015-01-01

Concentric tube robots are catheter-sized continuum robots that are well suited for minimally invasive surgery inside confined body cavities. These robots are constructed from sets of pre-curved superelastic tubes and are capable of assuming complex 3D curves. The family of 3D curves that the robot can assume depends on the number, curvatures, lengths and stiffnesses of the tubes in its tube set. The robot design problem involves solving for a tube set that will produce the family of curves necessary to perform a surgical procedure. At a minimum, these curves must enable the robot to smoothly extend into the body and to manipulate tools over the desired surgical workspace while respecting anatomical constraints. This paper introduces an optimization framework that utilizes procedureor patient-specific image-based anatomical models along with surgical workspace requirements to generate robot tube set designs. The algorithm searches for designs that minimize robot length and curvature and for which all paths required for the procedure consist of stable robot configurations. Two mechanics-based kinematic models are used. Initial designs are sought using a model assuming torsional rigidity. These designs are then refined using a torsionally-compliant model. The approach is illustrated with clinically relevant examples from neurosurgery and intracardiac surgery. PMID:26380575
Modeling of a 5-cell direct methanol fuel cell using adaptive-network-based fuzzy inference systems

Science.gov (United States)

Wang, Rongrong; Qi, Liang; Xie, Xiaofeng; Ding, Qingqing; Li, Chunwen; Ma, ChenChi M.

The methanol concentrations, temperature and current were considered as inputs, the cell voltage was taken as output, and the performance of a direct methanol fuel cell (DMFC) was modeled by adaptive-network-based fuzzy inference systems (ANFIS). The artificial neural network (ANN) and polynomial-based models were selected to be compared with the ANFIS in respect of quality and accuracy. Based on the ANFIS model obtained, the characteristics of the DMFC were studied. The results show that temperature and methanol concentration greatly affect the performance of the DMFC. Within a restricted current range, the methanol concentration does not greatly affect the stack voltage. In order to obtain higher fuel utilization efficiency, the methanol concentrations and temperatures should be adjusted according to the load on the system.
Modeling of a 5-cell direct methanol fuel cell using adaptive-network-based fuzzy inference systems

Energy Technology Data Exchange (ETDEWEB)

Wang, Rongrong; Li, Chunwen [Department of Automation, Tsinghua University, Beijing 100084 (China); Qi, Liang; Xie, Xiaofeng [Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084 (China); Ding, Qingqing [Department of Electrical Engineering, Tsinghua University, Beijing 100084 (China); Ma, ChenChi M. [National Tsing Hua University, Hsinchu 300 (China)

2008-12-01

The methanol concentrations, temperature and current were considered as inputs, the cell voltage was taken as output, and the performance of a direct methanol fuel cell (DMFC) was modeled by adaptive-network-based fuzzy inference systems (ANFIS). The artificial neural network (ANN) and polynomial-based models were selected to be compared with the ANFIS in respect of quality and accuracy. Based on the ANFIS model obtained, the characteristics of the DMFC were studied. The results show that temperature and methanol concentration greatly affect the performance of the DMFC. Within a restricted current range, the methanol concentration does not greatly affect the stack voltage. In order to obtain higher fuel utilization efficiency, the methanol concentrations and temperatures should be adjusted according to the load on the system. (author)
MODELING NITRATE CONCENTRATION IN GROUND WATER USING REGRESSION AND NEURAL NETWORKS

OpenAIRE

Ramasamy, Nacha; Krishnan, Palaniappa; Bernard, John C.; Ritter, William F.

2003-01-01

Nitrate concentration in ground water is a major problem in specific agricultural areas. Using regression and neural networks, this study models nitrate concentration in ground water as a function of iron concentration in ground water, season and distance of the well from a poultry house. Results from both techniques are comparable and show that the distance of the well from a poultry house has a significant effect on nitrate concentration in groundwater.
Modeling groundwater nitrate concentrations in private wells in Iowa

Science.gov (United States)

Wheeler, David C.; Nolan, Bernard T.; Flory, Abigail R.; DellaValle, Curt T.; Ward, Mary H.

2015-01-01

Contamination of drinking water by nitrate is a growing problem in many agricultural areas of the country. Ingested nitrate can lead to the endogenous formation of N-nitroso compounds, potent carcinogens. We developed a predictive model for nitrate concentrations in private wells in Iowa. Using 34,084 measurements of nitrate in private wells, we trained and tested random forest models to predict log nitrate levels by systematically assessing the predictive performance of 179 variables in 36 thematic groups (well depth, distance to sinkholes, location, land use, soil characteristics, nitrogen inputs, meteorology, and other factors). The final model contained 66 variables in 17 groups. Some of the most important variables were well depth, slope length within 1 km of the well, year of sample, and distance to nearest animal feeding operation. The correlation between observed and estimated nitrate concentrations was excellent in the training set (r-square = 0.77) and was acceptable in the testing set (r-square = 0.38). The random forest model had substantially better predictive performance than a traditional linear regression model or a regression tree. Our model will be used to investigate the association between nitrate levels in drinking water and cancer risk in the Iowa participants of the Agricultural Health Study cohort.
Modeling groundwater nitrate concentrations in private wells in Iowa.

Science.gov (United States)

Wheeler, David C; Nolan, Bernard T; Flory, Abigail R; DellaValle, Curt T; Ward, Mary H

2015-12-01

Contamination of drinking water by nitrate is a growing problem in many agricultural areas of the country. Ingested nitrate can lead to the endogenous formation of N-nitroso compounds, potent carcinogens. We developed a predictive model for nitrate concentrations in private wells in Iowa. Using 34,084 measurements of nitrate in private wells, we trained and tested random forest models to predict log nitrate levels by systematically assessing the predictive performance of 179 variables in 36 thematic groups (well depth, distance to sinkholes, location, land use, soil characteristics, nitrogen inputs, meteorology, and other factors). The final model contained 66 variables in 17 groups. Some of the most important variables were well depth, slope length within 1 km of the well, year of sample, and distance to nearest animal feeding operation. The correlation between observed and estimated nitrate concentrations was excellent in the training set (r-square=0.77) and was acceptable in the testing set (r-square=0.38). The random forest model had substantially better predictive performance than a traditional linear regression model or a regression tree. Our model will be used to investigate the association between nitrate levels in drinking water and cancer risk in the Iowa participants of the Agricultural Health Study cohort. Copyright © 2015 Elsevier B.V. All rights reserved.
A statistical analysis of three ensembles of crop model responses totemperature and CO₂concentration

DEFF Research Database (Denmark)

Makowski, D; Asseng, S; Ewert, F.

2015-01-01

Ensembles of process-based crop models are increasingly used to simulate crop growth for scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of simulated crop yield data...
Illumination uniformity issue explored via two-stage solar concentrator system based on Fresnel lens and compound flat concentrator

International Nuclear Information System (INIS)

Yeh, Naichia

2016-01-01

This paper illustrates details about the solar radiation distribution on the target of a two-stage solar concentrator that combines the Fresnel lens (FL) and the compound flat concentrator (CFC). The paper starts with a review of some FL development milestones such as the two-stage systems and the comparisons of flat vs. curved lenses in addition to the most noteworthy FL-based solar energy application, concentration photovoltaic (CPV). Through the review of the FL based CPV and two-stage concentrators, this study leads to the development of an algorithm to explore the spectrum distribution insight on the receiver of a two-stage (FL plus CFC) solar concentration system. It established the potential for using a correctly positioned 2nd stage reflector of right dimension to selectively redirect the desired spectrum on the target area so as to enhance the concentration flux intensity and uniformity at the same time. The study also helped to chart out the approximate locations of certain spectrum segments on the FL's target area, which is useful for exploring the spectrum control mechanism via the Fresnel lenses. - Highlights: • Map out the approximate locations of spectrum segments on FL's focal area. • Use the 2nd stage reflector to selectively reflect the desired spectrum on target. • Explore the spectrum distribution insight on FL solar concentrators' target area.
Modelling concentration-analgesia relationships for morphine to evaluate experimental pain models

DEFF Research Database (Denmark)

Sverrisdóttir, Eva; Foster, David John Richard; Upton, Richard Neil

2015-01-01

The aim of this study was to develop population pharmacokinetic-pharmacodynamic models for morphine in experimental pain induced by skin heat and muscle pressure, and to evaluate the experimental pain models with regard to assessment of morphine pharmacodynamics. In a randomized, double......-blind, placebo-controlled, crossover study, 39 healthy volunteers received an oral dose of 30 mg morphine hydrochloride or placebo. Non-linear mixed effects modelling was used to describe the plasma concentrations of morphine and metabolites, and the analgesic effect of morphine on experimental pain in skin...... and muscle. Baseline pain metrics varied between individuals and occasions, and were described with interindividual and interoccasion variability. Placebo-response did not change with time. For both pain metrics, morphine effect was proportional to baseline pain and was described with a linear model...

Global Monthly CO2 Flux Inversion Based on Results of Terrestrial Ecosystem Modeling

Science.gov (United States)

Deng, F.; Chen, J.; Peters, W.; Krol, M.

2008-12-01

Most of our understanding of the sources and sinks of atmospheric CO2 has come from inverse studies of atmospheric CO2 concentration measurements. However, the number of currently available observation stations and our ability to simulate the diurnal planetary boundary layer evolution over continental regions essentially limit the number of regions that can be reliably inverted globally, especially over continental areas. In order to overcome these restrictions, a nested inverse modeling system was developed based on the Bayesian principle for estimating carbon fluxes of 30 regions in North America and 20 regions for the rest of the globe. Inverse modeling was conducted in monthly steps using CO2 concentration measurements of 5 years (2000 - 2005) with the following two models: (a) An atmospheric transport model (TM5) is used to generate the transport matrix where the diurnal variation n of atmospheric CO2 concentration is considered to enhance the use of the afternoon-hour average CO2 concentration measurements over the continental sites. (b) A process-based terrestrial ecosystem model (BEPS) is used to produce hourly step carbon fluxes, which could minimize the limitation due to our inability to solve the inverse problem in a high resolution, as the background of our inversion. We will present our recent results achieved through a combination of the bottom-up modeling with BEPS and the top-down modeling based on TM5 driven by offline meteorological fields generated by the European Centre for Medium Range Weather Forecast (ECMFW).
Technological research of bituminization of model concentrates of radioactive wastes

International Nuclear Information System (INIS)

Breza, M.; Timulak, J.; Krejci, F.; Pekar, A.; Krajc, T.; Hladky, E.

1986-01-01

In the years 1981-1984 research was carried out of bituminization technology on model concentrates whose physical and chemical composition approximated that of radioactive concentrates from WWER-440 type nuclear power plants. The bitumen emulsion Silembit EAS-60 was used for bituminization. The process of bituminization took place at a temperature of approximately 180 degC in a rotary film evaporator into which was proportioned both the model concentrate and the bitumen emulsion heated to a temperature of 50 to 60 degC. All basic technical parameters of the process were controlled on an hourly basis. The experiments demonstrated the following technological conditions of bituminization: pressure of heating steam must be maintained within 0.85 and 0.95 MPa; optimal output of the evaporator (type FRO-2 S) is 100 to 120 kg of evaporated water/h; concentrates with a borate content must be heated to a temperature of 80 to 90 degC prior to their introduction into the evaporator; the pH value of the concentrates must be adjusted such as to be within the range of 11.0 to 11.5 or 7.0 to 8.0; the concentrate and the bitumen emulsion must be proportioned evenly; the optimal speed of the rotor is 500 r.p.m.; the load of the rotor must be monitored continuously because it indicates changes in the flow values of the bitumen composition. The experience gained was used in the operation of the pilot plant bituminization line for actual concentrates from the V-1 nuclear power plant. (A.K.)
A modeling approach to compare ΣPCB concentrations between congener-specific analyses

Science.gov (United States)

Gibson, Polly P.; Mills, Marc A.; Kraus, Johanna M.; Walters, David M.

2017-01-01

Changes in analytical methods over time pose problems for assessing long-term trends in environmental contamination by polychlorinated biphenyls (PCBs). Congener-specific analyses vary widely in the number and identity of the 209 distinct PCB chemical configurations (congeners) that are quantified, leading to inconsistencies among summed PCB concentrations (ΣPCB) reported by different studies. Here we present a modeling approach using linear regression to compare ΣPCB concentrations derived from different congener-specific analyses measuring different co-eluting groups. The approach can be used to develop a specific conversion model between any two sets of congener-specific analytical data from similar samples (similar matrix and geographic origin). We demonstrate the method by developing a conversion model for an example data set that includes data from two different analytical methods, a low resolution method quantifying 119 congeners and a high resolution method quantifying all 209 congeners. We used the model to show that the 119-congener set captured most (93%) of the total PCB concentration (i.e., Σ209PCB) in sediment and biological samples. ΣPCB concentrations estimated using the model closely matched measured values (mean relative percent difference = 9.6). General applications of the modeling approach include (a) generating comparable ΣPCB concentrations for samples that were analyzed for different congener sets; and (b) estimating the proportional contribution of different congener sets to ΣPCB. This approach may be especially valuable for enabling comparison of long-term remediation monitoring results even as analytical methods change over time.
Physiologically Based Pharmacokinetic Model for Terbinafine in Rats and Humans

Science.gov (United States)

Hosseini-Yeganeh, Mahboubeh; McLachlan, Andrew J.

2002-01-01

The aim of this study was to develop a physiologically based pharmacokinetic (PB-PK) model capable of describing and predicting terbinafine concentrations in plasma and tissues in rats and humans. A PB-PK model consisting of 12 tissue and 2 blood compartments was developed using concentration-time data for tissues from rats (n = 33) after intravenous bolus administration of terbinafine (6 mg/kg of body weight). It was assumed that all tissues except skin and testis tissues were well-stirred compartments with perfusion rate limitations. The uptake of terbinafine into skin and testis tissues was described by a PB-PK model which incorporates a membrane permeability rate limitation. The concentration-time data for terbinafine in human plasma and tissues were predicted by use of a scaled-up PB-PK model, which took oral absorption into consideration. The predictions obtained from the global PB-PK model for the concentration-time profile of terbinafine in human plasma and tissues were in close agreement with the observed concentration data for rats. The scaled-up PB-PK model provided an excellent prediction of published terbinafine concentration-time data obtained after the administration of single and multiple oral doses in humans. The estimated volume of distribution at steady state (Vss) obtained from the PB-PK model agreed with the reported value of 11 liters/kg. The apparent volume of distribution of terbinafine in skin and adipose tissues accounted for 41 and 52%, respectively, of the Vss for humans, indicating that uptake into and redistribution from these tissues dominate the pharmacokinetic profile of terbinafine. The PB-PK model developed in this study was capable of accurately predicting the plasma and tissue terbinafine concentrations in both rats and humans and provides insight into the physiological factors that determine terbinafine disposition. PMID:12069977
Modeling the Factors Impacting Pesticide Concentrations in Groundwater Wells

DEFF Research Database (Denmark)

Aisopou, Angeliki; Binning, Philip John; Albrechtsen, Hans-Jørgen

2015-01-01

This study examines the effect of pumping, hydrogeology, and pesticide characteristics on pesticide concentrations in production wells using a reactive transport model in two conceptual hydrogeologic systems; a layered aquifer with and without a stream present. The pumping rate can significantly...... affect the pesticide breakthrough time and maximum concentration at the well. The effect of the pumping rate on the pesticide concentration depends on the hydrogeology of the aquifer; in a layered aquifer, a high pumping rate resulted in a considerably different breakthrough than a low pumping rate......, while in an aquifer with a stream the effect of the pumping rate was insignificant. Pesticide application history and properties have also a great impact on the effect of the pumping rate on the concentration at the well. The findings of the study show that variable pumping rates can generate temporal...
Theoretical optimization of base doping concentration for radiation resistance of InGaP subcells of InGaP/GaAs/Ge based on minority-carrier lifetime

International Nuclear Information System (INIS)

Elfiky, Dalia; Yamaguchi, Masafumi; Sasaki, Takuo

2010-01-01

One of the fundamental objectives for research and development of space solar cells is to improve their radiation resistance. InGaP solar cells with low base carrier concentrations under low-energy proton irradiations have shown high radiation resistances. In this study, an analytical model for low-energy proton radiation damage to InGaP subcells based on a fundamental approach for radiative and nonradiative recombinations has been proposed. The radiation resistance of InGaP subcells as a function of base carrier concentration has been analyzed by using the radiative recombination lifetime and damage coefficient K for the minority-carrier lifetime of InGaP. Numerical analysis shows that an InGaP solar cell with a lower base carrier concentration is more radiation-resistant. Satisfactory agreements between analytical and experimental results have been obtained, and these results show the validity of the analytical procedure. The damage coefficients for minority-carrier diffusion length and carrier removal rate with low-energy proton irradiations have been observed to be dependent on carrier concentration through this study. As physical mechanisms behind the difference observed between the radiation-resistant properties of various base doping concentrations, two mechanisms, namely, the effect of a depletion layer as a carrier collection layer and generation of the impurity-related complex defects due to low-energy protons stopping within the active region, have been proposed. (author)
Nitrogen dioxide concentrations in neighborhoods adjacent to a commercial airport: a land use regression modeling study

Directory of Open Access Journals (Sweden)

Spengler John D

2010-11-01

Full Text Available Abstract Background There is growing concern in communities surrounding airports regarding the contribution of various emission sources (such as aircraft and ground support equipment to nearby ambient concentrations. We used extensive monitoring of nitrogen dioxide (NO2 in neighborhoods surrounding T.F. Green Airport in Warwick, RI, and land-use regression (LUR modeling techniques to determine the impact of proximity to the airport and local traffic on these concentrations. Methods Palmes diffusion tube samplers were deployed along the airport's fence line and within surrounding neighborhoods for one to two weeks. In total, 644 measurements were collected over three sampling campaigns (October 2007, March 2008 and June 2008 and each sampling location was geocoded. GIS-based variables were created as proxies for local traffic and airport activity. A forward stepwise regression methodology was employed to create general linear models (GLMs of NO2 variability near the airport. The effect of local meteorology on associations with GIS-based variables was also explored. Results Higher concentrations of NO2 were seen near the airport terminal, entrance roads to the terminal, and near major roads, with qualitatively consistent spatial patterns between seasons. In our final multivariate model (R2 = 0.32, the local influences of highways and arterial/collector roads were statistically significant, as were local traffic density and distance to the airport terminal (all p Conclusion Our study has shown that there are clear local variations in NO2 in the neighborhoods that surround an urban airport, which are spatially consistent across seasons. LUR modeling demonstrated a strong influence of local traffic, except the smallest roads that predominate in residential areas, as well as proximity to the airport terminal.
An analytical model for nanoparticles concentration resulting from infusion into poroelastic brain tissue.

Science.gov (United States)

Pizzichelli, G; Di Michele, F; Sinibaldi, E

2016-02-01

We consider the infusion of a diluted suspension of nanoparticles (NPs) into poroelastic brain tissue, in view of relevant biomedical applications such as intratumoral thermotherapy. Indeed, the high impact of the related pathologies motivates the development of advanced therapeutic approaches, whose design also benefits from theoretical models. This study provides an analytical expression for the time-dependent NPs concentration during the infusion into poroelastic brain tissue, which also accounts for particle binding onto cells (by recalling relevant results from the colloid filtration theory). Our model is computationally inexpensive and, compared to fully numerical approaches, permits to explicitly elucidate the role of the involved physical aspects (tissue poroelasticity, infusion parameters, NPs physico-chemical properties, NP-tissue interactions underlying binding). We also present illustrative results based on parameters taken from the literature, by considering clinically relevant ranges for the infusion parameters. Moreover, we thoroughly assess the model working assumptions besides discussing its limitations. While not laying any claims of generality, our model can be used to support the development of more ambitious numerical approaches, towards the preliminary design of novel therapies based on NPs infusion into brain tissue. Copyright © 2015 Elsevier Inc. All rights reserved.
Specific-activity and concentration model applied to cesium movement in an oligotrophic lake

International Nuclear Information System (INIS)

Vanderploeg, H.A.; Booth, R.S.; Clark, F.H.

1975-01-01

A linear systems-analysis model was derived to simulate the time-dependent dynamics of specific activity and concentration of radionuclides in aquatic systems. Transfer coefficients were determined for movement of 137 Cs in the components of an oligotrophic lake. These coefficients were defined in terms of basic environmental and ecological data so that the model can be applied to a wide variety of sites. Simulations with a model that ignored sediment--water interactions predicted much higher 137 Cs specific activities in the lake water and biota than did those with the complete model. Comparing 137 Cs concentrations predicted by the model with concentrations reported for the biota of an experimentally contaminated oligotrophic lake indicated that the transfer coefficients derived for the biota are adequate
Development of a model for radon concentration in indoor air

International Nuclear Information System (INIS)

Jelle, Bjørn Petter

2012-01-01

A model is developed for calculation of the radon concentration in indoor air. The model takes into account various important parameters, e.g. radon concentration in ground, radon diffusion resistance of radon barrier, air permeance of ground, air pressure difference between outdoor ground and indoor at ground level, ventilation of the building ground and number of air changes per hour due to ventilation. Characteristic case studies are depicted in selected 2D and 3D graphical plots for easy visualization and interpretation. The radon transport into buildings might be dominated by diffusion, pressure driven flow or a mixture of both depending on the actual values of the various parameters. The results of our work indicate that with realistic or typical values of the parameters, most of the transport of radon from the building ground to the indoor air is due to air leakage driven by pressure differences through the construction. By incorporation of various and realistic values in the radon model, valuable information about the miscellaneous parameters influencing the indoor radon level is gained. Hence, the presented radon model may be utilized as a simple yet versatile and powerful tool for examining which preventive or remedial measures should be carried out to achieve an indoor radon level below the reference level as set by the authorities. - Highlights: ► Model development for calculation of radon concentration in indoor air. ► Radon model accounting for various important parameters. ► Characteristic case studies depicted in 2D and 3D graphical plots. ► May be utilized for examining radon preventive measures.
Evaluation of Modeling NO2 Concentrations Driven by Satellite-Derived and Bottom-Up Emission Inventories Using In-Situ Measurements Over China

Science.gov (United States)

Liu, Fei; van der A, Ronald J.; Eskes, Henk; Ding, Jieying; Mijling, Bas

2018-01-01

Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modeling surface NO2 concentrations from the CHIMERE regional chemical transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modeled ratio of NO2 to NOz. The model accurately reproduces the spatial variability in NO2 from in situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slopeD0.74 and 0.64 for the daily mean and daytime only) and the MIX (slopeD1.3 and 1.1) inventories, respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modeled concentrations is reduced, with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban or rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10-40% higher than the corresponding model grid cell mean. This reduces the estimate of the negative bias of the DECSO-based simulation to the range of -30 to 0% on average and more firmly establishes that the MIX inventory is biased high over major cities. The performance of
Evaluation of modeling NO2 concentrations driven by satellite-derived and bottom-up emission inventories using in situ measurements over China

Science.gov (United States)

Liu, Fei; van der A, Ronald J.; Eskes, Henk; Ding, Jieying; Mijling, Bas

2018-03-01

Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modeling surface NO2 concentrations from the CHIMERE regional chemical transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modeled ratio of NO2 to NOz. The model accurately reproduces the spatial variability in NO2 from in situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slope = 0.74 and 0.64 for the daily mean and daytime only) and the MIX (slope = 1.3 and 1.1) inventories, respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modeled concentrations is reduced, with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban or rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10-40 % higher than the corresponding model grid cell mean. This reduces the estimate of the negative bias of the DECSO-based simulation to the range of -30 to 0 % on average and more firmly establishes that the MIX inventory is biased high over major cities. The
Modeling and simulation of the solar concentrator in photovoltaic systems through the application of a new BRDF function model

Science.gov (United States)

Plachta, Kamil

2016-04-01

The paper presents a new algorithm that uses a combination of two models of BRDF functions: Torrance-Sparrow model and HTSG model. The knowledge of technical parameters of a surface is especially useful in the construction of the solar concentrator. The concentrator directs the reflected solar radiation on the surface of photovoltaic panels, increasing the amount of incident radiance. The software applying algorithm allows to calculate surface parameters of the solar concentrator. Performed simulation showing the share of diffuse component and directional component in reflected stream for surfaces made from particular materials. The impact of share of each component in reflected stream on the efficiency of the solar concentrator and photovoltaic surface has also been described. Subsequently, simulation change the value of voltage, current and power output of monocrystalline photovoltaic panels installed in a solar concentrator system has been made for selected surface of materials solar concentrator.
Modelling the growth and ethanol production of Brettanomyces bruxellensis at different glucose concentrations.

Science.gov (United States)

Aguilar-Uscanga, M G; Garcia-Alvarado, Y; Gomez-Rodriguez, J; Phister, T; Delia, M L; Strehaiano, P

2011-08-01

To study the effect of glucose concentrations on the growth by Brettanomyces bruxellensis yeast strain in batch experiments and develop a mathematical model for kinetic behaviour analysis of yeast growing in batch culture. A Matlab algorithm was developed for the estimation of model parameters. Glucose fermentation by B. bruxellensis was studied by varying its concentration (5, 9.3, 13.8, 16.5, 17.6 and 21.4%). The increase in substrate concentration up to a certain limit was accompanied by an increase in ethanol and biomass production; at a substrate concentration of 50-138 g l(-1), the ethanol and biomass production were 24, 59 and 6.3, 11.4 g l(-1), respectively. However, an increase in glucose concentration to 165 g l(-1) led to a drastic decrease in product formation and substrate utilization. The model successfully simulated the batch kinetic observed in all cases. The confidence intervals were also estimated at each phase at a 0.95 probability level in a t-Student distribution for f degrees of freedom. The maximum ethanol and biomass yields were obtained with an initial glucose concentration of 138 g l(-1). These experiments illustrate the importance of using a mathematical model applied to kinetic behaviour on glucose concentration by B. bruxellensis. © 2011 The Authors. Letters in Applied Microbiology © 2011 The Society for Applied Microbiology.
Investigation of Primary Factors Affecting the Variation of Modeled Oak Pollen Concentrations: A Case Study for Southeast Texas in 2010

Science.gov (United States)

Jeon, Wonbae; Choi, Yunsoo; Roy, Anirban; Pan, Shuai; Price, Daniel; Hwang, Mi-Kyoung; Kim, Kyu Rang; Oh, Inbo

2018-02-01

Oak pollen concentrations over the Houston-Galveston-Brazoria (HGB) area in southeastern Texas were modeled and evaluated against in-situ data. We modified the Community Multi-scale Air Quality (CMAQ) model to include oak pollen emission, dispersion, and deposition. The Oak Pollen Emission Model (OPEM) calculated gridded oak pollen emissions, which are based on a parameterized equation considering a plant-specific factor ( C e ), surface characteristics, and meteorology. The simulation period was chosen to be February 21 to April 30 in the spring of 2010, when the observed monthly mean oak pollen concentrations were the highest in six years (2009-2014). The results indicated C e and meteorology played an important role in the calculation of oak pollen emissions. While C e was critical in determining the magnitude of oak pollen emissions, meteorology determined their variability. In particular, the contribution of the meteorology to the variation in oak pollen emissions increased with the oak pollen emission rate. The evaluation results using in-situ surface data revealed that the model underestimated pollen concentrations and was unable to accurately reproduce the peak pollen episodes. The model error was likely due to uncertainty in climatology-based C e used for the estimation of oak pollen emissions and inaccuracy in the wind fields from the Weather Research and Forecast (WRF) model.
Technical Performance and Economic Evaluation of Evaporative and Membrane-Based Concentration for Biomass-Derived Sugars

International Nuclear Information System (INIS)

Sievers, David A.; Stickel, Jonathan J.; Grundl, Nicholas J.; Tao, Ling

2017-01-01

Several conversion pathways of lignocellulosic biomass to advanced biofuels require or benefit from using concentrated sugar syrups of 600 g/L or greater. And while concentration may seem straightforward, thermal sugar degradation and energy efficiency remain major concerns. This study evaluated the trade-offs in product recovery, energy consumption, and economics between evaporative and membrane-based concentration methods. The degradation kinetics of xylose and glucose were characterized and applied to an evaporator process simulation. Though significant sugar loss was predicted for certain scenarios due to the Maillard reaction, industrially common falling-film plate evaporators offer short residence times (<5 min) and are expected to limit sugar losses. Membrane concentration experiments characterized flux and sugar rejection, but diminished flux occurred at >100 g/L. A second step using evaporation is necessary to achieve target concentrations. Techno-economic process model simulations evaluated the overall economics of concentrating a 35 g/L sugar stream to 600 g/L in a full-scale biorefinery. A two-step approach of preconcentrating using membranes and finishing with an evaporator consumed less energy than evaporation alone but was more expensive because of high capital expenses of the membrane units.
TwinFocus, a concentrated photovoltaic module based on mature technologies

Directory of Open Access Journals (Sweden)

Antonini Piergiorgio

2014-01-01

Full Text Available Among solar power generation, concentrated photovoltaics (CPV based on multijunction (MJ solar cells, is one of the most promising technology for hot climates. The fact that multijunction solar cells based on direct band gap semiconductors demonstrate lower dependence on temperature than silicon solar cells boosted their use in concentrated photovoltaics modules. Departing from the mainstream design of Fresnel lenses, the CPV module based on TwinFocus design with off-axis quasi parabolic mirrors differentiates itself for its compactness and the possibility of easy integration also in roof-top applications. A detailed description of the module and of the systems will be given together with measured performances, and expectations for the next release.
Principal component analysis and neurocomputing-based models for total ozone concentration over different urban regions of India

Science.gov (United States)

Chattopadhyay, Goutami; Chattopadhyay, Surajit; Chakraborthy, Parthasarathi

2012-07-01

The present study deals with daily total ozone concentration time series over four metro cities of India namely Kolkata, Mumbai, Chennai, and New Delhi in the multivariate environment. Using the Kaiser-Meyer-Olkin measure, it is established that the data set under consideration are suitable for principal component analysis. Subsequently, by introducing rotated component matrix for the principal components, the predictors suitable for generating artificial neural network (ANN) for daily total ozone prediction are identified. The multicollinearity is removed in this way. Models of ANN in the form of multilayer perceptron trained through backpropagation learning are generated for all of the study zones, and the model outcomes are assessed statistically. Measuring various statistics like Pearson correlation coefficients, Willmott's indices, percentage errors of prediction, and mean absolute errors, it is observed that for Mumbai and Kolkata the proposed ANN model generates very good predictions. The results are supported by the linearly distributed coordinates in the scatterplots.
PBPK and population modelling to interpret urine cadmium concentrations of the French population

Energy Technology Data Exchange (ETDEWEB)

Béchaux, Camille, E-mail: Camille.bechaux@anses.fr [ANSES, French Agency for Food, Environmental and Occupational Health Safety, 27-31 Avenue du Général Leclerc, 94701 Maisons-Alfort (France); Bodin, Laurent [ANSES, French Agency for Food, Environmental and Occupational Health Safety, 27-31 Avenue du Général Leclerc, 94701 Maisons-Alfort (France); Clémençon, Stéphan [Telecom ParisTech, 46 rue Barrault, 75634 Paris Cedex 13 (France); Crépet, Amélie [ANSES, French Agency for Food, Environmental and Occupational Health Safety, 27-31 Avenue du Général Leclerc, 94701 Maisons-Alfort (France)

2014-09-15

As cadmium accumulates mainly in kidney, urinary concentrations are considered as relevant data to assess the risk related to cadmium. The French Nutrition and Health Survey (ENNS) recorded the concentration of cadmium in the urine of the French population. However, as with all biomonitoring data, it needs to be linked to external exposure for it to be interpreted in term of sources of exposure and for risk management purposes. The objective of this work is thus to interpret the cadmium biomonitoring data of the French population in terms of dietary and cigarette smoke exposures. Dietary and smoking habits recorded in the ENNS study were combined with contamination levels in food and cigarettes to assess individual exposures. A PBPK model was used in a Bayesian population model to link this external exposure with the measured urinary concentrations. In this model, the level of the past exposure was corrected thanks to a scaling function which account for a trend in the French dietary exposure. It resulted in a modelling which was able to explain the current urinary concentrations measured in the French population through current and past exposure levels. Risk related to cadmium exposure in the general French population was then assessed from external and internal critical values corresponding to kidney effects. The model was also applied to predict the possible urinary concentrations of the French population in 2030 assuming there will be no more changes in the exposures levels. This scenario leads to significantly lower concentrations and consequently lower related risk. - Highlights: • Interpretation of urine cadmium concentrations in France • PBPK and Bayesian population modelling of cadmium exposure • Assessment of the historic time-trend of the cadmium exposure in France • Risk assessment from current and future external and internal exposure.
PBPK and population modelling to interpret urine cadmium concentrations of the French population

International Nuclear Information System (INIS)

Béchaux, Camille; Bodin, Laurent; Clémençon, Stéphan; Crépet, Amélie

2014-01-01

As cadmium accumulates mainly in kidney, urinary concentrations are considered as relevant data to assess the risk related to cadmium. The French Nutrition and Health Survey (ENNS) recorded the concentration of cadmium in the urine of the French population. However, as with all biomonitoring data, it needs to be linked to external exposure for it to be interpreted in term of sources of exposure and for risk management purposes. The objective of this work is thus to interpret the cadmium biomonitoring data of the French population in terms of dietary and cigarette smoke exposures. Dietary and smoking habits recorded in the ENNS study were combined with contamination levels in food and cigarettes to assess individual exposures. A PBPK model was used in a Bayesian population model to link this external exposure with the measured urinary concentrations. In this model, the level of the past exposure was corrected thanks to a scaling function which account for a trend in the French dietary exposure. It resulted in a modelling which was able to explain the current urinary concentrations measured in the French population through current and past exposure levels. Risk related to cadmium exposure in the general French population was then assessed from external and internal critical values corresponding to kidney effects. The model was also applied to predict the possible urinary concentrations of the French population in 2030 assuming there will be no more changes in the exposures levels. This scenario leads to significantly lower concentrations and consequently lower related risk. - Highlights: • Interpretation of urine cadmium concentrations in France • PBPK and Bayesian population modelling of cadmium exposure • Assessment of the historic time-trend of the cadmium exposure in France • Risk assessment from current and future external and internal exposure

Assimilating concentration observations for transport and dispersion modeling in a meandering wind field

Science.gov (United States)

Haupt, Sue Ellen; Beyer-Lout, Anke; Long, Kerrie J.; Young, George S.

Assimilating concentration data into an atmospheric transport and dispersion model can provide information to improve downwind concentration forecasts. The forecast model is typically a one-way coupled set of equations: the meteorological equations impact the concentration, but the concentration does not generally affect the meteorological field. Thus, indirect methods of using concentration data to influence the meteorological variables are required. The problem studied here involves a simple wind field forcing Gaussian dispersion. Two methods of assimilating concentration data to infer the wind direction are demonstrated. The first method is Lagrangian in nature and treats the puff as an entity using feature extraction coupled with nudging. The second method is an Eulerian field approach akin to traditional variational approaches, but minimizes the error by using a genetic algorithm (GA) to directly optimize the match between observations and predictions. Both methods show success at inferring the wind field. The GA-variational method, however, is more accurate but requires more computational time. Dynamic assimilation of a continuous release modeled by a Gaussian plume is also demonstrated using the genetic algorithm approach.
A QCM-D study of the concentration- and time-dependent interactions of human LL37 with model mammalian lipid bilayers.

Science.gov (United States)

Lozeau, Lindsay D; Rolle, Marsha W; Camesano, Terri A

2018-07-01

The human antimicrobial peptide LL37 is promising as an alternative to antibiotics due to its biophysical interactions with charged bacterial lipids. However, its clinical potential is limited due to its interactions with zwitterionic mammalian lipids leading to cytotoxicity. Mechanistic insight into the LL37 interactions with mammalian lipids may enable rational design of less toxic LL37-based therapeutics. To this end, we studied concentration- and time-dependent interactions of LL37 with zwitterionic model phosphatidylcholine (PC) bilayers with quartz crystal microbalance with dissipation (QCM-D). LL37 mass adsorption and PC bilayer viscoelasticity changes were monitored by measuring changes in frequency (Δf) and dissipation (ΔD), respectively. The Voigt-Kelvin viscoelastic model was applied to Δf and ΔD to study changes in bilayer thickness and density with LL37 concentration. At low concentrations (0.10-1.00 μM), LL37 adsorbed onto bilayers in a concentration-dependent manner. Further analyses of Δf, ΔD and thickness revealed that peptide saturation on the bilayers was a threshold for interactions observed above 2.00 μM, interactions that were rapid, multi-step, and reached equilibrium in a concentration- and time-dependent manner. Based on these data, we proposed a model of stable transmembrane pore formation at 2.00-10.0 μM, or transition from a primarily lipid to a primarily protein film with a transmembrane pore formation intermediate state at concentrations of LL37 > 10 μM. The concentration-dependent interactions between LL37 and PC bilayers correlated with the observed concentration-dependent biological activities of LL37 (antimicrobial, immunomodulatory and non-cytotoxic at 0.1-1.0 μM, hemolytic and some cytotoxicity at 2.0-13 μM and cytotoxic at >13 μM). Copyright © 2018 Elsevier B.V. All rights reserved.
Concentrator optical characterization using computer mathematical modelling and point source testing

Science.gov (United States)

Dennison, E. W.; John, S. L.; Trentelman, G. F.

1984-01-01

The optical characteristics of a paraboloidal solar concentrator are analyzed using the intercept factor curve (a format for image data) to describe the results of a mathematical model and to represent reduced data from experimental testing. This procedure makes it possible not only to test an assembled concentrator, but also to evaluate single optical panels or to conduct non-solar tests of an assembled concentrator. The use of three-dimensional ray tracing computer programs to calculate the mathematical model is described. These ray tracing programs can include any type of optical configuration from simple paraboloids to array of spherical facets and can be adapted to microcomputers or larger computers, which can graphically display real-time comparison of calculated and measured data.
Detection of ultra-low oxygen concentration based on the fluorescence blinking dynamics of single molecules

Science.gov (United States)

Wu, Ruixiang; Chen, Ruiyun; Zhou, Haitao; Qin, Yaqiang; Zhang, Guofeng; Qin, Chengbing; Gao, Yan; Gao, Yajun; Xiao, Liantuan; Jia, Suotang

2018-01-01

We present a sensitive method for detection of ultra-low oxygen concentrations based on the fluorescence blinking dynamics of single molecules. The relationship between the oxygen concentration and the fraction of time spent in the off-state, stemming from the population and depopulation of triplet states and radical cationic states, can be fitted with a two-site quenching model in the Stern-Volmer plot. The oxygen sensitivity is up to 43.42 kPa-1 in the oxygen partial pressure region as low as 0.01-0.25 kPa, which is seven times higher than that of the fluorescence intensity indicator. This method avoids the limitation of the sharp and non-ignorable fluctuations that occur during the measurement of fluorescence intensity, providing potential applications in the field of low oxygen-concentration monitoring in life science and industry.
Modeling the performance of low concentration photovoltaic systems

Energy Technology Data Exchange (ETDEWEB)

Reis, F. [SESUL, Faculdade de Ciencias da Universidade de Lisboa, 1749-016 Lisboa (Portugal); WS Energia, Ed. Tecnologia II 47, Taguspark, Oeiras (Portugal); Brito, M.C. [SESUL, Faculdade de Ciencias da Universidade de Lisboa, 1749-016 Lisboa (Portugal); Corregidor, V.; Wemans, J. [WS Energia, Ed. Tecnologia II 47, Taguspark, Oeiras (Portugal); Sorasio, G. [WS Energia, Ed. Tecnologia II 47, Taguspark, Oeiras (Portugal); Centro Richerche ISCAT, VS Pellico, 12037, Saluzzo (Italy)

2010-07-15

A theoretical model has been developed to describe the response of V-trough systems in terms of module temperature, power output and energy yield using as inputs the atmospheric conditions. The model was adjusted to DoubleSun {sup registered} concentration technology, which integrates dual-axis tracker and conventional mono-crystalline Si modules. The good agreement between model predictions and the results obtained at WS Energia laboratory, Portugal, validated the model. It is shown that DoubleSun {sup registered} technology increases up to 86% the yearly energy yield of conventional modules relative to a fixed flat-plate system. The model was also used to perform a sensitivity analysis, in order to highlight the relevance of the leading working parameters (such as irradiance) in system performance (energy yield and module temperature). Model results show that the operation module temperature is always below the maximum working temperature defined by the module manufacturers. (author)
PBTK modeling demonstrates contribution of dermal and inhalation exposure components to end-exhaled breath concentrations of naphthalene.

Science.gov (United States)

Kim, David; Andersen, Melvin E; Chao, Yi-Chun E; Egeghy, Peter P; Rappaport, Stephen M; Nylander-French, Leena A

2007-06-01

Dermal and inhalation exposure to jet propulsion fuel 8 (JP-8) have been measured in a few occupational exposure studies. However, a quantitative understanding of the relationship between external exposures and end-exhaled air concentrations has not been described for occupational and environmental exposure scenarios. Our goal was to construct a physiologically based toxicokinetic (PBTK) model that quantitatively describes the relative contribution of dermal and inhalation exposures to the end-exhaled air concentrations of naphthalene among U.S. Air Force personnel. The PBTK model comprised five compartments representing the stratum corneum, viable epidermis, blood, fat, and other tissues. The parameters were optimized using exclusively human exposure and biological monitoring data. The optimized values of parameters for naphthalene were a) permeability coefficient for the stratum corneum 6.8 x 10(-5) cm/hr, b) permeability coefficient for the viable epidermis 3.0 x 10(-3) cm/hr, c) fat:blood partition coefficient 25.6, and d) other tissue:blood partition coefficient 5.2. The skin permeability coefficient was comparable to the values estimated from in vitro studies. Based on simulations of workers' exposures to JP-8 during aircraft fuel-cell maintenance operations, the median relative contribution of dermal exposure to the end-exhaled breath concentration of naphthalene was 4% (10th percentile 1% and 90th percentile 11%). PBTK modeling allowed contributions of the end-exhaled air concentration of naphthalene to be partitioned between dermal and inhalation routes of exposure. Further study of inter- and intraindividual variations in exposure assessment is required to better characterize the toxicokinetic behavior of JP-8 components after occupational and/or environmental exposures.
Biodynamic modelling and the prediction of accumulated trace metal concentrations in the polychaete Arenicola marina

International Nuclear Information System (INIS)

Casado-Martinez, M. Carmen; Smith, Brian D.; DelValls, T. Angel; Luoma, Samuel N.; Rainbow, Philip S.

2009-01-01

The use of biodynamic models to understand metal uptake directly from sediments by deposit-feeding organisms still represents a special challenge. In this study, accumulated concentrations of Cd, Zn and Ag predicted by biodynamic modelling in the lugworm Arenicola marina have been compared to measured concentrations in field populations in several UK estuaries. The biodynamic model predicted accumulated field Cd concentrations remarkably accurately, and predicted bioaccumulated Ag concentrations were in the range of those measured in lugworms collected from the field. For Zn the model showed less but still good comparability, accurately predicting Zn bioaccumulation in A. marina at high sediment concentrations but underestimating accumulated Zn in the worms from sites with low and intermediate levels of Zn sediment contamination. Therefore, it appears that the physiological parameters experimentally derived for A. marina are applicable to the conditions encountered in these environments and that the assumptions made in the model are plausible. - Biodynamic modelling predicts accumulated field concentrations of Ag, Cd and Zn in the deposit-feeding polychaete Arenicola marina.
Metallurgical source-contribution analysis of PM10 annual average concentration: A dispersion modeling approach in moravian-silesian region

Directory of Open Access Journals (Sweden)

P. Jančík

2013-10-01

Full Text Available The goal of the article is to present analysis of metallurgical industry contribution to annual average PM10 concentrations in Moravian-Silesian based on means of the air pollution modelling in accord with the Czech reference methodology SYMOS´97.
Lithography-free nanofluidic concentrator based on droplets-on-demand system

Science.gov (United States)

Yu, Miao; Zhou, Hongbo; Yao, Shuhuai

2013-11-01

Biomarkers are usually low-abundance proteins in biofluids and below detection limit of conventional biosensors. Nanofluidic concentration devices allow efficient biomolecules trapping by utilizing ion concentration polarization near nanochannels. However, once the electric field is turned off, the electrokinetic concentration plug cannot maintain its concentration status and starts to diffuse. In order to maintain the high concentration and extract the concentrated sample for further analysis, a good approach is to encapsulate these plugs into water-in-oil droplets. Here we developed a nanofluidic concentrator based on droplet-on-demand generator to encapsulate concentrated sample in nL droplets. The lithography-free nanochannels were patterned by thermal cracking on the surface of PS Petri-dish. The resulting nanochannel arrays were 30 nm in depth. In combination with microchannels on PDMS, the micro-nano hybrid chip was developed. We used FITC solution to demonstrate that the chip significantly increased the sample concentration for more than 100 folds within 5 minutes. By tuning the pulsed pressure imposed by the solenoid valve connected to the concentration channel, the system can generate a desired volume of droplet with a target sample concentration at a prescribed time. This work was supported by the Research Grants Council of Hong Kong under General Research Fund (Grant No. 621110).
Bayesian spatio-temporal modeling of particulate matter concentrations in Peninsular Malaysia

Science.gov (United States)

Manga, Edna; Awang, Norhashidah

2016-06-01

This article presents an application of a Bayesian spatio-temporal Gaussian process (GP) model on particulate matter concentrations from Peninsular Malaysia. We analyze daily PM10 concentration levels from 35 monitoring sites in June and July 2011. The spatiotemporal model set in a Bayesian hierarchical framework allows for inclusion of informative covariates, meteorological variables and spatiotemporal interactions. Posterior density estimates of the model parameters are obtained by Markov chain Monte Carlo methods. Preliminary data analysis indicate information on PM10 levels at sites classified as industrial locations could explain part of the space time variations. We include the site-type indicator in our modeling efforts. Results of the parameter estimates for the fitted GP model show significant spatio-temporal structure and positive effect of the location-type explanatory variable. We also compute some validation criteria for the out of sample sites that show the adequacy of the model for predicting PM10 at unmonitored sites.
Relevance analysis and short-term prediction of PM2.5 concentrations in Beijing based on multi-source data

Science.gov (United States)

Ni, X. Y.; Huang, H.; Du, W. P.

2017-02-01

The PM2.5 problem is proving to be a major public crisis and is of great public-concern requiring an urgent response. Information about, and prediction of PM2.5 from the perspective of atmospheric dynamic theory is still limited due to the complexity of the formation and development of PM2.5. In this paper, we attempted to realize the relevance analysis and short-term prediction of PM2.5 concentrations in Beijing, China, using multi-source data mining. A correlation analysis model of PM2.5 to physical data (meteorological data, including regional average rainfall, daily mean temperature, average relative humidity, average wind speed, maximum wind speed, and other pollutant concentration data, including CO, NO2, SO2, PM10) and social media data (microblog data) was proposed, based on the Multivariate Statistical Analysis method. The study found that during these factors, the value of average wind speed, the concentrations of CO, NO2, PM10, and the daily number of microblog entries with key words 'Beijing; Air pollution' show high mathematical correlation with PM2.5 concentrations. The correlation analysis was further studied based on a big data's machine learning model- Back Propagation Neural Network (hereinafter referred to as BPNN) model. It was found that the BPNN method performs better in correlation mining. Finally, an Autoregressive Integrated Moving Average (hereinafter referred to as ARIMA) Time Series model was applied in this paper to explore the prediction of PM2.5 in the short-term time series. The predicted results were in good agreement with the observed data. This study is useful for helping realize real-time monitoring, analysis and pre-warning of PM2.5 and it also helps to broaden the application of big data and the multi-source data mining methods.
Modeling uranium transport in acidic contaminated groundwater with base addition

Energy Technology Data Exchange (ETDEWEB)

Zhang, Fan [Institute of Tibetan Plateau Research, Chinese Academy of Sciences; Luo, Wensui [ORNL; Parker, Jack C. [University of Tennessee, Knoxville (UTK); Brooks, Scott C [ORNL; Watson, David B [ORNL; Jardine, Philip [University of Tennessee, Knoxville (UTK); Gu, Baohua [ORNL

2011-01-01

This study investigates reactive transport modeling in a column of uranium(VI)-contaminated sediments with base additions in the circulating influent. The groundwater and sediment exhibit oxic conditions with low pH, high concentrations of NO{sub 3}{sup -}, SO{sub 4}{sup 2-}, U and various metal cations. Preliminary batch experiments indicate that additions of strong base induce rapid immobilization of U for this material. In the column experiment that is the focus of the present study, effluent groundwater was titrated with NaOH solution in an inflow reservoir before reinjection to gradually increase the solution pH in the column. An equilibrium hydrolysis, precipitation and ion exchange reaction model developed through simulation of the preliminary batch titration experiments predicted faster reduction of aqueous Al than observed in the column experiment. The model was therefore modified to consider reaction kinetics for the precipitation and dissolution processes which are the major mechanism for Al immobilization. The combined kinetic and equilibrium reaction model adequately described variations in pH, aqueous concentrations of metal cations (Al, Ca, Mg, Sr, Mn, Ni, Co), sulfate and U(VI). The experimental and modeling results indicate that U(VI) can be effectively sequestered with controlled base addition due to sorption by slowly precipitated Al with pH-dependent surface charge. The model may prove useful to predict field-scale U(VI) sequestration and remediation effectiveness.
Modeling uranium transport in acidic contaminated groundwater with base addition

International Nuclear Information System (INIS)

Zhang Fan; Luo Wensui; Parker, Jack C.; Brooks, Scott C.; Watson, David B.; Jardine, Philip M.; Gu Baohua

2011-01-01

This study investigates reactive transport modeling in a column of uranium(VI)-contaminated sediments with base additions in the circulating influent. The groundwater and sediment exhibit oxic conditions with low pH, high concentrations of NO 3 - , SO 4 2- , U and various metal cations. Preliminary batch experiments indicate that additions of strong base induce rapid immobilization of U for this material. In the column experiment that is the focus of the present study, effluent groundwater was titrated with NaOH solution in an inflow reservoir before reinjection to gradually increase the solution pH in the column. An equilibrium hydrolysis, precipitation and ion exchange reaction model developed through simulation of the preliminary batch titration experiments predicted faster reduction of aqueous Al than observed in the column experiment. The model was therefore modified to consider reaction kinetics for the precipitation and dissolution processes which are the major mechanism for Al immobilization. The combined kinetic and equilibrium reaction model adequately described variations in pH, aqueous concentrations of metal cations (Al, Ca, Mg, Sr, Mn, Ni, Co), sulfate and U(VI). The experimental and modeling results indicate that U(VI) can be effectively sequestered with controlled base addition due to sorption by slowly precipitated Al with pH-dependent surface charge. The model may prove useful to predict field-scale U(VI) sequestration and remediation effectiveness.
Modeling uranium transport in acidic contaminated groundwater with base addition

Energy Technology Data Exchange (ETDEWEB)

Zhang Fan, E-mail: zhangfan@itpcas.ac.cn [Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, P.O. Box 2871, Beijing, 100085 (China); Luo Wensui [Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021 (China); Parker, Jack C. [Institute for a Secure and Sustainable Environment, Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, TN 37996 (United States); Brooks, Scott C.; Watson, David B. [Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Jardine, Philip M. [Biosystems Engineering and Soil Science Department, University of Tennessee, Knoxville, TN 37996 (United States); Gu Baohua [Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)

2011-06-15

This study investigates reactive transport modeling in a column of uranium(VI)-contaminated sediments with base additions in the circulating influent. The groundwater and sediment exhibit oxic conditions with low pH, high concentrations of NO{sub 3}{sup -}, SO{sub 4}{sup 2-}, U and various metal cations. Preliminary batch experiments indicate that additions of strong base induce rapid immobilization of U for this material. In the column experiment that is the focus of the present study, effluent groundwater was titrated with NaOH solution in an inflow reservoir before reinjection to gradually increase the solution pH in the column. An equilibrium hydrolysis, precipitation and ion exchange reaction model developed through simulation of the preliminary batch titration experiments predicted faster reduction of aqueous Al than observed in the column experiment. The model was therefore modified to consider reaction kinetics for the precipitation and dissolution processes which are the major mechanism for Al immobilization. The combined kinetic and equilibrium reaction model adequately described variations in pH, aqueous concentrations of metal cations (Al, Ca, Mg, Sr, Mn, Ni, Co), sulfate and U(VI). The experimental and modeling results indicate that U(VI) can be effectively sequestered with controlled base addition due to sorption by slowly precipitated Al with pH-dependent surface charge. The model may prove useful to predict field-scale U(VI) sequestration and remediation effectiveness.
Watershed regressions for pesticides (warp) models for predicting atrazine concentrations in Corn Belt streams

Science.gov (United States)

Stone, Wesley W.; Gilliom, Robert J.

2012-01-01

Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region-specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP-CB) were developed for annual maximum moving-average (14-, 21-, 30-, 60-, and 90-day durations) and annual 95th-percentile atrazine concentrations in streams of the Corn Belt region. The WARP-CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model-development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model-development sites. The WARP-CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine-use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP-CB models. The WARP-CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine-use intensities of 17 kg/km2 of watershed area or greater.
RADON CONCENTRATION TIME SERIES MODELING AND APPLICATION DISCUSSION.

Science.gov (United States)

Stránský, V; Thinová, L

2017-11-01

In the year 2010 a continual radon measurement was established at Mladeč Caves in the Czech Republic using a continual radon monitor RADIM3A. In order to model radon time series in the years 2010-15, the Box-Jenkins Methodology, often used in econometrics, was applied. Because of the behavior of radon concentrations (RCs), a seasonal integrated, autoregressive moving averages model with exogenous variables (SARIMAX) has been chosen to model the measured time series. This model uses the time series seasonality, previously acquired values and delayed atmospheric parameters, to forecast RC. The developed model for RC time series is called regARIMA(5,1,3). Model residuals could be retrospectively compared with seismic evidence of local or global earthquakes, which occurred during the RCs measurement. This technique enables us to asses if continuously measured RC could serve an earthquake precursor. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
An ELM Based Online Soft Sensing Approach for Alumina Concentration Detection

Directory of Open Access Journals (Sweden)

Sen Zhang

2015-01-01

Full Text Available The concentration of alumina in the electrolyte is of great significance during the production of aluminum; it may affect the stability of aluminum reduction cell and the current efficiency. However, the concentration of alumina is hard to be detected online because of the special circumstance in the aluminum reduction cell. At present, there is lack of fast and accurate soft sensing methods for alumina concentration and existing methods can not meet the needs for online measurement. In this paper, a novel soft sensing method based on a modified extreme learning machine (MELM for online measurement of the alumina concentration is proposed. The modified ELM algorithm is based on the enhanced random search which is called incremental extreme learning machine in some references. It randomly chooses the input weights and analytically determines the output weights without manual intervention. The simulation results show that the approach can give more accurate estimations of alumina concentration with faster learning speed compared with other methods such as BP and SVM.
Ultra Low Concentration Adsorption Equilibria

National Research Council Canada - National Science Library

Mahle, John J; Buettner, Leonard C; LeVan, M. D; Schindler, Bryan J

2006-01-01

.... Specifically this work focuses on novel experimental and modeling methods to characterize and predict at ultra-low chemical vapor concentrations the protection afforded by adsorption-based vapor filtration systems...
A prediction model of ammonia emission from a fattening pig room based on the indoor concentration using adaptive neuro fuzzy inference system

Energy Technology Data Exchange (ETDEWEB)

Xie, Qiuju, E-mail: xqj197610@163.com [Institute of Information Technology, Heilongjiang Bayi Agricultural University, Daqing 163319 (China); Ni, Ji-qin [Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907 (United States); Su, Zhongbin [Institute of Electric and Information, Northeast Agricultural University, Harbin 150030 (China)

2017-03-05

Highlights: • A prediction model of ammonia emission was built based on the indoor ammonia concentration prediction model using ANFIS. • Five kinds of membership functions were compared to get a well fitted prediction model. • Compared with the BP and MLRM model, the ANFIS prediction model with “gbell” membership function has the best performances. - Abstract: Ammonia (NH{sub 3}) is considered one of the significant pollutions contributor to indoor air quality and odor gas emission from swine house because of the negative impact on the health of pigs, the workers and local environment. Prediction models could provide a reasonable way for pig industries and environment regulatory to determine environment control strategies and give an effective method to evaluate the air quality. The adaptive neuro fuzzy inference system (ANFIS) simulates human’s vague thinking manner to solve the ambiguity and nonlinear problems which are difficult to be processed by conventional mathematics. Five kinds of membership functions were used to build a well fitted ANFIS prediction model. It was shown that the prediction model with “Gbell” membership function had the best capabilities among those five kinds of membership functions, and it had the best performances compared with backpropagation (BP) neuro network model and multiple linear regression model (MLRM) both in wintertime and summertime, the smallest value of mean square error (MSE), mean absolute percentage error (MAPE) and standard deviation (SD) are 0.002 and 0.0047, 31.1599 and 23.6816, 0.0564 and 0.0802, respectively, and the largest coefficients of determination (R{sup 2}) are 0.6351 and 0.6483, repectively. The ANFIS prediction model could be served as a beneficial strategy for the environment control system that has input parameters with highly fluctuating, complexity, and non-linear relationship.
A prediction model of ammonia emission from a fattening pig room based on the indoor concentration using adaptive neuro fuzzy inference system

International Nuclear Information System (INIS)

Xie, Qiuju; Ni, Ji-qin; Su, Zhongbin

2017-01-01

Highlights: • A prediction model of ammonia emission was built based on the indoor ammonia concentration prediction model using ANFIS. • Five kinds of membership functions were compared to get a well fitted prediction model. • Compared with the BP and MLRM model, the ANFIS prediction model with “gbell” membership function has the best performances. - Abstract: Ammonia (NH_3) is considered one of the significant pollutions contributor to indoor air quality and odor gas emission from swine house because of the negative impact on the health of pigs, the workers and local environment. Prediction models could provide a reasonable way for pig industries and environment regulatory to determine environment control strategies and give an effective method to evaluate the air quality. The adaptive neuro fuzzy inference system (ANFIS) simulates human’s vague thinking manner to solve the ambiguity and nonlinear problems which are difficult to be processed by conventional mathematics. Five kinds of membership functions were used to build a well fitted ANFIS prediction model. It was shown that the prediction model with “Gbell” membership function had the best capabilities among those five kinds of membership functions, and it had the best performances compared with backpropagation (BP) neuro network model and multiple linear regression model (MLRM) both in wintertime and summertime, the smallest value of mean square error (MSE), mean absolute percentage error (MAPE) and standard deviation (SD) are 0.002 and 0.0047, 31.1599 and 23.6816, 0.0564 and 0.0802, respectively, and the largest coefficients of determination (R"2) are 0.6351 and 0.6483, repectively. The ANFIS prediction model could be served as a beneficial strategy for the environment control system that has input parameters with highly fluctuating, complexity, and non-linear relationship.

YOGYAKARTA AIR BORNE QUALITY BASED ON THE LEAD PARTICULATE CONCENTRATION

Directory of Open Access Journals (Sweden)

Zaenal Abidin

2010-06-01

Full Text Available Analysis of Yogyakarta air quality based on concentration of lead particulate using Fast Neutron Activation Analysis (FNAA method has been done. The sample was taken 3 times in 16 strategic locations of Yogyakarta city using Hi-Vol air sampler that equipped with cellulose filter TFA 2133. The sample irradiated for 30 min with 14 MeV fast neutron and then counted using gamma spectroscopy (AccuSpec. The result indicated that concentration of Pb-208 along Diponegoro street up to Janti street respectively are minimally (0.689 - 0.775 mg/m3, and maximally: (1.598 - 1.785 mg/m3. According to DIY governor decree No. 153/2002 about the limited toxicity ambient on Yogyakarta area it is concentration that Pb. The concentration of Pb-208 are still below the permitted value of 2 mg/m3, but in certain areas, the Pb concentration is almost equal to upper limit of permitted concentration of Pb. Keywords: air borne, neutron generator, FNAA
ANN modelling of sediment concentration in the dynamic glacial environment of Gangotri in Himalaya.

Science.gov (United States)

Singh, Nandita; Chakrapani, G J

2015-08-01

The present study explores for the first time the possibility of modelling sediment concentration with artificial neural networks (ANNs) at Gangotri, the source of Bhagirathi River in the Himalaya. Discharge, rainfall and temperature have been considered as the main controlling factors of variations in sediment concentration in the dynamic glacial environment of Gangotri. Fourteen feed forward neural networks with error back propagation algorithm have been created, trained and tested for prediction of sediment concentration. Seven models (T1-T7) have been trained and tested in the non-updating mode whereas remaining seven models (T1a-T7a) have been trained in the updating mode. The non-updating mode refers to the scenario where antecedent time (previous time step) values are not used as input to the model. In case of the updating mode, antecedent time values are used as network inputs. The inputs applied in the models are either the variables mentioned above as individual factors (single input networks) or a combination of them (multi-input networks). The suitability of employing antecedent time-step values as network inputs has hence been checked by comparative analysis of model performance in the two modes. The simple feed forward network has been improvised with a series parallel non-linear autoregressive with exogenous input (NARX) architecture wherein true values of sediment concentration have been fed as input during training. In the glacial scenario of Gangotri, maximum sediment movement takes place during the melt period (May-October). Hence, daily data of discharge, rainfall, temperature and sediment concentration for five consecutive melt periods (May-October, 2000-2004) have been used for modelling. High Coefficient of determination values [0.77-0.88] have been obtained between observed and ANN-predicted values of sediment concentration. The study has brought out relationships between variables that are not reflected in normal statistical analysis. A
Remote sensing estimation of the total phosphorus concentration in a large lake using band combinations and regional multivariate statistical modeling techniques.

Science.gov (United States)

Gao, Yongnian; Gao, Junfeng; Yin, Hongbin; Liu, Chuansheng; Xia, Ting; Wang, Jing; Huang, Qi

2015-03-15

Remote sensing has been widely used for ater quality monitoring, but most of these monitoring studies have only focused on a few water quality variables, such as chlorophyll-a, turbidity, and total suspended solids, which have typically been considered optically active variables. Remote sensing presents a challenge in estimating the phosphorus concentration in water. The total phosphorus (TP) in lakes has been estimated from remotely sensed observations, primarily using the simple individual band ratio or their natural logarithm and the statistical regression method based on the field TP data and the spectral reflectance. In this study, we investigated the possibility of establishing a spatial modeling scheme to estimate the TP concentration of a large lake from multi-spectral satellite imagery using band combinations and regional multivariate statistical modeling techniques, and we tested the applicability of the spatial modeling scheme. The results showed that HJ-1A CCD multi-spectral satellite imagery can be used to estimate the TP concentration in a lake. The correlation and regression analysis showed a highly significant positive relationship between the TP concentration and certain remotely sensed combination variables. The proposed modeling scheme had a higher accuracy for the TP concentration estimation in the large lake compared with the traditional individual band ratio method and the whole-lake scale regression-modeling scheme. The TP concentration values showed a clear spatial variability and were high in western Lake Chaohu and relatively low in eastern Lake Chaohu. The northernmost portion, the northeastern coastal zone and the southeastern portion of western Lake Chaohu had the highest TP concentrations, and the other regions had the lowest TP concentration values, except for the coastal zone of eastern Lake Chaohu. These results strongly suggested that the proposed modeling scheme, i.e., the band combinations and the regional multivariate
Modelling of in-stream nitrogen and phosphorus concentrations using different sampling strategies for calibration data

Science.gov (United States)

Jomaa, Seifeddine; Jiang, Sanyuan; Yang, Xiaoqiang; Rode, Michael

2016-04-01

It is known that a good evaluation and prediction of surface water pollution is mainly limited by the monitoring strategy and the capability of the hydrological water quality model to reproduce the internal processes. To this end, a compromise sampling frequency, which can reflect the dynamical behaviour of leached nutrient fluxes responding to changes in land use, agriculture practices and point sources, and appropriate process-based water quality model are required. The objective of this study was to test the identification of hydrological water quality model parameters (nitrogen and phosphorus) under two different monitoring strategies: (1) regular grab-sampling approach and (2) regular grab-sampling with additional monitoring during the hydrological events using automatic samplers. First, the semi-distributed hydrological water quality HYPE (Hydrological Predictions for the Environment) model was successfully calibrated (1994-1998) for discharge (NSE = 0.86), nitrate-N (lowest NSE for nitrate-N load = 0.69), particulate phosphorus and soluble phosphorus in the Selke catchment (463 km2, central Germany) for the period 1994-1998 using regular grab-sampling approach (biweekly to monthly for nitrogen and phosphorus concentrations). Second, the model was successfully validated during the period 1999-2010 for discharge, nitrate-N, particulate-phosphorus and soluble-phosphorus (lowest NSE for soluble phosphorus load = 0.54). Results, showed that when additional sampling during the events with random grab-sampling approach was used (period 2011-2013), the hydrological model could reproduce only the nitrate-N and soluble phosphorus concentrations reasonably well. However, when additional sampling during the hydrological events was considered, the HYPE model could not represent the measured particulate phosphorus. This reflects the importance of suspended sediment during the hydrological events increasing the concentrations of particulate phosphorus. The HYPE model could
Heavy metal concentrations in plants and different harvestable parts: A soil-plant equilibrium model

International Nuclear Information System (INIS)

Guala, Sebastian D.; Vega, Flora A.; Covelo, Emma F.

2010-01-01

A mathematical interaction model, validated by experimental results, was developed to modeling the metal uptake by plants and induced growth decrease, by knowing metal in soils. The model relates the dynamics of the uptake of metals from soil to plants. Also, two types of relationships are tested: total and available metal content. The model successfully fitted the experimental data and made it possible to predict the threshold values of total mortality with a satisfactory approach. Data are taken from soils treated with Cd and Ni for ryegrass (Lolium perenne, L.) and oats (Avena sativa L.), respectively. Concentrations are measured in the aboveground biomass of plants. In the latter case, the concentration of metals in different parts of the plants (tillering, shooting and earing) is also modeled. At low concentrations, the effects of metals are moderate, and the dynamics appear to be linear. However, increasing concentrations show nonlinear behaviors. - The model proposed in this study makes possible to characterize the nonlinear behavior of the soil-plant interaction with metal pollution.
Heavy metal concentrations in plants and different harvestable parts: A soil-plant equilibrium model

Energy Technology Data Exchange (ETDEWEB)

Guala, Sebastian D. [Instituto de Ciencias, Universidad Nacional de General Sarmiento, Gutierrez 1150, Los Polvorines, Buenos Aires (Argentina); Vega, Flora A. [Departamento de Bioloxia Vexetal e Ciencia do Solo, Facultade de Bioloxia, Universidade de Vigo, Lagoas, Marcosende, 36310 Vigo, Pontevedra (Spain); Covelo, Emma F., E-mail: emmaf@uvigo.e [Departamento de Bioloxia Vexetal e Ciencia do Solo, Facultade de Bioloxia, Universidade de Vigo, Lagoas, Marcosende, 36310 Vigo, Pontevedra (Spain)

2010-08-15

A mathematical interaction model, validated by experimental results, was developed to modeling the metal uptake by plants and induced growth decrease, by knowing metal in soils. The model relates the dynamics of the uptake of metals from soil to plants. Also, two types of relationships are tested: total and available metal content. The model successfully fitted the experimental data and made it possible to predict the threshold values of total mortality with a satisfactory approach. Data are taken from soils treated with Cd and Ni for ryegrass (Lolium perenne, L.) and oats (Avena sativa L.), respectively. Concentrations are measured in the aboveground biomass of plants. In the latter case, the concentration of metals in different parts of the plants (tillering, shooting and earing) is also modeled. At low concentrations, the effects of metals are moderate, and the dynamics appear to be linear. However, increasing concentrations show nonlinear behaviors. - The model proposed in this study makes possible to characterize the nonlinear behavior of the soil-plant interaction with metal pollution.
Sensitivity of modeled ozone concentrations to uncertainties in biogenic emissions

International Nuclear Information System (INIS)

Roselle, S.J.

1992-06-01

The study examines the sensitivity of regional ozone (O3) modeling to uncertainties in biogenic emissions estimates. The United States Environmental Protection Agency's (EPA) Regional Oxidant Model (ROM) was used to simulate the photochemistry of the northeastern United States for the period July 2-17, 1988. An operational model evaluation showed that ROM had a tendency to underpredict O3 when observed concentrations were above 70-80 ppb and to overpredict O3 when observed values were below this level. On average, the model underpredicted daily maximum O3 by 14 ppb. Spatial patterns of O3, however, were reproduced favorably by the model. Several simulations were performed to analyze the effects of uncertainties in biogenic emissions on predicted O3 and to study the effectiveness of two strategies of controlling anthropogenic emissions for reducing high O3 concentrations. Biogenic hydrocarbon emissions were adjusted by a factor of 3 to account for the existing range of uncertainty in these emissions. The impact of biogenic emission uncertainties on O3 predictions depended upon the availability of NOx. In some extremely NOx-limited areas, increasing the amount of biogenic emissions decreased O3 concentrations. Two control strategies were compared in the simulations: (1) reduced anthropogenic hydrocarbon emissions, and (2) reduced anthropogenic hydrocarbon and NOx emissions. The simulations showed that hydrocarbon emission controls were more beneficial to the New York City area, but that combined NOx and hydrocarbon controls were more beneficial to other areas of the Northeast. Hydrocarbon controls were more effective as biogenic hydrocarbon emissions were reduced, whereas combined NOx and hydrocarbon controls were more effective as biogenic hydrocarbon emissions were increased
A dynamic growth model of vegetative soya bean plants: model structure and behaviour under varying root temperature and nitrogen concentration

Science.gov (United States)

Lim, J. T.; Wilkerson, G. G.; Raper, C. D. Jr; Gold, H. J.

1990-01-01

A differential equation model of vegetative growth of the soya bean plant (Glycine max (L.) Merrill cv. Ransom') was developed to account for plant growth in a phytotron system under variation of root temperature and nitrogen concentration in nutrient solution. The model was tested by comparing model outputs with data from four different experiments. Model predictions agreed fairly well with measured plant performance over a wide range of root temperatures and over a range of nitrogen concentrations in nutrient solution between 0.5 and 10.0 mmol NO3- in the phytotron environment. Sensitivity analyses revealed that the model was most sensitive to changes in parameters relating to carbohydrate concentration in the plant and nitrogen uptake rate.
Modeling of nitrogen oxides (NO(x)) concentrations resulting from ships at berth.

Science.gov (United States)

Abdul-Wahab, Sabah A; Elkamel, Ali; Al Balushi, Abdullah S; Al-Damkhi, Ali M; Siddiqui, Rafiq A

2008-12-01

Oxides of nitrogen (NO(x)) emissions from ships (marine vessels) contribute to poor air quality that negatively impacts public health and communities in coastal areas and far inland. These emissions often excessively harm human health, environment, wildlife habituates, and quality of life of communities and indigenous of people who live near ports. This study was conducted to assess the impact of NO(x) emissions origination from ships at berth on a nearby community. It was undertaken at Said Bin Sultan Naval base in Wullayat Al-Mussana (Sultanate of Oman) during the year 2005. The Industrial Source Complex Short Term (ISCST) model was adopted to determine the dispersion of NO(x) into port and beyond into surrounding urban areas. The hourly and monthly contours (isopleths) of NO(x) concentrations in and around the port were plotted. The results were analyzed to determine the affected area and the level of NO(x) concentrations. The highest concentration points in the studied area were also identified. The isopleths of NO(x) indicated that most shipping emissions of NO(x) occur at the port can be transported over land. The output results can help to derive advice of recommendations ships operators and environmentalists to take the correct decision to prevent workers and surrounded environment from pollution.
Quantitative spatially resolved measurement of tissue chromophore concentrations using photoacoustic spectroscopy: application to the measurement of blood oxygenation and haemoglobin concentration

Science.gov (United States)

Laufer, Jan; Delpy, Dave; Elwell, Clare; Beard, Paul

2007-01-01

A new approach based on pulsed photoacoustic spectroscopy for non-invasively quantifying tissue chromophore concentrations with high spatial resolution has been developed. The technique is applicable to the quantification of tissue chromophores such as oxyhaemoglobin (HbO2) and deoxyhaemoglobin (HHb) for the measurement of physiological parameters such as blood oxygen saturation (SO2) and total haemoglobin concentration. It can also be used to quantify the local accumulation of targeted contrast agents used in photoacoustic molecular imaging. The technique employs a model-based inversion scheme to recover the chromophore concentrations from photoacoustic measurements. This comprises a numerical forward model of the detected time-dependent photoacoustic signal that incorporates a multiwavelength diffusion-based finite element light propagation model to describe the light transport and a time-domain acoustic model to describe the generation, propagation and detection of the photoacoustic wave. The forward model is then inverted by iteratively fitting it to measurements of photoacoustic signals acquired at different wavelengths to recover the chromophore concentrations. To validate this approach, photoacoustic signals were generated in a tissue phantom using nanosecond laser pulses between 740 nm and 1040 nm. The tissue phantom comprised a suspension of intralipid, blood and a near-infrared dye in which three tubes were immersed. Blood at physiological haemoglobin concentrations and oxygen saturation levels ranging from 2% to 100% was circulated through the tubes. The signal amplitude from different temporal sections of the detected photoacoustic waveforms was plotted as a function of wavelength and the forward model fitted to these data to recover the concentrations of HbO2 and HHb, total haemoglobin concentration and SO2. The performance was found to compare favourably to that of a laboratory CO-oximeter with measurement resolutions of ±3.8 g l-1 (±58 µM) and ±4
Quantitative spatially resolved measurement of tissue chromophore concentrations using photoacoustic spectroscopy: application to the measurement of blood oxygenation and haemoglobin concentration

Energy Technology Data Exchange (ETDEWEB)

Laufer, Jan; Delpy, Dave; Elwell, Clare; Beard, Paul [Department of Medical Physics and Bioengineering, University College London, Malet Place Engineering Building, London WC1E 6BT (United Kingdom)

2007-01-07

A new approach based on pulsed photoacoustic spectroscopy for non-invasively quantifying tissue chromophore concentrations with high spatial resolution has been developed. The technique is applicable to the quantification of tissue chromophores such as oxyhaemoglobin (HbO{sub 2}) and deoxyhaemoglobin (HHb) for the measurement of physiological parameters such as blood oxygen saturation (SO{sub 2}) and total haemoglobin concentration. It can also be used to quantify the local accumulation of targeted contrast agents used in photoacoustic molecular imaging. The technique employs a model-based inversion scheme to recover the chromophore concentrations from photoacoustic measurements. This comprises a numerical forward model of the detected time-dependent photoacoustic signal that incorporates a multiwavelength diffusion-based finite element light propagation model to describe the light transport and a time-domain acoustic model to describe the generation, propagation and detection of the photoacoustic wave. The forward model is then inverted by iteratively fitting it to measurements of photoacoustic signals acquired at different wavelengths to recover the chromophore concentrations. To validate this approach, photoacoustic signals were generated in a tissue phantom using nanosecond laser pulses between 740 nm and 1040 nm. The tissue phantom comprised a suspension of intralipid, blood and a near-infrared dye in which three tubes were immersed. Blood at physiological haemoglobin concentrations and oxygen saturation levels ranging from 2% to 100% was circulated through the tubes. The signal amplitude from different temporal sections of the detected photoacoustic waveforms was plotted as a function of wavelength and the forward model fitted to these data to recover the concentrations of HbO{sub 2} and HHb, total haemoglobin concentration and SO{sub 2}. The performance was found to compare favourably to that of a laboratory CO-oximeter with measurement resolutions of {+-}3
Quantitative spatially resolved measurement of tissue chromophore concentrations using photoacoustic spectroscopy: application to the measurement of blood oxygenation and haemoglobin concentration

International Nuclear Information System (INIS)

Laufer, Jan; Delpy, Dave; Elwell, Clare; Beard, Paul

2007-01-01

A new approach based on pulsed photoacoustic spectroscopy for non-invasively quantifying tissue chromophore concentrations with high spatial resolution has been developed. The technique is applicable to the quantification of tissue chromophores such as oxyhaemoglobin (HbO 2 ) and deoxyhaemoglobin (HHb) for the measurement of physiological parameters such as blood oxygen saturation (SO 2 ) and total haemoglobin concentration. It can also be used to quantify the local accumulation of targeted contrast agents used in photoacoustic molecular imaging. The technique employs a model-based inversion scheme to recover the chromophore concentrations from photoacoustic measurements. This comprises a numerical forward model of the detected time-dependent photoacoustic signal that incorporates a multiwavelength diffusion-based finite element light propagation model to describe the light transport and a time-domain acoustic model to describe the generation, propagation and detection of the photoacoustic wave. The forward model is then inverted by iteratively fitting it to measurements of photoacoustic signals acquired at different wavelengths to recover the chromophore concentrations. To validate this approach, photoacoustic signals were generated in a tissue phantom using nanosecond laser pulses between 740 nm and 1040 nm. The tissue phantom comprised a suspension of intralipid, blood and a near-infrared dye in which three tubes were immersed. Blood at physiological haemoglobin concentrations and oxygen saturation levels ranging from 2% to 100% was circulated through the tubes. The signal amplitude from different temporal sections of the detected photoacoustic waveforms was plotted as a function of wavelength and the forward model fitted to these data to recover the concentrations of HbO 2 and HHb, total haemoglobin concentration and SO 2 . The performance was found to compare favourably to that of a laboratory CO-oximeter with measurement resolutions of ±3.8 g l -1 (±58 �
An Assessment of the Model of Concentration Addition for Predicting the Estrogenic Activity of Chemical Mixtures in Wastewater Treatment Works Effluents

Science.gov (United States)

Thorpe, Karen L.; Gross-Sorokin, Melanie; Johnson, Ian; Brighty, Geoff; Tyler, Charles R.

2006-01-01

The effects of simple mixtures of chemicals, with similar mechanisms of action, can be predicted using the concentration addition model (CA). The ability of this model to predict the estrogenic effects of more complex mixtures such as effluent discharges, however, has yet to be established. Effluents from 43 U.K. wastewater treatment works were analyzed for the presence of the principal estrogenic chemical contaminants, estradiol, estrone, ethinylestradiol, and nonylphenol. The measured concentrations were used to predict the estrogenic activity of each effluent, employing the model of CA, based on the relative potencies of the individual chemicals in an in vitro recombinant yeast estrogen screen (rYES) and a short-term (14-day) in vivo rainbow trout vitellogenin induction assay. Based on the measured concentrations of the four chemicals in the effluents and their relative potencies in each assay, the calculated in vitro and in vivo responses compared well and ranged between 3.5 and 87 ng/L of estradiol equivalents (E2 EQ) for the different effluents. In the rYES, however, the measured E2 EQ concentrations in the effluents ranged between 0.65 and 43 ng E2 EQ/L, and they varied against those predicted by the CA model. Deviations in the estimation of the estrogenic potency of the effluents by the CA model, compared with the measured responses in the rYES, are likely to have resulted from inaccuracies associated with the measurement of the chemicals in the extracts derived from the complex effluents. Such deviations could also result as a consequence of interactions between chemicals present in the extracts that disrupted the activation of the estrogen response elements in the rYES. E2 EQ concentrations derived from the vitellogenic response in fathead minnows exposed to a series of effluent dilutions were highly comparable with the E2 EQ concentrations derived from assessments of the estrogenic potency of these dilutions in the rYES. Together these data support the
Modelling study of magnetic and concentration phase transition in ultrathin antiferromagnetic films

International Nuclear Information System (INIS)

Leonid, Afremov; Aleksandr, Petrov

2014-01-01

Using the method of the ''average spin'' a modelling study of magnetic and concentration phase transition in ultrathin antiferromagnetic of different crystalline structure has been carried out. It has been shown, that relative change of Neel temperature is subject to the power law with negative index which doesn't depend on the film's crystal kind. The calculation of the dependence of phase transition critical concentration in diluted magnetic material on the film thickness has been made out. The legitimacy of the use of the method developed for modelling of magnetic and concentration phase transition in different nanostructures is certified by accordance between the results of calculations and the experimental data
Data-based Non-Markovian Model Inference

Science.gov (United States)

Ghil, Michael

2015-04-01

This talk concentrates on obtaining stable and efficient data-based models for simulation and prediction in the geosciences and life sciences. The proposed model derivation relies on using a multivariate time series of partial observations from a large-dimensional system, and the resulting low-order models are compared with the optimal closures predicted by the non-Markovian Mori-Zwanzig formalism of statistical physics. Multilayer stochastic models (MSMs) are introduced as both a very broad generalization and a time-continuous limit of existing multilevel, regression-based approaches to data-based closure, in particular of empirical model reduction (EMR). We show that the multilayer structure of MSMs can provide a natural Markov approximation to the generalized Langevin equation (GLE) of the Mori-Zwanzig formalism. A simple correlation-based stopping criterion for an EMR-MSM model is derived to assess how well it approximates the GLE solution. Sufficient conditions are given for the nonlinear cross-interactions between the constitutive layers of a given MSM to guarantee the existence of a global random attractor. This existence ensures that no blow-up can occur for a very broad class of MSM applications. The EMR-MSM methodology is first applied to a conceptual, nonlinear, stochastic climate model of coupled slow and fast variables, in which only slow variables are observed. The resulting reduced model with energy-conserving nonlinearities captures the main statistical features of the slow variables, even when there is no formal scale separation and the fast variables are quite energetic. Second, an MSM is shown to successfully reproduce the statistics of a partially observed, generalized Lokta-Volterra model of population dynamics in its chaotic regime. The positivity constraint on the solutions' components replaces here the quadratic-energy-preserving constraint of fluid-flow problems and it successfully prevents blow-up. This work is based on a close
Quantification of Concentration of Microalgae Anabaena Cylindrica, Coal-bed Methane Water Isolates Nannochloropsis Gaditana and PW-95 in Aquatic Solutions through Hyperspectral Reflectance Measurement and Analytical Model Establishment

Science.gov (United States)

Zhou, Z.; Zhou, X.; Apple, M. E.; Spangler, L.

2017-12-01

Three species of microalgae, Anabaena cylindrica (UTEX # 1611), coal-bed methane water isolates Nannochloropsis gaditana and PW-95 were cultured for the measurements of their hyperspectral profiles in different concentrations. The hyperspectral data were measured by an Analytical Spectral Devices (ASD) spectroradiomter with the spectral resolution of 1 nanometer over the wavelength ranges from 350nm to 1050 nm for samples of microalgae of different concentration. Concentration of microalgae was measured using a Hemocytometer under microscope. The objective of this study is to establish the relation between spectral reflectance and micro-algal concentration so that microalgae concentration can be measured remotely by space- or airborne hyperspectral or multispectral sensors. Two types of analytical models, linear reflectance-concentration model and Lamber-Beer reflectance-concentration model, were established for each species. For linear modeling, the wavelength with the maximum correlation coefficient between the reflectance and concentrations of algae was located and then selected for each species of algae. The results of the linear models for each species are shown in Fig.1(a), in which Refl_1, Refl_2, and Refl_3 represent the reflectance of Anabaena, N. Gaditana, and PW-95 respectively. C1, C2, and C3 represent the Concentrations of Anabaena, N. Gaditana, and PW-95 respectively. The Lamber-Beer models were based on the Lambert-Beer Law, which states that the intensity of light propagating in a substance dissolved in a fully transmitting solvent is directly proportional to the concentration of the substance and the path length of the light through the solution. Thus, for the Lamber-Beer modeling, a wavelength with large absorption in red band was selected for each species. The results of Lambert-Beer models for each species are shown in Fig.1(b). Based on the Lamber-Beer models, the absorption coefficient for the three different species will be quantified.
A prediction model for assessing residential radon concentration in Switzerland

International Nuclear Information System (INIS)

Hauri, Dimitri D.; Huss, Anke; Zimmermann, Frank; Kuehni, Claudia E.; Röösli, Martin

2012-01-01

Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the nationwide Swiss radon database collected between 1994 and 2004. Of these, 80% randomly selected measurements were used for model development and the remaining 20% for an independent model validation. A multivariable log-linear regression model was fitted and relevant predictors selected according to evidence from the literature, the adjusted R², the Akaike's information criterion (AIC), and the Bayesian information criterion (BIC). The prediction model was evaluated by calculating Spearman rank correlation between measured and predicted values. Additionally, the predicted values were categorised into three categories (50th, 50th–90th and 90th percentile) and compared with measured categories using a weighted Kappa statistic. The most relevant predictors for indoor radon levels were tectonic units and year of construction of the building, followed by soil texture, degree of urbanisation, floor of the building where the measurement was taken and housing type (P-values <0.001 for all). Mean predicted radon values (geometric mean) were 66 Bq/m³ (interquartile range 40–111 Bq/m³) in the lowest exposure category, 126 Bq/m³ (69–215 Bq/m³) in the medium category, and 219 Bq/m³ (108–427 Bq/m³) in the highest category. Spearman correlation between predictions and measurements was 0.45 (95%-CI: 0.44; 0.46) for the development dataset and 0.44 (95%-CI: 0.42; 0.46) for the validation dataset. Kappa coefficients were 0.31 for the development and 0.30 for the validation dataset, respectively. The model explained 20% overall variability (adjusted R²). In conclusion, this residential radon prediction model, based on a large number of measurements, was demonstrated to be
SVM-based multisensor data fusion for phase concentration measurement in biomass-coal co-combustion

Science.gov (United States)

Wang, Xiaoxin; Hu, Hongli; Jia, Huiqin; Tang, Kaihao

2018-05-01

In this paper, the electrical method combines the electrostatic sensor and capacitance sensor to measure the phase concentration of pulverized coal/biomass/air three-phase flow through data fusion technology. In order to eliminate the effects of flow regimes and improve the accuracy of the phase concentration measurement, the mel frequency cepstrum coefficient features extracted from electrostatic signals are used to train the Continuous Gaussian Mixture Hidden Markov Model (CGHMM) for flow regime identification. Support Vector Machine (SVM) is introduced to establish the concentration information fusion model under identified flow regimes. The CGHMM models and SVM models are transplanted on digital signal processing (DSP) to realize on-line accurate measurement. The DSP flow regime identification time is 1.4 ms, and the concentration predict time is 164 μs, which can fully meet the real-time requirement. The average absolute value of the relative error of the pulverized coal is about 1.5% and that of the biomass is about 2.2%.
Agent-Based Computational Modeling of Cell Culture ...

Science.gov (United States)

Quantitative characterization of cellular dose in vitro is needed for alignment of doses in vitro and in vivo. We used the agent-based software, CompuCell3D (CC3D), to provide a stochastic description of cell growth in culture. The model was configured so that isolated cells assumed a “fried egg shape” but became increasingly cuboidal with increasing confluency. The surface area presented by each cell to the overlying medium varies from cell-to-cell and is a determinant of diffusional flux of toxicant from the medium into the cell. Thus, dose varies among cells for a given concentration of toxicant in the medium. Computer code describing diffusion of H2O2 from medium into each cell and clearance of H2O2 was calibrated against H2O2 time-course data (25, 50, or 75 uM H2O2 for 60 min) obtained with the Amplex Red assay for the medium and the H2O2-sensitive fluorescent reporter, HyPer, for cytosol. Cellular H2O2 concentrations peaked at about 5 min and were near baseline by 10 min. The model predicted a skewed distribution of surface areas, with between cell variation usually 2 fold or less. Predicted variability in cellular dose was in rough agreement with the variation in the HyPer data. These results are preliminary, as the model was not calibrated to the morphology of a specific cell type. Future work will involve morphology model calibration against human bronchial epithelial (BEAS-2B) cells. Our results show, however, the potential of agent-based modeling
Concentration factors for fish

International Nuclear Information System (INIS)

Feldt, W.; Lauer, R.; Melzer, M.; Siebert, W.

1978-01-01

Concentration factors are defined as operators allowing to calculate the specific activity of fish meat from a given concentration of an element in the water. This parameter depends among others from the content of stable isotopes and homologues in the different waters. If this parameter is reasonably to be used for model calculations it must be referred to water with all of its content substances, these calculations also being based on this type of 'water'. (orig.) [de

Circulating Angiopoietin-2 and Its Soluble Receptor Tie-2 Concentrations Are Related to Renal Function in Two Population-Based Cohorts

DEFF Research Database (Denmark)

Hennings, Anna; Hannemann, Anke; Rettig, Rainer

2016-01-01

BACKGROUND: An intact angiopoietin/Tie-2 ligand receptor system is indispensable for life. High circulating angiopoietin-2 (Ang-2) concentrations are strongly associated with kidney disease involving the progressive loss of glomerular filtration. The aim of our study was to investigate the associ......BACKGROUND: An intact angiopoietin/Tie-2 ligand receptor system is indispensable for life. High circulating angiopoietin-2 (Ang-2) concentrations are strongly associated with kidney disease involving the progressive loss of glomerular filtration. The aim of our study was to investigate...... the associations between renal function and serum Ang-2 or serum Tie-2 concentrations in the general population. METHODS: Data of 3081 and 4088 subjects from two population-based studies, the Study of Health in Pomerania (SHIP-1) and SHIP-Trend, were used. Renal function was assessed by serum creatinine, cystatin...... C concentration, creatinine-based estimated glomerular filtration rate [eGFR(crea)], cystatin C-based eGFR [eGFR(cys)] and urinary albumin-to-creatinine ratio (uACR). Analyses of variance and linear regression models were calculated. RESULTS: In both cohorts, strong positive associations between...
Transient Model of Hybrid Concentrated Photovoltaic with Thermoelectric Generator

DEFF Research Database (Denmark)

Mahmoudi Nezhad, Sajjad; Qing, Shaowei; Rezaniakolaei, Alireza

2017-01-01

Transient performance of a concentrated photovoltaic thermoelectric (CPV-TEG) hybrid system is modeled and investigated. A heat sink with water, as the working fluid has been implemented as the cold reservoir of the hybrid system to harvest the heat loss from CPV cell and to increase the efficiency...
Predicting Gran alkalinity and calcium concentrations in river waters over a national scale using a novel modification to the G-BASH model

International Nuclear Information System (INIS)

Cresser, Malcolm S.; Ahmed, Nayan; Smart, Richard P.; Arowolo, Toyin; Calver, Louise J.; Chapman, Pippa J.

2006-01-01

Monthly stream water calcium and Gran alkalinity concentration data from 11 sub-catchments of the Nether Beck in the English Lake District have been used to appraise the transferability of the Scottish, River Dee-based G-BASH model. Readily available riparian zone geochemistry and flow paths were used initially to predict minimum and mean stream water concentrations at the Nether Beck, based on calibration equations from the River Dee catchment data. Predicted values significantly exceeded observed values. Differences in runoff between the two areas, leading to a dilution effect in the Nether Beck, explained most of the difference between observed and predicted values. Greater acid deposition in the Lake District also reduced stream water Gran alkalinity concentrations in that area. If regional differences in precipitation, evapotranspiration and pollutant deposition are incorporated into the model, it may then be used reliably to predict catchment susceptibility to acidification over a wide regional (national) scale. - A modified G-BASH model predicts calcium and Gran alkalinity in streams at a national scale, taking account of regional deposition and climatic variations
Dynamic experiments with high bisphenol-A concentrations modelled with an ASM model extended to include a separate XOC degrading microorganism

DEFF Research Database (Denmark)

Lindblom, Erik Ulfson; Press-Kristensen, Kåre; Vanrolleghem, P.A.

2009-01-01

The perspective of this work is to develop a model, which can be used to better understand and optimize wastewater treatment plants that are able to remove xenobiotic organic compounds (XOCs) in combination with removal of traditional pollutants. Results from dynamic experiments conducted...... with the endocrine disrupting XOC bisphenol-A (BPA) in an activated sludge process with real wastewater were used to hypothesize an ASM-based process model including aerobic growth of a specific BPA-degrading microorganism and sorption of BPA to sludge. A parameter estimation method was developed, which...... simultaneously utilizes steady-state background concentrations and dynamic step response data, as well as conceptual simplifications of the plant configuration. Validation results show that biodegradation of BPA is sensitive to operational conditions before and during the experiment and that the proposed model...
A practical demonstration in modelling diclofenac and propranolol river water concentrations using a GIS hydrology model in a rural UK catchment

Energy Technology Data Exchange (ETDEWEB)

Johnson, A.C. [Centre for Ecology and Hydrology (CEH) Wallingford, Benson Lane, Wallingford, Oxfordshire OX10 8BB (United Kingdom)]. E-mail: ajo@ceh.ac.uk; Keller, V. [Centre for Ecology and Hydrology (CEH) Wallingford, Benson Lane, Wallingford, Oxfordshire OX10 8BB (United Kingdom); Williams, R.J. [Centre for Ecology and Hydrology (CEH) Wallingford, Benson Lane, Wallingford, Oxfordshire OX10 8BB (United Kingdom); Young, A. [Centre for Ecology and Hydrology (CEH) Wallingford, Benson Lane, Wallingford, Oxfordshire OX10 8BB (United Kingdom)

2007-03-15

An existing GIS hydrology water quality model, LF2000-WQX, was applied to predict the concentrations of the pharmaceuticals diclofenac and propranalol in catchments. As a practical exercise the predominantly rural Tamar (UK) catchment was chosen. Consumption, excretion, and fate data were used to estimate the pharmaceutical input load for the model. The predicted concentrations throughout most of the catchment were 1 ng/L or less under low flow (90th percentile) conditions. However, at a few locations, downstream of small sewage treatment plants, concentrations above 25 ng/L were predicted. This exercise shows that it is relatively straightforward to predict the concentrations of new and emerging organic microcontaminants in real catchments using existing GIS hydrology water quality models. Further testing will be required to establish their accuracy. - A GIS hydrology model was used to predict pharmaceutical concentration hot spots in a rural catchment.
A practical demonstration in modelling diclofenac and propranolol river water concentrations using a GIS hydrology model in a rural UK catchment

International Nuclear Information System (INIS)

Johnson, A.C.; Keller, V.; Williams, R.J.; Young, A.

2007-01-01

An existing GIS hydrology water quality model, LF2000-WQX, was applied to predict the concentrations of the pharmaceuticals diclofenac and propranalol in catchments. As a practical exercise the predominantly rural Tamar (UK) catchment was chosen. Consumption, excretion, and fate data were used to estimate the pharmaceutical input load for the model. The predicted concentrations throughout most of the catchment were 1 ng/L or less under low flow (90th percentile) conditions. However, at a few locations, downstream of small sewage treatment plants, concentrations above 25 ng/L were predicted. This exercise shows that it is relatively straightforward to predict the concentrations of new and emerging organic microcontaminants in real catchments using existing GIS hydrology water quality models. Further testing will be required to establish their accuracy. - A GIS hydrology model was used to predict pharmaceutical concentration hot spots in a rural catchment
Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network.

Science.gov (United States)

Han, Hong-Gui; Zhang, Lu; Hou, Ying; Qiao, Jun-Fei

2016-02-01

A nonlinear model predictive control (NMPC) scheme is developed in this paper based on a self-organizing recurrent radial basis function (SR-RBF) neural network, whose structure and parameters are adjusted concurrently in the training process. The proposed SR-RBF neural network is represented in a general nonlinear form for predicting the future dynamic behaviors of nonlinear systems. To improve the modeling accuracy, a spiking-based growing and pruning algorithm and an adaptive learning algorithm are developed to tune the structure and parameters of the SR-RBF neural network, respectively. Meanwhile, for the control problem, an improved gradient method is utilized for the solution of the optimization problem in NMPC. The stability of the resulting control system is proved based on the Lyapunov stability theory. Finally, the proposed SR-RBF neural network-based NMPC (SR-RBF-NMPC) is used to control the dissolved oxygen (DO) concentration in a wastewater treatment process (WWTP). Comparisons with other existing methods demonstrate that the SR-RBF-NMPC can achieve a considerably better model fitting for WWTP and a better control performance for DO concentration.
Mathematical modeling of high-rate Anammox UASB reactor based on granular packing patterns

International Nuclear Information System (INIS)

Tang, Chong-Jian; He, Rui; Zheng, Ping; Chai, Li-Yuan; Min, Xiao-Bo

2013-01-01

Highlights: ► A novel model was conducted to estimate volumetric nitrogen conversion rates. ► The packing patterns of the granules in Anammox reactor are investigated. ► The simple cubic packing pattern was simulated in high-rate Anammox UASB reactor. ► Operational strategies concerning sludge concentration were proposed by the modeling. -- Abstract: A novel mathematical model was developed to estimate the volumetric nitrogen conversion rates of a high-rate Anammox UASB reactor based on the packing patterns of granular sludge. A series of relationships among granular packing density, sludge concentration, hydraulic retention time and volumetric conversion rate were constructed to correlate Anammox reactor performance with granular packing patterns. It was suggested that the Anammox granules packed as the equivalent simple cubic pattern in high-rate UASB reactor with packing density of 50–55%, which not only accommodated a high concentration of sludge inside the reactor, but also provided large pore volume, thus prolonging the actual substrate conversion time. Results also indicated that it was necessary to improve Anammox reactor performance by enhancing substrate loading when sludge concentration was higher than 37.8 gVSS/L. The established model was carefully calibrated and verified, and it well simulated the performance of granule-based high-rate Anammox UASB reactor
Mathematical modeling of high-rate Anammox UASB reactor based on granular packing patterns

Energy Technology Data Exchange (ETDEWEB)

Tang, Chong-Jian, E-mail: chjtangzju@yahoo.com.cn [Department of Environmental Engineering, School of Metallurgical Science and Engineering, Central South University, Changsha 410083 (China); National Engineering Research Center for Control and Treatment of Heavy Metal Pollution, Changsha 410083 (China); He, Rui; Zheng, Ping [Department of Environmental Engineering, Zhejiang University, Zijingang Campus, Hangzhou 310058 (China); Chai, Li-Yuan; Min, Xiao-Bo [Department of Environmental Engineering, School of Metallurgical Science and Engineering, Central South University, Changsha 410083 (China); National Engineering Research Center for Control and Treatment of Heavy Metal Pollution, Changsha 410083 (China)

2013-04-15

Highlights: ► A novel model was conducted to estimate volumetric nitrogen conversion rates. ► The packing patterns of the granules in Anammox reactor are investigated. ► The simple cubic packing pattern was simulated in high-rate Anammox UASB reactor. ► Operational strategies concerning sludge concentration were proposed by the modeling. -- Abstract: A novel mathematical model was developed to estimate the volumetric nitrogen conversion rates of a high-rate Anammox UASB reactor based on the packing patterns of granular sludge. A series of relationships among granular packing density, sludge concentration, hydraulic retention time and volumetric conversion rate were constructed to correlate Anammox reactor performance with granular packing patterns. It was suggested that the Anammox granules packed as the equivalent simple cubic pattern in high-rate UASB reactor with packing density of 50–55%, which not only accommodated a high concentration of sludge inside the reactor, but also provided large pore volume, thus prolonging the actual substrate conversion time. Results also indicated that it was necessary to improve Anammox reactor performance by enhancing substrate loading when sludge concentration was higher than 37.8 gVSS/L. The established model was carefully calibrated and verified, and it well simulated the performance of granule-based high-rate Anammox UASB reactor.
An Excel®-based visualization tool of 2-D soil gas concentration profiles in petroleum vapor intrusion.

Science.gov (United States)

Verginelli, Iason; Yao, Yijun; Suuberg, Eric M

2016-01-01

In this study we present a petroleum vapor intrusion tool implemented in Microsoft ® Excel ® using Visual Basic for Applications (VBA) and integrated within a graphical interface. The latter helps users easily visualize two-dimensional soil gas concentration profiles and indoor concentrations as a function of site-specific conditions such as source strength and depth, biodegradation reaction rate constant, soil characteristics and building features. This tool is based on a two-dimensional explicit analytical model that combines steady-state diffusion-dominated vapor transport in a homogeneous soil with a piecewise first-order aerobic biodegradation model, in which rate is limited by oxygen availability. As recommended in the recently released United States Environmental Protection Agency's final Petroleum Vapor Intrusion guidance, a sensitivity analysis and a simplified Monte Carlo uncertainty analysis are also included in the spreadsheet.
Charge transport model in nanodielectric composites based on quantum tunneling mechanism and dual-level traps

Energy Technology Data Exchange (ETDEWEB)

Li, Guochang; Chen, George, E-mail: gc@ecs.soton.ac.uk, E-mail: sli@mail.xjtu.edu.cn [State Key Laboratory of Electrical Insulation and Power Equipment, Xi' an Jiaotong University, Xi' an 710049 (China); School of Electronic and Computer Science, University of Southampton, Southampton SO17 1BJ (United Kingdom); Li, Shengtao, E-mail: gc@ecs.soton.ac.uk, E-mail: sli@mail.xjtu.edu.cn [State Key Laboratory of Electrical Insulation and Power Equipment, Xi' an Jiaotong University, Xi' an 710049 (China)

2016-08-08

Charge transport properties in nanodielectrics present different tendencies for different loading concentrations. The exact mechanisms that are responsible for charge transport in nanodielectrics are not detailed, especially for high loading concentration. A charge transport model in nanodielectrics has been proposed based on quantum tunneling mechanism and dual-level traps. In the model, the thermally assisted hopping (TAH) process for the shallow traps and the tunnelling process for the deep traps are considered. For different loading concentrations, the dominant charge transport mechanisms are different. The quantum tunneling mechanism plays a major role in determining the charge conduction in nanodielectrics with high loading concentrations. While for low loading concentrations, the thermal hopping mechanism will dominate the charge conduction process. The model can explain the observed conductivity property in nanodielectrics with different loading concentrations.
Statistical modeling of copper losses in the silicate slag of the sulfide concentrate smelting process

Directory of Open Access Journals (Sweden)

Savic Marija V.

2015-09-01

Full Text Available This article presents the results of the statistical modeling of copper losses in the silicate slag of the sulfide concentrates smelting process. The aim of this study was to define the correlation dependence of the degree of copper losses in the silicate slag on the following parameters of technological processes: SiO2, FeO, Fe3O4, CaO and Al2O3 content in the slag and copper content in the matte. Multiple linear regression analysis (MLRA, artificial neural networks (ANNs and adaptive network based fuzzy inference system (ANFIS were used as tools for mathematical analysis of the indicated problem. The best correlation coefficient (R2 = 0.719 of the final model was obtained using the ANFIS modeling approach.
Circulating Angiopoietin-2 and Its Soluble Receptor Tie-2 Concentrations Are Related to Renal Function in Two Population-Based Cohorts.

Science.gov (United States)

Hennings, Anna; Hannemann, Anke; Rettig, Rainer; Dörr, Marcus; Nauck, Matthias; Völzke, Henry; Lerch, Markus M; Lieb, Wolfgang; Friedrich, Nele

2016-01-01

An intact angiopoietin/Tie-2 ligand receptor system is indispensable for life. High circulating angiopoietin-2 (Ang-2) concentrations are strongly associated with kidney disease involving the progressive loss of glomerular filtration. The aim of our study was to investigate the associations between renal function and serum Ang-2 or serum Tie-2 concentrations in the general population. Data of 3081 and 4088 subjects from two population-based studies, the Study of Health in Pomerania (SHIP-1) and SHIP-Trend, were used. Renal function was assessed by serum creatinine, cystatin C concentration, creatinine-based estimated glomerular filtration rate [eGFR(crea)], cystatin C-based eGFR [eGFR(cys)] and urinary albumin-to-creatinine ratio (uACR). Analyses of variance and linear regression models were calculated. In both cohorts, strong positive associations between serum cystatin C concentrations and serum Ang-2 or Tie-2 concentrations as well as inverse associations between eGFR(cys) and serum Ang-2 or Tie-2 concentrations were found. These relations were also present in a subpopulation without hypertension or diabetes mellitus type 2. Furthermore, we detected weak U-shaped associations between serum creatinine concentrations or eGFR(crea) and serum Ang-2 concentrations. With respect to uACR a strong positive association with serum Ang-2 concentrations was revealed. Serum Ang-2 concentrations are strongly associated with sensitive parameters of renal impairment like serum cystatin C, uACR and eGFR(cys). These findings persisted even after exclusion of subjects with hypertension or diabetes mellitus type 2, conditions that predispose to chronic renal disease and are associated with increased Ang-2 concentrations. Interestingly, we did not detect the same strong relations between serum creatinine and eGFR(crea) with serum Ang-2 concentration. Additionally, significant association of serum Tie-2 concentrations with cystatin C and eGFR(cys) were detected.
Circulating Angiopoietin-2 and Its Soluble Receptor Tie-2 Concentrations Are Related to Renal Function in Two Population-Based Cohorts.

Directory of Open Access Journals (Sweden)

Anna Hennings

Full Text Available An intact angiopoietin/Tie-2 ligand receptor system is indispensable for life. High circulating angiopoietin-2 (Ang-2 concentrations are strongly associated with kidney disease involving the progressive loss of glomerular filtration. The aim of our study was to investigate the associations between renal function and serum Ang-2 or serum Tie-2 concentrations in the general population.Data of 3081 and 4088 subjects from two population-based studies, the Study of Health in Pomerania (SHIP-1 and SHIP-Trend, were used. Renal function was assessed by serum creatinine, cystatin C concentration, creatinine-based estimated glomerular filtration rate [eGFR(crea], cystatin C-based eGFR [eGFR(cys] and urinary albumin-to-creatinine ratio (uACR. Analyses of variance and linear regression models were calculated.In both cohorts, strong positive associations between serum cystatin C concentrations and serum Ang-2 or Tie-2 concentrations as well as inverse associations between eGFR(cys and serum Ang-2 or Tie-2 concentrations were found. These relations were also present in a subpopulation without hypertension or diabetes mellitus type 2. Furthermore, we detected weak U-shaped associations between serum creatinine concentrations or eGFR(crea and serum Ang-2 concentrations. With respect to uACR a strong positive association with serum Ang-2 concentrations was revealed.Serum Ang-2 concentrations are strongly associated with sensitive parameters of renal impairment like serum cystatin C, uACR and eGFR(cys. These findings persisted even after exclusion of subjects with hypertension or diabetes mellitus type 2, conditions that predispose to chronic renal disease and are associated with increased Ang-2 concentrations. Interestingly, we did not detect the same strong relations between serum creatinine and eGFR(crea with serum Ang-2 concentration. Additionally, significant association of serum Tie-2 concentrations with cystatin C and eGFR(cys were detected.
Modeling the interaction of light intensity, nutrient concentration and uranium toxicity in Lemna minor

Energy Technology Data Exchange (ETDEWEB)

Zimmer, E.; Horemans, N.; Vandenhove, H. [Belgian Nuclear Research Centre SCK-CEN (Belgium); Cedergreen, N. [University of Copenhagen (Denmark); Jager, T. [Vrije Universiteit Amsterdam (Netherlands)

2014-07-01

Radioecology aims at assessing the effect of radionuclides and radiation on the environment. Since we cannot test every possible environmental situation in the laboratory, we need modeling approaches to extrapolate the results of toxicity assays to environmentally relevant scenarios. Therefore, it is of crucial importance to understand the effect of relevant environmental factors, such as nutrients, temperature and light on the toxicity of the test. Radionuclides are often found to induce the production of reactive oxygen species (ROS). In plants, an overload of ROS can lead to disturbances of the photosynthetic system. Since the light intensity determines the efficiency of the photo-systems in plants, it can be expected to interact with the effect of radionuclides. The nutrient concentration of the test medium determines the physiological state of the plant, affecting in turn the plant's capability of dealing with stress and hence influences the toxicity of the contaminant. To study the interaction of stressors with environmental conditions, mechanistic effect modeling is promoted widely in ecotoxicology. In principle, the modelling aims at a mechanistic understanding of the different processes causing the stress individually, and integrating them in one framework to study their joint effect and possible interaction. We here present a mechanistic effect model for Lemna minor (common duckweed), which is based on Dynamic Energy Budget (DEB) theory. Models based on DEB have been used widely to study the effects of compounds on animals. Due to its general applicability to all types of organisms, it holds potential to be used for comparison of species and compounds in a broad context. Energy uptake from the environment is modeled explicitly, and metabolic rates are set to depend on temperature in DEB models. Therefore, they can be used to extrapolate effects to a wide range of environmentally relevant scenarios. Until now, the DEB research in ecotoxicology has
Transfer and concentration factors in laboratory and environmental conditions

International Nuclear Information System (INIS)

Paschoa, A.S.; Amaral, E.C.S.

1993-01-01

Environmental transfer factors, as well as concentration and accumulation factors, have been increasingly used in environmental dosimetric models. These models are often the basis for decision-making processes concerning radiological protection. However, the uncertainties associated with measured and default values of transfer and concentration factors are usually not taken into account in the decision making processes. In addition, laboratory-based values for these factors do not necessarily agree with site-specific and species-specific transfer and concentration factors. Soil-to-plant transfer factors and water-to-aquatic-organisms concentration factors are not only time and concentration-dependent, but also species-and site-specific environment-dependent. These uncertainties and dependencies may make the decision-making process, based on models, quite a difficult exercise. The current work examines, as an example, the time-dependent variations in the accumulation of 226 Ra in zooplankton in a laboratory experiment as compared with the concentration factor measured in a natural environment. In addition, the work reviews differences in 228 Ra and 226 Ra concentration factors for several plant families measured in a highly radioactive environment. (author). 9 refs, 3 figs, 3 tabs
ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

KAUST Repository

Kuwahara, Hiroyuki; Umarov, Ramzan; Almasri, Islam; Gao, Xin

2017-01-01

To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.
ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

KAUST Repository

Kuwahara, Hiroyuki

2017-03-01

To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.
Modeling radiocesium transport from a river catchment based on a physically-based distributed hydrological and sediment erosion model.

Science.gov (United States)

Kinouchi, Tsuyoshi; Yoshimura, Kazuya; Omata, Teppei

2015-01-01

The accident at the Fukushima Dai-ichi Nuclear Power Plant (FDNPP) in March 2011 resulted in the deposition of large quantities of radionuclides, such as (134)Cs and (137)Cs, over parts of eastern Japan. Since then high levels of radioactive contamination have been detected in large areas, including forests, agricultural land, and residential areas. Due to the strong adsorption capability of radiocesium to soil particles, radiocesium migrates with eroded sediments, follows the surface flow paths, and is delivered to more populated downstream regions and eventually to the Pacific Ocean. It is therefore important to understand the transport of contaminated sediments in the hydrological system and to predict changes in the spatial distribution of radiocesium concentrations by taking the land-surface processes related to sediment migration into consideration. In this study, we developed a distributed model to simulate the transport of water and contaminated sediment in a watershed hydrological system, and applied this model to a partially forested mountain catchment located in an area highly contaminated by the radioactive fallout. Observed discharge, sediment concentration, and cesium concentration measured from June 2011 until December 2012 were used for calibration of model parameters. The simulated discharge and sediment concentration both agreed well with observed values, while the cesium concentration was underestimated in the initial period following the accident. This result suggests that the leaching of radiocesium from the forest canopy, which was not considered in the model, played a significant role in its transport from the catchment. Based on the simulation results, we quantified the long-term fate of radiocesium over the study area and estimated that the effective half-life of (137)Cs deposited in the study area will be approximately 22 y due to the export of contaminated sediment by land-surface processes, and the amount of (137)Cs remaining in the
Performance model of metallic concentric tube recuperator with counter flow arrangement

Energy Technology Data Exchange (ETDEWEB)

Sharma, Harshdeep [HIET, Department of Mechanical Engineering, Ghaziabad, Uttar Pradesh (India); Kumar, Anoop; Goel, Varun [NIT, Department of Mechanical Engineering, Hamirpur, Himachal Pradesh (India)

2010-03-15

A performance model for counter flow arrangement in concentric tube recuperator that can be used to utilize the waste heat in the temperature range of 900-1,400 C is presented. The arrangement consists of metallic tubular inner and outer concentric shell with a small annular gap between two concentric shells. Flue gases pass through the inner shell while air passes through the annular gap in the reverse direction (counter flow arrangement). The height of the recuperator is divided into elements and an energy balance is performed on each elemental height. Results give necessary information about surface, gas and air temperature distribution, and the influence of operating conditions on recuperator performance. The recuperative effectiveness is found to be increased with increasing inlet gas temperature and decreased with increasing fuel flow rate. The present model accounts for all heat transfer processes pertinent to a counterflow radiation recuperator and provide a valuable tool for performance considerations. (orig.)

Optimization of artificial neural network models through genetic algorithms for surface ozone concentration forecasting.

Science.gov (United States)

Pires, J C M; Gonçalves, B; Azevedo, F G; Carneiro, A P; Rego, N; Assembleia, A J B; Lima, J F B; Silva, P A; Alves, C; Martins, F G

2012-09-01

This study proposes three methodologies to define artificial neural network models through genetic algorithms (GAs) to predict the next-day hourly average surface ozone (O(3)) concentrations. GAs were applied to define the activation function in hidden layer and the number of hidden neurons. Two of the methodologies define threshold models, which assume that the behaviour of the dependent variable (O(3) concentrations) changes when it enters in a different regime (two and four regimes were considered in this study). The change from one regime to another depends on a specific value (threshold value) of an explanatory variable (threshold variable), which is also defined by GAs. The predictor variables were the hourly average concentrations of carbon monoxide (CO), nitrogen oxide, nitrogen dioxide (NO(2)), and O(3) (recorded in the previous day at an urban site with traffic influence) and also meteorological data (hourly averages of temperature, solar radiation, relative humidity and wind speed). The study was performed for the period from May to August 2004. Several models were achieved and only the best model of each methodology was analysed. In threshold models, the variables selected by GAs to define the O(3) regimes were temperature, CO and NO(2) concentrations, due to their importance in O(3) chemistry in an urban atmosphere. In the prediction of O(3) concentrations, the threshold model that considers two regimes was the one that fitted the data most efficiently.
40 CFR 761.298 - Decisions based on PCB concentration measurements resulting from sampling.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Decisions based on PCB concentration... Cleanup and On-Site Disposal of Bulk PCB Remediation Waste and Porous Surfaces in Accordance With Â§ 761.61(a)(6) § 761.298 Decisions based on PCB concentration measurements resulting from sampling. (a) For...
Modeling of steroid estrogen contamination in UK and South Australian rivers predicts modest increases in concentrations in the future.

Science.gov (United States)

Green, Christopher; Williams, Richard; Kanda, Rakesh; Churchley, John; He, Ying; Thomas, Shaun; Goonan, Peter; Kumar, Anu; Jobling, Susan

2013-07-02

The prediction of risks posed by pharmaceuticals and personal care products in the aquatic environment now and in the future is one of the top 20 research questions regarding these contaminants following growing concern for their biological effects on fish and other animals. To this end it is important that areas experiencing the greatest risk are identified, particularly in countries experiencing water stress, where dilution of pollutants entering river networks is more limited. This study is the first to use hydrological models to estimate concentrations of pharmaceutical and natural steroid estrogens in a water stressed catchment in South Australia alongside a UK catchment and to forecast their concentrations in 2050 based on demographic and climate change predictions. The results show that despite their differing climates and demographics, modeled concentrations of steroid estrogens in effluents from Australian sewage treatment works and a receiving river were predicted (simulated) to be similar to those observed in the UK and Europe, exceeding the combined estradiol equivalent's predicted no effect concentration for feminization in wild fish. Furthermore, by 2050 a moderate increase in estrogenic contamination and the potential risk to wildlife was predicted with up to a 2-fold rise in concentrations.
Modelling daily dissolved oxygen concentration using least square support vector machine, multivariate adaptive regression splines and M5 model tree

Science.gov (United States)

Heddam, Salim; Kisi, Ozgur

2018-04-01

In the present study, three types of artificial intelligence techniques, least square support vector machine (LSSVM), multivariate adaptive regression splines (MARS) and M5 model tree (M5T) are applied for modeling daily dissolved oxygen (DO) concentration using several water quality variables as inputs. The DO concentration and water quality variables data from three stations operated by the United States Geological Survey (USGS) were used for developing the three models. The water quality data selected consisted of daily measured of water temperature (TE, °C), pH (std. unit), specific conductance (SC, μS/cm) and discharge (DI cfs), are used as inputs to the LSSVM, MARS and M5T models. The three models were applied for each station separately and compared to each other. According to the results obtained, it was found that: (i) the DO concentration could be successfully estimated using the three models and (ii) the best model among all others differs from one station to another.
A Mathematical Model of Neutral Lipid Content in terms of Initial Nitrogen Concentration and Validation in Coelastrum sp. HA-1 and Application in Chlorella sorokiniana

Directory of Open Access Journals (Sweden)

Zhenhua Yang

2017-01-01

Full Text Available Microalgae are considered to be a potential major biomass feedstock for biofuel due to their high lipid content. However, no correlation equations as a function of initial nitrogen concentration for lipid accumulation have been developed for simplicity to predict lipid production and optimize the lipid production process. In this study, a lipid accumulation model was developed with simple parameters based on the assumption protein synthesis shift to lipid synthesis by a linear function of nitrogen quota. The model predictions fitted well for the growth, lipid content, and nitrogen consumption of Coelastrum sp. HA-1 under various initial nitrogen concentrations. Then the model was applied successfully in Chlorella sorokiniana to predict the lipid content with different light intensities. The quantitative relationship between initial nitrogen concentrations and the final lipid content with sensitivity analysis of the model were also discussed. Based on the model results, the conversion efficiency from protein synthesis to lipid synthesis is higher and higher in microalgae metabolism process as nitrogen decreases; however, the carbohydrate composition content remains basically unchanged neither in HA-1 nor in C. sorokiniana.
A Mathematical Model of Neutral Lipid Content in terms of Initial Nitrogen Concentration and Validation in Coelastrum sp. HA-1 and Application in Chlorella sorokiniana

Science.gov (United States)

Zhao, Yue; Liu, Zhiyong; Liu, Chenfeng; Hu, Zhipeng

2017-01-01

Microalgae are considered to be a potential major biomass feedstock for biofuel due to their high lipid content. However, no correlation equations as a function of initial nitrogen concentration for lipid accumulation have been developed for simplicity to predict lipid production and optimize the lipid production process. In this study, a lipid accumulation model was developed with simple parameters based on the assumption protein synthesis shift to lipid synthesis by a linear function of nitrogen quota. The model predictions fitted well for the growth, lipid content, and nitrogen consumption of Coelastrum sp. HA-1 under various initial nitrogen concentrations. Then the model was applied successfully in Chlorella sorokiniana to predict the lipid content with different light intensities. The quantitative relationship between initial nitrogen concentrations and the final lipid content with sensitivity analysis of the model were also discussed. Based on the model results, the conversion efficiency from protein synthesis to lipid synthesis is higher and higher in microalgae metabolism process as nitrogen decreases; however, the carbohydrate composition content remains basically unchanged neither in HA-1 nor in C. sorokiniana. PMID:28194424
Banking Crisis Early Warning Model based on a Bayesian Model Averaging Approach

Directory of Open Access Journals (Sweden)

Taha Zaghdoudi

2016-08-01

Full Text Available The succession of banking crises in which most have resulted in huge economic and financial losses, prompted several authors to study their determinants. These authors constructed early warning models to prevent their occurring. It is in this same vein as our study takes its inspiration. In particular, we have developed a warning model of banking crises based on a Bayesian approach. The results of this approach have allowed us to identify the involvement of the decline in bank profitability, deterioration of the competitiveness of the traditional intermediation, banking concentration and higher real interest rates in triggering bank crisis.
Inter-annual variability of the atmospheric carbon dioxide concentrations as simulated with global terrestrial biosphere models and an atmospheric transport model

Energy Technology Data Exchange (ETDEWEB)

Fujita, Daisuke; Saeki, Tazu; Nakazawa, Takakiyo [Tohoku Univ., Sendai (Japan). Center for Atmospheric and Oceanic Studies; Ishizawa, Misa; Maksyutov, Shamil [Inst. for Global Change Research, Yokohama (Japan). Frontier Research System for Global Change; Thornton, Peter E. [National Center for Atmospheric Research, Boulder, CO (United States). Climate and Global Dynamics Div.

2003-04-01

Seasonal and inter-annual variations of atmospheric CO{sub 2} for the period from 1961 to 1997 have been simulated using a global tracer transport model driven by a new version of the Biome BioGeochemical Cycle model (Biome-BGC). Biome-BGC was forced by daily temperature and precipitation from the NCEP reanalysis dataset, and the calculated monthly-averaged CO{sub 2} fluxes were used as input to the global transport model. Results from an inter-comparison with the Carnegie-Ames-Stanford Approach model (CASA) and the Simulation model of Carbon CYCLE in Land Ecosystems (Sim-CYCLE) model are also reported. The phase of the seasonal cycle in the Northern Hemisphere was reproduced generally well by Biome-BGC, although the amplitude was smaller compared to the observations and to the other biosphere models. The CO{sub 2} time series simulated by Biome-BGC were compared to the global CO{sub 2} concentration anomalies from the observations at Mauna Loa and the South Pole. The modeled concentration anomalies matched the phase of the inter-annual variations in the atmospheric CO{sub 2} observations; however, the modeled amplitude was lower than the observed value in several cases. The result suggests that a significant part of the inter-annual variability in the global carbon cycle can be accounted for by the terrestrial biosphere models. Simulations performed with another climate-based model, Sim-CYCLE, produced a larger amplitude of inter-annual variability in atmospheric CO{sub 2}, making the amplitude closer to the observed range, but with a more visible phase mismatch in a number of time periods. This may indicate the need to increase the Biome-BGC model sensitivity to seasonal and inter-annual changes in temperature and precipitation.
Inter-annual variability of the atmospheric carbon dioxide concentrations as simulated with global terrestrial biosphere models and an atmospheric transport model

International Nuclear Information System (INIS)

Fujita, Daisuke; Saeki, Tazu; Nakazawa, Takakiyo; Ishizawa, Misa; Maksyutov, Shamil; Thornton, Peter E.

2003-01-01

Seasonal and inter-annual variations of atmospheric CO 2 for the period from 1961 to 1997 have been simulated using a global tracer transport model driven by a new version of the Biome BioGeochemical Cycle model (Biome-BGC). Biome-BGC was forced by daily temperature and precipitation from the NCEP reanalysis dataset, and the calculated monthly-averaged CO 2 fluxes were used as input to the global transport model. Results from an inter-comparison with the Carnegie-Ames-Stanford Approach model (CASA) and the Simulation model of Carbon CYCLE in Land Ecosystems (Sim-CYCLE) model are also reported. The phase of the seasonal cycle in the Northern Hemisphere was reproduced generally well by Biome-BGC, although the amplitude was smaller compared to the observations and to the other biosphere models. The CO 2 time series simulated by Biome-BGC were compared to the global CO 2 concentration anomalies from the observations at Mauna Loa and the South Pole. The modeled concentration anomalies matched the phase of the inter-annual variations in the atmospheric CO 2 observations; however, the modeled amplitude was lower than the observed value in several cases. The result suggests that a significant part of the inter-annual variability in the global carbon cycle can be accounted for by the terrestrial biosphere models. Simulations performed with another climate-based model, Sim-CYCLE, produced a larger amplitude of inter-annual variability in atmospheric CO 2 , making the amplitude closer to the observed range, but with a more visible phase mismatch in a number of time periods. This may indicate the need to increase the Biome-BGC model sensitivity to seasonal and inter-annual changes in temperature and precipitation
MATHEMATICAL MODELING AND NUMERICAL SOLUTION OF IRON CORROSION PROBLEM BASED ON CONDENSATION CHEMICAL PROPERTIES

Directory of Open Access Journals (Sweden)

Basuki Widodo

2012-02-01

Full Text Available Corrosion process is a natural case that happened at the various metals, where the corrosion process in electrochemical can be explained by using galvanic cell. The iron corrosion process is based on the acidity degree (pH of a condensation, iron concentration and condensation temperature of electrolyte. Those are applied at electrochemistry cell. The iron corrosion process at this electrochemical cell also able to generate electrical potential and electric current during the process takes place. This paper considers how to build a mathematical model of iron corrosion, electrical potential and electric current. The mathematical model further is solved using the finite element method. This iron corrosion model is built based on the iron concentration, condensation temperature, and iteration time applied. In the electric current density model, the current based on electric current that is happened at cathode and anode pole and the iteration time applied. Whereas on the potential electric model, it is based on the beginning of electric potential and the iteration time applied. The numerical results show that the part of iron metal, that is gristle caused by corrosion, is the part of metal that has function as anode and it has some influences, such as time depth difference, iron concentration and condensation temperature on the iron corrosion process and the sum of reduced mass during corrosion process. Moreover, difference influence of time and beginning electric potential has an effect on the electric potential, which emerges during corrosion process at the electrochemical cell. Whereas, at the electrical current is also influenced by difference of depth time and condensation temperature applied.Keywords: Iron Corrosion, Concentration of iron, Electrochemical Cell and Finite Element Method
Fitting diameter distribution models to data from forest inventories with concentric plot design

Energy Technology Data Exchange (ETDEWEB)

Nanos, N.; Sjöstedt de Luna, S.

2017-11-01

Aim: Several national forest inventories use a complex plot design based on multiple concentric subplots where smaller diameter trees are inventoried when lying in the smaller-radius subplots and ignored otherwise. Data from these plots are truncated with threshold (truncation) diameters varying according to the distance from the plot centre. In this paper we designed a maximum likelihood method to fit the Weibull diameter distribution to data from concentric plots. Material and methods: Our method (M1) was based on multiple truncated probability density functions to build the likelihood. In addition, we used an alternative method (M2) presented recently. We used methods M1 and M2 as well as two other reference methods to estimate the Weibull parameters in 40000 simulated plots. The spatial tree pattern of the simulated plots was generated using four models of spatial point patterns. Two error indices were used to assess the relative performance of M1 and M2 in estimating relevant stand-level variables. In addition, we estimated the Quadratic Mean plot Diameter (QMD) using Expansion Factors (EFs). Main results: Methods M1 and M2 produced comparable estimation errors in random and cluster tree spatial patterns. Method M2 produced biased parameter estimates in plots with inhomogeneous Poisson patterns. Estimation of QMD using EFs produced biased results in plots within inhomogeneous intensity Poisson patterns. Research highlights:We designed a new method to fit the Weibull distribution to forest inventory data from concentric plots that achieves high accuracy and precision in parameter estimates regardless of the within-plot spatial tree pattern.
Analysis and modelling of the factors controlling seed oil concentration in sunflower: a review

Directory of Open Access Journals (Sweden)

Andrianasolo Fety Nambinina

2016-03-01

Full Text Available Sunflower appears as a potentially highly competitive crop, thanks to the diversification of its market and the richness of its oil. However, seed oil concentration (OC – a commercial criterion for crushing industry – is subjected to genotypic and environmental effects that make it sometimes hardly predictable. It is assumed that more understanding of oil physiology combined with the use of crop models should permit to improve prediction and management of grain quality for various end-users. Main effects of temperature, water, nitrogen, plant density and fungal diseases were reviewed in this paper. Current generic and specific crop models which simulate oil concentration were found to be empirical and to lack of proper evaluation processes. Recently two modeling approaches integrating ecophysiological knowledge were developed by Andrianasolo (2014, Statistical and dynamic modelling of sunflower (Helianthus annuus L. grain composition as a function of agronomic and environmental factors, Ph.D. Thesis, INP Toulouse: (i a statistical approach relating OC to a range of explanatory variables (potential OC, temperature, water and nitrogen stress indices, intercepted radiation, plant density which resulted in prediction quality from 1.9 to 2.5 oil points depending on the nature of the models; (ii a dynamic approach, based on “source-sink” relationships involving leaves, stems, receptacles (as sources and hulls, proteins and oil (as sinks and using priority rules for carbon and nitrogen allocation. The latter model reproduced dynamic patterns of all source and sink components faithfully, but tended to overestimate OC. A better description of photosynthesis and nitrogen uptake, as well as genotypic parameters is expected to improve its performance.
A Risk Assessment Model for Bacterial Leaf Spot of Pepper (Capsicum annuum), Caused by Xanthomonas euvesicatoria, Based on Concentrations of Macronutrients, Micronutrients, and Micronutrient Ratios.

Science.gov (United States)

Dutta, B; Langston, D B; Luo, X; Carlson, S; Kichler, J; Gitaitis, R

2017-11-01

The phytopathogenic bacterium Xanthomonas euvesicatoria causes bacterial leaf spot (BLS) of pepper and has a worldwide distribution. BLS is difficult to control and an integrated management strategy that incorporates crop rotation, use of clean seed and clean plants, weed control, resistant varieties, applications of bactericides, biocontrol agents, and systemic acquired resistance (SAR) inducers is generally recommended. However, even with that arsenal of weapons, BLS can still be responsible for severe losses under favorable environmental conditions. Thus, additional tools need to be added to an overall integrated management strategy to combat BLS. In this article, we developed several models from 2012 to 2014 that were based on how macronutrients, micronutrients, and micronutrient ratios affect BLS severity. Factors used to select a model for validation included highly significant P values, high adjusted R 2 values, low variance inflation factor values (macronutrient and micronutrient concentrations affect plant disease resistance genes in the SAR pathway.
Variation in predicted internal concentrations in relation to PBPK model complexity for rainbow trout

Energy Technology Data Exchange (ETDEWEB)

Salmina, E.S.; Wondrousch, D. [UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Institute for Organic Chemistry, Technical University Bergakademie Freiberg, Leipziger Str. 29, 09596 Freiberg (Germany); Kühne, R. [UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Potemkin, V.A. [Department of Chemistry, South Ural State Medical University, Vorovskogo 64, 454048, Chelyabinsk (Russian Federation); Schüürmann, G. [UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Institute for Organic Chemistry, Technical University Bergakademie Freiberg, Leipziger Str. 29, 09596 Freiberg (Germany)

2016-04-15

The present study is motivated by the increasing demand to consider internal partitioning into tissues instead of exposure concentrations for the environmental toxicity assessment. To this end, physiologically based pharmacokinetic (PBPK) models can be applied. We evaluated the variation in accuracy of PBPK model outcomes depending on tissue constituents modeled as sorptive phases and chemical distribution tendencies addressed by molecular descriptors. The model performance was examined using data from 150 experiments for 28 chemicals collected from US EPA databases. The simplest PBPK model is based on the “K{sub ow}-lipid content” approach as being traditional for environmental toxicology. The most elaborated one considers five biological sorptive phases (polar and non-polar lipids, water, albumin and the remaining proteins) and makes use of LSER (linear solvation energy relationship) parameters to describe the compound partitioning behavior. The “K{sub ow}-lipid content”-based PBPK model shows more than one order of magnitude difference in predicted and measured values for 37% of the studied exposure experiments while for the most elaborated model this happens only for 7%. It is shown that further improvements could be achieved by introducing corrections for metabolic biotransformation and compound transmission hindrance through a cellular membrane. The analysis of the interface distribution tendencies shows that polar tissue constituents, namely water, polar lipids and proteins, play an important role in the accumulation behavior of polar compounds with H-bond donating functional groups. For compounds without H-bond donating fragments preferable accumulation phases are storage lipids and water depending on compound polarity. - Highlights: • For reliable predictions, models of a certain complexity should be compared. • For reliable predictions non-lipid fish tissue constituents should be considered. • H-donor compounds preferably accumulate in water
Variation in predicted internal concentrations in relation to PBPK model complexity for rainbow trout

International Nuclear Information System (INIS)

Salmina, E.S.; Wondrousch, D.; Kühne, R.; Potemkin, V.A.; Schüürmann, G.

2016-01-01

The present study is motivated by the increasing demand to consider internal partitioning into tissues instead of exposure concentrations for the environmental toxicity assessment. To this end, physiologically based pharmacokinetic (PBPK) models can be applied. We evaluated the variation in accuracy of PBPK model outcomes depending on tissue constituents modeled as sorptive phases and chemical distribution tendencies addressed by molecular descriptors. The model performance was examined using data from 150 experiments for 28 chemicals collected from US EPA databases. The simplest PBPK model is based on the “K_o_w-lipid content” approach as being traditional for environmental toxicology. The most elaborated one considers five biological sorptive phases (polar and non-polar lipids, water, albumin and the remaining proteins) and makes use of LSER (linear solvation energy relationship) parameters to describe the compound partitioning behavior. The “K_o_w-lipid content”-based PBPK model shows more than one order of magnitude difference in predicted and measured values for 37% of the studied exposure experiments while for the most elaborated model this happens only for 7%. It is shown that further improvements could be achieved by introducing corrections for metabolic biotransformation and compound transmission hindrance through a cellular membrane. The analysis of the interface distribution tendencies shows that polar tissue constituents, namely water, polar lipids and proteins, play an important role in the accumulation behavior of polar compounds with H-bond donating functional groups. For compounds without H-bond donating fragments preferable accumulation phases are storage lipids and water depending on compound polarity. - Highlights: • For reliable predictions, models of a certain complexity should be compared. • For reliable predictions non-lipid fish tissue constituents should be considered. • H-donor compounds preferably accumulate in water, polar
Characterizing mercury concentrations and fluxes in a Coastal Plain watershed: Insights from dynamic modeling and data

Science.gov (United States)

Golden, H.E.; Knightes, C.D.; Conrads, P.A.; Davis, G.M.; Feaster, T.D.; Journey, C.A.; Benedict, S.T.; Brigham, M.E.; Bradley, P.M.

2012-01-01

Mercury (Hg) is one of the leading water quality concerns in surface waters of the United States. Although watershed-scale Hg cycling research has increased in the past two decades, advances in modeling watershed Hg processes in diverse physiographic regions, spatial scales, and land cover types are needed. The goal of this study was to assess Hg cycling in a Coastal Plain system using concentrations and fluxes estimated by multiple watershed-scale models with distinct mathematical frameworks reflecting different system dynamics. We simulated total mercury (HgT, the sum of filtered and particulate forms) concentrations and fluxes from a Coastal Plain watershed (McTier Creek) using three watershed Hg models and an empirical load model. Model output was compared with observed in-stream HgT. We found that shallow subsurface flow is a potentially important transport mechanism of particulate HgT during periods when connectivity between the uplands and surface waters is maximized. Other processes (e.g., stream bank erosion, sediment re-suspension) may increase particulate HgT in the water column. Simulations and data suggest that variable source area (VSA) flow and lack of rainfall interactions with surface soil horizons result in increased dissolved HgT concentrations unrelated to DOC mobilization following precipitation events. Although flushing of DOC-HgT complexes from surface soils can also occur during this period, DOC-complexed HgT becomes more important during base flow conditions. TOPLOAD simulations highlight saturated subsurface flow as a primary driver of daily HgT loadings, but shallow subsurface flow is important for HgT loads during high-flow events. Results suggest limited seasonal trends in HgT dynamics.
Historical occupational trichloroethylene air concentrations based on inspection measurements from Shanghai, China.

Science.gov (United States)

Friesen, Melissa C; Locke, Sarah J; Chen, Yu-Cheng; Coble, Joseph B; Stewart, Patricia A; Ji, Bu-Tian; Bassig, Bryan; Lu, Wei; Xue, Shouzheng; Chow, Wong-Ho; Lan, Qing; Purdue, Mark P; Rothman, Nathaniel; Vermeulen, Roel

2015-01-01

Trichloroethylene (TCE) is a carcinogen that has been linked to kidney cancer and possibly other cancer sites including non-Hodgkin lymphoma. Its use in China has increased since the early 1990s with China's growing metal, electronic, and telecommunications industries. We examined historical occupational TCE air concentration patterns in a database of TCE inspection measurements collected in Shanghai, China to identify temporal trends and broad contrasts among occupations and industries. Using a database of 932 short-term, area TCE air inspection measurements collected in Shanghai worksites from 1968 through 2000 (median year 1986), we developed mixed-effects models to evaluate job-, industry-, and time-specific TCE air concentrations. Models of TCE air concentrations from Shanghai work sites predicted that exposures decreased 5-10% per year between 1968 and 2000. Measurements collected near launderers and dry cleaners had the highest predicted geometric means (GM for 1986 = 150-190 mg m(-3)). The majority (53%) of the measurements were collected in metal treatment jobs. In a model restricted to measurements in metal treatment jobs, predicted GMs for 1986 varied 35-fold across industries, from 11 mg m(-3) in 'other metal products/repair' industries to 390 mg m(-3) in 'ships/aircrafts' industries. TCE workplace air concentrations appeared to have dropped over time in Shanghai, China between 1968 and 2000. Understanding differences in TCE concentrations across time, occupations, and industries may assist future epidemiologic studies in China. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2014.
Application of a Weighted Regression Model for Reporting Nutrient and Sediment Concentrations, Fluxes, and Trends in Concentration and Flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, Results Through Water Year 2012

Science.gov (United States)

Chanat, Jeffrey G.; Moyer, Douglas L.; Blomquist, Joel D.; Hyer, Kenneth E.; Langland, Michael J.

2016-01-13

In the Chesapeake Bay watershed, estimated fluxes of nutrients and sediment from the bay’s nontidal tributaries into the estuary are the foundation of decision making to meet reductions prescribed by the Chesapeake Bay Total Maximum Daily Load (TMDL) and are often the basis for refining scientific understanding of the watershed-scale processes that influence the delivery of these constituents to the bay. Two regression-based flux and trend estimation models, ESTIMATOR and Weighted Regressions on Time, Discharge, and Season (WRTDS), were compared using data from 80 watersheds in the Chesapeake Bay Nontidal Water-Quality Monitoring Network (CBNTN). The watersheds range in size from 62 to 70,189 square kilometers and record lengths range from 6 to 28 years. ESTIMATOR is a constant-parameter model that estimates trends only in concentration; WRTDS uses variable parameters estimated with weighted regression, and estimates trends in both concentration and flux. WRTDS had greater explanatory power than ESTIMATOR, with the greatest degree of improvement evident for records longer than 25 years (30 stations; improvement in median model R2= 0.06 for total nitrogen, 0.08 for total phosphorus, and 0.05 for sediment) and the least degree of improvement for records of less than 10 years, for which the two models performed nearly equally. Flux bias statistics were comparable or lower (more favorable) for WRTDS for any record length; for 30 stations with records longer than 25 years, the greatest degree of improvement was evident for sediment (decrease of 0.17 in median statistic) and total phosphorus (decrease of 0.05). The overall between-station pattern in concentration trend direction and magnitude for all constituents was roughly similar for both models. A detailed case study revealed that trends in concentration estimated by WRTDS can operationally be viewed as a less-constrained equivalent to trends in concentration estimated by ESTIMATOR. Estimates of annual mean flow
Classification of archaeological pieces into their respective stratum by a chemometric model based on the soil concentration of 25 selected elements

International Nuclear Information System (INIS)

Carrero, J.A.; Goienaga, N.; Fdez-Ortiz de Vallejuelo, S.; Arana, G.; Madariaga, J.M.

2010-01-01

The aim of this work was to demonstrate that an archaeological ceramic piece has remained buried underground in the same stratum for centuries without being removed. For this purpose, a chemometric model based on Principal Component Analysis, Soft Independent Modelling of Class Analogy and Linear Discriminant Analysis classification techniques was created with the concentration of some selected elements of both soil of the stratum and soil adhered to the ceramic piece. Some ceramic pieces from four different stratigraphic units, coming from a roman archaeological site in Alava (North of Spain), and its respective stratum soils were collected. The soil adhered to the ceramic pieces was removed and treated in the same way as the soil from its respective stratum. The digestion was carried out following the US Environmental Pollution Agency EPA 3051A method. A total of 54 elements were determined in the extracts by a rapid screening inductively coupled plasma mass spectrometry method. After rejecting the major elements and those which could have changed from the original composition of the soils (migration or retention from/to the buried objects), the following elements (25) were finally taken into account to construct the model: Li, V, Co, As, Y, Nb, Sn, Ba, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Au, Th and U. A total of 33 subsamples were treated from 10 soils belonging to 4 different stratigraphic units. The final model groups and discriminate them in four groups, according to the stratigraphic unit, having both the stratum and soils adhered to the pieces falling down in the same group.
Probabilistic modelling of prospective environmental concentrations of gold nanoparticles from medical applications as a basis for risk assessment.

Science.gov (United States)

Mahapatra, Indrani; Sun, Tian Yin; Clark, Julian R A; Dobson, Peter J; Hungerbuehler, Konrad; Owen, Richard; Nowack, Bernd; Lead, Jamie

2015-12-22

The use of gold nanoparticles (Au-NP) based medical applications is rising due to their unique physical and chemical properties. Diagnostic devices based on Au-NP are already available in the market or are in clinical trials and Au-NP based therapeutics and theranostics (combined diagnostic and treatment modality) are in the research and development phase. Currently, no information on Au-NP consumption, material flows to and concentrations in the environment are available. Therefore, we estimated prospective maximal consumption of Au-NP from medical applications in the UK and US. We then modelled the Au-NP flows post-use and predicted their environmental concentrations. Furthermore, we assessed the environment risks of Au-NP by comparing the predicted environmental concentrations (PECs) with ecological threshold (PNEC) values. The mean annual estimated consumption of Au-NP from medical applications is 540 kg for the UK and 2700 kg for the US. Among the modelled concentrations of Au-NP in environmental compartments, the mean annual PEC of Au-NP in sludge for both the UK and US was estimated at 124 and 145 μg kg(-1), respectively. The mean PEC in surface water was estimated at 468 and 4.7 pg L(-1), respectively for the UK and US. The NOEC value for the water compartment ranged from 0.12 up to 26,800 μg L(-1), with most values in the range of 1000 μg L(-1). The results using the current set of data indicate that the environmental risk from Au-NP used in nanomedicine in surface waters and from agricultural use of biosolids is minimal in the near future, especially because we have used a worst-case use assessment. More Au-NP toxicity studies are needed for the soil compartment.

Physicologically Based Toxicokinetic Models of Tebuconazole and Application in Human Risk Assessment

DEFF Research Database (Denmark)

Jonsdottir, Svava Osk; Reffstrup, Trine Klein; Petersen, Annette

2016-01-01

(ADME) of tebuconazole. The developed models were validated on in vivo half-life data for rabbit with good results, and on plasma and tissue concentration-time course data of tebuconazole after i.v. administration in rabbit. In most cases, the predicted concentration levels were seen to be within......A series of physiologically based toxicokinetic (PBTK) models for tebuconazole were developed in four species, rat, rabbit, rhesus monkey, and human. The developed models were analyzed with respect to the application of the models in higher tier human risk assessment, and the prospect of using...... such models in risk assessment of cumulative and aggregate exposure is discussed. Relatively simple and biologically sound models were developed using available experimental data as parameters for describing the physiology of the species, as well as the absorption, distribution, metabolism, and elimination...
Reproducibility of Carbon and Water Cycle by an Ecosystem Process Based Model Using a Weather Generator and Effect of Temporal Concentration of Precipitation on Model Outputs

Science.gov (United States)

Miyauchi, T.; Machimura, T.

2014-12-01

GCM is generally used to produce input weather data for the simulation of carbon and water cycle by ecosystem process based models under climate change however its temporal resolution is sometimes incompatible to requirement. A weather generator (WG) is used for temporal downscaling of input weather data for models, where the effect of WG algorithms on reproducibility of ecosystem model outputs must be assessed. In this study simulated carbon and water cycle by Biome-BGC model using weather data measured and generated by CLIMGEN weather generator were compared. The measured weather data (daily precipitation, maximum, minimum air temperature) at a few sites for 30 years was collected from NNDC Online weather data. The generated weather data was produced by CLIMGEN parameterized using the measured weather data. NPP, heterotrophic respiration (HR), NEE and water outflow were simulated by Biome-BGC using measured and generated weather data. In the case of deciduous broad leaf forest in Lushi, Henan Province, China, 30 years average monthly NPP by WG was 10% larger than that by measured weather in the growing season. HR by WG was larger than that by measured weather in all months by 15% in average. NEE by WG was more negative in winter and was close to that by measured weather in summer. These differences in carbon cycle were because the soil water content by WG was larger than that by measured weather. The difference between monthly water outflow by WG and by measured weather was large and variable, and annual outflow by WG was 50% of that by measured weather. The inconsistency in carbon and water cycle by WG and measured weather was suggested be affected by the difference in temporal concentration of precipitation, which was assessed.
Panel Flutter Emulation Using a Few Concentrated Forces

Science.gov (United States)

Dhital, Kailash; Han, Jae-Hung

2018-04-01

The objective of this paper is to study the feasibility of panel flutter emulation using a few concentrated forces. The concentrated forces are considered to be equivalent to aerodynamic forces. The equivalence is carried out using surface spline method and principle of virtual work. The structural modeling of the plate is based on the classical plate theory and the aerodynamic modeling is based on the piston theory. The present approach differs from the linear panel flutter analysis in scheming the modal aerodynamics forces with unchanged structural properties. The solutions for the flutter problem are obtained numerically using the standard eigenvalue procedure. A few concentrated forces were considered with an optimization effort to decide their optimal locations. The optimization process is based on minimizing the error between the flutter bounds from emulated and linear flutter analysis method. The emulated flutter results for the square plate of four different boundary conditions using six concentrated forces are obtained with minimal error to the reference value. The results demonstrated the workability and viability of using concentrated forces in emulating real panel flutter. In addition, the paper includes the parametric studies of linear panel flutter whose proper literatures are not available.
Dechlorination kinetics of TCE at toxic TCE concentrations: Assessment of different models.

Science.gov (United States)

Haest, P J; Springael, D; Smolders, E

2010-01-01

The reductive dechlorination of trichloroethene (TCE) in a TCE source zone can be self-inhibited by TCE toxicity. A study was set up to examine the toxicity of TCE in terms of species specific degradation kinetics and microbial growth and to evaluate models that describe this self-inhibition. A batch experiment was performed using the TCE dechlorinating KB-1 culture at initial TCE concentrations ranging from 0.04mM to saturation (8.4mM). Biodegradation activity was highest at 0.3mM TCE and no activity was found at concentrations from 4 to 8mM. Species specific TCE and cis-DCE (cis-dichloroethene) degradation rates and Dehalococcoides numbers were modeled with Monod kinetics combined with either Haldane inhibition or a log-logistic dose-response inhibition on these rates. The log-logistic toxicity model appeared the most appropriate model and predicts that the species specific degradation activities are reduced by a factor 2 at about 1mM TCE, respectively cis-DCE. However, the model showed that the inhibitive effects on the time for TCE to ethene degradation are a complex function of degradation kinetics and the initial cell densities of the dechlorinating species. Our analysis suggests that the self-inhibition on biodegradation cannot be predicted by a single concentration threshold without information on the cell densities.
A statistical regression model for the estimation of acrylamide concentrations in French fries for excess lifetime cancer risk assessment.

Science.gov (United States)

Chen, Ming-Jen; Hsu, Hui-Tsung; Lin, Cheng-Li; Ju, Wei-Yuan

2012-10-01

Human exposure to acrylamide (AA) through consumption of French fries and other foods has been recognized as a potential health concern. Here, we used a statistical non-linear regression model, based on the two most influential factors, cooking temperature and time, to estimate AA concentrations in French fries. The R(2) of the predictive model is 0.83, suggesting the developed model was significant and valid. Based on French fry intake survey data conducted in this study and eight frying temperature-time schemes which can produce tasty and visually appealing French fries, the Monte Carlo simulation results showed that if AA concentration is higher than 168 ppb, the estimated cancer risk for adolescents aged 13-18 years in Taichung City would be already higher than the target excess lifetime cancer risk (ELCR), and that by taking into account this limited life span only. In order to reduce the cancer risk associated with AA intake, the AA levels in French fries might have to be reduced even further if the epidemiological observations are valid. Our mathematical model can serve as basis for further investigations on ELCR including different life stages and behavior and population groups. Copyright © 2012 Elsevier Ltd. All rights reserved.
Maximum Recommended Dosage of Lithium for Pregnant Women Based on a PBPK Model for Lithium Absorption

Directory of Open Access Journals (Sweden)

Scott Horton

2012-01-01

Full Text Available Treatment of bipolar disorder with lithium therapy during pregnancy is a medical challenge. Bipolar disorder is more prevalent in women and its onset is often concurrent with peak reproductive age. Treatment typically involves administration of the element lithium, which has been classified as a class D drug (legal to use during pregnancy, but may cause birth defects and is one of only thirty known teratogenic drugs. There is no clear recommendation in the literature on the maximum acceptable dosage regimen for pregnant, bipolar women. We recommend a maximum dosage regimen based on a physiologically based pharmacokinetic (PBPK model. The model simulates the concentration of lithium in the organs and tissues of a pregnant woman and her fetus. First, we modeled time-dependent lithium concentration profiles resulting from lithium therapy known to have caused birth defects. Next, we identified maximum and average fetal lithium concentrations during treatment. Then, we developed a lithium therapy regimen to maximize the concentration of lithium in the mother’s brain, while maintaining the fetal concentration low enough to reduce the risk of birth defects. This maximum dosage regimen suggested by the model was 400 mg lithium three times per day.
Mechanistic Physiologically Based Pharmacokinetic (PBPK) Model of the Heart Accounting for Inter-Individual Variability: Development and Performance Verification.

Science.gov (United States)

Tylutki, Zofia; Mendyk, Aleksander; Polak, Sebastian

2018-04-01

Modern model-based approaches to cardiac safety and efficacy assessment require accurate drug concentration-effect relationship establishment. Thus, knowledge of the active concentration of drugs in heart tissue is desirable along with inter-subject variability influence estimation. To that end, we developed a mechanistic physiologically based pharmacokinetic model of the heart. The models were described with literature-derived parameters and written in R, v.3.4.0. Five parameters were estimated. The model was fitted to amitriptyline and nortriptyline concentrations after an intravenous infusion of amitriptyline. The cardiac model consisted of 5 compartments representing the pericardial fluid, heart extracellular water, and epicardial intracellular, midmyocardial intracellular, and endocardial intracellular fluids. Drug cardiac metabolism, passive diffusion, active efflux, and uptake were included in the model as mechanisms involved in the drug disposition within the heart. The model accounted for inter-individual variability. The estimates of optimized parameters were within physiological ranges. The model performance was verified by simulating 5 clinical studies of amitriptyline intravenous infusion, and the simulated pharmacokinetic profiles agreed with clinical data. The results support the model feasibility. The proposed structure can be tested with the goal of improving the patient-specific model-based cardiac safety assessment and offers a framework for predicting cardiac concentrations of various xenobiotics. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control

OpenAIRE

Tsonyo Slavov; Olympia Roeva

2011-01-01

This paper focuses on design of a glucose concentration control system based on nonlinear model plant of E. coli MC4110 fed-batch cultivation process. Due to significant time delay in real time glucose concentration measurement, a correction is proposed in glucose concentration measurement and a Smith predictor (SP) control structure based on universal PID controller is designed. To reduce the influence of model error in SP structure the estimate of measured glucose concentration is used. For...
Use of Genetic Models to Study the Urinary Concentrating Mechanism

DEFF Research Database (Denmark)

Olesen, Emma Tina Bisgaard; Kortenoeven, Marleen L.A.; Fenton, Robert A.

2015-01-01

technology is providing critical new information about urinary concentrating processes and thus mechanisms for maintaining body water homeostasis. In this chapter we provide a brief overview of genetic mouse model generation, and then summarize findings in transgenic and knockout mice pertinent to our...
Predictive Modelling of Concentration of Dispersed Natural Gas in a Single Room

Directory of Open Access Journals (Sweden)

Abdulfatai JIMOH

2009-07-01

Full Text Available This paper aimed at developing a mathematical model equation to predict the concentration of natural gas in a single room. The model equation was developed by using theoretical method of predictive modelling. The model equation developed is as given in equation 28. The validity of the developed expression was tested through the simulation of experimental results using computer software called MathCAD Professional. Both experimental and simulated results were found to be in close agreement. The statistical analysis carried out through the correlation coefficients for the results of experiment 1, 2, 3 and 4 were found to be 0.9986, 1.0000, 0.9981 and 0.9999 respectively, which imply reasonable close fittings between the experimental and simulated concentrations of dispersed natural gas within the room. Thus, the model equation developed can be considered a good representation of the phenomena that occurred when there is a leakage or accidental release of such gas within the room.
Constructing a justice model based on Sen's capability approach

OpenAIRE

Yüksel, Sevgi; Yuksel, Sevgi

2008-01-01

The thesis provides a possible justice model based on Sen's capability approach. For this goal, we first analyze the general structure of a theory of justice, identifying the main variables and issues. Furthermore, based on Sen (2006) and Kolm (1998), we look at 'transcendental' and 'comparative' approaches to justice and concentrate on the sufficiency condition for the comparative approach. Then, taking Rawls' theory of justice as a starting point, we present how Sen's capability approach em...
Fabrication of Graded Porous and Skin-Core Structure RDX-Based Propellants via Supercritical CO2 Concentration Profile

Science.gov (United States)

Yang, Weitao; Li, Yuxiang; Ying, Sanjiu

2015-04-01

A fabrication process to produce graded porous and skin-core structure propellants via supercritical CO2 concentration profile is reported in this article. It utilizes a partial gas saturation technique to obtain nonequilibrium gas concentration profiles in propellants. Once foamed, the propellant obtains a graded porous or skin-pore structure. This fabrication method was studied with RDX(Hexogen)-based propellant under an SC-CO2 saturation condition. The principle was analyzed and the one-dimensional diffusion model was employed to estimate the gas diffusion coefficient and to predict the gas concentration profiles inside the propellant. Scanning electron microscopy images were used to analyze the effects of partial saturation on the inner structure. The results also suggested that the sorption time and desorption time played an important role in gas profile generation and controlled the inner structure of propellants.
Duality based direct resolution of unique profiles using zero concentration region information.

Science.gov (United States)

Tavakkoli, Elnaz; Rajkó, Róbert; Abdollahi, Hamid

2018-07-01

Self Modeling Curve Resolution (SMCR) is a class of techniques concerned with estimating pure profiles underlying a set of measurements on chemical systems. In general, the estimated profiles are ambiguous (non-unique) except if some special conditions fulfilled. Implementing the adequate information can reduce the so-called rotational ambiguity effectively, and in the most desirable cases lead to the unique solution. Therefore, studies on circumstances resulting in unique solution are of particular importance. The conditions of unique solution can particularly be studied based on duality principle. In bilinear chemical (e.g., spectroscopic) data matrix, there is a natural duality between its row and column vector spaces using minimal constraints (non-negativity of concentrations and absorbances). In this article, the conditions of the unique solution according to duality concept and using zero concentration region information is intended to show. A simulated dataset of three components and an experimental system with synthetic mixtures containing three amino acids tyrosine, phenylalanine and tryptophan are analyzed. It is shown that in the presence of sufficient information, the reliable unique solution is obtained that is valuable in analytical qualification and for quantitative verification analysis. Copyright © 2018 Elsevier B.V. All rights reserved.
Development of a stacked ensemble model for forecasting and analyzing daily average PM2.5 concentrations in Beijing, China.

Science.gov (United States)

Zhai, Binxu; Chen, Jianguo

2018-04-18

A stacked ensemble model is developed for forecasting and analyzing the daily average concentrations of fine particulate matter (PM 2.5 ) in Beijing, China. Special feature extraction procedures, including those of simplification, polynomial, transformation and combination, are conducted before modeling to identify potentially significant features based on an exploratory data analysis. Stability feature selection and tree-based feature selection methods are applied to select important variables and evaluate the degrees of feature importance. Single models including LASSO, Adaboost, XGBoost and multi-layer perceptron optimized by the genetic algorithm (GA-MLP) are established in the level 0 space and are then integrated by support vector regression (SVR) in the level 1 space via stacked generalization. A feature importance analysis reveals that nitrogen dioxide (NO 2 ) and carbon monoxide (CO) concentrations measured from the city of Zhangjiakou are taken as the most important elements of pollution factors for forecasting PM 2.5 concentrations. Local extreme wind speeds and maximal wind speeds are considered to extend the most effects of meteorological factors to the cross-regional transportation of contaminants. Pollutants found in the cities of Zhangjiakou and Chengde have a stronger impact on air quality in Beijing than other surrounding factors. Our model evaluation shows that the ensemble model generally performs better than a single nonlinear forecasting model when applied to new data with a coefficient of determination (R 2 ) of 0.90 and a root mean squared error (RMSE) of 23.69μg/m 3 . For single pollutant grade recognition, the proposed model performs better when applied to days characterized by good air quality than when applied to days registering high levels of pollution. The overall classification accuracy level is 73.93%, with most misclassifications made among adjacent categories. The results demonstrate the interpretability and generalizability of
Models for estimation of the 10B concentration after BPA-fructose complex infusion in patients during epithermal neutron irradiation in BNCT

International Nuclear Information System (INIS)

Ryynaenen, Paeivi M.; Kortesniemi, Mika; Coderre, Jeffrey A.; Diaz, Aidnag Z.; Hiismaeki, Pekka; Savolainen, Sauli E.

2000-01-01

Purpose: To create simple and reliable models for clinical practice for estimating the blood 10 B time-concentration curve after p-boronophenylalanine fructose complex (BPA-F) infusion in patients during neutron irradiation in boron neutron capture therapy (BNCT). Methods and Materials: BPA-F (290 mg BPA/kg body weight) was infused i.v. during two hours to 10 glioblastoma multiforme patients. Blood samples were collected during and after the infusion. Compartmental models and bi-exponential function fit were constructed based on the 10 B blood time-concentration curve. The constructed models were tested with data from six additional patients who received various amounts of infused BPA-F and data from one patient who received a one-hour infusion of 170 mg BPA/kg body weight. Results: The resulting open two-compartment model and bi-exponential function estimate the clearance of 10 B after 290 mg BPA/kg body weight infusion from the blood with satisfactory accuracy during the first irradiation field (1 ppm, i.e., 7%). The accuracy of the two models in predicting the clearance of 10 B during the second irradiation field are for two-compartment model 1.0 ppm (8%) and 0.2 ppm (2%) for bi-exponential function. The models predict the average blood 10 B concentration with an increasing accuracy as more data points are available during the treatment. Conclusion: By combining the two models, a robust and practical modeling tool is created for the estimation of the 10 B concentration in blood after BPA-F infusion
Improved daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed

International Nuclear Information System (INIS)

Grimm, J.W.; Lynch, J.A.

2005-01-01

Daily precipitation nitrate and ammonium concentration models were developed for the Chesapeake Bay Watershed (USA) using a linear least-squares regression approach and precipitation chemistry data from 29 National Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites. Only weekly samples that comprised a single precipitation event were used in model development. The most significant variables in both ammonium and nitrate models included: precipitation volume, the number of days since the last event, a measure of seasonality, latitude, and the proportion of land within 8 km covered by forest or devoted to industry and transportation. Additional variables included in the nitrate model were the proportion of land within 0.8 km covered by water and/or forest. Local and regional ammonia and nitrogen oxide emissions were not as well correlated as land cover. Modeled concentrations compared very well with event chemistry data collected at six NADP/AirMoN sites within the Chesapeake Bay Watershed. Wet deposition estimates were also consistent with observed deposition at selected sites. Accurately describing the spatial distribution of precipitation volume throughout the watershed is important in providing critical estimates of wet-fall deposition of ammonium and nitrate. - A linear least-squares regression approach was used to develop daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed
Measuring and modeling polymer concentration profiles near spindle boundaries argues that spindle microtubules regulate their own nucleation

Science.gov (United States)

Kaye, Bryan; Stiehl, Olivia; Foster, Peter J.; Shelley, Michael J.; Needleman, Daniel J.; Fürthauer, Sebastian

2018-05-01

Spindles are self-organized microtubule-based structures that segregate chromosomes during cell division. The mass of the spindle is controlled by the balance between microtubule turnover and nucleation. The mechanisms that control the spatial regulation of microtubule nucleation remain poorly understood. While previous work found that microtubule nucleators bind to pre-existing microtubules in the spindle, it is still unclear whether this binding regulates the activity of those nucleators. Here we use a combination of experiments and mathematical modeling to investigate this issue. We measured the concentration of microtubules and soluble tubulin in and around the spindle. We found a very sharp decay in the concentration of microtubules at the spindle interface. This is inconsistent with a model in which the activity of nucleators is independent of their association with microtubules but consistent with a model in which microtubule nucleators are only active when bound to pre-existing microtubules. This argues that the activity of microtubule nucleators is greatly enhanced when bound to pre-existing microtubules. Thus, microtubule nucleators are both localized and activated by the microtubules they generate.
Modeling uranium(VI) adsorption onto montmorillonite under varying carbonate concentrations: A surface complexation model accounting for the spillover effect on surface potential

Science.gov (United States)

Tournassat, C.; Tinnacher, R. M.; Grangeon, S.; Davis, J. A.

2018-01-01

The prediction of U(VI) adsorption onto montmorillonite clay is confounded by the complexities of: (1) the montmorillonite structure in terms of adsorption sites on basal and edge surfaces, and the complex interactions between the electrical double layers at these surfaces, and (2) U(VI) solution speciation, which can include cationic, anionic and neutral species. Previous U(VI)-montmorillonite adsorption and modeling studies have typically expanded classical surface complexation modeling approaches, initially developed for simple oxides, to include both cation exchange and surface complexation reactions. However, previous models have not taken into account the unique characteristics of electrostatic surface potentials that occur at montmorillonite edge sites, where the electrostatic surface potential of basal plane cation exchange sites influences the surface potential of neighboring edge sites ('spillover' effect). A series of U(VI) - Na-montmorillonite batch adsorption experiments was conducted as a function of pH, with variable U(VI), Ca, and dissolved carbonate concentrations. Based on the experimental data, a new type of surface complexation model (SCM) was developed for montmorillonite, that specifically accounts for the spillover effect using the edge surface speciation model by Tournassat et al. (2016a). The SCM allows for a prediction of U(VI) adsorption under varying chemical conditions with a minimum number of fitting parameters, not only for our own experimental results, but also for a number of published data sets. The model agreed well with many of these datasets without introducing a second site type or including the formation of ternary U(VI)-carbonato surface complexes. The model predictions were greatly impacted by utilizing analytical measurements of dissolved inorganic carbon (DIC) concentrations in individual sample solutions rather than assuming solution equilibration with a specific partial pressure of CO2, even when the gas phase was
Comparison of land use regression models for NO2 based on routine and campaign monitoring data from an urban area of Japan.

Science.gov (United States)

Kashima, Saori; Yorifuji, Takashi; Sawada, Norie; Nakaya, Tomoki; Eboshida, Akira

2018-08-01

Typically, land use regression (LUR) models have been developed using campaign monitoring data rather than routine monitoring data. However, the latter have advantages such as low cost and long-term coverage. Based on the idea that LUR models representing regional differences in air pollution and regional road structures are optimal, the objective of this study was to evaluate the validity of LUR models for nitrogen dioxide (NO 2 ) based on routine and campaign monitoring data obtained from an urban area. We selected the city of Suita in Osaka (Japan). We built a model based on routine monitoring data obtained from all sites (routine-LUR-All), and a model based on campaign monitoring data (campaign-LUR) within the city. Models based on routine monitoring data obtained from background sites (routine-LUR-BS) and based on data obtained from roadside sites (routine-LUR-RS) were also built. The routine LUR models were based on monitoring networks across two prefectures (i.e., Osaka and Hyogo prefectures). We calculated the predictability of the each model. We then compared the predicted NO 2 concentrations from each model with measured annual average NO 2 concentrations from evaluation sites. The routine-LUR-All and routine-LUR-BS models both predicted NO 2 concentrations well: adjusted R 2 =0.68 and 0.76, respectively, and root mean square error=3.4 and 2.1ppb, respectively. The predictions from the routine-LUR-All model were highly correlated with the measured NO 2 concentrations at evaluation sites. Although the predicted NO 2 concentrations from each model were correlated, the LUR models based on routine networks, and particularly those based on all monitoring sites, provided better visual representations of the local road conditions in the city. The present study demonstrated that LUR models based on routine data could estimate local traffic-related air pollution in an urban area. The importance and usefulness of data from routine monitoring networks should be
Validation of regression models for nitrate concentrations in the upper groundwater in sandy soils

International Nuclear Information System (INIS)

Sonneveld, M.P.W.; Brus, D.J.; Roelsma, J.

2010-01-01

For Dutch sandy regions, linear regression models have been developed that predict nitrate concentrations in the upper groundwater on the basis of residual nitrate contents in the soil in autumn. The objective of our study was to validate these regression models for one particular sandy region dominated by dairy farming. No data from this area were used for calibrating the regression models. The model was validated by additional probability sampling. This sample was used to estimate errors in 1) the predicted areal fractions where the EU standard of 50 mg l -1 is exceeded for farms with low N surpluses (ALT) and farms with higher N surpluses (REF); 2) predicted cumulative frequency distributions of nitrate concentration for both groups of farms. Both the errors in the predicted areal fractions as well as the errors in the predicted cumulative frequency distributions indicate that the regression models are invalid for the sandy soils of this study area. - This study indicates that linear regression models that predict nitrate concentrations in the upper groundwater using residual soil N contents should be applied with care.

New model of chlorine-wall reaction for simulating chlorine concentration in drinking water distribution systems.

Science.gov (United States)

Fisher, Ian; Kastl, George; Sathasivan, Arumugam

2017-11-15

Accurate modelling of chlorine concentrations throughout a drinking water system needs sound mathematical descriptions of decay mechanisms in bulk water and at pipe walls. Wall-reaction rates along pipelines in three different systems were calculated from differences between field chlorine profiles and accurately modelled bulk decay. Lined pipes with sufficiently large diameters (>500 mm) and higher chlorine concentrations (>0.5 mg/L) had negligible wall-decay rates, compared with bulk-decay rates. Further downstream, wall-reaction rate consistently increased (peaking around 0.15 mg/dm 2 /h) as chlorine concentration decreased, until mass-transport to the wall was controlling wall reaction. These results contradict wall-reaction models, including those incorporated in the EPANET software, which assume wall decay is of either zero-order (constant decay rate) or first-order (wall-decay rate reduces with chlorine concentration). Instead, results are consistent with facilitation of the wall reaction by biofilm activity, rather than surficial chemical reactions. A new model of wall reaction combines the effect of biofilm activity moderated by chlorine concentration and mass-transport limitation. This wall reaction model, with an accurate bulk chlorine decay model, is essential for sufficiently accurate prediction of chlorine residuals towards the end of distribution systems and therefore control of microbial contamination. Implementing this model in EPANET-MSX (or similar) software enables the accurate chlorine modelling required for improving disinfection strategies in drinking water networks. New insight into the effect of chlorine on biofilm can also assist in controlling biofilm to maintain chlorine residuals. Copyright © 2017 Elsevier Ltd. All rights reserved.
Inverse modeling of the Chernobyl source term using atmospheric concentration and deposition measurements

Science.gov (United States)

Evangeliou, Nikolaos; Hamburger, Thomas; Cozic, Anne; Balkanski, Yves; Stohl, Andreas

2017-07-01

This paper describes the results of an inverse modeling study for the determination of the source term of the radionuclides 134Cs, 137Cs and 131I released after the Chernobyl accident. The accident occurred on 26 April 1986 in the Former Soviet Union and released about 1019 Bq of radioactive materials that were transported as far away as the USA and Japan. Thereafter, several attempts to assess the magnitude of the emissions were made that were based on the knowledge of the core inventory and the levels of the spent fuel. More recently, when modeling tools were further developed, inverse modeling techniques were applied to the Chernobyl case for source term quantification. However, because radioactivity is a sensitive topic for the public and attracts a lot of attention, high-quality measurements, which are essential for inverse modeling, were not made available except for a few sparse activity concentration measurements far from the source and far from the main direction of the radioactive fallout. For the first time, we apply Bayesian inversion of the Chernobyl source term using not only activity concentrations but also deposition measurements from the most recent public data set. These observations refer to a data rescue attempt that started more than 10 years ago, with a final goal to provide available measurements to anyone interested. In regards to our inverse modeling results, emissions of 134Cs were estimated to be 80 PBq or 30-50 % higher than what was previously published. From the released amount of 134Cs, about 70 PBq were deposited all over Europe. Similar to 134Cs, emissions of 137Cs were estimated as 86 PBq, on the same order as previously reported results. Finally, 131I emissions of 1365 PBq were found, which are about 10 % less than the prior total releases. The inversion pushes the injection heights of the three radionuclides to higher altitudes (up to about 3 km) than previously assumed (≈ 2.2 km) in order to better match both concentration
Inverse modeling of the Chernobyl source term using atmospheric concentration and deposition measurements

Directory of Open Access Journals (Sweden)

N. Evangeliou

2017-07-01

Full Text Available This paper describes the results of an inverse modeling study for the determination of the source term of the radionuclides 134Cs, 137Cs and 131I released after the Chernobyl accident. The accident occurred on 26 April 1986 in the Former Soviet Union and released about 1019 Bq of radioactive materials that were transported as far away as the USA and Japan. Thereafter, several attempts to assess the magnitude of the emissions were made that were based on the knowledge of the core inventory and the levels of the spent fuel. More recently, when modeling tools were further developed, inverse modeling techniques were applied to the Chernobyl case for source term quantification. However, because radioactivity is a sensitive topic for the public and attracts a lot of attention, high-quality measurements, which are essential for inverse modeling, were not made available except for a few sparse activity concentration measurements far from the source and far from the main direction of the radioactive fallout. For the first time, we apply Bayesian inversion of the Chernobyl source term using not only activity concentrations but also deposition measurements from the most recent public data set. These observations refer to a data rescue attempt that started more than 10 years ago, with a final goal to provide available measurements to anyone interested. In regards to our inverse modeling results, emissions of 134Cs were estimated to be 80 PBq or 30–50 % higher than what was previously published. From the released amount of 134Cs, about 70 PBq were deposited all over Europe. Similar to 134Cs, emissions of 137Cs were estimated as 86 PBq, on the same order as previously reported results. Finally, 131I emissions of 1365 PBq were found, which are about 10 % less than the prior total releases. The inversion pushes the injection heights of the three radionuclides to higher altitudes (up to about 3 km than previously assumed (≈ 2.2 km in order
A probabilistic model-based soft sensor to monitor lactic acid bacteria fermentations

DEFF Research Database (Denmark)

Spann, Robert; Roca, Christophe; Kold, David

2018-01-01

A probabilistic soft sensor based on a mechanistic model was designed to monitor S. thermophilus fermentations, and validated with experimental lab-scale data. It considered uncertainties in the initial conditions, on-line measurements, and model parameters by performing Monte Carlo simulations...... the model parameters that were then used as input to the mechanistic model. The soft sensor predicted both the current state variables, as well as the future course of the fermentation, e.g. with a relative mean error of the biomass concentration of 8 %. This successful implementation of a process...... within the monitoring system. It predicted, therefore, the probability distributions of the unmeasured states, such as biomass, lactose, and lactic acid concentrations. To this end, a mechanistic model was developed first, and a statistical parameter estimation was performed in order to assess parameter...
The classification of PM10 concentrations in Johor Based on Seasonal Monsoons

Science.gov (United States)

Hamid, Hazrul Abdul; Hanafi Rahmat, Muhamad; Aisyah Sapani, Siti

2018-04-01

Air is the most important living resource in life. Contaminated air could adversely affect human health and the environment, especially during the monsoon season. Contamination occurs as a result of human action and haze. There are several pollutants present in the air where one of them is PM10. Secondary data was obtained from the Department of Environment from 2010 until 2014 and was analyzed using the hourly average of PM10 concentrations. This paper examined the relation between PM10 concentrations and the monsoon seasons (Northeast Monsoon and Southwest Monsoon) in Larkin and Pasir Gudang. It was expected that the concentration of PM10 would be higher during the Southwest Monsoon as it is a dry season. The data revealed that the highest PM10 concentrations were recorded between 2010 to 2014 during this particular monsoon season. The characteristics of PM10 concentration were compared using descriptive statistics based on the monsoon seasons and classified using the hierarchical cluster analysis (Ward Methods). The annual average of PM10 concentration during the Southwest Monsoon had exceeded the standard set by the Malaysia Ambient Air Quality Guidelines (50 μg/m3) while the PM10 concentration during the Northeast Monsoon was below the acceptable level for both stations. The dendrogram displayed showed two clusters for each monsoon season for both stations excepted for the PM10 concentration during the Northeast Monsoon in Larkin which was classified into three clusters due to the haze in 2010. Overall, the concentration of PM10 in 2013 was higher based on the clustering shown for every monsoon season at both stations according to the characteristics in the descriptive statistics.
Self assembly of rectangular shapes on concentration programming and probabilistic tile assembly models.

Science.gov (United States)

Kundeti, Vamsi; Rajasekaran, Sanguthevar

2012-06-01

Efficient tile sets for self assembling rectilinear shapes is of critical importance in algorithmic self assembly. A lower bound on the tile complexity of any deterministic self assembly system for an n × n square is [Formula: see text] (inferred from the Kolmogrov complexity). Deterministic self assembly systems with an optimal tile complexity have been designed for squares and related shapes in the past. However designing [Formula: see text] unique tiles specific to a shape is still an intensive task in the laboratory. On the other hand copies of a tile can be made rapidly using PCR (polymerase chain reaction) experiments. This led to the study of self assembly on tile concentration programming models. We present two major results in this paper on the concentration programming model. First we show how to self assemble rectangles with a fixed aspect ratio ( α:β ), with high probability, using Θ( α + β ) tiles. This result is much stronger than the existing results by Kao et al. (Randomized self-assembly for approximate shapes, LNCS, vol 5125. Springer, Heidelberg, 2008) and Doty (Randomized self-assembly for exact shapes. In: proceedings of the 50th annual IEEE symposium on foundations of computer science (FOCS), IEEE, Atlanta. pp 85-94, 2009)-which can only self assembly squares and rely on tiles which perform binary arithmetic. On the other hand, our result is based on a technique called staircase sampling . This technique eliminates the need for sub-tiles which perform binary arithmetic, reduces the constant in the asymptotic bound, and eliminates the need for approximate frames (Kao et al. Randomized self-assembly for approximate shapes, LNCS, vol 5125. Springer, Heidelberg, 2008). Our second result applies staircase sampling on the equimolar concentration programming model (The tile complexity of linear assemblies. In: proceedings of the 36th international colloquium automata, languages and programming: Part I on ICALP '09, Springer-Verlag, pp 235
Phosphorus Export Model Development in a Terminal Lake Basin using Concentration-Streamflow Relationship

Science.gov (United States)

Jeannotte, T.; Mahmood, T. H.; Matheney, R.; Hou, X.

2017-12-01

Nutrient export to streams and lakes by anthropogenic activities can lead to eutrophication and degradation of surface water quality. In Devils Lake, ND, the only terminal lake in the Northern Great Plains, the algae boom is of great concern due to the recent increase in streamflow and consequent rise in phosphorus (P) export from prairie agricultural fields. However, to date, very few studies explored the concentration (c) -streamflow (q) relationship in the headwater catchments of the Devils Lake basin. A robust watershed-scale quantitative framework would aid understanding of the c-q relationship, simulating P concentration and load. In this study, we utilize c-q relationships to develop a simple model to estimate phosphorus concentration and export from two headwater catchments of different size (Mauvais Coulee: 1032 km2 and Trib 3: 160 km2) draining to Devils Lake. Our goal is to link the phosphorus export model with a physically based hydrologic model to identify major drivers of phosphorus export. USGS provided the streamflow measurements, and we collected water samples (filtered and unfiltered) three times daily during the spring snowmelt season (March 31, 2017- April 12, 2017) at the outlets of both headwater catchments. Our results indicate that most P is dissolved and very little is particulate, suggesting little export of fine-grained sediment from agricultural fields. Our preliminary analyses in the Mauvais Coulee catchment show a chemostatic c-q relationship in the rising limb of the hydrograph, while the recession limb shows a linear and positive c-q relationship. The poor correlation in the rising limb of the hydrograph suggests intense flushing of P by spring snowmelt runoff. Flushing then continues in the recession limb of the hydrograph, but at a more constant rate. The estimated total P load for the Mauvais Coulee basin is 193 kg/km2, consistent with other catchments of similar size across the Red River of the North basin to the east. We expect
On-chip concentration of bacteria using a 3D dielectrophoretic chip and subsequent laser-based DNA extraction in the same chip

International Nuclear Information System (INIS)

Cho, Yoon-Kyoung; Kim, Tae-hyeong; Lee, Jeong-Gun

2010-01-01

We report the on-chip concentration of bacteria using a dielectrophoretic (DEP) chip with 3D electrodes and subsequent laser-based DNA extraction in the same chip. The DEP chip has a set of interdigitated Au post electrodes with 50 µm height to generate a network of non-uniform electric fields for the efficient trapping by DEP. The metal post array was fabricated by photolithography and subsequent Ni and Au electroplating. Three model bacteria samples (Escherichia coli, Staphylococcus epidermidis, Streptococcus mutans) were tested and over 80-fold concentrations were achieved within 2 min. Subsequently, on-chip DNA extraction from the concentrated bacteria in the 3D DEP chip was performed by laser irradiation using the laser-irradiated magnetic bead system (LIMBS) in the same chip. The extracted DNA was analyzed with silicon chip-based real-time polymerase chain reaction (PCR). The total process of on-chip bacteria concentration and the subsequent DNA extraction can be completed within 10 min including the manual operation time.
Soil and Water Assessment Tool model predictions of annual maximum pesticide concentrations in high vulnerability watersheds.

Science.gov (United States)

Winchell, Michael F; Peranginangin, Natalia; Srinivasan, Raghavan; Chen, Wenlin

2018-05-01

Recent national regulatory assessments of potential pesticide exposure of threatened and endangered species in aquatic habitats have led to increased need for watershed-scale predictions of pesticide concentrations in flowing water bodies. This study was conducted to assess the ability of the uncalibrated Soil and Water Assessment Tool (SWAT) to predict annual maximum pesticide concentrations in the flowing water bodies of highly vulnerable small- to medium-sized watersheds. The SWAT was applied to 27 watersheds, largely within the midwest corn belt of the United States, ranging from 20 to 386 km 2 , and evaluated using consistent input data sets and an uncalibrated parameterization approach. The watersheds were selected from the Atrazine Ecological Exposure Monitoring Program and the Heidelberg Tributary Loading Program, both of which contain high temporal resolution atrazine sampling data from watersheds with exceptionally high vulnerability to atrazine exposure. The model performance was assessed based upon predictions of annual maximum atrazine concentrations in 1-d and 60-d durations, predictions critical in pesticide-threatened and endangered species risk assessments when evaluating potential acute and chronic exposure to aquatic organisms. The simulation results showed that for nearly half of the watersheds simulated, the uncalibrated SWAT model was able to predict annual maximum pesticide concentrations within a narrow range of uncertainty resulting from atrazine application timing patterns. An uncalibrated model's predictive performance is essential for the assessment of pesticide exposure in flowing water bodies, the majority of which have insufficient monitoring data for direct calibration, even in data-rich countries. In situations in which SWAT over- or underpredicted the annual maximum concentrations, the magnitude of the over- or underprediction was commonly less than a factor of 2, indicating that the model and uncalibrated parameterization
HOTSED: a discrete element model for simulating hydrodynamic conditions and adsorbed and dissolved radioisotope concentrations in estuaries

International Nuclear Information System (INIS)

Fields, D.E.; Hetrick, D.M.

1978-12-01

A model has been developed to study the feasibility of simulating one-dimensional transport of radioisotope-tagged sediment in tidal-dominated estuaries. A preliminary one-dimensional model for simulating hydrodynamic, thermal, and dissolved radionuclide concentrations in tidal estuaries was merged with an improved version of the SEDTRN model, a multi-sediment-size class model of bedload and suspended sediment transport. The improved SEDTRN model, which employs a velocity-based rather than an energy-based sediment transport rate calculation and accounts for nonzero channel bed slope, is given credence by comparing its results in stand-alone form to those obtained using the parent model. Results of the latter model have been shown to compare favorably to field measurements. The combined preliminary model is called HOTSED. Details of model modifications, the addition of printer plot output capability, and a discussion of input and output structures are included. The HOTSED model is applied to the Hudson River under tidal-transient conditions and the transport ''tagged'' or radioisotope-bearing sediment is simulated. The code is designed specifically for applications with dominant tidal cycling. It requires, for a 76-element channel system, 270 thousand bytes of storage and, for a simulation of 25 hours, has an execution time of approximately five minutes on the IBM System 360/91 computer
Straightened cervical lordosis causes stress concentration: a finite element model study

Energy Technology Data Exchange (ETDEWEB)

Wei, Wei; Shi, Shiyuan; Fei, Jun; Wang, Yifan; Chen, Chunyue [Hangzhou Red Cross Hospital, Hangzhou, Zhejiang, (China); Liao, Shenhui [School of Information Science and Engineering, Central South University, Changsha, Hunan (China)

2013-03-15

In this study, we propose a finite element analysis of the complete cervical spine with straightened and normal physiological curvature by using a specially designed modelling system. An accurate finite element model is established to recommend plausible approaches to treatment of cervical spondylosis through the finite element analysis results. There are few reports of biomechanics influence of the straightened cervical curve. It is difficult to measure internal responses of cervical spine directly. However, the finite element method has been reported to have the capability to quantify both external and internal responses to mechanical loading, such as the strain and stress distribution of spinal components. We choose a subject with a straightened cervical spine from whom to collect the CT scan data, which formed the basis of the finite element analysis. By using a specially designed modelling system, a high quality finite element model of the complete cervical spine with straightened curvature was generated, which was then mapped to reconstruct a normal physiological curvature model by a volumetric mesh deformation method based on discrete differential properties. Then, the same boundary conditions were applied to do a comparison. The result demonstrated that the active movement range of straightened cervical spine decreased by 24–33 %, but the stress increased by 5–95 %. The stress was concentrated at the facet joint cartilage, uncovertebral joint and the disk. The results suggest that cervical lordosis may have a direct impact on cervical spondylosis treatment. These results may be useful for clinical treatment of cervical spondylosis with straightened curvature.
Straightened cervical lordosis causes stress concentration: a finite element model study

International Nuclear Information System (INIS)

Wei, Wei; Shi, Shiyuan; Fei, Jun; Wang, Yifan; Chen, Chunyue; Liao, Shenhui

2013-01-01

In this study, we propose a finite element analysis of the complete cervical spine with straightened and normal physiological curvature by using a specially designed modelling system. An accurate finite element model is established to recommend plausible approaches to treatment of cervical spondylosis through the finite element analysis results. There are few reports of biomechanics influence of the straightened cervical curve. It is difficult to measure internal responses of cervical spine directly. However, the finite element method has been reported to have the capability to quantify both external and internal responses to mechanical loading, such as the strain and stress distribution of spinal components. We choose a subject with a straightened cervical spine from whom to collect the CT scan data, which formed the basis of the finite element analysis. By using a specially designed modelling system, a high quality finite element model of the complete cervical spine with straightened curvature was generated, which was then mapped to reconstruct a normal physiological curvature model by a volumetric mesh deformation method based on discrete differential properties. Then, the same boundary conditions were applied to do a comparison. The result demonstrated that the active movement range of straightened cervical spine decreased by 24–33 %, but the stress increased by 5–95 %. The stress was concentrated at the facet joint cartilage, uncovertebral joint and the disk. The results suggest that cervical lordosis may have a direct impact on cervical spondylosis treatment. These results may be useful for clinical treatment of cervical spondylosis with straightened curvature.
Rich: Region-based Intelligent Cluster-Head Selection and Node Deployment Strategy in Concentric-based WSNs

Directory of Open Access Journals (Sweden)

FAN, C.-S.

2013-11-01

Full Text Available In a random deployment, sensor nodes are scattered randomly in the sensing field. Hence, the coverage can not be guaranteed. In contrast, the coverage of uniformly deployment is in general larger than the random deployment. However, uniformly deployment strategy may cause unbalanced traffic pattern in wireless sensor networks (WSNs. In this situation, larger load may be imposed to CHs (cluster heads around the sink. Therefore, CHs close to the sink use up their energy earlier than those farther away from the sink. To overcome this problem, we propose a novel node deployment strategy in the concentric model, namely, Region-based Intelligent Cluster-Head selection and node deployment strategy (called Rich. The coverage, energy consumption and data routing issues are well investigated and taken into consideration in the proposed Rich scheme. The simulation results show that the proposed Rich alleviates the unbalanced traffic pattern significantly, prolongs network lifetime and achieves satisfactory coverage ratio.
A simple model for predicting solute concentration in agricultural tile lines shortly after application

Directory of Open Access Journals (Sweden)

T. S. Steenhuis

1997-01-01

Full Text Available Agricultural tile drainage lines have been implicated as a source of pesticide contamination of surface waters. Field experiments were conducted and a simple model was developed to examine preferential transport of applied chemicals to agricultural tile lines. The conceptual model consists of two linear reservoirs, one near the soil surface and one near the tile drain. The connection between the two reservoirs is via preferential flow paths with very little interaction with the soil matrix. The model assumes that only part of the field contributes solutes to the tile drain. The model was evaluated with data from the field experiments in which chloride, 2,4-D, and atrazine concentrations were measured on eight tile-drained plots that were irrigated twice. Atrazine was applied two months prior to the experiment, 2,4-D was sprayed just before the first irrigation, and chloride before the second irrigation. All three chemicals were found in the tile effluent shortly after the rainfall began. Generally, the concentration increased with increased flow rates and decreased exponentially after the rainfall ceased. Although the simple model could simulate the observed chloride concentration patterns in the tile outflow for six of the eight plots, strict validation was not possible because of the difficulty with independent measurement of the data needed for a preferential flow model applied to field conditions. The results show that, to simulate pesticide concentration in tile lines, methods that can measure field averaged preferential flow characteristics need to be developed.
Assessing breeding potential of peregrine falcons based on chlorinated hydrocarbon concentrations in prey

Energy Technology Data Exchange (ETDEWEB)

Elliott, J.E. [Canadian Wildlife Service, Pacific Wildlife Research Centre, 5421 Robertson Rd., RR no. 1, Delta, British Columbia, V4K 3N2 (Canada)]. E-mail: john.elliott@ec.gc.ca; Miller, M.J. [Iolaire Ecological Consulting, 7899 Thrasher St., Mission, British Columbia, V2V 5H3 (Canada); Wilson, L.K. [Canadian Wildlife Service, Pacific Wildlife Research Centre, 5421 Robertson Rd., RR no. 1, Delta, British Columbia, V4K 3N2 (Canada)

2005-03-01

Peregrine falcons (Falco peregrinus) now breed successfully in most areas of North America from which they were previously extirpated. The loss during the mid-part of the last century of many of the world's peregrine populations was largely a consequence of impaired reproduction caused by the effects of DDE on eggshell quality and embryo hatchability. Population recovery has been attributed to re-introduction efforts, coupled with regulatory restrictions on the use of organochlorine pesticides. Peregrines have not returned to breed in some areas, such as the Okanagan Valley of British Columbia. That region has been extensively planted in fruit orchards which were treated annually with DDT during the early 1950s to the 1970s. Ongoing contamination of avian species, including potential peregrine prey, inhabiting orchards has been documented. In response to an initiative to release peregrines around the city of Kelowna in the Okanagan Valley, we collected potential peregrine prey species and analyzed whole bodies for chlorinated hydrocarbon residues. We used a simple bioaccumulation model to predict concentrations of DDE in peregrine eggs using concentrations in prey and estimates of dietary makeup as input. Peregrines would be expected to breed successfully only if they fed on a diet primarily of doves. Feeding on as little as 10% of other species such as starlings, robins, gulls and magpies would produce DDE concentrations in peregrine eggs greater than the threshold of 15 mg/kg. We also estimated the critical concentration of DDE in total prey to be about 0.5 mg/kg, one half of the previous most conservative criterion for peregrine prey. Concentrations of dieldrin and PCBs in peregrine prey are less than suggested critical levels. - Based on the level of DDE contamination of prey items, it seems unlikely that peregrine falcons could breed successfully throughout most of the Okanagan Valley of British Columbia.
Solvation-based vapour pressure model for (solvent + salt) systems in conjunction with the Antoine equation

International Nuclear Information System (INIS)

Senol, Aynur

2013-01-01

Highlights: • Vapour pressures of (solvent + salt) systems have been estimated through a solvation-based model. • Two structural forms of the generalized solvation model using the Antoine equation have been performed. • A simplified concentration-dependent vapour pressure model has been also processed. • The model reliability analysis has been performed in terms of a log-ratio objective function. • The reliability of the models has been interpreted in terms of the statistical design factors. -- Abstract: This study deals with modelling the vapour pressure of a (solvent + salt) system on the basis of the principles of LSER. The solvation model framework clarifies the simultaneous impact of several physical variables such as the vapour pressure of a pure solvent estimated by the Antoine equation, the solubility and solvatochromic parameters of the solvent and the physical properties of the ionic salt. It has been analyzed independently the performance of two structural forms of the generalized model, i.e., a relation depending on an integration of the properties of the solvent and the ionic salt and a relation on a reduced property-basis. A simplified concentration-dependent vapour pressure model has been also explored and implemented on the relevant systems. The vapour pressure data of sixteen (solvent + salt) systems have been processed to analyze statistically the reliability of existing models in terms of a log–ratio objective function. The proposed vapour pressure models match relatively well the observed performance, yielding the overall design factors of 1.066 and 1.073 for the solvation-based models with the integrated and reduced properties, and 1.008 for the concentration-based model, respectively
Modelling daily PM2.5 concentrations at high spatio-temporal resolution across Switzerland.

Science.gov (United States)

de Hoogh, Kees; Héritier, Harris; Stafoggia, Massimo; Künzli, Nino; Kloog, Itai

2018-02-01

Spatiotemporal resolved models were developed predicting daily fine particulate matter (PM 2.5 ) concentrations across Switzerland from 2003 to 2013. Relatively sparse PM 2.5 monitoring data was supplemented by imputing PM 2.5 concentrations at PM 10 sites, using PM 2.5 /PM 10 ratios at co-located sites. Daily PM 2.5 concentrations were first estimated at a 1 × 1km resolution across Switzerland, using Multiangle Implementation of Atmospheric Correction (MAIAC) spectral aerosol optical depth (AOD) data in combination with spatiotemporal predictor data in a four stage approach. Mixed effect models (1) were used to predict PM 2.5 in cells with AOD but without PM 2.5 measurements (2). A generalized additive mixed model with spatial smoothing was applied to generate grid cell predictions for those grid cells where AOD was missing (3). Finally, local PM 2.5 predictions were estimated at each monitoring site by regressing the residuals from the 1 × 1km estimate against local spatial and temporal variables using machine learning techniques (4) and adding them to the stage 3 global estimates. The global (1 km) and local (100 m) models explained on average 73% of the total,71% of the spatial and 75% of the temporal variation (all cross validated) globally and on average 89% (total) 95% (spatial) and 88% (temporal) of the variation locally in measured PM 2.5 concentrations. Copyright © 2017 Elsevier Ltd. All rights reserved.
Model ZD-I paper base weight measuring and controlling system

International Nuclear Information System (INIS)

Li Nianzu; Song Debin; Wu Guoliang; Hou Yaoxin; Li Dazhen

1988-01-01

Model ZD-I Base Weight Measuring and Controlling System has been developed for the automation process in paper-making industry. A single-board microprocessor is installed in the system. The mass thickness can be controlled within 1 g/m 2 if the changing range of concentration and water content is less than 10%
Hybrid photovoltaic-thermoelectric system for concentrated solar energy conversion: Experimental realization and modeling

Science.gov (United States)

Beeri, Ofer; Rotem, Oded; Hazan, Eden; Katz, Eugene A.; Braun, Avi; Gelbstein, Yaniv

2015-09-01

An experimental demonstration of the combined photovoltaic (PV) and thermoelectric conversion of concentrated sunlight (with concentration factor, X, up to ˜300) into electricity is presented. The hybrid system is based on a multi-junction PV cell and a thermoelectric generator (TEG). The latter increases the electric power of the system and dissipates some of the excessive heat. For X ≤ 200, the system's maximal efficiency, ˜32%, was mostly due to the contribution from the PV cell. With increasing X and system temperature, the PV cell's efficiency decreased while that of the TEG increased. Accordingly, the direct electrical contribution of the TEG started to dominate in the total system power, reaching ˜20% at X ≈ 290. Using a simple steady state finite element modeling, the cooling effect of the TEG on the hybrid system's efficiency was proved to be even more significant than its direct electrical contribution for high solar concentrations. As a result, the total efficiency contribution of the TEG reached ˜40% at X ≈ 200. This suggests a new system optimization concept that takes into account the PV cell's temperature dependence and the trade-off between the direct electrical generation and cooling capabilities of the TEG. It is shown that the hybrid system has a real potential to exceed 50% total efficiency by using more advanced PV cells and TE materials.
Financial Regulation in an Agent Based Macroeconomic Model

OpenAIRE

Riccetti, Luca; Russo, Alberto; Mauro, Gallegati

2013-01-01

Starting from the agent-based decentralized matching macroeconomic model proposed in Riccetti et al. (2012), we explore the effects of banking regulation on macroeconomic dynamics. In particular, we study the overall credit exposure and the lending concentration towards a single counterparty, finding that the portfolio composition seems to be more relevant than the overall exposure for banking stability, even if both features are very important. We show that a too tight regulation is dangerou...

Comparison of Spheroidal Carbonaceous Particle Data with Modelled Atmospheric Black Carbon Concentration and Deposition and Air Mass Sources in Northern Europe, 1850–2010

Directory of Open Access Journals (Sweden)

Meri Ruppel

2013-01-01

Full Text Available Spheroidal carbonaceous particles (SCP are a well-defined fraction of black carbon (BC, produced only by the incomplete combustion of fossil fuels such as coal and oil. Their past concentrations have been studied using environmental archives, but, additionally, historical trends of BC concentration and deposition can be estimated by modelling. These models are based on BC emission inventories, but actual measurements of BC concentration and deposition play an essential role in their evaluation and validation. We use the chemistry transport model OsloCTM2 to model historical time series of BC concentration and deposition from energy and industrial sources and compare these to sedimentary measurements of SCPs obtained from lake sediments in Northern Europe from 1850 to 2010. To determine the origin of SCPs we generated back trajectories of air masses to the study sites. Generally, trends of SCP deposition and modelled results agree reasonably well, showing rapidly increasing values from 1950, to a peak in 1980, and a decrease towards the present. Empirical SCP data show differences in deposition magnitude between the sites that are not captured by the model but which may be explained by different air mass transport patterns. The results highlight the need for numerous observational records to reliably validate model results.
Use of a risk-based hydrogeologic model to set remedial goals in a Puget Sound basin watershed

International Nuclear Information System (INIS)

Pascoe, G.; Gould, L.; Martin, J.; Riley, M.; Floyd, T.

1995-01-01

The Port of Seattle is redeveloping industrial land for a container terminal along the southwest Seattle waterfront. Concrete, asphalt, ballast, and a landfill geomembrane will cover the site and prevent direct contact with surface soils, so remedial goals focused on groundwater contamination from subsurface soils. Groundwater at the site flows along an old stormwater drain, in a filled estuary of a small creek, to Elliott Bay. Remedial goals for a variety of organic chemicals, metals, and TPH in subsurface soils were identified to protect marine receptors in the bay and their consumers. Washington State and federal marine water quality criteria were the starting points in the risk-based model, and corresponding concentrations of chemicals in groundwater were back-calculated through a hydrogeologic model. The hydrogeologic model included a mixing zone component in the bay and dilution/attenuation factors along the groundwater transport pathway that were determined from onsite groundwater and surface water chemical concentrations. A rearranged Summers equation was then applied in a second back-calculation to determine subsurface soil concentrations corresponding to the back calculated groundwater concentrations. The equation was based on calculated aquifer flow rates for the small creek watershed and rates of infiltration through surface materials calculated for each redevelopment soil cover type by the HELP model. Results of the risk-based hydrogeologic back-calculation model indicate that, depending on soil cover type at the site, concentrations in subsurface soils of PCBs from 2 to 1,000 mg/kg and of TPH up to free phase concentration would not result in risks to marine organisms or their consumers in Elliott Bay
Evanescent Wave Absorption Based Fiber Sensor for Measuring Glucose Solution Concentration

Science.gov (United States)

Marzuki, Ahmad; Candra Pratiwi, Arni; Suryanti, Venty

2018-03-01

An optical fiber sensor based on evanescent wave absorption designed for measuring glucose solution consentration was proposed. The sensor was made to detect absorbance of various wavelength in the glucose solution. The sensing element was fabricated by side polishing of multimode polymer optical fiber to form a D-shape. The sensing element was immersed in different concentration of glucoce solution. As light propagated through the optical fiber, the evanescent wave interacted with the glucose solution. Light was absorbed by the glucose solution. The larger concentration the glucose solution has, the more the evanescent wave was absorbed in particular wavelenght. Here in this paper, light absorbtion as function of glucose concentration was measured as function of wavelength (the color of LED). We have shown that the proposed sensor can demonstrated an increase of light absorption as function of glucose concentration.
Exploring the potential relationship between indoor air quality and the concentration of airborne culturable fungi: a combined experimental and neural network modeling study.

Science.gov (United States)

Liu, Zhijian; Cheng, Kewei; Li, Hao; Cao, Guoqing; Wu, Di; Shi, Yunjie

2018-02-01

Indoor airborne culturable fungi exposure has been closely linked to occupants' health. However, conventional measurement of indoor airborne fungal concentration is complicated and usually requires around one week for fungi incubation in laboratory. To provide an ultra-fast solution, here, for the first time, a knowledge-based machine learning model is developed with the inputs of indoor air quality data for estimating the concentration of indoor airborne culturable fungi. To construct a database for statistical analysis and model training, 249 data groups of air quality indicators (concentration of indoor airborne culturable fungi, indoor/outdoor PM 2.5 and PM 10 concentrations, indoor temperature, indoor relative humidity, and indoor CO 2 concentration) were measured from 85 residential buildings of Baoding (China) during the period of 2016.11.15-2017.03.15. Our results show that artificial neural network (ANN) with one hidden layer has good prediction performances, compared to a support vector machine (SVM). With the tolerance of ± 30%, the prediction accuracy of the ANN model with ten hidden nodes can at highest reach 83.33% in the testing set. Most importantly, we here provide a quick method for estimating the concentration of indoor airborne fungi that can be applied to real-time evaluation.
Probability density function modeling of scalar mixing from concentrated sources in turbulent channel flow

OpenAIRE

Bakosi, J.; Franzese, P.; Boybeyi, Z.

2010-01-01

Dispersion of a passive scalar from concentrated sources in fully developed turbulent channel flow is studied with the probability density function (PDF) method. The joint PDF of velocity, turbulent frequency and scalar concentration is represented by a large number of Lagrangian particles. A stochastic near-wall PDF model combines the generalized Langevin model of Haworth & Pope with Durbin's method of elliptic relaxation to provide a mathematically exact treatment of convective and viscous ...
System for measuring of air concentration in air-steam mixture during the transients

International Nuclear Information System (INIS)

Gorbenko, Gennady A.; Gakal, Pavlo G.; Epifanov, Konstantin S.; Osokin, Gennady V.; Smirnov, Sergey V.

2006-01-01

Description of system for air concentration measuring in air-steam mixture during the transients is represented. Air concentration measuring is based on discrete sampling method. The measuring system consists of sampler, transport pipeline, distributor and six measuring vessels. From the sampler air-steam mixture comes to distributor through transport pipeline and fills consecutively the measuring vessels. The true air concentration in place of measurement was defined based on measured air concentration in samples taken from measuring vessels. For this purpose, the mathematical model of transients in measuring system was developed. Air concentration transient in air-steam mixture in place of measurement was described in mathematical model by air concentration time-dependent function. The function parameters were defined based on air concentration measured in samples taken from measuring vessels. Estimated error of air concentration identification was about 10%. Measuring system was used in experiments on EREC BKV-213 test facility intended for testing of VVER-440/V-213 reactor barbotage-vacuum system
The measurement of thoron (220Rn) concentration in indoor air continuously using pylon model WLx

International Nuclear Information System (INIS)

Hasnel Sofyan

2011-01-01

The concentration of thoron ( 220 Rn) in particular location can be higher than radon ( 220 Rn), however, its presence is always neglected. This might be due to the difficulties in calibration and discrimination between radon and thoron. From biokinetic and dosimetric model, it has been known that the dominant contribution of thoron to the effective dose is in the lungs. UNSCEAR estimates the doses contribution of thoron and its progenies is between 5-10% of the annual dose received by the general public and the risk level is 4.4 times greater than radon and progenies. Therefore, it is necessary to study the thoron concentration in indoor air and workplaces. Radon-thoron concentration in indoor air can be determined by direct methods using Pylon Model WLx device and passive methods using Solid State Nuclear Track Detector (SSNTDs). In this research the measurement of thoron was carried out continuously using Pylon Model WLx equipment that is sensitive to radon for 24, 65, 72, 116 and 154 hours in different rooms. The measurement result showed that the mean value of thoron working level (WL) concentration obtained in room-1 was 2.53 ± 0.67 Bq/m 3 with maximum and minimum of thoron concentrations were 3.37 and 2.22 Bq/m 3 respectively. From the measurement in different locations, it was obtained that the largest and smallest average concentrations of thoron progenies were 0.83 ± 0.23 Bq/m 3 and 0.29 ± 0.64 Bq/m 3 , while the maximum and minimum concentration values were 7.80 Bq/m 3 and 0.01 Bq/m 3 respectively. Pylon Model WLx device is not enables to be used for longer and large scale survey area concurrently, so the SSNTDs which is sensitive to the emission of alpha particles and can measure cumulative thoron concentrations is required. (author)
Model-based experimental design for assessing effects of mixtures of chemicals

NARCIS (Netherlands)

Baas, J.; Stefanowicz, A.M.; Klimek, B.; Laskowski, R.; Kooijman, S.A.L.M.

2010-01-01

We exposed flour beetles (Tribolium castaneum) to a mixture of four poly aromatic hydrocarbons (PAHs). The experimental setup was chosen such that the emphasis was on assessing partial effects. We interpreted the effects of the mixture by a process-based model, with a threshold concentration for
A rheological model for elastohydrodynamic contacts based on primary laboratory data

Science.gov (United States)

Bair, S.; Winer, W. O.

1979-01-01

A shear rheological model based on primary laboratory data is proposed for concentrated contact lubrication. The model is a Maxwell model modified with a limiting shear stress. Three material properties are required: Low shear stress viscosity, limiting elastic shear modulus, and the limiting shear stress the material can withstand. All three are functions of temperature and pressure. In applying the model to EHD contacts the predicted response possesses the characteristics expected from several experiments reported in the literature and, in one specific case where direct comparison could be made, good numerical agreement is shown.
ABC Algorithm based Fuzzy Modeling of Optical Glucose Detection

Directory of Open Access Journals (Sweden)

SARACOGLU, O. G.

2016-08-01

Full Text Available This paper presents a modeling approach based on the use of fuzzy reasoning mechanism to define a measured data set obtained from an optical sensing circuit. For this purpose, we implemented a simple but effective an in vitro optical sensor to measure glucose content of an aqueous solution. Measured data contain analog voltages representing the absorbance values of three wavelengths measured from an RGB LED in different glucose concentrations. To achieve a desired model performance, the parameters of the fuzzy models are optimized by using the artificial bee colony (ABC algorithm. The modeling results presented in this paper indicate that the fuzzy model optimized by the algorithm provide a successful modeling performance having the minimum mean squared error (MSE of 0.0013 which are in clearly good agreement with the measurements.
Using model-based screening to help discover unknown environmental contaminants.

Science.gov (United States)

McLachlan, Michael S; Kierkegaard, Amelie; Radke, Michael; Sobek, Anna; Malmvärn, Anna; Alsberg, Tomas; Arnot, Jon A; Brown, Trevor N; Wania, Frank; Breivik, Knut; Xu, Shihe

2014-07-01

Of the tens of thousands of chemicals in use, only a small fraction have been analyzed in environmental samples. To effectively identify environmental contaminants, methods to prioritize chemicals for analytical method development are required. We used a high-throughput model of chemical emissions, fate, and bioaccumulation to identify chemicals likely to have high concentrations in specific environmental media, and we prioritized these for target analysis. This model-based screening was applied to 215 organosilicon chemicals culled from industrial chemical production statistics. The model-based screening prioritized several recognized organosilicon contaminants and generated hypotheses leading to the selection of three chemicals that have not previously been identified as potential environmental contaminants for target analysis. Trace analytical methods were developed, and the chemicals were analyzed in air, sewage sludge, and sediment. All three substances were found to be environmental contaminants. Phenyl-tris(trimethylsiloxy)silane was present in all samples analyzed, with concentrations of ∼50 pg m(-3) in Stockholm air and ∼0.5 ng g(-1) dw in sediment from the Stockholm archipelago. Tris(trifluoropropyl)trimethyl-cyclotrisiloxane and tetrakis(trifluoropropyl)tetramethyl-cyclotetrasiloxane were found in sediments from Lake Mjøsa at ∼1 ng g(-1) dw. The discovery of three novel environmental contaminants shows that models can be useful for prioritizing chemicals for exploratory assessment.
Metabolism and physiologically based pharmacokinetic modeling of flumioxazin in pregnant animals

Energy Technology Data Exchange (ETDEWEB)

Takaku, Tomoyuki, E-mail: takakut@sc.sumitomo-chem.co.jp; Nagahori, Hirohisa; Sogame, Yoshihisa

2014-06-15

A physiologically based pharmacokinetic (PBPK) model was developed to predict the concentration of flumioxazin, in the blood and fetus of pregnant humans during a theoretical accidental intake (1000 mg/kg). The data on flumioxazin concentration in pregnant rats (30 mg/kg po) was used to develop the PBPK model in pregnant rats using physiological parameters and chemical specific parameters. The rat PBPK model developed was extrapolated to a human model. Liver microsomes of female rats and a mixed gender of humans were used for the in vitro metabolism study. To determine the % of flumioxazin absorbed after administration at a dose of 1000 mg/kg assuming maximum accidental intake, the biliary excretion study of [phenyl-U-{sup 14}C]flumioxazin was conducted in bile duct-cannulated female rats (Crl:CD (SD)) to collect and analyze the bile, urine, feces, gastrointestinal tract, and residual carcass. The % of flumioxazin absorbed at a dose of 1000 mg/kg in rats was low (12.3%) by summing up {sup 14}C of the urine, bile, and residual carcass. The pregnant human model that was developed demonstrated that the maximum flumioxazin concentration in the blood and fetus of a pregnant human at a dose of 1000 mg/kg po was 0.86 μg/mL and 0.68 μg/mL, respectively, which is much lower than K{sub m} (202.4 μg/mL). Because the metabolism was not saturated and the absorption rate was low at a dose of 1000 mg/kg, the calculated flumioxazin concentration in pregnant humans was thought to be relatively low, considering the flumioxazin concentration in pregnant rats at a dose of 30 mg/kg. For the safety assessment of flumioxazin, these results would be useful for further in vitro toxicology experiments. - Highlights: • A PBPK model of flumioxazin in pregnant humans was developed. • Simulated flumioxazin concentration in pregnant humans was relatively low. • The results would be useful for further in vitro toxicology experiments.
Metabolism and physiologically based pharmacokinetic modeling of flumioxazin in pregnant animals

International Nuclear Information System (INIS)

Takaku, Tomoyuki; Nagahori, Hirohisa; Sogame, Yoshihisa

2014-01-01

A physiologically based pharmacokinetic (PBPK) model was developed to predict the concentration of flumioxazin, in the blood and fetus of pregnant humans during a theoretical accidental intake (1000 mg/kg). The data on flumioxazin concentration in pregnant rats (30 mg/kg po) was used to develop the PBPK model in pregnant rats using physiological parameters and chemical specific parameters. The rat PBPK model developed was extrapolated to a human model. Liver microsomes of female rats and a mixed gender of humans were used for the in vitro metabolism study. To determine the % of flumioxazin absorbed after administration at a dose of 1000 mg/kg assuming maximum accidental intake, the biliary excretion study of [phenyl-U- 14 C]flumioxazin was conducted in bile duct-cannulated female rats (Crl:CD (SD)) to collect and analyze the bile, urine, feces, gastrointestinal tract, and residual carcass. The % of flumioxazin absorbed at a dose of 1000 mg/kg in rats was low (12.3%) by summing up 14 C of the urine, bile, and residual carcass. The pregnant human model that was developed demonstrated that the maximum flumioxazin concentration in the blood and fetus of a pregnant human at a dose of 1000 mg/kg po was 0.86 μg/mL and 0.68 μg/mL, respectively, which is much lower than K m (202.4 μg/mL). Because the metabolism was not saturated and the absorption rate was low at a dose of 1000 mg/kg, the calculated flumioxazin concentration in pregnant humans was thought to be relatively low, considering the flumioxazin concentration in pregnant rats at a dose of 30 mg/kg. For the safety assessment of flumioxazin, these results would be useful for further in vitro toxicology experiments. - Highlights: • A PBPK model of flumioxazin in pregnant humans was developed. • Simulated flumioxazin concentration in pregnant humans was relatively low. • The results would be useful for further in vitro toxicology experiments
Whispering Gallery Mode Based Optical Fiber Sensor for Measuring Concentration of Salt Solution

Directory of Open Access Journals (Sweden)

Chia-Chin Chiang

2013-01-01

Full Text Available An optical fiber solution-concentration sensor based on whispering gallery mode (WGM is proposed in this paper. The WGM solution-concentration sensors were used to measure salt solutions, in which the concentrations ranged from 1% to 25% and the wavelength drifted from the left to the right. The experimental results showed an average sensitivity of approximately 0.372 nm/% and an R2 linearity of 0.8835. The proposed WGM sensors are of low cost, feasible for mass production, and durable for solution-concentration sensing.
A hybrid machine learning model to predict and visualize nitrate concentration throughout the Central Valley aquifer, California, USA

Science.gov (United States)

Ransom, Katherine M.; Nolan, Bernard T.; Traum, Jonathan A.; Faunt, Claudia; Bell, Andrew M.; Gronberg, Jo Ann M.; Wheeler, David C.; Zamora, Celia; Jurgens, Bryant; Schwarz, Gregory E.; Belitz, Kenneth; Eberts, Sandra; Kourakos, George; Harter, Thomas

2017-01-01

Intense demand for water in the Central Valley of California and related increases in groundwater nitrate concentration threaten the sustainability of the groundwater resource. To assess contamination risk in the region, we developed a hybrid, non-linear, machine learning model within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500 m below ground surface. A database of 145 predictor variables representing well characteristics, historical and current field and landscape-scale nitrogen mass balances, historical and current land use, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The boosted regression tree (BRT) method was used to screen and rank variables to predict nitrate concentration at the depths of domestic and public well supplies. The novel approach included as predictor variables outputs from existing physically based models of the Central Valley. The top five most important predictor variables included two oxidation/reduction variables (probability of manganese concentration to exceed 50 ppb and probability of dissolved oxygen concentration to be below 0.5 ppm), field-scale adjusted unsaturated zone nitrogen input for the 1975 time period, average difference between precipitation and evapotranspiration during the years 1971–2000, and 1992 total landscape nitrogen input. Twenty-five variables were selected for the final model for log-transformed nitrate. In general, increasing probability of anoxic conditions and increasing precipitation relative to potential evapotranspiration had a corresponding decrease in nitrate concentration predictions. Conversely, increasing 1975 unsaturated zone nitrogen leaching flux and 1992 total landscape nitrogen input had an increasing relative
Dynamic behavior of a multi-effect sugar concentrator system

International Nuclear Information System (INIS)

Aly, N.H.; Marwan, M.A.

1994-01-01

A transient mathematical model is developed to simulate the dynamic response of multi effect evaporator for sugar distiller concentrators at delta company, Egypt. Based on the mass and energy balance equations, a non linear mathematical model relating the system variables is obtained. This model allows to investigate the response of the unit parameters in both steady state and transient operating condition. Also, the response of the unit to perturbations in feed syrup, flow rate, concentration and heating steam temperature is studied. The predicted response based on the solution of the mathematical model is illustrated. The developed model proved to be efficient and capable to predict different operating conditions at steady state or transients variations. The study shows that an increase in heating steam temperature can be a critical factor due to caramelization of the syrup. 1 tab., 10 fig
Compact high-flux two-stage solar collectors based on tailored edge-ray concentrators

Science.gov (United States)

Friedman, Robert P.; Gordon, Jeffrey M.; Ries, Harald

1995-08-01

Using the recently-invented tailored edge-ray concentrator (TERC) approach for the design of compact two-stage high-flux solar collectors--a focusing primary reflector and a nonimaging TERC secondary reflector--we present: 1) a new primary reflector shape based on the TERC approach and a secondary TERC tailored to its particular flux map, such that more compact concentrators emerge at flux concentration levels in excess of 90% of the thermodynamic limit; and 2) calculations and raytrace simulations result which demonstrate the V-cone approximations to a wide variety of TERCs attain the concentration of the TERC to within a few percent, and hence represent practical secondary concentrators that may be superior to corresponding compound parabolic concentrator or trumpet secondaries.
A physiologically based pharmacokinetic model for ethylene oxide in mouse, rat, and human.

Science.gov (United States)

Fennell, T R; Brown, C D

2001-06-15

Ethylene oxide (EO) is widely used as a gaseous sterilant and industrial intermediate and is a direct-acting mutagen and carcinogen. The objective of these studies was to develop physiologically based pharmacokinetic (PB-PK) models for EO to describe the exposure-tissue dose relationship in rodents and humans. We previously reported results describing in vitro and in vivo kinetics of EO metabolism in male and female F344 rats and B6C3F1 mice. These studies were extended by determining the kinetics of EO metabolism in human liver cytosol and microsomes. The results indicate enzymatically catalyzed GSH conjugation via cytosolic glutathione S-transferase (cGST) and hydrolysis via microsomal epoxide hydrolase (mEH) occur in both rodents and humans. The in vitro kinetic constants were scaled to account for cytosolic (cGST) and microsomal (mEH) protein content and incorporated into PB-PK descriptions for mouse, rat, and human. Flow-limited models adequately predicted blood and tissue EO levels, disposition, and elimination kinetics determined experimentally in rats and mice, with the exception of testis concentrations, which were overestimated. Incorporation of a diffusion-limited description for testis improved the ability of the model to describe testis concentrations. The model accounted for nonlinear increases in blood and tissue concentrations that occur in mice on exposure to EO concentrations greater than 200 ppm. Species differences are predicted in the metabolism and exposure-dose relationship, with a nonlinear relationship observed in the mouse as a result of GSH depletion. These models represent an essential step in developing a mechanistically based EO exposure-dose-response description for estimating human risk from exposure to EO. Copyright 2001 Academic Press.
CO and NO2 pollution in a long two-way traffic road tunnel: investigation of NO2/NOx ratio and modelling of NO2 concentration.

Science.gov (United States)

Indrehus, O; Vassbotn, P

2001-02-01

The CO, NO and NO2 concentrations, visibility and air flow velocity were measured using continuous analysers in a long Norwegian road tunnel (7.5 km) with traffic in both directions in April 1994 and 1995. The traffic density was monitored at the same time. The NO2 concentration exceeded Norwegian air quality limits for road tunnels 17% of the time in 1994. The traffic through the tunnel decreased from 1994 to 1995, and the mean NO2 concentration was reduced from 0.73 to 0.22 ppm. The ventilation fan control, based on the CO concentration only, was unsatisfactory and the air flow was sometimes low for hours. Models for NO2 concentration based on CO concentration and absolute air flow velocity were developed and tested. The NO2/NOx ratio showed an increase for NOx levels above 2 ppm; a likely explanation for this phenomenon is NO oxidation by O2. Exposure to high NO2 concentrations may represent a health risk for people with respiratory and cardiac diseases. In long road tunnels with two-way traffic, this study indicates that ventilation fan control based on CO concentration should be adjusted for changes in vehicle CO emission and should be supplemented by air flow monitoring to limit the NO2 concentration.
Competition and Concentration in Bangladeshi Banking Sector: An Application of Panzar-Rosse Model

Directory of Open Access Journals (Sweden)

Md. Anwar Hossain Repon

2016-01-01

Full Text Available The purpose of this paper is to investigate the market structure and degree of concentration of Bangladeshi banking industry. The study measured market concentration by using widely recognized measures like k-bank concentration ratio and Herfindahl-Hirchman Index (HHI. It evaluates market structure by applying Panzar-Rosse Model over 8 years period from 2006 to 2013. The result of concentration measures indicates a decreasing trend and low level of market concentration in Bangladeshi banking industry over the sample period. The panzer-Rosse “H-Statistic” suggests that banks in Bangladesh are operating under monopolistic competition. Present paper contributes to a burgeoning literature on banking competition that has evolved significantly over the past periods on a developing country perspective like Bangladesh.

A Method for Estimating Urban Background Concentrations in Support of Hybrid Air Pollution Modeling for Environmental Health Studies

Directory of Open Access Journals (Sweden)

Saravanan Arunachalam

2014-10-01

Full Text Available Exposure studies rely on detailed characterization of air quality, either from sparsely located routine ambient monitors or from central monitoring sites that may lack spatial representativeness. Alternatively, some studies use models of various complexities to characterize local-scale air quality, but often with poor representation of background concentrations. A hybrid approach that addresses this drawback combines a regional-scale model to provide background concentrations and a local-scale model to assess impacts of local sources. However, this approach may double-count sources in the study regions. To address these limitations, we carefully define the background concentration as the concentration that would be measured if local sources were not present, and to estimate these background concentrations we developed a novel technique that combines space-time ordinary kriging (STOK of observations with outputs from a detailed chemistry-transport model with local sources zeroed out. We applied this technique to support an exposure study in Detroit, Michigan, for several pollutants (including NOx and PM2.5, and evaluated the estimated hybrid concentrations (calculated by combining the background estimates that addresses this issue of double counting with local-scale dispersion model estimates using observations. Our results demonstrate the strength of this approach specifically by eliminating the problem of double-counting reported in previous hybrid modeling approaches leading to improved estimates of background concentrations, and further highlight the relative importance of NOx vs. PM2.5 in their relative contributions to total concentrations. While a key limitation of this approach is the requirement for another detailed model simulation to avoid double-counting, STOK improves the overall characterization of background concentrations at very fine spatial scales.
Concentration addition, independent action and generalized concentration addition models for mixture effect prediction of sex hormone synthesis in vitro.

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Niels Hadrup

Full Text Available Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA, independent action (IA and generalized concentration addition (GCA models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot
Defect clustering in concentrated alloys during irradiation

International Nuclear Information System (INIS)

Hashimoto, T.; Shigenaka, N.; Fuse, M.

1992-01-01

A rate theory based model is presented to investigate the kinetics of interstitial clustering processes in a face-centered cubic (fcc) binary alloy containing A- and B-atoms. Three types of interstitial dumbbells, AA-, BB- and AB-type dumbbells, are considered. Conversions between these interstitial dumbbells are explicitly introduced into the formulation, based on the consideration of dumbbell configurations and movements. A di- interstitial is assumed to be the nucleus of a dislocation loop. Reactions of point defect production by irradiation, mutual recombination of an interstitial and a vacancy, dislocation loop nucleation and their growth are included in the model. Parameter values are chosen based on the atom size of the alloy elements, and dislocation loop formation kinetics are investigated while varying alloy compositions. Two different types of kinetics are obtained in accordance with the dominant loop nucleus types. Conversions between interstitial dumbbells are important in the determination of the interstitial dumbbell concentration ratios, of the dominant nucleus types, and consequently, the loop formation kinetics. Dislocation loop concentration decreases with increasing undersized atom content, but dose rate and temperature dependence of loop concentration are insensitive to alloy compositions. (author)
Modelling trends in soil solution concentrations under five forest-soil combinations in the Netherlands

NARCIS (Netherlands)

Salm, van der C.; Vries, de W.; Kros, J.

1996-01-01

The influence of forest and soil properties on changes in soil solution concentration upon a reduction deposition was examined for five forest-soil combinations with the dynamic RESAM model. Predicted concentrations decreased in the direction Douglas fir - Scotch pine - oak, due to decreased
Dexamethasone levels and base to apex concentration gradients in scala tympani perilymph following intracochlear delivery in the guinea pig

Science.gov (United States)

Hahn, Hartmut; Salt, Alec N.; Biegner, Thorsten; Kammerer, Bernd; Delabar, Ursular; Hartsock, Jared; Plontke, Stefan K.

2012-01-01

Hypothesis To determine whether intracochlearly applied dexamethasone will lead to better control of drug levels, higher peak concentrations and lower base-to apex concentration gradients in scala tympani (ST) of the guinea pig than after intratympanic (round window, RW) application. Background Local application of drugs to the RW results in substantial variation of intracochlear drug levels and significant base-to apex concentration gradients in ST. Methods Two μL of dexamethasone-phosphate (10 mg/mL) were injected into ST either through the RW membrane which was covered with 1% sodium hyaluronate gel or through a cochleostomy with a fluid tight seal of the micropipette. Perilymph was sequentially sampled from the apex at a single time point for each animal, at 20, 80, or 200 min after the injection ended. Results were mathematically interpreted by the means of an established computer model and compared with prior experiments performed by our group with the same experimental techniques but using intratympanic applications. Results Single intracochlear injections over 20 min resulted in approximately ten times higher peak concentrations (on average) than 2-3 hours of intratympanic application to the round window niche. Intracochlear drug levels were less variable and could be measured for at least up to 220 min. Concentration gradients along scala tympani were less pronounced. The remaining variability in intracochlear drug levels was attributable to perilymph and drug leak from the injection site. Conclusion With significantly higher, less variable drug levels and smaller base-to apex concentration gradients, intracochlear applications have advantages to intratympanic injections. For further development of this technique, it is of importance to control leaks of perilymph and drug from the injection site and to evaluate its clinical feasibility and associated risks. PMID:22588238
Influence of emissions on regional atmospheric mercury concentrations

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Bieser J.

2013-04-01

Full Text Available Mercury is a global pollutant that is rapidly transported in the atmosphere. Unlike the majority of air pollutants the background concentrations of mercury play a major role for the atmospheric concentrations on a hemispheric scale. In this study the influence of regional anthropogenic emissions in comparison to the global emissions on mercury concentrations over Europe are investigated. For this purpose an advanced threedimensional model system is used that consists of three components. The emission model SMOKE-EU, the meteorological model COSMO-CLM, and the chemistry transport model (CTM CMAQ. A variety of sensitivity runs is performed in order to determine the influence of different driving factors (i.e. boundary conditions, anthropogenic and natural emissions, emission factors, meteorological fields on the atmoshperic concentrations of different mercury species. This study is part of the European FP7 project GMOS (Global Mercury Observation System. The aim is to identify the most important drivers for atmospheric mercury in order to optimize future regional modelling studies in the course of the GMOS project. Moreover, the model results are used to determine areas of interest for air-plane based in-situ measurements which are also part of GMOS.
A Reputation-Based Identity Management Model for Cloud Computing

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Lifa Wu

2015-01-01

Full Text Available In the field of cloud computing, most research on identity management has concentrated on protecting user data. However, users typically leave a trail when they access cloud services, and the resulting user traceability can potentially lead to the leakage of sensitive user information. Meanwhile, malicious users can do harm to cloud providers through the use of pseudonyms. To solve these problems, we introduce a reputation mechanism and design a reputation-based identity management model for cloud computing. In the model, pseudonyms are generated based on a reputation signature so as to guarantee the untraceability of pseudonyms, and a mechanism that calculates user reputation is proposed, which helps cloud service providers to identify malicious users. Analysis verifies that the model can ensure that users access cloud services anonymously and that cloud providers assess the credibility of users effectively without violating user privacy.
A Comparison of Mathematical Models of Fish Mercury Concentration as a Function of Atmospheric Mercury Deposition Rate and Watershed Characteristics

Science.gov (United States)

Smith, R. A.; Moore, R. B.; Shanley, J. B.; Miller, E. K.; Kamman, N. C.; Nacci, D.

2009-12-01

Mercury (Hg) concentrations in fish and aquatic wildlife are complex functions of atmospheric Hg deposition rate, terrestrial and aquatic watershed characteristics that influence Hg methylation and export, and food chain characteristics determining Hg bioaccumulation. Because of the complexity and incomplete understanding of these processes, regional-scale models of fish tissue Hg concentration are necessarily empirical in nature, typically constructed through regression analysis of fish tissue Hg concentration data from many sampling locations on a set of potential explanatory variables. Unless the data sets are unusually long and show clear time trends, the empirical basis for model building must be based solely on spatial correlation. Predictive regional scale models are highly useful for improving understanding of the relevant biogeochemical processes, as well as for practical fish and wildlife management and human health protection. Mechanistically, the logical arrangement of explanatory variables is to multiply each of the individual Hg source terms (e.g. dry, wet, and gaseous deposition rates, and residual watershed Hg) for a given fish sampling location by source-specific terms pertaining to methylation, watershed transport, and biological uptake for that location (e.g. SO4 availability, hill slope, lake size). This mathematical form has the desirable property that predicted tissue concentration will approach zero as all individual source terms approach zero. One complication with this form, however, is that it is inconsistent with the standard linear multiple regression equation in which all terms (including those for sources and physical conditions) are additive. An important practical disadvantage of a model in which the Hg source terms are additive (rather than multiplicative) with their modifying factors is that predicted concentration is not zero when all sources are zero, making it unreliable for predicting the effects of large future reductions in
Electrode-electrolyte interface model of tripolar concentric ring electrode and electrode paste.

Science.gov (United States)

Nasrollaholhosseini, Seyed Hadi; Steele, Preston; Besio, Walter G

2016-08-01

Electrodes are used to transform ionic currents to electrical currents in biological systems. Modeling the electrode-electrolyte interface could help to optimize the performance of the electrode interface to achieve higher signal to noise ratios. There are previous reports of accurate models for single-element biomedical electrodes. In this paper we develop a model for the electrode-electrolyte interface for tripolar concentric ring electrodes (TCRE) that are used to record brain signals.
Calibrating passive sampling and passive dosing techniques to lipid based concentrations

DEFF Research Database (Denmark)

Mayer, Philipp; Schmidt, Stine Nørgaard; Annika, A.

2011-01-01

Equilibrium sampling into various formats of the silicone polydimethylsiloxane (PDMS) is increasingly used to measure the exposure of hydrophobic organic chemicals in environmental matrices, and passive dosing from silicone is increasingly used to control and maintain their exposure in laboratory...... coated vials and with Head Space Solid Phase Microextraction (HS-SPME) yielded lipid based concentrations that were in good agreement with each other, but about a factor of two higher than measured lipid-normalized concentrations in the organisms. Passive dosing was applied to bioconcentration...
A comparison of tripolar concentric ring electrode and spline Laplacians on a four-layer concentric spherical model.

Science.gov (United States)

Liu, Xiang; Makeyev, Oleksandr; Besio, Walter

2011-01-01

We have simulated a four-layer concentric spherical head model. We calculated the spline and tripolar Laplacian estimates and compared them to the analytical Laplacian on the spherical surface. In the simulations we used five different dipole groups and two electrode configurations. The comparison shows that the tripolar Laplacian has higher correlation coefficient to the analytical Laplacian in the electrode configurations tested (19, standard 10/20 locations and 64 electrodes).
Prediction of human CNS pharmacokinetics using a physiologically-based pharmacokinetic modeling approach

NARCIS (Netherlands)

Yamamoto, Yumi; Valitalo, Pyry A.; Wong, Yin Cheong; Huntjens, Dymphy R.; Proost, Johannes H.; Vermeulen, An; Krauwinkel, Walter; Beukers, Margot W.; Kokki, Hannu; Kokki, Merja; Danhof, Meindert; van Hasselt, Johan G. C.; de Lange, Elizabeth C. M.

2018-01-01

Knowledge of drug concentration-time profiles at the central nervous system (CNS) target-site is critically important for rational development of CNS targeted drugs. Our aim was to translate a recently published comprehensive CNS physiologically-based pharmacokinetic (PBPK) model from rat to human,
Data-based modelling of the Earth's dynamic magnetosphere: a review

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N. A. Tsyganenko

2013-10-01

Full Text Available This paper reviews the main advances in the area of data-based modelling of the Earth's distant magnetic field achieved during the last two decades. The essence and the principal goal of the approach is to extract maximum information from available data, using physically realistic and flexible mathematical structures, parameterized by the most relevant and routinely accessible observables. Accordingly, the paper concentrates on three aspects of the modelling: (i mathematical methods to develop a computational "skeleton" of a model, (ii spacecraft databases, and (iii parameterization of the magnetospheric models by the solar wind drivers and/or ground-based indices. The review is followed by a discussion of the main issues concerning further progress in the area, in particular, methods to assess the models' performance and the accuracy of the field line mapping. The material presented in the paper is organized along the lines of the author Julius-Bartels' Medal Lecture during the General Assembly 2013 of the European Geosciences Union.
Concentration Limits in the Cement Based Swiss Repository for Long-lived, Intermediate-level Radioactive Wastes (LMA)

International Nuclear Information System (INIS)

Berner, Urs

1999-12-01

The Swiss repository concept for long-lived, intermediate-level radioactive wastes (LMA), in Swiss terminology) foresees cylindrical concrete silos surrounded by a ring of granulated bentonite to deposit the waste. As one of the possible options and similar to the repository for high level wastes, the silos will be located in a deep crystalline host rock. Solidified with concrete in steel drums, the waste is stacked into a silo and the silo is then backfilled with a porous mortar. To characterize the release of radionuclides from the repository, the safety assessment considers first the dissolution into the pore water of the concrete, and then diffusion through the outer bentonite ring into the deep crystalline groundwater. For 19 safety relevant radionuclides (isotopes of U, Th, Pa, Np, Pu, Am, Ni, Zr, Mo, Nb, Se, Sr, Ra, Tc, Sn, I, C, Cs, Cl) the report recommends maximum elemental concentrations to be expected in the cement pore water of the particularly considered repository. These limits will form the parameter base for subsequent release model chains. Concentration limits in a geochemical environment are usually obtained from thermodynamic equilibrium calculations performed with geochemical speciation codes. However, earlier studies revealed that this procedure does not always lead to reliable results. Main reasons for this are the complexity of the systems considered, as well as the lacking completeness of, and the uncertainty associated with the thermodynamic data. To improve the recommended maximum concentrations for a distinct repository design, this work includes additional design- and system-dependent criteria. The following processes, inventories and properties are considered in particular: a) recent experimental investigations, particularly from cement systems, b) thermodynamic model calculations when reliable data are available, c) total inventories of radionuclides, d) sorption- and co-precipitation processes, e) dilution with stable isotopes, f
Concentration-driven models revisited: towards a unified framework to model settling tanks in water resource recovery facilities.

Science.gov (United States)

Torfs, Elena; Martí, M Carmen; Locatelli, Florent; Balemans, Sophie; Bürger, Raimund; Diehl, Stefan; Laurent, Julien; Vanrolleghem, Peter A; François, Pierre; Nopens, Ingmar

2017-02-01

A new perspective on the modelling of settling behaviour in water resource recovery facilities is introduced. The ultimate goal is to describe in a unified way the processes taking place both in primary settling tanks (PSTs) and secondary settling tanks (SSTs) for a more detailed operation and control. First, experimental evidence is provided, pointing out distributed particle properties (such as size, shape, density, porosity, and flocculation state) as an important common source of distributed settling behaviour in different settling unit processes and throughout different settling regimes (discrete, hindered and compression settling). Subsequently, a unified model framework that considers several particle classes is proposed in order to describe distributions in settling behaviour as well as the effect of variations in particle properties on the settling process. The result is a set of partial differential equations (PDEs) that are valid from dilute concentrations, where they correspond to discrete settling, to concentrated suspensions, where they correspond to compression settling. Consequently, these PDEs model both PSTs and SSTs.
Validation of predicted exponential concentration profiles of chemicals in soils

International Nuclear Information System (INIS)

Hollander, Anne; Baijens, Iris; Ragas, Ad; Huijbregts, Mark; Meent, Dik van de

2007-01-01

Multimedia mass balance models assume well-mixed homogeneous compartments. Particularly for soils, this does not correspond to reality, which results in potentially large uncertainties in estimates of transport fluxes from soils. A theoretically expected exponential decrease model of chemical concentrations with depth has been proposed, but hardly tested against empirical data. In this paper, we explored the correspondence between theoretically predicted soil concentration profiles and 84 field measured profiles. In most cases, chemical concentrations in soils appear to decline exponentially with depth, and values for the chemical specific soil penetration depth (d p ) are predicted within one order of magnitude. Over all, the reliability of multimedia models will improve when they account for depth-dependent soil concentrations, so we recommend to take into account the described theoretical exponential decrease model of chemical concentrations with depth in chemical fate studies. In this model the d p -values should estimated be either based on local conditions or on a fixed d p -value, which we recommend to be 10 cm for chemicals with a log K ow > 3. - Multimedia mass model predictions will improve when taking into account depth dependent soil concentrations
The Applicability of the Distribution Coefficient, KD, Based on Non-Aggregated Particulate Samples from Lakes with Low Suspended Solids Concentrations.

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Aine Marie Gormley-Gallagher

Full Text Available Separate phases of metal partitioning behaviour in freshwater lakes that receive varying degrees of atmospheric contamination and have low concentrations of suspended solids were investigated to determine the applicability of the distribution coefficient, KD. Concentrations of Pb, Ni, Co, Cu, Cd, Cr, Hg and Mn were determined using a combination of filtration methods, bulk sample collection and digestion and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS. Phytoplankton biomass, suspended solids concentrations and the organic content of the sediment were also analysed. By distinguishing between the phytoplankton and (inorganic lake sediment, transient variations in KD were observed. Suspended solids concentrations over the 6-month sampling campaign showed no correlation with the KD (n = 15 for each metal, p > 0.05 for Mn (r2 = 0.0063, Cu (r2 = 0.0002, Cr (r2 = 0.021, Ni (r2 = 0.0023, Cd (r2 = 0.00001, Co (r2 = 0.096, Hg (r2 = 0.116 or Pb (r2 = 0.164. The results implied that colloidal matter had less opportunity to increase the dissolved (filter passing fraction, which inhibited the spurious lowering of KD. The findings conform to the increasingly documented theory that the use of KD in modelling may mask true information on metal partitioning behaviour. The root mean square error of prediction between the directly measured total metal concentrations and those modelled based on the separate phase fractions were ± 3.40, 0.06, 0.02, 0.03, 0.44, 484.31, 80.97 and 0.1 μg/L for Pb, Cd, Mn, Cu, Hg, Ni, Cr and Co respectively. The magnitude of error suggests that the separate phase models for Mn and Cu can be used in distribution or partitioning models for these metals in lake water.
Measurement of fluorophore concentrations and fluorescence quantum yield in tissue-simulating phantoms using three diffusion models of steady-state spatially resolved fluorescence

Energy Technology Data Exchange (ETDEWEB)

Diamond, Kevin R; Farrell, Thomas J; Patterson, Michael S [Department of Medical Physics, Juravinski Cancer Centre and McMaster University, 699 Concession Street, Hamilton, Ontario L8V 5C2 (Canada)

2003-12-21

Steady-state diffusion theory models of fluorescence in tissue have been investigated for recovering fluorophore concentrations and fluorescence quantum yield. Spatially resolved fluorescence, excitation and emission reflectance were calculated by diffusion theory and Monte Carlo simulations, and measured using a multi-fibre probe on tissue-simulating phantoms containing either aluminium phthalocyanine tetrasulfonate (AlPcS{sub 4}), Photofrin or meso-tetra-(4-sulfonatophenyl)-porphine dihydrochloride (TPPS{sub 4}). The accuracy of the fluorophore concentration and fluorescence quantum yield recovered by three different models of spatially resolved fluorescence were compared. The models were based on: (a) weighted difference of the excitation and emission reflectance, (b) fluorescence due to a point excitation source or (c) fluorescence due to a pencil beam excitation source. When literature values for the fluorescence quantum yield were used for each of the fluorophores, the fluorophore absorption coefficient (and hence concentration) at the excitation wavelengthwas recovered with a root-mean-square accuracy of 11.4% using the point source model of fluorescence and 8.0% using the more complicated pencil beam excitation model. The accuracy was calculated over a broad range of optical properties and fluorophore concentrations. The weighted difference of reflectance model performed poorly, with a root-mean-square error in concentration of about 50%. Monte Carlo simulations suggest that there are some situations where the weighted difference of reflectance is as accurate as the other two models, although this was not confirmed experimentally. Estimates of the fluorescence quantum yield in multiple scattering media were also made by determining independently from the fitted absorption spectrum and applying the various diffusion theory models. The fluorescence quantum yields for AlPcS{sub 4} and TPPS{sub 4} were calculated to be 0.59 {+-} 0.03 and 0.121 {+-} 0
Measurement of fluorophore concentrations and fluorescence quantum yield in tissue-simulating phantoms using three diffusion models of steady-state spatially resolved fluorescence

International Nuclear Information System (INIS)

Diamond, Kevin R; Farrell, Thomas J; Patterson, Michael S

2003-01-01

Steady-state diffusion theory models of fluorescence in tissue have been investigated for recovering fluorophore concentrations and fluorescence quantum yield. Spatially resolved fluorescence, excitation and emission reflectance were calculated by diffusion theory and Monte Carlo simulations, and measured using a multi-fibre probe on tissue-simulating phantoms containing either aluminium phthalocyanine tetrasulfonate (AlPcS 4 ), Photofrin or meso-tetra-(4-sulfonatophenyl)-porphine dihydrochloride (TPPS 4 ). The accuracy of the fluorophore concentration and fluorescence quantum yield recovered by three different models of spatially resolved fluorescence were compared. The models were based on: (a) weighted difference of the excitation and emission reflectance, (b) fluorescence due to a point excitation source or (c) fluorescence due to a pencil beam excitation source. When literature values for the fluorescence quantum yield were used for each of the fluorophores, the fluorophore absorption coefficient (and hence concentration) at the excitation wavelengthwas recovered with a root-mean-square accuracy of 11.4% using the point source model of fluorescence and 8.0% using the more complicated pencil beam excitation model. The accuracy was calculated over a broad range of optical properties and fluorophore concentrations. The weighted difference of reflectance model performed poorly, with a root-mean-square error in concentration of about 50%. Monte Carlo simulations suggest that there are some situations where the weighted difference of reflectance is as accurate as the other two models, although this was not confirmed experimentally. Estimates of the fluorescence quantum yield in multiple scattering media were also made by determining independently from the fitted absorption spectrum and applying the various diffusion theory models. The fluorescence quantum yields for AlPcS 4 and TPPS 4 were calculated to be 0.59 ± 0.03 and 0.121 ± 0.001 respectively using the point
Effect of Graphite Concentration on Shear-Wave Speed in Gelatin-Based Tissue-Mimicking Phantoms

Science.gov (United States)

Anderson, Pamela G.; Rouze, Ned C.; Palmeri, Mark L.

2011-01-01

Elasticity-based imaging modalities are becoming popular diagnostic tools in clinical practice. Gelatin-based, tissue mimicking phantoms that contain graphite as the acoustic scattering material are commonly used in testing and validating elasticity-imaging methods to quantify tissue stiffness. The gelatin bloom strength and concentration are used to control phantom stiffness. While it is known that graphite concentration can be modulated to control acoustic attenuation, the impact of graphite concentrationon phantom elasticity has not been characterized in these gelatin phantoms. This work investigates the impact of graphite concentration on phantom shear stiffness as characterized by shear-wave speed measurements using impulsive acoustic-radiation-force excitations. Phantom shear-wave speed increased by 0.83 (m/s)/(dB/(cm MHz)) when increasing the attenuation coefficient slope of the phantom material through increasing graphite concentration. Therefore, gelatin-phantom stiffness can be affected by the conventional ways that attenuation is modulated through graphite concentration in these phantoms. PMID:21710828

A comparison between model and rule based control of a periodic activated sludge process

DEFF Research Database (Denmark)

Isaacs, Steven Howard; Thornberg, D.

1997-01-01

Two strategies for control of nitrogen removal in an alternating activated sludge plant are compared. One is based on simple model predictions determining the cycle length at the beginning of each cycle. The other is based on simple rules relating present ammonia and nitrate concentrations. Both ...
Dexamethasone levels and base-to-apex concentration gradients in the scala tympani perilymph after intracochlear delivery in the guinea pig.

Science.gov (United States)

Hahn, Hartmut; Salt, Alec N; Biegner, Thorsten; Kammerer, Bernd; Delabar, Ursular; Hartsock, Jared J; Plontke, Stefan K

2012-06-01

To determine whether intracochlearly applied dexamethasone will lead to better control of drug levels, higher peak concentrations, and lower base-to-apex concentration gradients in the scala tympani (ST) of the guinea pig than after intratympanic (round window [RW]) application. Local application of drugs to the RW results in substantial variation of intracochlear drug levels and significant base-to-apex concentration gradients in ST. Two microliters of dexamethasone-phosphate (10 mg/ml) were injected into ST either through the RW membrane, which was covered with 1% sodium hyaluronate gel or through a cochleostomy with a fluid tight seal of the micropipette. Perilymph was sequentially sampled from the apex at a single time point for each animal, at 20, 80, or 200 min after the injection ended. Results were mathematically interpreted by means of an established computer model and compared with previous experiments performed by our group with the same experimental techniques but using intratympanic applications. Single intracochlear injections of 20 minutes resulted in approximately 10 times higher peak concentrations (on average) than 2 to 3 hours of intratympanic application to the RW niche. Intracochlear drug levels were less variable and could be measured for over 220 minutes. Concentration gradients along the scala tympani were less pronounced. The remaining variability in intracochlear drug levels was attributable to perilymph and drug leak from the injection site. With significantly higher, less variable drug levels and smaller base-to-apex concentration gradients, intracochlear applications have advantages to intratympanic injections. For further development of this technique, it is of importance to control leaks of perilymph and drug from the injection site and to evaluate its clinical feasibility and associated risks.
Simple concentration-dependent pair interaction model for large-scale simulations of Fe-Cr alloys

International Nuclear Information System (INIS)

Levesque, Maximilien; Martinez, Enrique; Fu, Chu-Chun; Nastar, Maylise; Soisson, Frederic

2011-01-01

This work is motivated by the need for large-scale simulations to extract physical information on the iron-chromium system that is a binary model alloy for ferritic steels used or proposed in many nuclear applications. From first-principles calculations and the experimental critical temperature we build a new energetic rigid lattice model based on pair interactions with concentration and temperature dependence. Density functional theory calculations in both norm-conserving and projector augmented-wave approaches have been performed. A thorough comparison of these two different ab initio techniques leads to a robust parametrization of the Fe-Cr Hamiltonian. Mean-field approximations and Monte Carlo calculations are then used to account for temperature effects. The predictions of the model are in agreement with the most recent phase diagram at all temperatures and compositions. The solubility of Cr in Fe below 700 K remains in the range of about 6 to 12%. It reproduces the transition between the ordering and demixing tendency and the spinodal decomposition limits are also in agreement with the values given in the literature.
Caffeine Citrate Dosing Adjustments to Assure Stable Caffeine Concentrations in Preterm Neonates.

Science.gov (United States)

Koch, Gilbert; Datta, Alexandre N; Jost, Kerstin; Schulzke, Sven M; van den Anker, John; Pfister, Marc

2017-12-01

To identify dosing strategies that will assure stable caffeine concentrations in preterm neonates despite changing caffeine clearance during the first 8 weeks of life. A 3-step simulation approach was used to compute caffeine doses that would achieve stable caffeine concentrations in the first 8 weeks after birth: (1) a mathematical weight change model was developed based on published weight distribution data; (2) a pharmacokinetic model was developed based on published models that accounts for individual body weight, postnatal, and gestational age on caffeine clearance and volume of distribution; and (3) caffeine concentrations were simulated for different dosing regimens. A standard dosing regimen of caffeine citrate (using a 20 mg/kg loading dose and 5 mg/kg/day maintenance dose) is associated with a maximal trough caffeine concentration of 15 mg/L after 1 week of treatment. However, trough concentrations subsequently exhibit a clinically relevant decrease because of increasing clearance. Model-based simulations indicate that an adjusted maintenance dose of 6 mg/kg/day in the second week, 7 mg/kg/day in the third to fourth week and 8 mg/kg/day in the fifth to eighth week assures stable caffeine concentrations with a target trough concentration of 15 mg/L. To assure stable caffeine concentrations during the first 8 weeks of life, the caffeine citrate maintenance dose needs to be increased by 1 mg/kg every 1-2 weeks. These simple adjustments are expected to maintain exposure to stable caffeine concentrations throughout this important developmental period and might enhance both the short- and long-term beneficial effects of caffeine treatment. Copyright © 2017 Elsevier Inc. All rights reserved.
A numerical model for a thermally-regenerative ammonia-based flow battery using for low grade waste heat recovery

Science.gov (United States)

Wang, Weiguang; Shu, Gequn; Tian, Hua; Zhu, Xiuping

2018-06-01

A stationary and a transient two-dimensional models, based on the universal conservation laws and coupled with electrochemical reactions, are firstly applied to describe a single thermally-regenerative ammonia-based flow battery (TR-AFB), and emphasis is placed on studying the effects of reactant concentrations, physical properties of the electrolyte, flow rates and geometric parameters of flow channels on the battery performance. The model includes several experimental parameters measured by cyclic voltammetry (CV), chronoamperometry (CA) and Tafel plot. The results indicate that increasing NH3 concentration has a decisive effect on the improvement of power production and is beneficial to use higher Cu2+ concentrations, but the endurance of membrane and self-discharge need to be considered at the same time. It is also suggested that appropriately reducing the initial Cu(NH3)42+ concentration can promote power and energy densities and mitigate cyclical fluctuation. The relation between the energy and power densities is given, and the models are validated by some experimental data.
Theoretical modelling of solar dish concentrator

International Nuclear Information System (INIS)

Yaaseen Rafeeu; Mohd Zainal Abidin Abdul Kadir; Senan Mohamed Abdulla; Nor Mariah Adam

2009-01-01

Full text: Concentrating solar power (CSP) technologies could be one of the major contributor to worlds future energy needs and which would be cheap and clean sources of energy. This would improve energy utilization, higher conversion efficiency with reliable and affordable supply of electricity to the public. The proposed approach is using different size and depth of solar dish concentrators to improve solar fraction using the aluminium foil as reflector. In this paper, different measurement of solar concentrators is investigated and aims to aims to introducing an improved methodology for solar fraction on incoming solar energy in wet climate. (author)
Modelling street level PM10 concentrations across Europe: source apportionment and possible futures

Directory of Open Access Journals (Sweden)

G. Kiesewetter

2015-02-01

Full Text Available Despite increasing emission controls, particulate matter (PM has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter 10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are largely eliminated in a scenario applying the best available emission control technologies to the maximal technically feasible extent.
Responses of Mixed-Phase Cloud Condensates and Cloud Radiative Effects to Ice Nucleating Particle Concentrations in NCAR CAM5 and DOE ACME Climate Models

Science.gov (United States)

Liu, X.; Shi, Y.; Wu, M.; Zhang, K.

2017-12-01

Mixed-phase clouds frequently observed in the Arctic and mid-latitude storm tracks have the substantial impacts on the surface energy budget, precipitation and climate. In this study, we first implement the two empirical parameterizations (Niemand et al. 2012 and DeMott et al. 2015) of heterogeneous ice nucleation for mixed-phase clouds in the NCAR Community Atmosphere Model Version 5 (CAM5) and DOE Accelerated Climate Model for Energy Version 1 (ACME1). Model simulated ice nucleating particle (INP) concentrations based on Niemand et al. and DeMott et al. are compared with those from the default ice nucleation parameterization based on the classical nucleation theory (CNT) in CAM5 and ACME, and with in situ observations. Significantly higher INP concentrations (by up to a factor of 5) are simulated from Niemand et al. than DeMott et al. and CNT especially over the dust source regions in both CAM5 and ACME. Interestingly the ACME model simulates higher INP concentrations than CAM5, especially in the Polar regions. This is also the case when we nudge the two models' winds and temperature towards the same reanalysis, indicating more efficient transport of aerosols (dust) to the Polar regions in ACME. Next, we examine the responses of model simulated cloud liquid water and ice water contents to different INP concentrations from three ice nucleation parameterizations (Niemand et al., DeMott et al., and CNT) in CAM5 and ACME. Changes in liquid water path (LWP) reach as much as 20% in the Arctic regions in ACME between the three parameterizations while the LWP changes are smaller and limited in the Northern Hemispheric mid-latitudes in CAM5. Finally, the impacts on cloud radiative forcing and dust indirect effects on mixed-phase clouds are quantified with the three ice nucleation parameterizations in CAM5 and ACME.
Longitudinal study of alcohol consumption and HDL concentrations: a community-based study.

Science.gov (United States)

Huang, Shue; Li, Junjuan; Shearer, Gregory C; Lichtenstein, Alice H; Zheng, Xiaoming; Wu, Yuntao; Jin, Cheng; Wu, Shouling; Gao, Xiang

2017-04-01

Background: In cross-sectional studies and short-term clinical trials, it has been suggested that there is a positive dose-response relation between alcohol consumption and HDL concentrations. However, prospective data have been limited. Objective: We sought to determine the association between total alcohol intake, the type of alcohol-containing beverage, and the 6-y (2006-2012) longitudinal change in HDL-cholesterol concentrations in a community-based cohort. Design: A total of 71,379 Chinese adults (mean age: 50 y) who were free of cardiovascular diseases and cancer and did not use cholesterol-lowering agents during follow-up were included in the study. Alcohol intake was assessed via a questionnaire in 2006 (baseline), and participants were classified into the following categories of alcohol consumption: never, past, light (women: 0-0.4 servings/d; men: 0-0.9 servings/d), moderate (women: 0.5-1.0 servings/d; men: 1-2 servings/d), and heavy (women: >1.0 servings/d; men: >2 servings/d). HDL-cholesterol concentrations were measured in 2006, 2008, 2010, and 2012. We used generalized estimating equation models to examine the associations between baseline alcohol intake and the change in HDL-cholesterol concentrations with adjustment for age, sex, smoking, physical activity, obesity, hypertension, diabetes, liver function, and C-reactive protein concentrations. Results: An umbrella-shaped association was observed between total alcohol consumption and changes in HDL-cholesterol concentrations. Compared with never drinkers, past, light, moderate, and heavy drinkers experienced slower decreases in HDL cholesterol of 0.012 mmol · L -1 · y -1 (95% CI: 0.008, 0.016 mmol · L -1 · y -1 ), 0.013 mmol · L -1 · y -1 (95% CI: 0.010, 0.016 mmol · L -1 · y -1 ), 0.017 mmol · L -1 · y -1 (95% CI: 0.009, 0.025 mmol · L -1 · y -1 ), and 0.008 mmol · L -1 · y -1 (95% CI: 0.005, 0.011 mmol · L -1 · y -1 ), respectively ( P alcohol consumption was associated with the
The interaction of the flux errors and transport errors in modeled atmospheric carbon dioxide concentrations

Science.gov (United States)

Feng, S.; Lauvaux, T.; Butler, M. P.; Keller, K.; Davis, K. J.; Jacobson, A. R.; Schuh, A. E.; Basu, S.; Liu, J.; Baker, D.; Crowell, S.; Zhou, Y.; Williams, C. A.

2017-12-01

Regional estimates of biogenic carbon fluxes over North America from top-down atmospheric inversions and terrestrial biogeochemical (or bottom-up) models remain inconsistent at annual and sub-annual time scales. While top-down estimates are impacted by limited atmospheric data, uncertain prior flux estimates and errors in the atmospheric transport models, bottom-up fluxes are affected by uncertain driver data, uncertain model parameters and missing mechanisms across ecosystems. This study quantifies both flux errors and transport errors, and their interaction in the CO2 atmospheric simulation. These errors are assessed by an ensemble approach. The WRF-Chem model is set up with 17 biospheric fluxes from the Multiscale Synthesis and Terrestrial Model Intercomparison Project, CarbonTracker-Near Real Time, and the Simple Biosphere model. The spread of the flux ensemble members represents the flux uncertainty in the modeled CO2 concentrations. For the transport errors, WRF-Chem is run using three physical model configurations with three stochastic perturbations to sample the errors from both the physical parameterizations of the model and the initial conditions. Additionally, the uncertainties from boundary conditions are assessed using four CO2 global inversion models which have assimilated tower and satellite CO2 observations. The error structures are assessed in time and space. The flux ensemble members overall overestimate CO2 concentrations. They also show larger temporal variability than the observations. These results suggest that the flux ensemble is overdispersive. In contrast, the transport ensemble is underdispersive. The averaged spatial distribution of modeled CO2 shows strong positive biogenic signal in the southern US and strong negative signals along the eastern coast of Canada. We hypothesize that the former is caused by the 3-hourly downscaling algorithm from which the nighttime respiration dominates the daytime modeled CO2 signals and that the latter
Mutant prevention concentration, pharmacokinetic-pharmacodynamic integration, and modeling of enrofloxacin data established in diseased buffalo calves.

Science.gov (United States)

Ramalingam, B; Sidhu, P K; Kaur, G; Venkatachalam, D; Rampal, S

2015-12-01

The pharmacokinetic-pharmacodynamic (PK/PD) modeling of enrofloxacin data using mutant prevention concentration (MPC) of enrofloxacin was conducted in febrile buffalo calves to optimize dosage regimen and to prevent the emergence of antimicrobial resistance. The serum peak concentration (Cmax ), terminal half-life (t1/2 K10) , apparent volume of distribution (Vd(area) /F), and mean residence time (MRT) of enrofloxacin were 1.40 ± 0.27 μg/mL, 7.96 ± 0.86 h, 7.74 ± 1.26 L/kg, and 11.57 ± 1.01 h, respectively, following drug administration at dosage 12 mg/kg by intramuscular route. The minimum inhibitory concentration (MIC), minimum bactericidal concentration, and MPC of enrofloxacin against Pasteurella multocida were 0.055, 0.060, and 1.45 μg/mL, respectively. Modeling of ex vivo growth inhibition data to the sigmoid Emax equation provided AUC24 h /MIC values to produce effects of bacteriostatic (33 h), bactericidal (39 h), and bacterial eradication (41 h). The estimated daily dosage of enrofloxacin in febrile buffalo calves was 3.5 and 8.4 mg/kg against P. multocida/pathogens having MIC90 ≤0.125 and 0.30 μg/mL, respectively, based on the determined AUC24 h /MIC values by modeling PK/PD data. The lipopolysaccharide-induced fever had no direct effect on the antibacterial activity of the enrofloxacin and alterations in PK of the drug, and its metabolite will be beneficial for its use to treat infectious diseases caused by sensitive pathogens in buffalo species. In addition, in vitro MPC data in conjunction with in vivo PK data indicated that clinically it would be easier to eradicate less susceptible strains of P. multocida in diseased calves. © 2015 John Wiley & Sons Ltd.
A terrestrial biosphere model optimized to atmospheric CO2 concentration and above ground woody biomass

Science.gov (United States)

Saito, M.; Ito, A.; Maksyutov, S. S.

2013-12-01

This study documents an optimization of a prognostic biosphere model (VISIT; Vegetation Integrative Similator for Trace gases) to observations of atmospheric CO2 concentration and above ground woody biomass by using a Bayesian inversion method combined with an atmospheric tracer transport model (NIES-TM; National Institute for Environmental Studies / Frontier Research Center for Global Change (NIES/FRCGC) off-line global atmospheric tracer transport model). The assimilated observations include 74 station records of surface atmospheric CO2 concentration and aggregated grid data sets of above ground woody biomass (AGB) and net primary productivity (NPP) over the globe. Both the biosphere model and the atmospheric transport model are used at a horizontal resolution of 2.5 deg x 2.5 deg grid with temporal resolutions of a day and an hour, respectively. The atmospheric transport model simulates atmospheric CO2 concentration with nine vertical levels using daily net ecosystem CO2 exchange rate (NEE) from the biosphere model, oceanic CO2 flux, and fossil fuel emission inventory. The models are driven by meteorological data from JRA-25 (Japanese 25-year ReAnalysis) and JCDAS (JMA Climate Data Assimilation System). Statistically optimum physiological parameters in the biosphere model are found by iterative minimization of the corresponding Bayesian cost function. We select thirteen physiological parameter with high sensitivity to NEE, NPP, and AGB for the minimization. Given the optimized physiological parameters, the model shows error reductions in seasonal variation of the CO2 concentrations especially in the northern hemisphere due to abundant observation stations, while errors remain at a few stations that are located in coastal coastal area and stations in the southern hemisphere. The model also produces moderate estimates of the mean magnitudes and probability distributions in AGB and NPP for each biome. However, the model fails in the simulation of the terrestrial
Model-Based Individualized Treatment of Chemotherapeutics: Bayesian Population Modeling and Dose Optimization.

Directory of Open Access Journals (Sweden)

Devaraj Jayachandran

Full Text Available 6-Mercaptopurine (6-MP is one of the key drugs in the treatment of many pediatric cancers, auto immune diseases and inflammatory bowel disease. 6-MP is a prodrug, converted to an active metabolite 6-thioguanine nucleotide (6-TGN through enzymatic reaction involving thiopurine methyltransferase (TPMT. Pharmacogenomic variation observed in the TPMT enzyme produces a significant variation in drug response among the patient population. Despite 6-MP's widespread use and observed variation in treatment response, efforts at quantitative optimization of dose regimens for individual patients are limited. In addition, research efforts devoted on pharmacogenomics to predict clinical responses are proving far from ideal. In this work, we present a Bayesian population modeling approach to develop a pharmacological model for 6-MP metabolism in humans. In the face of scarcity of data in clinical settings, a global sensitivity analysis based model reduction approach is used to minimize the parameter space. For accurate estimation of sensitive parameters, robust optimal experimental design based on D-optimality criteria was exploited. With the patient-specific model, a model predictive control algorithm is used to optimize the dose scheduling with the objective of maintaining the 6-TGN concentration within its therapeutic window. More importantly, for the first time, we show how the incorporation of information from different levels of biological chain-of response (i.e. gene expression-enzyme phenotype-drug phenotype plays a critical role in determining the uncertainty in predicting therapeutic target. The model and the control approach can be utilized in the clinical setting to individualize 6-MP dosing based on the patient's ability to metabolize the drug instead of the traditional standard-dose-for-all approach.
Model-Based Individualized Treatment of Chemotherapeutics: Bayesian Population Modeling and Dose Optimization

Science.gov (United States)

Jayachandran, Devaraj; Laínez-Aguirre, José; Rundell, Ann; Vik, Terry; Hannemann, Robert; Reklaitis, Gintaras; Ramkrishna, Doraiswami

2015-01-01

6-Mercaptopurine (6-MP) is one of the key drugs in the treatment of many pediatric cancers, auto immune diseases and inflammatory bowel disease. 6-MP is a prodrug, converted to an active metabolite 6-thioguanine nucleotide (6-TGN) through enzymatic reaction involving thiopurine methyltransferase (TPMT). Pharmacogenomic variation observed in the TPMT enzyme produces a significant variation in drug response among the patient population. Despite 6-MP’s widespread use and observed variation in treatment response, efforts at quantitative optimization of dose regimens for individual patients are limited. In addition, research efforts devoted on pharmacogenomics to predict clinical responses are proving far from ideal. In this work, we present a Bayesian population modeling approach to develop a pharmacological model for 6-MP metabolism in humans. In the face of scarcity of data in clinical settings, a global sensitivity analysis based model reduction approach is used to minimize the parameter space. For accurate estimation of sensitive parameters, robust optimal experimental design based on D-optimality criteria was exploited. With the patient-specific model, a model predictive control algorithm is used to optimize the dose scheduling with the objective of maintaining the 6-TGN concentration within its therapeutic window. More importantly, for the first time, we show how the incorporation of information from different levels of biological chain-of response (i.e. gene expression-enzyme phenotype-drug phenotype) plays a critical role in determining the uncertainty in predicting therapeutic target. The model and the control approach can be utilized in the clinical setting to individualize 6-MP dosing based on the patient’s ability to metabolize the drug instead of the traditional standard-dose-for-all approach. PMID:26226448
Evaluation of local stress and local hydrogen concentration at grain boundary using three-dimensional polycrystalline model

International Nuclear Information System (INIS)

Ebihara, Ken-ichi; Itakura, Mitsuhiro; Yamaguchi, Masatake; Kaburaki, Hideo; Suzudo, Tomoaki

2010-01-01

The decohesion model in which hydrogen segregating at grain boundaries reduces cohesive energy is considered to explain hydrogen embrittlement. Although there are several experimental and theoretical supports of this model, its total process is still unclear. In order to understand hydrogen embrittlement in terms of the decohesion model, therefore, it is necessary to evaluate stress and hydrogen concentration at grain boundaries under experimental conditions and to verify the grain boundary decohesion process. Under this consideration, we evaluated the stress and the hydrogen concentration at grain boundaries in the three-dimensional polycrystalline model which was generated by the random Voronoi tessellation. The crystallographic anisotropy was given to each grain. As the boundary conditions of the calculations, data extracted from the results calculated in the notched round-bar specimen model under the tensile test condition in which fracture of the steel specimen is observed was given to the polycrystalline model. As a result, it was found that the evaluated stress does not reach the fracture stress which was estimated under the condition of the evaluated hydrogen concentration by first principles calculations. Therefore, it was considered that the initiation of grain boundary fracture needs other factors except the stress concentration due to the crystallographic anisotropy. (author)
Modelling deposition and air concentration of reduced nitrogen in Poland and sensitivity to variability in annual meteorology.

Science.gov (United States)

Kryza, Maciej; Dore, Anthony J; Błaś, Marek; Sobik, Mieczysław

2011-04-01

The relative contribution of reduced nitrogen to acid and eutrophic deposition in Europe has increased recently as a result of European policies which have been successful in reducing SO(2) and NO(x) emissions but have had smaller impacts on ammonia (NH(3)) emissions. In this paper the Fine Resolution Atmospheric Multi-pollutant Exchange (FRAME) model was used to calculate the spatial patterns of annual average ammonia and ammonium (NH(4)(+)) air concentrations and reduced nitrogen (NH(x)) dry and wet deposition with a 5 km × 5 km grid for years 2002-2005. The modelled air concentrations of NH(3) and dry deposition of NH(x) show similar spatial patterns for all years considered. The largest year to year changes were found for wet deposition, which vary considerably with precipitation amount. The FRAME modelled air concentrations and wet deposition are in reasonable agreement with available measurements (Pearson's correlation coefficients above 0.6 for years 2002-2005), and with spatial patterns of concentrations and deposition of NH(x) reported with the EMEP results, but show larger spatial gradients. The error statistics show that the FRAME model results are in better agreement with measurements if compared with EMEP estimates. The differences in deposition budgets calculated with FRAME and EMEP do not exceed 17% for wet and 6% for dry deposition, with FRAME estimates higher than for EMEP wet deposition for modelled period and lower or equal for dry deposition. The FRAME estimates of wet deposition budget are lower than the measurement-based values reported by the Chief Inspectorate of Environmental Protection of Poland, with the differences by approximately 3%. Up to 93% of dry and 53% of wet deposition of NH(x) in Poland originates from national sources. Over the western part of Poland and mountainous areas in the south, transboundary transport can contribute over 80% of total (dry + wet) NH(x) deposition. The spatial pattern of the relative contribution of
Joint Application of Concentrations and Isotopic Signatures to Investigate the Global Atmospheric Carbon Monoxide Budget: Inverse Modeling Approach

Science.gov (United States)

Park, K.; Mak, J. E.; Emmons, L. K.

2008-12-01

Carbon monoxide is not only an important component for determining the atmospheric oxidizing capacity but also a key trace gas in the atmospheric chemistry of the Earth's background environment. The global CO cycle and its change are closely related to both the change of CO mixing ratio and the change of source strength. Previously, to estimate the global CO budget, most top-down estimation techniques have been applied the concentrations of CO solely. Since CO from certain sources has a unique isotopic signature, its isotopes provide additional information to constrain its sources. Thus, coupling the concentration and isotope fraction information enables to tightly constrain CO flux by its sources and allows better estimations on the global CO budget. MOZART4 (Model for Ozone And Related chemical Tracers), a 3-D global chemical transport model developed at NCAR, MPI for meteorology and NOAA/GFDL and is used to simulate the global CO concentration and its isotopic signature. Also, a tracer version of MOZART4 which tagged for C16O and C18O from each region and each source was developed to see their contributions to the atmosphere efficiently. Based on the nine-year-simulation results we analyze the influences of each source of CO to the isotopic signature and the concentration. Especially, the evaluations are focused on the oxygen isotope of CO (δ18O), which has not been extensively studied yet. To validate the model performance, CO concentrations and isotopic signatures measured from MPI, NIWA and our lab are compared to the modeled results. The MOZART4 reproduced observational data fairly well; especially in mid to high latitude northern hemisphere. Bayesian inversion techniques have been used to estimate the global CO budget with combining observed and modeled CO concentration. However, previous studies show significant differences in their estimations on CO source strengths. Because, in addition to the CO mixing ratio, isotopic signatures are independent tracers
Scattering Solar Thermal Concentrators

Energy Technology Data Exchange (ETDEWEB)

Giebink, Noel C. [Pennsylvania State Univ., State College, PA (United States)

2015-01-31

This program set out to explore a scattering-based approach to concentrate sunlight with the aim of improving collector field reliability and of eliminating wind loading and gross mechanical movement through the use of a stationary collection optic. The approach is based on scattering sunlight from the focal point of a fixed collection optic into the confined modes of a sliding planar waveguide, where it is transported to stationary tubular heat transfer elements located at the edges. Optical design for the first stage of solar concentration, which entails focusing sunlight within a plane over a wide range of incidence angles (>120 degree full field of view) at fixed tilt, led to the development of a new, folded-path collection optic that dramatically out-performs the current state-of-the-art in scattering concentration. Rigorous optical simulation and experimental testing of this collection optic have validated its performance. In the course of this work, we also identified an opportunity for concentrating photovoltaics involving the use of high efficiency microcells made in collaboration with partners at the University of Illinois. This opportunity exploited the same collection optic design as used for the scattering solar thermal concentrator and was therefore pursued in parallel. This system was experimentally demonstrated to achieve >200x optical concentration with >70% optical efficiency over a full day by tracking with <1 cm of lateral movement at fixed latitude tilt. The entire scattering concentrator waveguide optical system has been simulated, tested, and assembled at small scale to verify ray tracing models. These models were subsequently used to predict the full system optical performance at larger, deployment scale ranging up to >1 meter aperture width. Simulations at an aperture widths less than approximately 0.5 m with geometric gains ~100x predict an overall optical efficiency in the range 60-70% for angles up to 50 degrees from normal. However, the
Comparison of Highly Resolved Model-Based Exposure Metrics for Traffic-Related Air Pollutants to Support Environmental Health Studies

Directory of Open Access Journals (Sweden)

Shih Ying Chang

2015-12-01

Full Text Available Human exposure to air pollution in many studies is represented by ambient concentrations from space-time kriging of observed values. Space-time kriging techniques based on a limited number of ambient monitors may fail to capture the concentration from local sources. Further, because people spend more time indoors, using ambient concentration to represent exposure may cause error. To quantify the associated exposure error, we computed a series of six different hourly-based exposure metrics at 16,095 Census blocks of three Counties in North Carolina for CO, NOx, PM2.5, and elemental carbon (EC during 2012. These metrics include ambient background concentration from space-time ordinary kriging (STOK, ambient on-road concentration from the Research LINE source dispersion model (R-LINE, a hybrid concentration combining STOK and R-LINE, and their associated indoor concentrations from an indoor infiltration mass balance model. Using a hybrid-based indoor concentration as the standard, the comparison showed that outdoor STOK metrics yielded large error at both population (67% to 93% and individual level (average bias between −10% to 95%. For pollutants with significant contribution from on-road emission (EC and NOx, the on-road based indoor metric performs the best at the population level (error less than 52%. At the individual level, however, the STOK-based indoor concentration performs the best (average bias below 30%. For PM2.5, due to the relatively low contribution from on-road emission (7%, STOK-based indoor metric performs the best at both population (error below 40% and individual level (error below 25%. The results of the study will help future epidemiology studies to select appropriate exposure metric and reduce potential bias in exposure characterization.
Electron concentration and phase stability in NbCr2-based Laves phase alloys

Energy Technology Data Exchange (ETDEWEB)

Zhu, J.H.; Liaw, P.K. [Univ. of Tennessee, Knoxville, TN (United States). Dept. of Materials Science and Engineering; Liu, C.T. [Oak Ridge National Lab., TN (United States). Metals and Ceramics Div.

1997-05-12

Phase stability in NbCr{sub 2}-based transition-metal Laves phases was studied, based on the data reported for binary X-Cr, Nb-X, and ternary Nb-Cr-X phase diagrams. It was shown that when the atomic size ratios are kept identical, the average electron concentration factor, e/a, is the dominating factor in controlling the phase stability of NbCr{sub 2}-based transition-metal Laves phases. The e/a ratios for different Laves polytypes were determined as followed: with e/a < 5.76, the C15 structure is stabilized; at an e/a range of 5.88--7.53, the C14 structure is stabilized; with e/a > 7.65, the C15 structure is stabilized again. A further increase in the electron concentration factor (e/a > 8) leads to the disordering of the alloy. The electron concentration effect on the phase stability of Mg-based Laves phases and transition-metal A{sub 3}B intermetallic compounds is also reviewed and compared with the present observations in transition-metal Laves phases. In order to verify the e/a/phase stability relationship experimentally, additions of Cu (with e/a = 11) were selected to replace Cr in the NbCr{sub 2} Laves phase. Experimental results for the ternary Nb-Cr-Cu system are reported and discussed in terms of the correlation between the e/a ratio and phase stability in NbCr{sub 2}-based Laves phases. A new phase was found, which has an average composition of Nb-47Cr-3Cu. Within the solubility limit, the electron concentration and phase stability relationship is obeyed in the Nb-Cr-Cu system.

An analytical/numerical correlation study of the multiple concentric cylinder model for the thermoplastic response of metal matrix composites

Science.gov (United States)

Pindera, Marek-Jerzy; Salzar, Robert S.; Williams, Todd O.

1993-01-01

The utility of a recently developed analytical micromechanics model for the response of metal matrix composites under thermal loading is illustrated by comparison with the results generated using the finite-element approach. The model is based on the concentric cylinder assemblage consisting of an arbitrary number of elastic or elastoplastic sublayers with isotropic or orthotropic, temperature-dependent properties. The elastoplastic boundary-value problem of an arbitrarily layered concentric cylinder is solved using the local/global stiffness matrix formulation (originally developed for elastic layered media) and Mendelson's iterative technique of successive elastic solutions. These features of the model facilitate efficient investigation of the effects of various microstructural details, such as functionally graded architectures of interfacial layers, on the evolution of residual stresses during cool down. The available closed-form expressions for the field variables can readily be incorporated into an optimization algorithm in order to efficiently identify optimal configurations of graded interfaces for given applications. Comparison of residual stress distributions after cool down generated using finite-element analysis and the present micromechanics model for four composite systems with substantially different temperature-dependent elastic, plastic, and thermal properties illustrates the efficacy of the developed analytical scheme.
Analytical model of impurity concentration during steam generation in permeable porous structures

International Nuclear Information System (INIS)

Polonskii, V.S.; Orlov, A.V.

1993-01-01

A model is proposed to describe the mass transfer of impurities during steam generation on a surface covered by porous deposits of corrosion products. The model is based on replacement of the actual structure of the deposits by a system of cylindrical fluid and vapor channels in which the flow of vapor and a liquid film is described by the Navier-Stokes equations. The driving force in the process is assumed to be the difference in the Laplacian pressures due to surface tension on the front and back sides of elongated vapor bubbles. Calculations performed for the operating conditions of the drums of the steam generators of nuclear power plants with water-moderated water-cooled reactors show that the mass transfer rate is extremely low in the gaps in cold drums and that the concentration of aggressive impurities deep within these channels may reach two or more orders of magnitude-thus leading to rapid corrosion. Almost complete vaporization occurs in the capillary channels of hot drums with deposits, which probably precludes corrosion in the channel depths. However, corrosion damage remains a possibility at the entrance to the channels (on the side of the second loop)
Modeling concentration patterns of agricultural and urban micropollutants in surface waters in catchment of mixed land use

Science.gov (United States)

Stamm, C.; Scheidegger, R.; Bader, H. P.

2012-04-01

Organic micropollutants detected in surface waters can originate from agricultural and urban sources. Depending on the use of the compounds, the temporal loss patterns vary substantially. Therefore models that simulate water quality in watersheds of mixed land use have to account for all relevant sources. We present here simulation results of a transport model that describes the dynamic of several biocidal compounds as well as the behaviour of human pharmaceuticals. The model consists of the sub-model Rexpo simulating the transfer of the compounds from the point of application to the stream in semi-lumped manner. The river sub-model, which is programmed in the Aquasim software, describes the fate of the compounds in the stream. Both sub-models are process-based. The Rexpo sub-model was calibrated at the scale of a small catchment of 25 km2, which is inhabited by about 12'000 people. Based on the resulting model parameters the loss dynamics of two herbicides (atrazine, isoproturon) and a compound of mixed urban and agricultural use (diuron) were predicted for two nested catchment of 212 and 1696 km2, respectively. The model output was compared to observed time-series of concentrations and loads obtained for the entire year 2009. Additionally, the fate of two pharmaceuticals with constant input (carbamazepine, diclofenac) was simulated for improving the understanding of possible degradation processes. The simulated loads and concentrations of the biocidal compounds differed by a factor of 2 to 3 from the observations. In general, the seasonal patterns were well captured by the model. However, a detailed analysis of the seasonality revealed substantial input uncertainty for the application of the compounds. The model results also demonstrated that for the dynamics of rain-driven losses of biocidal compounds the semi-lumped approach of the Rexpo sub-model was sufficient. Only for simulating the photolytic degradation of diclofenac in the stream the detailed
3d Finite Element Modelling of Non-Crimp Fabric Based Fibre Composite Based on X-Ray Ct Data

DEFF Research Database (Denmark)

Jespersen, Kristine Munk; Asp, Leif; Mikkelsen, Lars Pilgaard

2017-01-01

initiation and progression in the material. In the current study, the real bundle structure inside a non-crimp fabric based fibre composite is extracted from 3D X-ray CT images and imported into ABAQUS for numerical modelling.The local stress concentrations when loaded in tension caused by the fibre bundle...
Unifying Model-Based and Reactive Programming within a Model-Based Executive

Science.gov (United States)

Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)

1999-01-01

Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.
Modelling the distribution of 222Rn concentration in a multi level, general purpose building

International Nuclear Information System (INIS)

Toro, Laszlo; Noditi, Mihaela; Gheorghe, Raluca; Gheorghe, Dan

2008-01-01

The importance of 222 Rn (radon) in the indoor air related to the exposure form natural sources is relatively well documented. About 30% of the individual effective dose from natural sources is coming from the inhalation of 222 Rn and his short lived daughters. In unfavorable conditions given by the soil porosity and the existence of upward air movement in the soil there is a possibility to have unusually high radon concentration in houses even on soil with 'normal' 226 Ra content. Some construction solutions (high indoor spaces) should generate a significant indoor-outdoor negative pressure differences and consequently upward air currents (stack effect) which will facilitate the entrance of radon in the building. This effect will multiply the possibility of migration of radon in the building. The difficulty of the prediction of radon migration in the soil-building system increase the importance of the mathematical modelling of the behavior of radon-soil emission, infiltration and migration in the building - in areas with high radon potential. For one level simple buildings there are several models in the literature but the information regarding the multilevel building models are relatively scarce. Two different approaches used to describe the behavior of the radon gas in large (mainly high) buildings have been analyzed: Direct approach: computational fluid dynamics, solving the transport equations for the whole building (the domain of the solution of the transport and flow equations is delimited by the building envelope - the external walls); the openings (internal and external) and ventilation are defined by the boundary conditions. This approach is quite complex, the equations are solved (numerically) for highly inhomogeneous medium but is based on the fundamental processes governing the transport. In the same time it gives the possibility to obtain a concentration pattern in every part of the building. Multi-zone approach treating the building as interconnected
The concentric model of human working memory: A validation study using complex span and updating tasks

Directory of Open Access Journals (Sweden)

Velichkovsky B. B.

2017-09-01

Full Text Available Background. Working memory (WM seems to be central to most forms of high-level cognition. This fact is fueling the growing interest in studying its structure and functional organization. The influential “concentric model” (Oberauer, 2002 suggests that WM contains a processing component and two storage components with different capacity limitations and sensitivity to interference. There is, to date, only limited support for the concentric model in the research literature, and it is limited to a number of specially designed tasks. Objective. In the present paper, we attempted to validate the concentric model by testing its major predictions using complex span and updating tasks in a number of experimental paradigms. Method. The model predictions were tested with the help of review of data obtained primarily in our own experiments in several research domains, including Sternberg’s additive factors method; factor structure of WM; serial position effects in WM; and WM performance in a sample with episodic long-term memory deficits. Results. Predictions generated by the concentric model were shown to hold in all these domains. In addition, several new properties of WM were identified. In particular, we recently found that WM indeed contains a processing component which functions independent of storage components. In turn, the latter were found to form a storage hierarchy which balances fast access to selected items, with the storing of large amounts of potentially relevant information. Processing and storage in WM were found to be dependent on shared cognitive resources which are dynamically allocated between WM components according to actual task requirements. e implications of these findings for the theory of WM are discussed. Conclusion. The concentric model was shown to be valid with respect to standard WM tasks. The concentric model others promising research perspectives for the study of higher- order cognition, including underlying
A Process-Based Model of TCA Cycle Functioning to Analyze Citrate Accumulation in Pre- and Post-Harvest Fruits.

Science.gov (United States)

Etienne, Audrey; Génard, Michel; Bugaud, Christophe

2015-01-01

Citrate is one of the most important organic acids in many fruits and its concentration plays a critical role in organoleptic properties. The regulation of citrate accumulation throughout fruit development, and the origins of the phenotypic variability of the citrate concentration within fruit species remain to be clarified. In the present study, we developed a process-based model of citrate accumulation based on a simplified representation of the TCA cycle to predict citrate concentration in fruit pulp during the pre- and post-harvest stages. Banana fruit was taken as a reference because it has the particularity of having post-harvest ripening, during which citrate concentration undergoes substantial changes. The model was calibrated and validated on the two stages, using data sets from three contrasting cultivars in terms of citrate accumulation, and incorporated different fruit load, potassium supply, and harvest dates. The model predicted the pre and post-harvest dynamics of citrate concentration with fairly good accuracy for the three cultivars. The model suggested major differences in TCA cycle functioning among cultivars during post-harvest ripening of banana, and pointed to a potential role for NAD-malic enzyme and mitochondrial malate carriers in the genotypic variability of citrate concentration. The sensitivity of citrate accumulation to growth parameters and temperature differed among cultivars during post-harvest ripening. Finally, the model can be used as a conceptual basis to study citrate accumulation in fleshy fruits and may be a powerful tool to improve our understanding of fruit acidity.
Optimization of DNA Sensor Model Based Nanostructured Graphene Using Particle Swarm Optimization Technique

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Hediyeh Karimi

2013-01-01

Full Text Available It has been predicted that the nanomaterials of graphene will be among the candidate materials for postsilicon electronics due to their astonishing properties such as high carrier mobility, thermal conductivity, and biocompatibility. Graphene is a semimetal zero gap nanomaterial with demonstrated ability to be employed as an excellent candidate for DNA sensing. Graphene-based DNA sensors have been used to detect the DNA adsorption to examine a DNA concentration in an analyte solution. In particular, there is an essential need for developing the cost-effective DNA sensors holding the fact that it is suitable for the diagnosis of genetic or pathogenic diseases. In this paper, particle swarm optimization technique is employed to optimize the analytical model of a graphene-based DNA sensor which is used for electrical detection of DNA molecules. The results are reported for 5 different concentrations, covering a range from 0.01 nM to 500 nM. The comparison of the optimized model with the experimental data shows an accuracy of more than 95% which verifies that the optimized model is reliable for being used in any application of the graphene-based DNA sensor.
Simultaneous extraction and concentration of water pollution tracers using ionic-liquid-based systems.

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Dinis, Teresa B V; Passos, Helena; Lima, Diana L D; Sousa, Ana C A; Coutinho, João A P; Esteves, Valdemar I; Freire, Mara G

2017-07-29

Human activities are responsible for the release of innumerous substances into the aquatic environment. Some of these substances can be used as pollution tracers to identify contamination sources and to prioritize monitoring and remediation actions. Thus, their identification and quantification are of high priority. However, due to their presence in complex matrices and at significantly low concentrations, a pre-treatment/concentration step is always required. As an alternative to the currently used pre-treatment methods, mainly based on solid-phase extractions, aqueous biphasic systems (ABS) composed of ionic liquids (ILs) and K 3 C 6 H 5 O 7 are here proposed for the simultaneous extraction and concentration of mixtures of two important pollution tracers, caffeine (CAF) and carbamazepine (CBZ). An initial screening of the IL chemical structure was carried out, with extraction efficiencies of both tracers to the IL-rich phase ranging between 95 and 100%, obtained in a single-step. These systems were then optimized in order to simultaneously concentrate CAF and CBZ from water samples followed by HPLC-UV analysis, for which no interferences of the ABS phase-forming components and other interferents present in a wastewater effluent sample have been found. Based on the saturation solubility data of both pollution tracers in the IL-rich phase, the maximum estimated concentration factors of CAF and CBZ are 28595- and 8259-fold. IL-based ABS can be thus envisioned as effective pre-treatment techniques of environmentally-related aqueous samples for a more accurate monitoring of mixtures of pollution tracers. Copyright © 2017 Elsevier B.V. All rights reserved.
Statistical analysis of PM₁₀ concentrations at different locations in Malaysia.

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Sansuddin, Nurulilyana; Ramli, Nor Azam; Yahaya, Ahmad Shukri; Yusof, Noor Faizah Fitri Md; Ghazali, Nurul Adyani; Madhoun, Wesam Ahmed Al

2011-09-01

Malaysia has experienced several haze events since the 1980s as a consequence of the transboundary movement of air pollutants emitted from forest fires and open burning activities. Hazy episodes can result from local activities and be categorized as "localized haze". General probability distributions (i.e., gamma and log-normal) were chosen to analyze the PM(10) concentrations data at two different types of locations in Malaysia: industrial (Johor Bahru and Nilai) and residential (Kota Kinabalu and Kuantan). These areas were chosen based on their frequently high PM(10) concentration readings. The best models representing the areas were chosen based on their performance indicator values. The best distributions provided the probability of exceedances and the return period between the actual and predicted concentrations based on the threshold limit given by the Malaysian Ambient Air Quality Guidelines (24-h average of 150 μg/m(3)) for PM(10) concentrations. The short-term prediction for PM(10) exceedances in 14 days was obtained using the autoregressive model.
Reactive Transport Modeling Investigation of High Dissolved Sulfide Concentrations in Sedimentary Basin Rocks

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Xie, M.; Mayer, U. K.; MacQuarrie, K. T. B.

2017-12-01

Water with total dissolved sulfide in excess of 1 mmol L-1is widely found in groundwater at intermediate depths in sedimentary basins, including regions of the Michigan basin in southeastern Ontario, Canada. Conversely, at deeper and shallower depths, relatively low total dissolved sulfide concentrations have been reported. The mechanisms responsible for the occurrence of these brackish sulfide-containing waters are not fully understood. Anaerobic microbial sulfate reduction is a common process resulting in the formation of high sulfide concentrations. Sulfate reduction rates depend on many factors including the concentration of sulfate, the abundance of organic substances, redox conditions, temperature, salinity and the species of sulfate reducing bacteria (SRB). A sedimentary basin-specific conceptual model considering the effect of salinity on the rate of sulfate reduction was developed and implemented in the reactive transport model MIN3P-THCm. Generic 2D basin-scale simulations were undertaken to provide a potential explanation for the dissolved sulfide distribution observed in the Michigan basin. The model is 440 km in the horizontal dimension and 4 km in depth, and contains fourteen sedimentary rock units including shales, sandstones, limestones, dolostone and evaporites. The main processes considered are non-isothermal density dependent flow, kinetically-controlled mineral dissolution/precipitation and its feedback on hydraulic properties, cation exchange, redox reactions, biogenic sulfate reduction, and hydromechanical coupling due to glaciation-deglaciation events. Two scenarios were investigated focusing on conditions during an interglacial period and the transient evolution during a glaciation-deglaciation cycle. Inter-glaciation simulations illustrate that the presence of high salinity brines strongly suppress biogenic sulfate reduction. The transient simulations show that glaciation-deglaciation cycles can have an impact on the maximum depth of
A 2-D process-based model for suspended sediment dynamics: a first step towards ecological modeling

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Achete, F. M.; van der Wegen, M.; Roelvink, D.; Jaffe, B.

2015-06-01

In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.
A 2-D process-based model for suspended sediment dynamics: A first step towards ecological modeling

Science.gov (United States)

Achete, F. M.; van der Wegen, M.; Roelvink, D.; Jaffe, B.

2015-01-01

In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.
Deriving Total Suspended Matter Concentration from the Near-Infrared-Based Inherent Optical Properties over Turbid Waters: A Case Study in Lake Taihu

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Wei Shi

2018-02-01

Full Text Available Normalized water-leaving radiance spectra nLw(λ, particle backscattering coefficients bbp(λ in the near-infrared (NIR wavelengths, and total suspended matter (TSM concentrations over turbid waters are analytically correlated. To demonstrate the use of bbp(λ in the NIR wavelengths in coastal and inland waters, we used in situ optics and TSM data to develop two TSM algorithms from measurements of the Visible Infrared Imaging Radiometer Suite (VIIRS onboard the Suomi National Polar-orbiting Partnership (SNPP using backscattering coefficients at the two NIR bands bbp(745 and bbp(862 for Lake Taihu. The correlation coefficients between the modeled TSM concentrations from bbp(745 and bbp(862 and the in situ TSM are 0.93 and 0.92, respectively. A different in situ dataset acquired between 2012 and 2016 for Lake Taihu was used to validate the performance of the NIR TSM algorithms for VIIRS-SNPP observations. TSM concentrations derived from VIIRS-SNPP observations with these two NIR bbp(λ-based TSM algorithms matched well with in situ TSM concentrations in Lake Taihu between 2012 and 2016. The normalized root mean square errors (NRMSEs for the two NIR algorithms are 0.234 and 0.226, respectively. The two NIR-based TSM algorithms are used to compute the satellite-derived TSM concentrations to study the seasonal and interannual variability of the TSM concentration in Lake Taihu between 2012 and 2016. In fact, the NIR-based TSM algorithms are analytically based with minimal in situ data to tune the coefficients. They are not sensitive to the possible nLw(λ saturation in the visible bands for highly turbid waters, and have the potential to be used for estimation of TSM concentrations in turbid waters with similar NIR nLw(λ spectra as those in Lake Taihu.
Ethanol and ethyl glucuronide urine concentrations after ethanol-based hand antisepsis with and without permitted alcohol consumption.

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Gessner, Stephan; Below, Elke; Diedrich, Stephan; Wegner, Christian; Gessner, Wiebke; Kohlmann, Thomas; Heidecke, Claus-Dieter; Bockholdt, Britta; Kramer, Axel; Assadian, Ojan; Below, Harald

2016-09-01

During hand antisepsis, health care workers (HCWs) are exposed to alcohol by dermal contact and by inhalation. Concerns have been raised that high alcohol absorptions may adversely affect HCWs, particularly certain vulnerable individuals such as pregnant women or individuals with genetic deficiencies of aldehyde dehydrogenase. We investigated the kinetics of HCWs' urinary concentrations of ethanol and its metabolite ethyl glucuronide (EtG) during clinical work with and without previous consumption of alcoholic beverages by HCWs. The median ethanol concentration was 0.7 mg/L (interquartile range [IQR], 0.5-1.9 mg/L; maximum, 9.2 mg/L) during abstinence and 12.2 mg/L (IQR, 1.5-139.6 mg/L; maximum, 1,020.1 mg/L) during alcohol consumption. During abstinence, EtG reached concentrations of up to 958 ng/mL. When alcohol consumption was permitted, the median EtG concentration of all samples was 2,593 ng/mL (IQR, 890.8-3,576 ng/mL; maximum, 5,043 ng/mL). Although alcohol consumption was strongly correlated with both EtG and ethanol in urine, no significant correlation for the frequency of alcoholic hand antisepsis was observed in the linear mixed models. The use of ethanol-based handrub induces measurable ethanol and EtG concentrations in urine. Compared with consumption of alcoholic beverages or use of consumer products containing ethanol, the amount of ethanol absorption resulting from handrub applications is negligible. In practice, there is no evidence of any harmful effect of using ethanol-based handrubs as much as it is clinically necessary. Copyright © 2016 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
Air Pollution Modelling to Predict Maximum Ground Level Concentration for Dust from a Palm Oil Mill Stack

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Regina A. A.

2010-12-01

Full Text Available The study is to model emission from a stack to estimate ground level concentration from a palm oil mill. The case study is a mill located in Kuala Langat, Selangor. Emission source is from boilers stacks. The exercise determines the estimate the ground level concentrations for dust to the surrounding areas through the utilization of modelling software. The surround area is relatively flat, an industrial area surrounded by factories and with palm oil plantations in the outskirts. The model utilized in the study was to gauge the worst-case scenario. Ambient air concentrations were garnered calculate the increase to localized conditions. Keywords: emission, modelling, palm oil mill, particulate, POME
Testing seasonal and long-term controls of streamwater DOC using empirical and process-based models.

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Futter, Martyn N; de Wit, Heleen A

2008-12-15

Concentrations of dissolved organic carbon (DOC) in surface waters are increasing across Europe and parts of North America. Several mechanisms have been proposed to explain these increases including reductions in acid deposition, change in frequency of winter storms and changes in temperature and precipitation patterns. We used two modelling approaches to identify the mechanisms responsible for changing surface water DOC concentrations. Empirical regression analysis and INCA-C, a process-based model of stream-water DOC, were used to simulate long-term (1986--2003) patterns in stream water DOC concentrations in a small boreal stream. Both modelling approaches successfully simulated seasonal and inter-annual patterns in DOC concentration. In both models, seasonal patterns of DOC concentration were controlled by hydrology and inter-annual patterns were explained by climatic variation. There was a non-linear relationship between warmer summer temperatures and INCA-C predicted DOC. Only the empirical model was able to satisfactorily simulate the observed long-term increase in DOC. The observed long-term trends in DOC are likely to be driven by in-soil processes controlled by SO4(2-) and Cl(-) deposition, and to a lesser extent by temperature-controlled processes. Given the projected changes in climate and deposition, future modelling and experimental research should focus on the possible effects of soil temperature and moisture on organic carbon production, sorption and desorption rates, and chemical controls on organic matter solubility.
Augmented switching linear dynamical system model for gas concentration estimation with MOX sensors in an open sampling system.

Science.gov (United States)

Di Lello, Enrico; Trincavelli, Marco; Bruyninckx, Herman; De Laet, Tinne

2014-07-11

In this paper, we introduce a Bayesian time series model approach for gas concentration estimation using Metal Oxide (MOX) sensors in Open Sampling System (OSS). Our approach focuses on the compensation of the slow response of MOX sensors, while concurrently solving the problem of estimating the gas concentration in OSS. The proposed Augmented Switching Linear System model allows to include all the sources of uncertainty arising at each step of the problem in a single coherent probabilistic formulation. In particular, the problem of detecting on-line the current sensor dynamical regime and estimating the underlying gas concentration under environmental disturbances and noisy measurements is formulated and solved as a statistical inference problem. Our model improves, with respect to the state of the art, where system modeling approaches have been already introduced, but only provided an indirect relative measures proportional to the gas concentration and the problem of modeling uncertainty was ignored. Our approach is validated experimentally and the performances in terms of speed of and quality of the gas concentration estimation are compared with the ones obtained using a photo-ionization detector.
CFD Modeling of Flow, Temperature, and Concentration Fields in a Pilot-Scale Rotary Hearth Furnace

Science.gov (United States)

Liu, Ying; Su, Fu-Yong; Wen, Zhi; Li, Zhi; Yong, Hai-Quan; Feng, Xiao-Hong

2014-01-01

A three-dimensional mathematical model for simulation of flow, temperature, and concentration fields in a pilot-scale rotary hearth furnace (RHF) has been developed using a commercial computational fluid dynamics software, FLUENT. The layer of composite pellets under the hearth is assumed to be a porous media layer with CO source and energy sink calculated by an independent mathematical model. User-defined functions are developed and linked to FLUENT to process the reduction process of the layer of composite pellets. The standard k-ɛ turbulence model in combination with standard wall functions is used for modeling of gas flow. Turbulence-chemistry interaction is taken into account through the eddy-dissipation model. The discrete ordinates model is used for modeling of radiative heat transfer. A comparison is made between the predictions of the present model and the data from a test of the pilot-scale RHF, and a reasonable agreement is found. Finally, flow field, temperature, and CO concentration fields in the furnace are investigated by the model.

An analytical model for solute transport through a GCL-based two-layered liner considering biodegradation

Energy Technology Data Exchange (ETDEWEB)

Guan, C. [Institute of Hydrology and Water Resources Engineering, Zhejiang University, Hangzhou 310058 (China); Xie, H.J., E-mail: xiehaijian@zju.edu.cn [Institute of Hydrology and Water Resources Engineering, Zhejiang University, Hangzhou 310058 (China); MOE Key Laboratory of Soft Soils and Geoenvironmental Engineering, Zhejiang University, Hangzhou 310058 (China); Wang, Y.Z.; Chen, Y.M.; Jiang, Y.S.; Tang, X.W. [MOE Key Laboratory of Soft Soils and Geoenvironmental Engineering, Zhejiang University, Hangzhou 310058 (China)

2014-01-01

An analytical model for solute advection and dispersion in a two-layered liner consisting of a geosynthetic clay liner (GCL) and a soil liner (SL) considering the effect of biodegradation was proposed. The analytical solution was derived by Laplace transformation and was validated over a range of parameters using the finite-layer method based software Pollute v7.0. Results show that if the half-life of the solute in GCL is larger than 1 year, the degradation in GCL can be neglected for solute transport in GCL/SL. When the half-life of GCL is less than 1 year, neglecting the effect of degradation in GCL on solute migration will result in a large difference of relative base concentration of GCL/SL (e.g., 32% for the case with half-life of 0.01 year). The 100-year solute base concentration can be reduced by a factor of 2.2 when the hydraulic conductivity of the SL was reduced by an order of magnitude. The 100-year base concentration was reduced by a factor of 155 when the half life of the contaminant in the SL was reduced by an order of magnitude. The effect of degradation is more important in approving the groundwater protection level than the hydraulic conductivity. The analytical solution can be used for experimental data fitting, verification of complicated numerical models and preliminary design of landfill liner systems. - Highlights: •Degradation of contaminants was considered in modeling solute transport in GCL/SL. •Analytical solutions were derived for assessment of GCL/SL with degradation. •Degradation in GCL can be ignored as half-life is larger than 1 year. •Base concentration is more sensitive to half-life of SL than to permeability of SL.
An analytical model for solute transport through a GCL-based two-layered liner considering biodegradation

International Nuclear Information System (INIS)

Guan, C.; Xie, H.J.; Wang, Y.Z.; Chen, Y.M.; Jiang, Y.S.; Tang, X.W.

2014-01-01

An analytical model for solute advection and dispersion in a two-layered liner consisting of a geosynthetic clay liner (GCL) and a soil liner (SL) considering the effect of biodegradation was proposed. The analytical solution was derived by Laplace transformation and was validated over a range of parameters using the finite-layer method based software Pollute v7.0. Results show that if the half-life of the solute in GCL is larger than 1 year, the degradation in GCL can be neglected for solute transport in GCL/SL. When the half-life of GCL is less than 1 year, neglecting the effect of degradation in GCL on solute migration will result in a large difference of relative base concentration of GCL/SL (e.g., 32% for the case with half-life of 0.01 year). The 100-year solute base concentration can be reduced by a factor of 2.2 when the hydraulic conductivity of the SL was reduced by an order of magnitude. The 100-year base concentration was reduced by a factor of 155 when the half life of the contaminant in the SL was reduced by an order of magnitude. The effect of degradation is more important in approving the groundwater protection level than the hydraulic conductivity. The analytical solution can be used for experimental data fitting, verification of complicated numerical models and preliminary design of landfill liner systems. - Highlights: •Degradation of contaminants was considered in modeling solute transport in GCL/SL. •Analytical solutions were derived for assessment of GCL/SL with degradation. •Degradation in GCL can be ignored as half-life is larger than 1 year. •Base concentration is more sensitive to half-life of SL than to permeability of SL
Experimental determination and modelling of interface area concentration in horizontal stratified flow

International Nuclear Information System (INIS)

Junqua-Moullet, Alexandra

2003-01-01

This research thesis concerns the modelling and experimentation of biphasic liquid/gas flows (water/air) while using the two-fluid model, a six-equation model. The author first addresses the modelling of interfacial magnitudes for a known topology (problem of two-fluid model closure, closure relationships for some variables, equation for a given configuration). She reports the development of an equation system for interfacial magnitudes. The next parts deal with experiments and report the study of stratified flows in the THALC experiment, and more particularly the study of the interfacial area concentration and of the liquid velocities in such flows. Results are discussed, as well as their consistency
Physiologically Based Pharmacokinetic and Absorption Modeling for Osmotic Pump Products.

Science.gov (United States)

Ni, Zhanglin; Talattof, Arjang; Fan, Jianghong; Tsakalozou, Eleftheria; Sharan, Satish; Sun, Dajun; Wen, Hong; Zhao, Liang; Zhang, Xinyuan

2017-07-01

Physiologically based pharmacokinetic (PBPK) and absorption modeling approaches were employed for oral extended-release (ER) drug products based on an osmotic drug delivery system (osmotic pumps). The purpose was to systemically evaluate the in vivo relevance of in vitro dissolution for this type of formulation. As expected, in vitro dissolution appeared to be generally predictive of in vivo PK profiles, because of the unique feature of this delivery system that the in vitro and in vivo release of osmotic pump drug products is less susceptible to surrounding environment in the gastrointestinal (GI) tract such as pH, hydrodynamic, and food effects. The present study considered BCS (Biopharmaceutics Classification System) class 1, 2, and 3 drug products with half-lives ranging from 2 to greater than 24 h. In some cases, the colonic absorption models needed to be adjusted to account for absorption in the colon. C max (maximum plasma concentration) and AUCt (area under the concentration curve) of the studied drug products were sensitive to changes in colon permeability and segmental GI transit times in a drug product-dependent manner. While improvement of the methodology is still warranted for more precise prediction (e.g., colonic absorption and dynamic movement in the GI tract), the results from the present study further emphasized the advantage of using PBPK modeling in addressing product-specific questions arising from regulatory review and drug development.
Digital Image Analysis of Yeast Single Cells Growing in Two Different Oxygen Concentrations to Analyze the Population Growth and to Assist Individual-Based Modeling.

Science.gov (United States)

Ginovart, Marta; Carbó, Rosa; Blanco, Mónica; Portell, Xavier

2017-01-01

Nowadays control of the growth of Saccharomyces to obtain biomass or cellular wall components is crucial for specific industrial applications. The general aim of this contribution is to deal with experimental data obtained from yeast cells and from yeast cultures to attempt the integration of the two levels of information, individual and population, to progress in the control of yeast biotechnological processes by means of the overall analysis of this set of experimental data, and to assist in the improvement of an individual-based model, namely, INDISIM- Saccha . Populations of S. cerevisiae growing in liquid batch culture, in aerobic and microaerophilic conditions, were studied. A set of digital images was taken during the population growth, and a protocol for the treatment and analyses of the images obtained was established. The piecewise linear model of Buchanan was adjusted to the temporal evolutions of the yeast populations to determine the kinetic parameters and changes of growth phases. In parallel, for all the yeast cells analyzed, values of direct morphological parameters, such as area, perimeter, major diameter, minor diameter, and derived ones, such as circularity and elongation, were obtained. Graphical and numerical methods from descriptive statistics were applied to these data to characterize the growth phases and the budding state of the yeast cells in both experimental conditions, and inferential statistical methods were used to compare the diverse groups of data achieved. Oxidative metabolism of yeast in a medium with oxygen available and low initial sugar concentration can be taken into account in order to obtain a greater number of cells or larger cells. Morphological parameters were analyzed statistically to identify which were the most useful for the discrimination of the different states, according to budding and/or growth phase, in aerobic and microaerophilic conditions. The use of the experimental data for subsequent modeling work was then
Development of system on predicting uranium concentration from pregnant solution

International Nuclear Information System (INIS)

Yi Weiping

2004-01-01

Uranium concentration from pregnant solution is primary index of process for in-situ leaching of uranium, and the suitable method with which to predicate this index and effective means to solve it with were continuously studied hard. SPUC-system on predicting uranium concentration based on GM model of gray system theory is developed, and the mathematical model, constitution, function and theory foundation of this system are introduced. (authors)
Model-based experimental design for assessing effects of mixtures of chemicals

Energy Technology Data Exchange (ETDEWEB)

Baas, Jan, E-mail: jan.baas@falw.vu.n [Vrije Universiteit of Amsterdam, Dept of Theoretical Biology, De Boelelaan 1085, 1081 HV Amsterdam (Netherlands); Stefanowicz, Anna M., E-mail: anna.stefanowicz@uj.edu.p [Institute of Environmental Sciences, Jagiellonian University, Gronostajowa 7, 30-387 Krakow (Poland); Klimek, Beata, E-mail: beata.klimek@uj.edu.p [Institute of Environmental Sciences, Jagiellonian University, Gronostajowa 7, 30-387 Krakow (Poland); Laskowski, Ryszard, E-mail: ryszard.laskowski@uj.edu.p [Institute of Environmental Sciences, Jagiellonian University, Gronostajowa 7, 30-387 Krakow (Poland); Kooijman, Sebastiaan A.L.M., E-mail: bas@bio.vu.n [Vrije Universiteit of Amsterdam, Dept of Theoretical Biology, De Boelelaan 1085, 1081 HV Amsterdam (Netherlands)

2010-01-15

We exposed flour beetles (Tribolium castaneum) to a mixture of four poly aromatic hydrocarbons (PAHs). The experimental setup was chosen such that the emphasis was on assessing partial effects. We interpreted the effects of the mixture by a process-based model, with a threshold concentration for effects on survival. The behavior of the threshold concentration was one of the key features of this research. We showed that the threshold concentration is shared by toxicants with the same mode of action, which gives a mechanistic explanation for the observation that toxic effects in mixtures may occur in concentration ranges where the individual components do not show effects. Our approach gives reliable predictions of partial effects on survival and allows for a reduction of experimental effort in assessing effects of mixtures, extrapolations to other mixtures, other points in time, or in a wider perspective to other organisms. - We show a mechanistic approach to assess effects of mixtures in low concentrations.
Model-based experimental design for assessing effects of mixtures of chemicals

International Nuclear Information System (INIS)

Baas, Jan; Stefanowicz, Anna M.; Klimek, Beata; Laskowski, Ryszard; Kooijman, Sebastiaan A.L.M.

2010-01-01

We exposed flour beetles (Tribolium castaneum) to a mixture of four poly aromatic hydrocarbons (PAHs). The experimental setup was chosen such that the emphasis was on assessing partial effects. We interpreted the effects of the mixture by a process-based model, with a threshold concentration for effects on survival. The behavior of the threshold concentration was one of the key features of this research. We showed that the threshold concentration is shared by toxicants with the same mode of action, which gives a mechanistic explanation for the observation that toxic effects in mixtures may occur in concentration ranges where the individual components do not show effects. Our approach gives reliable predictions of partial effects on survival and allows for a reduction of experimental effort in assessing effects of mixtures, extrapolations to other mixtures, other points in time, or in a wider perspective to other organisms. - We show a mechanistic approach to assess effects of mixtures in low concentrations.
Simulation And Forecasting of Daily Pm10 Concentrations Using Autoregressive Models In Kagithane Creek Valley, Istanbul

Science.gov (United States)

Ağaç, Kübra; Koçak, Kasım; Deniz, Ali

2015-04-01

A time series approach using autoregressive model (AR), moving average model (MA) and seasonal autoregressive integrated moving average model (SARIMA) were used in this study to simulate and forecast daily PM10 concentrations in Kagithane Creek Valley, Istanbul. Hourly PM10 concentrations have been measured in Kagithane Creek Valley between 2010 and 2014 periods. Bosphorus divides the city in two parts as European and Asian parts. The historical part of the city takes place in Golden Horn. Our study area Kagithane Creek Valley is connected with this historical part. The study area is highly polluted because of its topographical structure and industrial activities. Also population density is extremely high in this site. The dispersion conditions are highly poor in this creek valley so it is necessary to calculate PM10 levels for air quality and human health. For given period there were some missing PM10 concentration values so to make an accurate calculations and to obtain exact results gap filling method was applied by Singular Spectrum Analysis (SSA). SSA is a new and efficient method for gap filling and it is an state-of-art modeling. SSA-MTM Toolkit was used for our study. SSA is considered as a noise reduction algorithm because it decomposes an original time series to trend (if exists), oscillatory and noise components by way of a singular value decomposition. The basic SSA algorithm has stages of decomposition and reconstruction. For given period daily and monthly PM10 concentrations were calculated and episodic periods are determined. Long term and short term PM10 concentrations were analyzed according to European Union (EU) standards. For simulation and forecasting of high level PM10 concentrations, meteorological data (wind speed, pressure and temperature) were used to see the relationship between daily PM10 concentrations. Fast Fourier Transformation (FFT) was also applied to the data to see the periodicity and according to these periods models were built
Dynamical coupling of PBPK/PD and AUC-based toxicity models for arsenic in tilapia Oreochromis mossambicus from blackfoot disease area in Taiwan

International Nuclear Information System (INIS)

Liao, C.-M.; Liang, H.-M.; Chen, B.-C.; Singh Sher; Tsai, J.-W.; Chou, Y.-H.; Lin, W.-T.

2005-01-01

A physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models were developed for arsenic (As) in tilapia Oreochromis mossambicus from blackfoot disease area in Taiwan. The PBPK/PD model structure consisted of muscle, gill, gut wall, alimentary canal, and liver, which were interconnected by blood circulation. We integrate the target organ concentrations and dynamic response describing uptake, metabolism, and disposition of As and the associated area-under-curve (AUC)-based toxicological dynamics following an acute exposure. The model validations were compared against the field observations from real tilapia farms and previously published uptake/depuration experimental data, indicating that predicted and measured As concentrations in major organs of tilapia were in good agreement. The model was utilized to reasonably simulate and construct a dose-dependent dynamic response between mortality effect and equilibrium target organ concentrations. Model simulations suggest that tilapia gills may serve as a surrogate sensitive biomarker of short-term exposure to As. This integrated As PBPK/PD/AUC model quantitatively estimates target organ concentration and dynamic response in tilapia and is a strong framework for future waterborne metal model development and for refining a biologically-based risk assessment for exposure of aquatic species to waterborne metals under a variety of scenarios. - Integrated toxicity models can identify dynamic responses of fish to arsenic
Dynamical coupling of PBPK/PD and AUC-based toxicity models for arsenic in tilapia Oreochromis mossambicus from blackfoot disease area in Taiwan

Energy Technology Data Exchange (ETDEWEB)

Liao, C.-M. [Ecotoxicological Modeling Center, Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan 10617 (China)]. E-mail: cmliao@ntu.edu.tw; Liang, H.-M. [Ecotoxicological Modeling Center, Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan 10617 (China); Chen, B.-C. [Department of Post-Modern Agriculture, Mingdao University, Changhua, Taiwan 52345 (China); Singh Sher [Center of Genomics Medicine, School of Medicine, National Taiwan University, Taipei, Taiwan 10617 (China); Tsai, J.-W. [Ecotoxicological Modeling Center, Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan 10617 (China); Chou, Y.-H. [Ecotoxicological Modeling Center, Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan 10617 (China); Lin, W.-T. [Environment Change Research Center, Academia Sinica, Nankang, Taipei, Taiwan 11517 (China)

2005-05-01

A physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models were developed for arsenic (As) in tilapia Oreochromis mossambicus from blackfoot disease area in Taiwan. The PBPK/PD model structure consisted of muscle, gill, gut wall, alimentary canal, and liver, which were interconnected by blood circulation. We integrate the target organ concentrations and dynamic response describing uptake, metabolism, and disposition of As and the associated area-under-curve (AUC)-based toxicological dynamics following an acute exposure. The model validations were compared against the field observations from real tilapia farms and previously published uptake/depuration experimental data, indicating that predicted and measured As concentrations in major organs of tilapia were in good agreement. The model was utilized to reasonably simulate and construct a dose-dependent dynamic response between mortality effect and equilibrium target organ concentrations. Model simulations suggest that tilapia gills may serve as a surrogate sensitive biomarker of short-term exposure to As. This integrated As PBPK/PD/AUC model quantitatively estimates target organ concentration and dynamic response in tilapia and is a strong framework for future waterborne metal model development and for refining a biologically-based risk assessment for exposure of aquatic species to waterborne metals under a variety of scenarios. - Integrated toxicity models can identify dynamic responses of fish to arsenic.
Development of Fresnel-based Concentrated Photovoltaic (CPV System with Uniform Irradiance

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Irfan Ullah

2014-12-01

Full Text Available Different designs have been presented to achieve high concentration and uniformity for the concentrated photovoltaic (CPV system. Most of the designs have issues of low efficiency in terms of irradiance uniformity. To this end, we present a design methodology to increase irradiance uniformity over solar cell. The system consists of an eight-fold Fresnel lens as a primary optical element (POE and an optical lens, which consists of eight parts, as a secondary optical element (SOE. Sunlight is focused through the POE and then light is spread over cell through the SOE. In the design, maximum sunlight is passed over cell by minimizing losses. Results have shown that the proposed CPV design gives good irradiance uniformity. The concentration module based on this novel design is a promising option for the development of a cost-effective photovoltaic solar energy generation.
The future distribution of the savannah biome: model-based and biogeographic contingency.

Science.gov (United States)

Moncrieff, Glenn R; Scheiter, Simon; Langan, Liam; Trabucco, Antonio; Higgins, Steven I

2016-09-19

The extent of the savannah biome is expected to be profoundly altered by climatic change and increasing atmospheric CO2 concentrations. Contrasting projections are given when using different modelling approaches to estimate future distributions. Furthermore, biogeographic variation within savannahs in plant function and structure is expected to lead to divergent responses to global change. Hence the use of a single model with a single savannah tree type will likely lead to biased projections. Here we compare and contrast projections of South American, African and Australian savannah distributions from the physiologically based Thornley transport resistance statistical distribution model (TTR-SDM)-and three versions of a dynamic vegetation model (DVM) designed and parametrized separately for specific continents. We show that attempting to extrapolate any continent-specific model globally biases projections. By 2070, all DVMs generally project a decrease in the extent of savannahs at their boundary with forests, whereas the TTR-SDM projects a decrease in savannahs at their boundary with aridlands and grasslands. This difference is driven by forest and woodland expansion in response to rising atmospheric CO2 concentrations in DVMs, unaccounted for by the TTR-SDM. We suggest that the most suitable models of the savannah biome for future development are individual-based dynamic vegetation models designed for specific biogeographic regions.This article is part of the themed issue 'Tropical grassy biomes: linking ecology, human use and conservation'. © 2016 The Author(s).
Modeling of the pyruvate production with Escherichia coli: comparison of mechanistic and neural networks-based models.

Science.gov (United States)

Zelić, B; Bolf, N; Vasić-Racki, D

2006-06-01

Three different models: the unstructured mechanistic black-box model, the input-output neural network-based model and the externally recurrent neural network model were used to describe the pyruvate production process from glucose and acetate using the genetically modified Escherichia coli YYC202 ldhA::Kan strain. The experimental data were used from the recently described batch and fed-batch experiments [ Zelić B, Study of the process development for Escherichia coli-based pyruvate production. PhD Thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, Zagreb, Croatia, July 2003. (In English); Zelić et al. Bioproc Biosyst Eng 26:249-258 (2004); Zelić et al. Eng Life Sci 3:299-305 (2003); Zelić et al Biotechnol Bioeng 85:638-646 (2004)]. The neural networks were built out of the experimental data obtained in the fed-batch pyruvate production experiments with the constant glucose feed rate. The model validation was performed using the experimental results obtained from the batch and fed-batch pyruvate production experiments with the constant acetate feed rate. Dynamics of the substrate and product concentration changes was estimated using two neural network-based models for biomass and pyruvate. It was shown that neural networks could be used for the modeling of complex microbial fermentation processes, even in conditions in which mechanistic unstructured models cannot be applied.
Estimation of Alcohol Concentration of Red Wine Based on Cole-Cole Plot

Science.gov (United States)

Watanabe, Kota; Taka, Yoshinori; Fujiwara, Osamu

To evaluate the quality of wine, we previously measured the complex relative permittivity of wine in the frequency range from 10 MHz to 6 GHz with a network analyzer, and suggested a possibility that the maturity and alcohol concentration of wine can simultaneously be estimated from the Cole-Cole plot. Although the absolute accuracy has not been examined yet, this method will enable one to estimate the alcohol concentration of alcoholic beverages without any distillation equipment simply. In this study, to investigate the estimation accuracy of the alcohol concentration of wine by its Cole-Cole plots, we measured the complex relative permittivity of pure water and diluted ethanol solution from 100 MHz to 40 GHz, and obtained the dependence of the Cole-Cole plot parameters on alcohol concentration and temperature. By using these results as calibration data, we estimated the alcohol concentration of red wine from the Cole-Cole plots, which was compared with the measured one based on a distillation method. As a result, we have confirmed that the estimated alcohol concentration of red wine agrees with the measured results in an absolute error by less than 1 %.
Size distribution and concentrations of heavy metals in atmospheric aerosols originating from industrial emissions as predicted by the HYSPLIT model

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Chen, Bing; Stein, Ariel F.; Maldonado, Pabla Guerrero; Sanchez de la Campa, Ana M.; Gonzalez-Castanedo, Yolanda; Castell, Nuria; de la Rosa, Jesus D.

2013-06-01

This study presents a description of the emission, transport, dispersion, and deposition of heavy metals contained in atmospheric aerosols emitted from a large industrial complex in southern Spain using the HYSPLIT model coupled with high- (MM5) and low-resolution (GDAS) meteorological simulations. The dispersion model was configured to simulate eight size fractions (17 μm) of metals based on direct measurements taken at the industrial emission stacks. Twelve stacks in four plants were studied and the stacks showed considerable differences for both emission fluxes and size ranges of metals. We model the dispersion of six major metals; Cr, Co, Ni, La, Zn, and Mo, which represent 77% of the total mass of the 43 measured elements. The prediction shows that the modeled industrial emissions produce an enrichment of heavy metals by a factor of 2-5 for local receptor sites when compared to urban and rural background areas in Spain. The HYSPLIT predictions based on the meteorological fields from MM5 show reasonable consistence with the temporal evolution of concentrations of Cr, Co, and Ni observed at three sites downwind of the industrial area. The magnitude of concentrations of metals at two receptors was underestimated for both MM5 (by a factor of 2-3) and GDAS (by a factor of 4-5) meteorological runs. The model prediction shows that heavy metal pollution from industrial emissions in this area is dominated by the ultra-fine (<0.66 μm) and fine (<2.5 μm) size fractions.
A Study on Pharmacokinetics of Bosentan with Systems Modeling, Part 1: Translating Systemic Plasma Concentration to Liver Exposure in Healthy Subjects.

Science.gov (United States)

Li, Rui; Niosi, Mark; Johnson, Nathaniel; Tess, David A; Kimoto, Emi; Lin, Jian; Yang, Xin; Riccardi, Keith A; Ryu, Sangwoo; El-Kattan, Ayman F; Maurer, Tristan S; Tremaine, Larry M; Di, Li

2018-04-01

Understanding liver exposure of hepatic transporter substrates in clinical studies is often critical, as it typically governs pharmacodynamics, drug-drug interactions, and toxicity for certain drugs. However, this is a challenging task since there is currently no easy method to directly measure drug concentration in the human liver. Using bosentan as an example, we demonstrate a new approach to estimate liver exposure based on observed systemic pharmacokinetics from clinical studies using physiologically based pharmacokinetic modeling. The prediction was verified to be both accurate and precise using sensitivity analysis. For bosentan, the predicted pseudo steady-state unbound liver-to-unbound systemic plasma concentration ratio was 34.9 (95% confidence interval: 4.2, 50). Drug-drug interaction (i.e., CYP3A and CYP2B6 induction) and inhibition of hepatic transporters (i.e., bile salt export pump, multidrug resistance-associated proteins, and sodium-taurocholate cotransporting polypeptide) were predicted based on the estimated unbound liver tissue or plasma concentrations. With further validation and refinement, we conclude that this approach may serve to predict human liver exposure and complement other methods involving tissue biopsy and imaging. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.
Mathematical Model to Predict Skin Concentration after Topical Application of Drugs

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Hiroaki Todo

2013-12-01

Full Text Available Skin permeation experiments have been broadly done since 1970s to 1980s as an evaluation method for transdermal drug delivery systems. In topically applied drug and cosmetic formulations, skin concentration of chemical compounds is more important than their skin permeations, because primary target site of the chemical compounds is skin surface or skin tissues. Furthermore, the direct pharmacological reaction of a metabolically stable drug that binds with specific receptors of known expression levels in an organ can be determined by Hill’s equation. Nevertheless, little investigation was carried out on the test method of skin concentration after topically application of chemical compounds. Recently we investigated an estimating method of skin concentration of the chemical compounds from their skin permeation profiles. In the study, we took care of “3Rs” issues for animal experiments. We have proposed an equation which was capable to estimate animal skin concentration from permeation profile through the artificial membrane (silicone membrane and animal skin. This new approach may allow the skin concentration of a drug to be predicted using Fick’s second law of diffusion. The silicone membrane was found to be useful as an alternative membrane to animal skin for predicting skin concentration of chemical compounds, because an extremely excellent extrapolation to animal skin concentration was attained by calculation using the silicone membrane permeation data. In this chapter, we aimed to establish an accurate and convenient method for predicting the concentration profiles of drugs in the skin based on the skin permeation parameters of topically active drugs derived from steady-state skin permeation experiments.
Sedimentology models from activity concentration measurements: application to the 'Bay of Cadiz' Natural Park (SW Spain)

International Nuclear Information System (INIS)

Ligero, R.A.; Vidal, J.; Melendez, M.J.; Hamani, M.; Casas-Ruiz, M.

2009-01-01

A previous study on seabed sediments of the Bay of Cadiz (SW of Spain) enabled us to identify several relations between sedimentological variables and activity concentrations of environmental radionuclides such as 137 Cs, 226 Ra, 232 Th and 40 K. In this paper the study has been extended to a large neighbouring inter-tidal area in order to establish if the above mentioned models can be generalized. As a result we have determined that the measured activity concentrations are closely to the values predicted by the theoretical models (correlation coefficient range = 0.85-0.93). Furthermore, the proposal model for granulometric facies as a function of activity concentrations of the abovementioned radionuclides provides for the sediments distribution a representation which agrees with the values of the tidal energy distribution obtained using numeric models calibrated with experimental data from current meters and water level recorders
Improved daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed.

Science.gov (United States)

Grimm, J W; Lynch, J A

2005-06-01

Daily precipitation nitrate and ammonium concentration models were developed for the Chesapeake Bay Watershed (USA) using a linear least-squares regression approach and precipitation chemistry data from 29 National Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites. Only weekly samples that comprised a single precipitation event were used in model development. The most significant variables in both ammonium and nitrate models included: precipitation volume, the number of days since the last event, a measure of seasonality, latitude, and the proportion of land within 8km covered by forest or devoted to industry and transportation. Additional variables included in the nitrate model were the proportion of land within 0.8km covered by water and/or forest. Local and regional ammonia and nitrogen oxide emissions were not as well correlated as land cover. Modeled concentrations compared very well with event chemistry data collected at six NADP/AirMoN sites within the Chesapeake Bay Watershed. Wet deposition estimates were also consistent with observed deposition at selected sites. Accurately describing the spatial distribution of precipitation volume throughout the watershed is important in providing critical estimates of wet-fall deposition of ammonium and nitrate.

Thermodynamic and kinetic modelling of the reduction of concentrated nitric acid

International Nuclear Information System (INIS)

Sicsic, David

2011-01-01

This research thesis aimed at determining and quantifying the different stages of the reduction mechanism in the case of concentrated nitric acid. After having reported the results of a bibliographical study on the chemical and electrochemical behaviour of concentrated nitric media (generalities, chemical equilibriums, NOx reactivity, electrochemical reduction of nitric acid), the author reports the development and discusses the results of a thermodynamic simulation of a nitric environment at 25 C. This allowed the main species to be identified in the liquid and gaseous phases of nitric acid solutions. The author reports an experimental electrochemical investigation coupled with analytic techniques (infrared and UV-visible spectroscopy) and shows that the reduction process depends on the cathodic overvoltage, and identifies three potential areas. A kinetic modelling of the stationary state and of the impedance is then developed in order to better determine, discuss and quantify the reduction process. The application of this kinetic model to the preliminary results of an electrochemical study performed on 304 L steel is then discussed [fr
Analyzing the capacity of the Daphnia magna and Pseudokirchneriella subcapitata bioavailability models to predict chronic zinc toxicity at high pH and low calcium concentrations and formulation of a generalized bioavailability model for D. magna.

Science.gov (United States)

Van Regenmortel, Tina; Berteloot, Olivier; Janssen, Colin R; De Schamphelaere, Karel A C

2017-10-01

Risk assessment in the European Union implements Zn bioavailability models to derive predicted-no-effect concentrations for Zn. These models are validated within certain boundaries (i.e., pH ≤ 8 and Ca concentrations ≥ 5mg/L), but a substantial fraction of the European surface waters falls outside these boundaries. Therefore, we evaluated whether the chronic Zn biotic ligand model (BLM) for Daphnia magna and the chronic bioavailability model for Pseudokirchneriella subcapitata could be extrapolated to pH > 8 and Ca concentrations model can accurately predict Zn toxicity for Ca concentrations down to 0.8 mg/L and pH values up to 8.5. Because the chronic Zn BLM for D. magna could not be extrapolated beyond its validity boundaries for pH, a generalized bioavailability model (gBAM) was developed. Of 4 gBAMs developed, we recommend the use of gBAM-D, which combines a log-linear relation between the 21-d median effective concentrations (expressed as free Zn 2+ ion activity) and pH, with more conventional BLM-type competition constants for Na, Ca, and Mg. This model is a first step in further improving the accuracy of chronic toxicity predictions of Zn as a function of water chemistry, which can decrease the uncertainty in implementing the bioavailability-based predicted-no-effect concentration in the risk assessment of high-pH and low-Ca concentration regions in Europe. Environ Toxicol Chem 2017;36:2781-2798. © 2017 SETAC. © 2017 SETAC.
A Process-Based Model of TCA Cycle Functioning to Analyze Citrate Accumulation in Pre- and Post-Harvest Fruits.

Directory of Open Access Journals (Sweden)

Audrey Etienne

Full Text Available Citrate is one of the most important organic acids in many fruits and its concentration plays a critical role in organoleptic properties. The regulation of citrate accumulation throughout fruit development, and the origins of the phenotypic variability of the citrate concentration within fruit species remain to be clarified. In the present study, we developed a process-based model of citrate accumulation based on a simplified representation of the TCA cycle to predict citrate concentration in fruit pulp during the pre- and post-harvest stages. Banana fruit was taken as a reference because it has the particularity of having post-harvest ripening, during which citrate concentration undergoes substantial changes. The model was calibrated and validated on the two stages, using data sets from three contrasting cultivars in terms of citrate accumulation, and incorporated different fruit load, potassium supply, and harvest dates. The model predicted the pre and post-harvest dynamics of citrate concentration with fairly good accuracy for the three cultivars. The model suggested major differences in TCA cycle functioning among cultivars during post-harvest ripening of banana, and pointed to a potential role for NAD-malic enzyme and mitochondrial malate carriers in the genotypic variability of citrate concentration. The sensitivity of citrate accumulation to growth parameters and temperature differed among cultivars during post-harvest ripening. Finally, the model can be used as a conceptual basis to study citrate accumulation in fleshy fruits and may be a powerful tool to improve our understanding of fruit acidity.
A comparative Thermal Analysis of conventional parabolic receiver tube and Cavity model tube in a Solar Parabolic Concentrator

Science.gov (United States)

Arumugam, S.; Ramakrishna, P.; Sangavi, S.

2018-02-01

Improvements in heating technology with solar energy is gaining focus, especially solar parabolic collectors. Solar heating in conventional parabolic collectors is done with the help of radiation concentration on receiver tubes. Conventional receiver tubes are open to atmosphere and loose heat by ambient air currents. In order to reduce the convection losses and also to improve the aperture area, we designed a tube with cavity. This study is a comparative performance behaviour of conventional tube and cavity model tube. The performance formulae were derived for the cavity model based on conventional model. Reduction in overall heat loss coefficient was observed for cavity model, though collector heat removal factor and collector efficiency were nearly same for both models. Improvement in efficiency was also observed in the cavity model’s performance. The approach towards the design of a cavity model tube as the receiver tube in solar parabolic collectors gave improved results and proved as a good consideration.
Multi-objective decision-making model based on CBM for an aircraft fleet

Science.gov (United States)

Luo, Bin; Lin, Lin

2018-04-01

Modern production management patterns, in which multi-unit (e.g., a fleet of aircrafts) are managed in a holistic manner, have brought new challenges for multi-unit maintenance decision making. To schedule a good maintenance plan, not only does the individual machine maintenance have to be considered, but also the maintenance of the other individuals have to be taken into account. Since most condition-based maintenance researches for aircraft focused on solely reducing maintenance cost or maximizing the availability of single aircraft, as well as considering that seldom researches concentrated on both the two objectives: minimizing cost and maximizing the availability of a fleet (total number of available aircraft in fleet), a multi-objective decision-making model based on condition-based maintenance concentrated both on the above two objectives is established. Furthermore, in consideration of the decision maker may prefer providing the final optimal result in the form of discrete intervals instead of a set of points (non-dominated solutions) in real decision-making problem, a novel multi-objective optimization method based on support vector regression is proposed to solve the above multi-objective decision-making model. Finally, a case study regarding a fleet is conducted, with the results proving that the approach efficiently generates outcomes that meet the schedule requirements.
Modelling the impact of room temperature on concentrations of polychlorinated biphenyls (PCBs) in indoor air

DEFF Research Database (Denmark)

Lyng, Nadja; Clausen, Per Axel; Lundsgaard, Claus

2016-01-01

tested on field data from a PCB remediation case in an apartment in another contaminated building complex where PCB concentrations and temperature were measured simultaneously and regularly throughout one year. The model fitted relatively well with the regression of measured PCB air concentrations, ln...
Activity Prediction of Schiff Base Compounds using Improved QSAR Models of Cinnamaldehyde Analogues and Derivatives

Directory of Open Access Journals (Sweden)

Hui Wang

2015-10-01

Full Text Available In past work, QSAR (quantitative structure-activity relationship models of cinnamaldehyde analogues and derivatives (CADs have been used to predict the activities of new chemicals based on their mass concentrations, but these approaches are not without shortcomings. Therefore, molar concentrations were used instead of mass concentrations to determine antifungal activity. New QSAR models of CADs against Aspergillus niger and Penicillium citrinum were established, and the molecular design of new CADs was performed. The antifungal properties of the designed CADs were tested, and the experimental Log AR values were in agreement with the predicted Log AR values. The results indicate that the improved QSAR models are more reliable and can be effectively used for CADs molecular design and prediction of the activity of CADs. These findings provide new insight into the development and utilization of cinnamaldehyde compounds.
Spectral filtering modulation method for estimation of hemoglobin concentration and oxygenation based on a single fluorescence emission spectrum in tissue phantoms.

Science.gov (United States)

Liu, Quan; Vo-Dinh, Tuan

2009-10-01

to the scattering property of the tissue model for the chosen probe geometry. A simple two-step ratiometric method based on the SFM of fluorescence spectra is proposed to estimate the total hemoglobin concentration and oxygenation in a tissue model using only a single fluorescence emission spectrum. This method is immune to the variation in system throughput caused by inconsistent optical coupling because of its ratiometric nature. Calibration curves are insensitive to the scattering coefficient for the chosen probe geometry. Moreover, since only fluorescence intensities at a few wavelengths in a single fluorescence emission spectrum are needed in this method, the SFM method minimizes the amount of required data and reduces the data acquisition time. Finally, since this method does not use nonlinear regression, it can dramatically save computation time in data processing. The high sensitivity of the proposed method to superficial tissue volumes makes it ideal for fluorescence based oximetry and medical diagnostics in applications such as early epithelial cancer diagnosis or wherever the measured tissue volume is exposed to the outside such as in open surgery.
Cluster-based analysis of multi-model climate ensembles

Science.gov (United States)

Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.

2018-06-01

Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and
Reformulated and alternative fuels: modeled impacts on regional air quality with special emphasis on surface ozone concentration.

Science.gov (United States)

Schell, Benedikt; Ackermann, Ingmar J; Hass, Heinz

2002-07-15

The comprehensive European Air Pollution and Dispersion model system was used to estimate the impacts of the usage of reformulated and alternative fuels on regional air quality with special emphasis on surface ozone concentrations. A severe western European summer smog episode in July 1994 has been used as a reference, and the model predictions have been evaluated for this episode. A forecast simulation for the year 2005 (TREND) has been performed, including the future emission development based on the current legislation and technologies available. The results of the scenario TREND are used as a baseline for the other 2005 fuel scenarios, including fuel reformulation, fuel sulfur content, and compressed natural gas (CNG) as an alternative fuel. Compared to the year 1994, significant reductions in episode peak ozone concentrations and ozone grid hours are predicted for the TREND scenario. These reductions are even more pronounced within the investigated alternative and reformulated fuel scenarios. Especially, low sulfur fuels are appropriate for an immediate improvement in air quality, because they effect the emissions of the whole fleet. Furthermore, the simulation results indicate that the introduction of CNG vehicles would also enhance air quality with respect to ozone.
Mathematical modeling of the ethanol fermentation of cashew apple juice by a flocculent yeast: the effect of initial substrate concentration and temperature.

Science.gov (United States)

Pinheiro, Álvaro Daniel Teles; da Silva Pereira, Andréa; Barros, Emanuel Meneses; Antonini, Sandra Regina Ceccato; Cartaxo, Samuel Jorge Marques; Rocha, Maria Valderez Ponte; Gonçalves, Luciana Rocha B

2017-08-01

In this work, the effect of initial sugar concentration and temperature on the production of ethanol by Saccharomyces cerevisiae CCA008, a flocculent yeast, using cashew apple juice in a 1L-bioreactor was studied. The experimental results were used to develop a kinetic model relating biomass, ethanol production and total reducing sugar consumption. Monod, Andrews, Levenspiel and Ghose and Tyagi models were investigated to represent the specific growth rate without inhibition, with inhibition by substrate and with inhibition by product, respectively. Model validation was performed using a new set of experimental data obtained at 34 °C and using 100 g L -1 of initial substrate concentration. The model proposed by Ghose and Tyagi was able to accurately describe the dynamics of ethanol production by S. cerevisiae CCA008 growing on cashew apple juice, containing an initial reducing sugar concentration ranging from 70 to 170 g L -1 and temperature, from 26 to 42 °C. The model optimization was also accomplished based on the following parameters: percentage volume of ethanol per volume of solution (%V ethanol /V solution ), efficiency and reaction productivity. The optimal operational conditions were determined using response surface graphs constructed with simulated data, reaching an efficiency and a productivity of 93.5% and 5.45 g L -1 h -1 , respectively.
Physiologically based pharmacokinetic and pharmacodynamic modeling of an antagonist (SM-406/AT-406) of multiple inhibitor of apoptosis proteins (IAPs) in a mouse xenograft model of human breast cancer.

Science.gov (United States)

Zhang, Tao; Li, Yanyan; Zou, Peng; Yu, Jing-yu; McEachern, Donna; Wang, Shaomeng; Sun, Duxin

2013-09-01

The inhibitors of apoptosis proteins (IAPs) are a class of key apoptosis regulators overexpressed or dysregulated in cancer. SM-406/AT-406 is a potent and selective small molecule mimetic of Smac that antagonizes the inhibitor of apoptosis proteins (IAPs). A physiologically based pharmacokinetic and pharmacodynamic (PBPK-PD) model was developed to predict the tissue concentration-time profiles of SM-406, the related onco-protein levels in tumor, and the tumor growth inhibition in a mouse model bearing human breast cancer xenograft. In the whole body physiologically based pharmacokinetic (PBPK) model for pharmacokinetics characterization, a well stirred (perfusion rate-limited) model was used to describe SM-406 pharmacokinetics in the lung, heart, kidney, intestine, liver and spleen, and a diffusion rate-limited (permeability limited) model was used for tumor. Pharmacodynamic (PD) models were developed to correlate the SM-406 concentration in tumor to the cIAP1 degradation, pro-caspase 8 decrease, CL-PARP accumulation and tumor growth inhibition. The PBPK-PD model well described the experimental pharmacokinetic data, the pharmacodynamic biomarker responses and tumor growth. This model may be helpful to predict tumor and plasma SM-406 concentrations in the clinic. Copyright © 2013 John Wiley & Sons, Ltd.
Modeling the response of forest isoprene emissions to future increases in atmospheric CO2 concentration and changes in climate (Invited)

Science.gov (United States)

Monson, R. K.; Heald, C. L.; Guenther, A. B.; Wilkinson, M.

2009-12-01

Isoprene emissions from plants to the atmosphere are sensitive to changes in temperature, light and atmospheric CO2 concentration in both the short- (seconds-to-minutes) and long-term (hours-to-months). We now understand that the different time constants for these responses are due to controls by different sets of biochemical and physiological processes n leaves. Progress has been made in the past few years toward converting this process-level understanding into quantitative models. In this talk, we consider this progress with special emphasis on the short- and long-term responses to atmospheric CO2 concentration and temperature. A new biochemically-based model is presented for describing the CO2 responses, and the model is deployed in a global context to predict interactions between the influences of temperature and CO2 on the global isoprene emission rate. The model is based on the theory of enzyme-substrate kinetics, particularly with regard to those reactions that produce puruvate or glyceraldehyde 3-phosphate, the two chloroplastic substrates for isoprene biosynthesis. In the global model, when we accounted for CO2 inhibition of isoprene emission in the long-term response, we observed little impact on present-day global isoprene emission (increase from 508 to 523 Tg C yr-1). However, the large increases in future isoprene emissions predicted from past models which are due to a projected warmer climate, were entirely offset by including the CO2 effects. The isoprene emission response to CO2 was dominated by the long-term growth environment effect, with modulations of 10% or less from the short-term effect. We use this analysis as a framework for grounding future global models of isoprene emission in biochemical and physiological observations.
Na+/K(+)pump activity in photoreceptors of the blowfly Calliphora : A model analysis based on membrane potential measurements

NARCIS (Netherlands)

Gerster, U; Stavenga, DG; Backhaus, W

Na+/K+-pump activity and intracellular Na+ and K+ concentration changes in blowfly photoreceptors are derived from intracellular potential measurements in vivo with a model based on the Goldman-Hodgkin-Katz theory for membrane currents. The relation between the intracellular Na+ concentration and
Enhancing performance of a linear dielectric based concentrating photovoltaic system using a reflective film along the edge

International Nuclear Information System (INIS)

Baig, Hasan; Sarmah, Nabin; Chemisana, Daniel; Rosell, Joan; Mallick, Tapas K.

2014-01-01

In the present study, we model and analyse the performance of a dielectric based linear concentrating photovoltaic system using ray tracing and finite element methods. The results obtained are compared with the experiments. The system under study is a linear asymmetric CPC (Compound Parabolic Concentrator) designed to operate under extreme incident angles of 0° and 55° and have a geometrical concentration ratio of 2.8×. Initial experiments showed a maximum PR (power ratio) of 2.2 compared to a non concentrating counterpart. An improvement to this has been proposed and verified by adding a reflective film along the edges of the concentrator to capture the escaping rays and minimise optical losses. The addition of the reflective film changes the incoming distribution on the solar cell. Results show an increase of 16% in the average power output while using this reflective film. On including the thermal effects it was found that the overall benefit changes to about 6% while using a reflective film. Additionally, the effects of the non-uniformity of the incoming radiation are also analysed and reported for both the cases. It is found that adding the reflective film drops the maximum power at the output by only 0.5% due to the effect of non-uniformity. - Highlights: • Optical, thermal and electrical analysis of a concentrating photovoltaic system. • Improvement in performance by use of reflective film along the edge. • Experimental validation of results. • Effects of non-uniform illumination on the performance of the CPV system. • Impact of temperature profile on the overall performance
A new turbine model for enhancing convective heat transfer in the presence of low volume concentration of Ag-Oil Nanofluids

Science.gov (United States)

Jafarimoghaddam, Amin; Aberoumand, Sadegh; Jafarimoghaddam, Reza

2018-05-01

This study aims to experimentally investigate and introduce a new model for enhancing convective heat transfer in the presence of Ag/ oil nanofluid. An annular tube was designed with a turbine element attached to the inner tube. The inner tube was a bearing shaft which could rotate with the rotation of turbine element. As the previous works by authors, the setup was conducted with a fully developed laminar flow regime with the Reynolds numbers less than 160. The outer surface of the annular tube was heated by an element with constant heat flux of 204 W. Ag/ oil nanofluid was used in different volume concentrations of 0.011%, 0.044% and 0.171%. The new model could enhance the convective heat transfer coefficient up to 54% (compared to the simple annular tube in the case of base fluid) for the best studied case (nanofluid with the volume concentration of 0.171%) while the friction factor remained low. The new model can be applied for related applications regarding Ag/ oil nanofluid as a new step in enhancing the convective heat transfer coefficient.
Determining Radium-226 concentration from Radon-222 emanation in building materials: a theoretical model

International Nuclear Information System (INIS)

Barreto, Rafael C.; Perna, Allan F.N.; Narloch, Danielle C.; Del Claro, Flavia; Correa, Janine N.; Paschuk, Sergei A.

2017-01-01

It was developed an improved theoretical model capable to estimate the radium concentration in building materials solely measuring the radon-222 concentration in a con ned atmosphere. This non-destructive technique is not limited by the size of the samples, and it intrinsically includes back diffusion. The resulting equation provides the exact solution for the concentration of radon-222 as a function of time and distance in one dimension. The effective concentration of radium-226 is a fit parameter of this equation. In order to reduce its complexity, this equation was simplified considering two cases: low diffusion in the building material compared to the air, and a building material initially saturated with radon-222. These simplified versions of the exact one dimension solution were used to t experimental data. Radon-222 concentration was continuously measured for twelve days with an AlphaGUARD TM detector, located at the Laboratory of Applied Nuclear Physics at Universidade Tecnologica Federal do Parana (UTFPR). This model was applied to two different materials: cement mortar and concrete, which results were respectively (15:7 ±8:3) Bq=kg and (10:5±2:4) Bq=kg for the radium-226 effective concentration. This estimation was confronted with the direct measurements of radium in the same materials (same sources) using gamma-ray spectrometry, fulfilled at Centro de Desenvolvimento da Tecnologia Nuclear (CDTN), which results were respectively (13:81±0:23) Bq=kg and (12:61±0:22) Bq=kg. (author)
Determining Radium-226 concentration from Radon-222 emanation in building materials: a theoretical model

Energy Technology Data Exchange (ETDEWEB)

Barreto, Rafael C.; Perna, Allan F.N.; Narloch, Danielle C.; Del Claro, Flavia; Correa, Janine N.; Paschuk, Sergei A., E-mail: baarreth@gmail.com, E-mail: allan_perna@hotmail.com, E-mail: daninarloch@hotmail.com, E-mail: aviadelclaro@gmail.com, E-mail: janine_nicolosi@hotmail.com, E-mail: spaschuk@gmail.com [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil). Departamento Academico de Fisica e Departamento Academico de Construcao Civil

2017-07-01

It was developed an improved theoretical model capable to estimate the radium concentration in building materials solely measuring the radon-222 concentration in a con ned atmosphere. This non-destructive technique is not limited by the size of the samples, and it intrinsically includes back diffusion. The resulting equation provides the exact solution for the concentration of radon-222 as a function of time and distance in one dimension. The effective concentration of radium-226 is a fit parameter of this equation. In order to reduce its complexity, this equation was simplified considering two cases: low diffusion in the building material compared to the air, and a building material initially saturated with radon-222. These simplified versions of the exact one dimension solution were used to t experimental data. Radon-222 concentration was continuously measured for twelve days with an AlphaGUARD{sup TM} detector, located at the Laboratory of Applied Nuclear Physics at Universidade Tecnologica Federal do Parana (UTFPR). This model was applied to two different materials: cement mortar and concrete, which results were respectively (15:7 ±8:3) Bq=kg and (10:5±2:4) Bq=kg for the radium-226 effective concentration. This estimation was confronted with the direct measurements of radium in the same materials (same sources) using gamma-ray spectrometry, fulfilled at Centro de Desenvolvimento da Tecnologia Nuclear (CDTN), which results were respectively (13:81±0:23) Bq=kg and (12:61±0:22) Bq=kg. (author)
Reconstructing historical radionuclide concentrations along the east coast of Ireland using a compartmental model

International Nuclear Information System (INIS)

Smith, C.N.; Clarke, S.; McDonald, P.; Goshawk, J.A.; Jones, S.R.

2000-01-01

A mathematical model is presented that simulates the annually averaged transport of radionuclides, originating from the BNFL reprocessing plant at Sellafield, throughout the Irish Sea. The model, CUMBRIA77, represents the processes of radionuclide transport and dispersion in the marine environment and allows predictions of radionuclide concentration in various environmental media, including biota, to be made throughout the whole of the Irish Sea. In this paper we describe the use of the model to reconstruct the historical activity concentrations of 137Cs and 239+240Pu in a variety of environmental media in the western Irish Sea and along the Irish east coast back to 1950. This reconstruction exercise is of interest because only limited measurements of 137Cs and 239+240Pu activity are available prior to the 1980s. The predictions were compared to the available measured data to validate their accuracy. The results of the reconstruction indicate that activity concentrations of 137Cs in the western Irish Sea follow a similar, though slightly delayed and smoothed, profile to the discharges from the Sellafield site, with concentrations at the time of peak discharge (the mid-1970s) being around an order of magnitude higher than those measured in the 1980s and 1990s. By contrast, the concentrations of 239+240Pu at the time of peak discharges were similar to those presently measured. These differences reflect the distinct marine chemistries of the two nuclides, in particular the higher propensity of plutonium to bind to sediments leading to extended transport times. Despite these differences in behaviour the doses to Irish seafood consumers from 137Cs remain significantly higher than those from 239+240Pu
Prediction of hydroxyl concentrations in cement pore water using a numerical cement hydration model

NARCIS (Netherlands)

Eijk, van R.J.; Brouwers, H.J.H.

2000-01-01

In this paper, a 3D numerical cement hydration model is used for predicting alkali and hydroxyl concentrations in cement pore water. First, this numerical model is calibrated for Dutch cement employing both chemical shrinkage and calorimetric experiments. Secondly, the strength development of some

Acid-base chemistry of white wine: analytical characterisation and chemical modelling.

Science.gov (United States)

Prenesti, Enrico; Berto, Silvia; Toso, Simona; Daniele, Pier Giuseppe

2012-01-01

A chemical model of the acid-base properties is optimized for each white wine under study, together with the calculation of their ionic strength, taking into account the contributions of all significant ionic species (strong electrolytes and weak one sensitive to the chemical equilibria). Coupling the HPLC-IEC and HPLC-RP methods, we are able to quantify up to 12 carboxylic acids, the most relevant substances responsible of the acid-base equilibria of wine. The analytical concentration of carboxylic acids and of other acid-base active substances was used as input, with the total acidity, for the chemical modelling step of the study based on the contemporary treatment of overlapped protonation equilibria. New protonation constants were refined (L-lactic and succinic acids) with respect to our previous investigation on red wines. Attention was paid for mixed solvent (ethanol-water mixture), ionic strength, and temperature to ensure a thermodynamic level to the study. Validation of the chemical model optimized is achieved by way of conductometric measurements and using a synthetic "wine" especially adapted for testing.
Acid-Base Chemistry of White Wine: Analytical Characterisation and Chemical Modelling

Directory of Open Access Journals (Sweden)

Enrico Prenesti

2012-01-01

Full Text Available A chemical model of the acid-base properties is optimized for each white wine under study, together with the calculation of their ionic strength, taking into account the contributions of all significant ionic species (strong electrolytes and weak one sensitive to the chemical equilibria. Coupling the HPLC-IEC and HPLC-RP methods, we are able to quantify up to 12 carboxylic acids, the most relevant substances responsible of the acid-base equilibria of wine. The analytical concentration of carboxylic acids and of other acid-base active substances was used as input, with the total acidity, for the chemical modelling step of the study based on the contemporary treatment of overlapped protonation equilibria. New protonation constants were refined (L-lactic and succinic acids with respect to our previous investigation on red wines. Attention was paid for mixed solvent (ethanol-water mixture, ionic strength, and temperature to ensure a thermodynamic level to the study. Validation of the chemical model optimized is achieved by way of conductometric measurements and using a synthetic “wine” especially adapted for testing.
Acid-Base Chemistry of White Wine: Analytical Characterisation and Chemical Modelling

Science.gov (United States)

Prenesti, Enrico; Berto, Silvia; Toso, Simona; Daniele, Pier Giuseppe

2012-01-01

A chemical model of the acid-base properties is optimized for each white wine under study, together with the calculation of their ionic strength, taking into account the contributions of all significant ionic species (strong electrolytes and weak one sensitive to the chemical equilibria). Coupling the HPLC-IEC and HPLC-RP methods, we are able to quantify up to 12 carboxylic acids, the most relevant substances responsible of the acid-base equilibria of wine. The analytical concentration of carboxylic acids and of other acid-base active substances was used as input, with the total acidity, for the chemical modelling step of the study based on the contemporary treatment of overlapped protonation equilibria. New protonation constants were refined (L-lactic and succinic acids) with respect to our previous investigation on red wines. Attention was paid for mixed solvent (ethanol-water mixture), ionic strength, and temperature to ensure a thermodynamic level to the study. Validation of the chemical model optimized is achieved by way of conductometric measurements and using a synthetic “wine” especially adapted for testing. PMID:22566762
Microfluidic acoustophoretic force based low-concentration oil separation and detection from the environment.

Science.gov (United States)

Wang, Han; Liu, Zhongzheng; Kim, Sungman; Koo, Chiwan; Cho, Younghak; Jang, Dong-Young; Kim, Yong-Joe; Han, Arum

2014-03-07

Detecting and quantifying extremely low concentrations of oil from the environment have broad applications in oil spill monitoring in ocean and coastal areas as well as in oil leakage monitoring on land. Currently available methods for low-concentration oil detection are bulky or costly with limited sensitivities. Thus they are difficult to be used as portable and field-deployable detectors in the case of oil spills or for monitoring the long-term effects of dispersed oil on marine and coastal ecosystems. Here, we present a low-concentration oil droplet trapping and detection microfluidic system based on the acoustophoresis phenomenon where oil droplets in water having a negative acoustic contrast factor move towards acoustic pressure anti-nodes. By trapping oil droplets from water samples flowing through a microfluidic channel, even very low concentrations of oil droplets can be concentrated to a detectable level for further analyses, which is a significant improvement over currently available oil detection systems. Oil droplets in water were successfully trapped and accumulated in a circular acoustophoretic trapping chamber of the microfluidic device and detected using a custom-built compact fluorescent detector based on the natural fluorescence of the trapped crude oil droplets. After the on-line detection, crude oil droplets released from the trapping chamber were successfully separated into a collection outlet by acoustophoretic force for further off-chip analyses. The developed microfluidic system provides a new way of trapping, detecting, and separating low-concentration crude oil from environmental water samples and holds promise as a low-cost field-deployable oil detector with extremely high sensitivity. The microfluidic system and operation principle are expected to be utilized in a wide range of applications where separating, concentrating, and detecting small particles having a negative acoustic contrast factor are required.
Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model

Science.gov (United States)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2014-02-01

Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation
Modeling and performance analysis of a concentrated photovoltaic–thermoelectric hybrid power generation system

International Nuclear Information System (INIS)

Lamba, Ravita; Kaushik, S.C.

2016-01-01

Highlights: • Thermodynamic model of concentrated photovoltaic–thermoelectric system is analysed. • Thomson effect reduces the power output of PV, TE and hybrid PV–TEG system. • Effect of thermocouple number, irradiance, PV and TE current have been studied. • The optimum concentration ratio for maximum power output has been found out. • The overall efficiency and power output of hybrid PV–TEG system has been improved. - Abstract: In this study, a thermodynamic model for analysing the performance of a concentrated photovoltaic–thermoelectric generator (CPV–TEG) hybrid system including Thomson effect in conjunction with Seebeck, Joule and Fourier heat conduction effects has been developed and simulated in MATALB environment. The expressions for calculating the temperature of photovoltaic (PV) module, hot and cold sides of thermoelectric (TE) module are derived analytically as well. The effect of concentration ratio, number of thermocouples in TE module, solar irradiance, PV module current and TE module current on power output and efficiency of the PV, TEG and hybrid PV–TEG system have been studied. The optimum concentration ratio corresponding to maximum power output of the hybrid system has been found out. It has been observed that by considering Thomson effect in TEG module, the power output of the PV, TE and hybrid PV–TEG systems decreases and at C = 1 and 5, it reduces the power output of hybrid system by 0.7% and 4.78% respectively. The results of this study may provide basis for performance optimization of a practical irreversible CPV–TEG hybrid system.
Modelling horizontal and vertical concentration profiles of ozone and oxides of nitrogen within high-latitude urban areas

International Nuclear Information System (INIS)

Nicholson, J.P.; Weston, K.J.

2001-01-01

Urban ozone concentrations are determined by the balance between ozone destruction, chemical production and supply through advection and turbulent down-mixing from higher levels. At high latitudes, low levels of solar insolation and high horizontal advection speeds reduce the photochemical production and the spatial ozone concentration patterns are largely determined by the reaction of ozone with nitric oxide and dry deposition to the surface. A Lagrangian column model has been developed to simulate the mean (monthly and annual) three-dimensional structure in ozone and nitrogen oxides (NO x ) concentrations in the boundary-layer within and immediately around an urban area. The short-time-scale photochemical processes of ozone and NO x , as well as emissions and deposition to the ground, are simulated. The model has a horizontal resolution of 1x1km and high resolution in the vertical. It has been applied over a 100x100km domain containing the city of Edinburgh (at latitude 56 o N) to simulate the city-scale processes of pollutants. Results are presented, using averaged wind-flow frequencies and appropriate stability conditions, to show the extent of the depletion of ozone by city emissions. The long-term average spatial patterns in the surface ozone and NO x concentrations over the model domain are reproduced quantitatively. The model shows the average surface ozone concentrations in the urban area to be lower than the surrounding rural areas by typically 50% and that the areas experiencing a 20% ozone depletion are generally restricted to within the urban area. The depletion of the ozone concentration to less than 50% of the rural surface values extends only 20m vertically above the urban area. A series of monitoring sites for ozone, nitric oxide and nitrogen dioxide on a north-south transect through the city - from an urban, through a semi-rural, to a remote rural location - allows the comparison of modelled with observed data for the mean diurnal cycle of ozone
Quantitative acid-base physiology using the Stewart model. Does it improve our understanding of what is really wrong?

NARCIS (Netherlands)

Derksen, R.; Scheffer, G.J.; Hoeven, J.G. van der

2006-01-01

Traditional theories of acid-base balance are based on the Henderson-Hasselbalch equation to calculate proton concentration. The recent revival of quantitative acid-base physiology using the Stewart model has increased our understanding of complicated acid-base disorders, but has also led to several
In vitro-in vivo extrapolation: estimation of human serum concentrations of chemicals equivalent to cytotoxic concentrations in vitro

International Nuclear Information System (INIS)

Guelden, Michael; Seibert, Hasso

2003-01-01

In the present study an extrapolation model for estimating serum concentrations of chemicals equivalent to in vitro effective concentrations is developed and applied to median cytotoxic concentrations (EC 50 ) determined in vitro. Nominal concentrations of a chemical in serum and in vitro are regarded as equivalent, if they result in the same aqueous concentration of the unbound form. The algorithm used is based on equilibrium distribution and requires albumin binding data, the octanol-water partition coefficient (K ow ), and the albumin concentrations and lipid volume fractions in vitro and in serum. The chemicals studied cover wide ranges of cytotoxic potency (EC 50 : 2.5-530000 μM) and lipophilicity (log K ow : -5 to 7). Their albumin binding characteristics have been determined by means of an in vitro cytotoxicity test as described previously. The equivalent serum concentrations of 19 of the 33 compounds investigated, having high protein binding and/or lipophilicity, were substantially higher than the EC 50 -values, by factors of 2.5-58. Prominent deviations between the equivalent nominal concentrations in serum and in vitro were largely restricted to chemicals with higher cytotoxic potency (EC 50 ≤1000 μM). The results suggest that estimates of equivalent serum concentrations based on in vitro data are robust for chemicals with low lipophilicity (log K ow ≤2) and low potency (EC 50 >1000 μM). With more potent chemicals or those with higher lipophilicity partitioning into lipids and/or binding to serum proteins have to be taken into account when estimating in vivo serum concentrations equivalent to in vitro effective concentrations
The effective effect-site propofol concentration for induction and intubation with two pharmacokinetic models in morbidly obese patients using total body weight.

Science.gov (United States)

Echevarría, Ghislaine C; Elgueta, María F; Donoso, María T; Bugedo, Diego A; Cortínez, Luis I; Muñoz, Hernán R

2012-10-01

Most pharmacokinetic (PK) models used for propofol administration are based on studies in normal-weight patients. Extrapolation of these models for morbidly obese patients is controversial. Using 2 PK models and a target-controlled infusion system, we determined the predicted propofol effect-site concentration (Ce) needed for induction of anesthesia in morbidly obese subjects using total body weight. Sixty-six morbidly obese subjects from 18 to 50 years of age were randomized to receive propofol to reach and maintain a predetermined propofol Ce, based on the PK models of either Marsh or Schnider. All patients were monitored with a Bispectral Index electroencephalographic monitor. Fentanyl 3 μg/kg total body weight was administered before starting the propofol infusion. After loss of consciousness, vecuronium was administered to facilitate endotracheal intubation. Groups of 6 patients each received propofol at a different, predetermined target propofol Ce. An "effective Ce" (ECe) was defined as the propofol Ce that provided adequate hypnosis (Bispectral Index <60) during the complete induction period (45 seconds after reaching the predetermined target Ce until 5 minutes after tracheal intubation). Heart rate and arterial blood pressure were measured every 1 minute throughout the study period. Probit regression analysis was performed to calculate the effective propofol Ce values to induce hypnosis in 50% (ECe(50)) and 95% (ECe(95)) of patients with 95% confidence intervals (CIs). Patient characteristics were similar between models and across the propofol target concentration groups. The ECe(50) of propofol was 3.4 μg/mL (95% CI: 2.9, 3.7 μg/mL) with the Marsh model and 4.5 μg/mL (95% CI: 4.1, 4.8 μg/mL) with the Schnider model (P < 0.001). The ECe(95) values were 4.2 μg/mL (95% CI: 3.8, 6.2 μg/mL) and 5.5 μg/mL (95% CI: 5.0, 7.2 μg/mL) with Marsh and Schnider models, respectively. At the ECe(95), hemodynamic effects were similar with the 2 PK models
Free volume model: High-temperature deformation of a Zr-based bulk metallic glass

International Nuclear Information System (INIS)

Bletry, M.; Guyot, P.; Blandin, J.J.; Soubeyroux, J.L.

2006-01-01

The homogeneous deformation of a zirconium-based bulk metallic glass is investigated in the glass transition region. Compression tests at different temperatures and strain rates have been conducted. The mechanical behavior is analyzed in the framework of the free volume model, taking into account the dependence of the flow defect concentration on deformation. The activation volume is evaluated and allows one to gather the viscosity data (for the different strain rates and temperatures) on a unique master curve. It is also shown that, due to the relation between flow defect concentration and free volume, it is not possible to deduce the equilibrium flow defect concentration directly from mechanical measurements. However, if this parameter is arbitrarily chosen, mechanical measurements give access to the other parameters of the model, these parameters for the alloy under investigation being of the same order of magnitude as those for other metallic glasses
Concentration and Diversity of Availability and Use in Information Systems: A Positive Reinforcement Model.

Science.gov (United States)

Rousseau, Ronald

1992-01-01

Proposes a mathematical model to explain the observed concentration or diversity of nominal classes in information retrieval systems. The Lorenz Curve is discussed, Information Production Process (IPP) is explained, and a heuristic explanation of circumstances in which the model might be used is offered. (30 references) (LRW)
Evaluation of a concentric biopsychosocial model of well-being in persons with spinal cord injuries.

Science.gov (United States)

Smedema, Susan Miller

2017-05-01

The objective of this study was to evaluate a concentric biopsychosocial model of well-being in individuals with spinal cord injuries (SCI). Adults (N = 235) with SCI participated in this study. A cross-sectional design with hierarchical regression and Andrew Hayes' (2013) PROCESS mediation analysis procedure was used to evaluate the model. Each step of the hierarchical regression on life satisfaction, in which biological variables were entered first, social variables were entered second, and psychological variables were entered third, was significant. Examining the standardized partial coefficients, pain, interpersonal self-efficacy, social support, hope-agency, and self-esteem were all significantly associated with life satisfaction, controlling for variables in each outward ring of the concentric model. Four serial mediational analyses were also conducted in which the social and psychological variables significantly partially mediated the relationship between pain and life satisfaction. The results provide support for a concentric biopsychosocial model of well-being in persons with SCI. Rehabilitation interventions should focus on augmenting biopsychosocial factors to allow for maximum improvement in well-being outcomes in individuals with SCI. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Model for calculation of concentration and load on behalf of accidents with radioactive materials

International Nuclear Information System (INIS)

Janssen, L.A.M.; Heugten, W.H.H. van

1987-04-01

In the project 'Information- and calculation-system for disaster combatment', by order of the Dutch government, a demonstration model has been developed for a diagnosis system for accidents. In this demonstration a model is used to calculate the concentration- and dose-distributions caused by incidental emissions of limited time. This model is described in this report. 4 refs.; 2 figs.; 3 tabs
Method for recovering aroma concentrate from a caffeine- or theobromine-comprising food base material

NARCIS (Netherlands)

Kattenberg, H.R.; Willemsen, J.H.A.; Starmans, D.A.J.; Hoving, H.D.; Winters, M.G.M.

2002-01-01

Described is a method for recovering aroma concentrate from a caffeine- or theobromine-comprising food base material, such as coffee or tea, and in particular cocoa, at least comprising the steps of: introducing the food base material into an aqueous extractant and incubating the food base material
Modeling and optimization of tissue 10B concentration and dosimetry for arbitrary BPA-F infusion schedules in humans

International Nuclear Information System (INIS)

Kiger, W.S. III; Newton, T.H.; Palmer, M.R.

2000-01-01

Separate compartmental models have been derived for the concentration of 10 B resulting from BPA-F infusion in the central vascular space (i.e., blood or, more appropriately, plasma) and in glioblastoma multiforme and normal brain. By coupling the model for the temporal variation of 10 B concentration in the central vascular space with that for tissue, the dynamic behavior of the 10 B concentration and the resulting dosimetry in the relevant tissues and blood may be predicted for arbitrary infusion schedules. This coupled model may be used as a tool for identifying the optimal time for BNCT irradiation and optimal BPA-F infusion schedule (i.e., temporal targeting) in humans without the need for expensive and time-consuming pharmacokinetic studies for every infusion schedule considered. This model was used to analyze the concentration profiles resulting from a wide range of infusion schedules and their implications for dosimetry. (author)
On-line monitoring and modelling based process control of high rate nitrification - lab scale experimental results

Energy Technology Data Exchange (ETDEWEB)

Pirsing, A. [Technische Univ. Berlin (Germany). Inst. fuer Verfahrenstechnik; Wiesmann, U. [Technische Univ. Berlin (Germany). Inst. fuer Verfahrenstechnik; Kelterbach, G. [Technische Univ. Berlin (Germany). Inst. fuer Mess- und Regelungstechnik; Schaffranietz, U. [Technische Univ. Berlin (Germany). Inst. fuer Mess- und Regelungstechnik; Roeck, H. [Technische Univ. Berlin (Germany). Inst. fuer Mess- und Regelungstechnik; Eichner, B. [Technische Univ. Berlin (Germany). Inst. fuer Anorganische und Analytische Chemie; Szukal, S. [Technische Univ. Berlin (Germany). Inst. fuer Anorganische und Analytische Chemie; Schulze, G. [Technische Univ. Berlin (Germany). Inst. fuer Anorganische und Analytische Chemie

1996-09-01

This paper presents a new concept for the control of nitrification in highly polluted waste waters. The approach is based on mathematical modelling. To determine the substrate degradation rates of the microorganisms involved, a mathematical model using gas measurement is used. A fuzzy-controller maximises the capacity utilisation efficiencies. The experiments carried out in a lab-scale reactor demonstrate that even with highly varying ammonia concentrations in the influent, the nitrogen concentrations in the effluent can be kept within legal limits. (orig.). With 11 figs.
Communication: Modeling of concentration dependent water diffusivity in ionic solutions: Role of intermolecular charge transfer

Energy Technology Data Exchange (ETDEWEB)

Yao, Yi; Berkowitz, Max L., E-mail: maxb@unc.edu, E-mail: ykanai@unc.edu; Kanai, Yosuke, E-mail: maxb@unc.edu, E-mail: ykanai@unc.edu [Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 (United States)

2015-12-28

The translational diffusivity of water in solutions of alkali halide salts depends on the identity of ions, exhibiting dramatically different behavior even in solutions of similar salts of NaCl and KCl. The water diffusion coefficient decreases as the salt concentration increases in NaCl. Yet, in KCl solution, it slightly increases and remains above bulk value as salt concentration increases. Previous classical molecular dynamics simulations have failed to describe this important behavior even when polarizable models were used. Here, we show that inclusion of dynamical charge transfer among water molecules produces results in a quantitative agreement with experiments. Our results indicate that the concentration-dependent diffusivity reflects the importance of many-body effects among the water molecules in aqueous ionic solutions. Comparison with quantum mechanical calculations shows that a heterogeneous and extended distribution of charges on water molecules around the ions due to ion-water and also water-water charge transfer plays a very important role in controlling water diffusivity. Explicit inclusion of the charge transfer allows us to model accurately the difference in the concentration-dependent water diffusivity between Na{sup +} and K{sup +} ions in simulations, and it is likely to impact modeling of a wide range of systems for medical and technological applications.
Development of a flocculation sub-model for a 3-D CFD model based on rectangular settling tanks.

Science.gov (United States)

Gong, M; Xanthos, S; Ramalingam, K; Fillos, J; Beckmann, K; Deur, A; McCorquodale, J A

2011-01-01

To assess performance and evaluate alternatives to improve the efficiency of rectangular Gould II type final settling tanks (FSTs), New York City Department of Environmental Protection and City College of NY developed a 3D computer model depicting the actual structural configuration of the tanks and the current and proposed hydraulic and solids loading rates. Fluent 6.3.26™ was the base platform for the computational fluid dynamics (CFD) model, for which sub-models of the SS settling characteristics, turbulence, flocculation and rheology were incorporated. This was supplemented by field and bench scale experiments to quantify the coefficients integral to the sub-models. The 3D model developed can be used to consider different baffle arrangements, sludge withdrawal mechanisms and loading alternatives to the FSTs. Flocculation in the front half of the rectangular tank especially in the region before and after the inlet baffle is one of the vital parameters that influences the capture efficiency of SS. Flocculation could be further improved by capturing medium and small size particles by creating an additional zone with an in-tank baffle. This was one of the methods that was adopted in optimizing the performance of the tank where the CCNY 3D CFD model was used to locate the in-tank baffle position. This paper describes the development of the flocculation sub-model and the relationship of the flocculation coefficients in the known Parker equation to the initial mixed liquor suspended solids (MLSS) concentration X0. A new modified equation is proposed removing the dependency of the breakup coefficient to the initial value of X0 based on preliminary data using normal and low concentration mixed liquor suspended solids values in flocculation experiments performed.
Evolution of the concentration PDF in random environments modeled by global random walk

Science.gov (United States)

Suciu, Nicolae; Vamos, Calin; Attinger, Sabine; Knabner, Peter

2013-04-01

The evolution of the probability density function (PDF) of concentrations of chemical species transported in random environments is often modeled by ensembles of notional particles. The particles move in physical space along stochastic-Lagrangian trajectories governed by Ito equations, with drift coefficients given by the local values of the resolved velocity field and diffusion coefficients obtained by stochastic or space-filtering upscaling procedures. A general model for the sub-grid mixing also can be formulated as a system of Ito equations solving for trajectories in the composition space. The PDF is finally estimated by the number of particles in space-concentration control volumes. In spite of their efficiency, Lagrangian approaches suffer from two severe limitations. Since the particle trajectories are constructed sequentially, the demanded computing resources increase linearly with the number of particles. Moreover, the need to gather particles at the center of computational cells to perform the mixing step and to estimate statistical parameters, as well as the interpolation of various terms to particle positions, inevitably produce numerical diffusion in either particle-mesh or grid-free particle methods. To overcome these limitations, we introduce a global random walk method to solve the system of Ito equations in physical and composition spaces, which models the evolution of the random concentration's PDF. The algorithm consists of a superposition on a regular lattice of many weak Euler schemes for the set of Ito equations. Since all particles starting from a site of the space-concentration lattice are spread in a single numerical procedure, one obtains PDF estimates at the lattice sites at computational costs comparable with those for solving the system of Ito equations associated to a single particle. The new method avoids the limitations concerning the number of particles in Lagrangian approaches, completely removes the numerical diffusion, and

Predicting adsorptive removal of chlorophenol from aqueous solution using artificial intelligence based modeling approaches.

Science.gov (United States)

Singh, Kunwar P; Gupta, Shikha; Ojha, Priyanka; Rai, Premanjali

2013-04-01

The research aims to develop artificial intelligence (AI)-based model to predict the adsorptive removal of 2-chlorophenol (CP) in aqueous solution by coconut shell carbon (CSC) using four operational variables (pH of solution, adsorbate concentration, temperature, and contact time), and to investigate their effects on the adsorption process. Accordingly, based on a factorial design, 640 batch experiments were conducted. Nonlinearities in experimental data were checked using Brock-Dechert-Scheimkman (BDS) statistics. Five nonlinear models were constructed to predict the adsorptive removal of CP in aqueous solution by CSC using four variables as input. Performances of the constructed models were evaluated and compared using statistical criteria. BDS statistics revealed strong nonlinearity in experimental data. Performance of all the models constructed here was satisfactory. Radial basis function network (RBFN) and multilayer perceptron network (MLPN) models performed better than generalized regression neural network, support vector machines, and gene expression programming models. Sensitivity analysis revealed that the contact time had highest effect on adsorption followed by the solution pH, temperature, and CP concentration. The study concluded that all the models constructed here were capable of capturing the nonlinearity in data. A better generalization and predictive performance of RBFN and MLPN models suggested that these can be used to predict the adsorption of CP in aqueous solution using CSC.
Streamline-concentration balance model for in-situ uranium leaching and site restoration

International Nuclear Information System (INIS)

Bommer, P.M.; Schechter, R.S.; Humenick, M.J.

1981-03-01

This work presents two computer models. One describes in-situ uranium leaching and the other describes post leaching site restoration. Both models use a streamline generator to set up the flow field over the reservoir. The leaching model then uses the flow data in a concentration balance along each streamline coupled with the appropriate reaction kinetics to calculate uranium production. The restoration model uses the same procedure except that binary cation exchange is used as the restoring mechanism along each streamline and leaching cation clean up is simulated. The mathematical basis for each model is shown in detail along with the computational schemes used. Finally, the two models have been used with several data sets to point out their capabilities and to illustrate important leaching and restoration parameters and schemes
Streamline-concentration balance model for in situ uranium leaching and site restoration

International Nuclear Information System (INIS)

Bommer, P.M.

1979-01-01

This work presents two computer models. One describes in situ uranium leaching and the other describes post leaching site restoration. Both models use a streamline generator to set up the flow field over the reservoir. The leaching model then uses the flow data in a concentration balance along each streamline coupled with the appropriate reaction kinetics to calculate uranium production. The restoration model uses the same procedure ecept that binary cation exchange is used as the restoring mechanism along each streamline and leaching cation clean up is stimulated. The mathematical basis for each model is shown in detail along with the computational schemes used. Finally, the two models have been used with several data sets to point out their capabilities and to illustrate important leaching and restoration parameters and schemes
An advanced analysis and modelling the air pollutant concentration temporal dynamics in atmosphere of the industrial cities: Odessa city

Science.gov (United States)

Buyadzhi, V. V.; Glushkov, A. V.; Khetselius, O. Yu; Ternovsky, V. B.; Serga, I. N.; Bykowszczenko, N.

2017-10-01

Results of analysis and modelling the air pollutant (dioxide of nitrogen) concentration temporal dynamics in atmosphere of the industrial city Odessa are presented for the first time and based on computing by nonlinear methods of the chaos and dynamical systems theories. A chaotic behaviour is discovered and investigated. To reconstruct the corresponding strange chaotic attractor, the time delay and embedding dimension are computed. The former is determined by the methods of autocorrelation function and average mutual information, and the latter is calculated by means of correlation dimension method and algorithm of false nearest neighbours. It is shown that low-dimensional chaos exists in the nitrogen dioxide concentration time series under investigation. Further, the Lyapunov’s exponents spectrum, Kaplan-Yorke dimension and Kolmogorov entropy are computed.
Monitoring and modeling wetland chloride concentrations in relationship to oil and gas development

Science.gov (United States)

Post van der Burg, Max; Tangen, Brian A.

2015-01-01

Extraction of oil and gas via unconventional methods is becoming an important aspect of energy production worldwide. Studying the effects of this development in countries where these technologies are being widely used may provide other countries, where development may be proposed, with some insight in terms of concerns associated with development. A fairly recent expansion of unconventional oil and gas development in North America provides such an opportunity. Rapid increases in energy development in North America have caught the attention of managers and scientists as a potential stressor for wildlife and their habitats. Of particular concern in the Northern Great Plains of the U.S. is the potential for chloride-rich produced water associated with unconventional oil and gas development to alter the water chemistry of wetlands. We describe a landscape scale modeling approach designed to examine the relationship between potential chloride contamination in wetlands and patterns of oil and gas development. We used a spatial Bayesian hierarchical modeling approach to assess multiple models explaining chloride concentrations in wetlands. These models included effects related to oil and gas wells (e.g. age of wells, number of wells) and surficial geology (e.g. glacial till, outwash). We found that the model containing the number of wells and the surficial geology surrounding a wetland best explained variation in chloride concentrations. Our spatial predictions showed regions of localized high chloride concentrations. Given the spatiotemporal variability of regional wetland water chemistry, we do not regard our results as predictions of contamination, but rather as a way to identify locations that may require more intensive sampling or further investigation. We suggest that an approach like the one outlined here could easily be extended to more of an adaptive monitoring approach to answer questions about chloride contamination risk that are of interest to managers.
Mechanism-Based Modeling of Gastric Emptying Rate and Gallbladder Emptying in Response to Caloric Intake

DEFF Research Database (Denmark)

Guiastrennec, B; Sonne, David Peick; Hansen, M

2016-01-01

Bile acids released postprandially modify the rate and extent of absorption of lipophilic compounds. The present study aimed to predict gastric emptying (GE) rate and gallbladder emptying (GBE) patterns in response to caloric intake. A mechanism-based model for GE, cholecystokinin plasma concentr......Bile acids released postprandially modify the rate and extent of absorption of lipophilic compounds. The present study aimed to predict gastric emptying (GE) rate and gallbladder emptying (GBE) patterns in response to caloric intake. A mechanism-based model for GE, cholecystokinin plasma...... concentrations, and GBE was developed on data from 33 patients with type 2 diabetes and 33 matched nondiabetic individuals who were administered various test drinks. A feedback action of the caloric content entering the proximal small intestine was identified for the rate of GE. The cholecystokinin...
Comparison of depth-averaged concentration and bed load flux sediment transport models of dam-break flow

Directory of Open Access Journals (Sweden)

Jia-heng Zhao

2017-10-01

Full Text Available This paper presents numerical simulations of dam-break flow over a movable bed. Two different mathematical models were compared: a fully coupled formulation of shallow water equations with erosion and deposition terms (a depth-averaged concentration flux model, and shallow water equations with a fully coupled Exner equation (a bed load flux model. Both models were discretized using the cell-centered finite volume method, and a second-order Godunov-type scheme was used to solve the equations. The numerical flux was calculated using a Harten, Lax, and van Leer approximate Riemann solver with the contact wave restored (HLLC. A novel slope source term treatment that considers the density change was introduced to the depth-averaged concentration flux model to obtain higher-order accuracy. A source term that accounts for the sediment flux was added to the bed load flux model to reflect the influence of sediment movement on the momentum of the water. In a one-dimensional test case, a sensitivity study on different model parameters was carried out. For the depth-averaged concentration flux model, Manning's coefficient and sediment porosity values showed an almost linear relationship with the bottom change, and for the bed load flux model, the sediment porosity was identified as the most sensitive parameter. The capabilities and limitations of both model concepts are demonstrated in a benchmark experimental test case dealing with dam-break flow over variable bed topography.
Platinum Concentration and Pathologic Response to Cisplatin-Based Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer.

Directory of Open Access Journals (Sweden)

Elizabeth A Guancial

Full Text Available Platinum (Pt-based chemotherapy is the standard of care for muscle-invasive bladder cancer (MIBC. However, resistance is a major limitation. Reduced intratumoral drug accumulation is an important mechanism of platinum resistance. Our group previously demonstrated a significant correlation between tissue Pt concentration and tumor response to Pt-based neoadjuvant chemotherapy (NAC in lung cancer. We hypothesized that increased Pt concentration in radical cystectomy (RC specimens would correlate with improved pathologic response to Pt-based NAC in MIBC.A cohort of 19 clinically annotated, archived, fresh frozen RC specimens from patients with MIBC treated with Pt-based NAC was identified [ypT0 (pathologic complete response, pCR, N = 4; ≤ypT1N0M0 (pathologic partial response, pPR, N = 6; ≥ypT2 (minimal pathologic response/progression, N = 9]. RC specimens from 2 patients with MIBC who did not receive NAC and 1 treated with a non-Pt containing NAC regimen were used as negative controls. Total Pt concentration in normal adjacent urothelial tissue and bladder tumors from RC specimens was measured by flameless atomic absorption spectrophotometry.Total Pt concentration in normal urothelium differed by tumor pathologic response (P = 0.011. Specimens with pCR had the highest Pt concentrations compared to those with pPR (P = 0.0095 or no response/progression (P = 0.020. There was no significant difference in Pt levels in normal urothelium and tumor between pPR and no response/progression groups (P = 0.37; P = 0.25, respectively.Our finding of increased intracellular Pt in RC specimens with pCR following NAC for MIBC compared to those with residual disease suggests that enhanced Pt accumulation may be an important determinant of Pt sensitivity. Factors that modulate intracellular Pt concentration, such as expression of Pt transporters, warrant further investigation as predictive biomarkers of response to Pt-based NAC in MIBC.
Virtual iron concentration imaging based on dual-energy CT for noninvasive quantification and grading of liver iron content: An iron overload rabbit model study

Energy Technology Data Exchange (ETDEWEB)

Luo, Xian Fu; Yang, Yi; Xie, Xue Qian; Zhang, Huan; Chai, Wei Min; Yan, Fu Hua [Shanghai Jiao Tong University School of Medicine, Department of Radiology, Ruijin Hospital, Shanghai (China); Yan, Jing [Siemens Shanghai Medical Equipment Ltd., Shanghai (China); Wang, Li [Fudan University, Center of Analysis and Measurement, Shanghai (China); Schmidt, Bernhard [Siemens AG, Healthcare Sector, Forchheim (Germany)

2015-09-15

To assess the accuracy of liver iron content (LIC) quantification and grading ability associated with clinical LIC stratification using virtual iron concentration (VIC) imaging on dual-energy CT (DECT) in an iron overload rabbit model. Fifty-one rabbits were prepared as iron-loaded models by intravenous injection of iron dextran. DECT was performed at 80 and 140 kVp. VIC images were derived from an iron-specific algorithm. Postmortem LIC assessments were conducted on an inductively coupled plasma (ICP) spectrometer. Correlation between VIC and LIC was analyzed. VIC were stratified according to the corresponding clinical LIC thresholds of 1.8, 3.2, 7.0, and 15.0 mg Fe/g. Diagnostic performance of stratification was evaluated by receiver operating characteristic analysis. VIC linearly correlated with LIC (r = 0.977, P < 0.01). No significant difference was observed between VIC-derived LICs and ICP (P > 0.05). For the four clinical LIC thresholds, the corresponding cutoff values of VIC were 19.6, 25.3, 36.9, and 61.5 HU, respectively. The highest sensitivity (100 %) and specificity (100 %) were achieved at the threshold of 15.0 mg Fe/g. Virtual iron concentration imaging on DECT showed potential ability to accurately quantify and stratify hepatic iron accumulation in the iron overload rabbit model. (orig.)
Fractional kalman filter to estimate the concentration of air pollution

Science.gov (United States)

Vita Oktaviana, Yessy; Apriliani, Erna; Khusnul Arif, Didik

2018-04-01

Air pollution problem gives important effect in quality environment and quality of human’s life. Air pollution can be caused by nature sources or human activities. Pollutant for example Ozone, a harmful gas formed by NOx and volatile organic compounds (VOCs) emitted from various sources. The air pollution problem can be modeled by TAPM-CTM (The Air Pollution Model with Chemical Transport Model). The model shows concentration of pollutant in the air. Therefore, it is important to estimate concentration of air pollutant. Estimation method can be used for forecast pollutant concentration in future and keep stability of air quality. In this research, an algorithm is developed, based on Fractional Kalman Filter to solve the model of air pollution’s problem. The model will be discretized first and then it will be estimated by the method. The result shows that estimation of Fractional Kalman Filter has better accuracy than estimation of Kalman Filter. The accuracy was tested by applying RMSE (Root Mean Square Error).
Robustness of intra urban land-use regression models for ultrafine particles and black carbon based on mobile monitoring.

Science.gov (United States)

Kerckhoffs, Jules; Hoek, Gerard; Vlaanderen, Jelle; van Nunen, Erik; Messier, Kyle; Brunekreef, Bert; Gulliver, John; Vermeulen, Roel

2017-11-01

Land-use regression (LUR) models for ultrafine particles (UFP) and Black Carbon (BC) in urban areas have been developed using short-term stationary monitoring or mobile platforms in order to capture the high variability of these pollutants. However, little is known about the comparability of predictions of mobile and short-term stationary models and especially the validity of these models for assessing residential exposures and the robustness of model predictions developed in different campaigns. We used an electric car to collect mobile measurements (n = 5236 unique road segments) and short-term stationary measurements (3 × 30min, n = 240) of UFP and BC in three Dutch cities (Amsterdam, Utrecht, Maastricht) in 2014-2015. Predictions of LUR models based on mobile measurements were compared to (i) measured concentrations at the short-term stationary sites, (ii) LUR model predictions based on short-term stationary measurements at 1500 random addresses in the three cities, (iii) externally obtained home outdoor measurements (3 × 24h samples; n = 42) and (iv) predictions of a LUR model developed based upon a 2013 mobile campaign in two cities (Amsterdam, Rotterdam). Despite the poor model R 2 of 15%, the ability of mobile UFP models to predict measurements with longer averaging time increased substantially from 36% for short-term stationary measurements to 57% for home outdoor measurements. In contrast, the mobile BC model only predicted 14% of the variation in the short-term stationary sites and also 14% of the home outdoor sites. Models based upon mobile and short-term stationary monitoring provided fairly high correlated predictions of UFP concentrations at 1500 randomly selected addresses in the three Dutch cities (R 2 = 0.64). We found higher UFP predictions (of about 30%) based on mobile models opposed to short-term model predictions and home outdoor measurements with no clear geospatial patterns. The mobile model for UFP was stable over different settings as
Multifractal modeling of the production of concentrated sugar syrup crystal

International Nuclear Information System (INIS)

Bi Sheng; Gao Jianbo

2016-01-01

High quality, concentrated sugar syrup crystal is produced in a critical step in cane sugar production: the clarification process. It is characterized by two variables: the color of the produced sugar and its clarity degree. We show that the temporal variations of these variables follow power-law distributions and can be well modeled by multiplicative cascade multifractal processes. These interesting properties suggest that the degradation in color and clarity degree has a system-wide cause. In particular, the cascade multifractal model suggests that the degradation in color and clarity degree can be equivalently accounted for by the initial “impurities” in the sugarcane. Hence, more effective cleaning of the sugarcane before the clarification stage may lead to substantial improvement in the effect of clarification. (paper)
Modeling number of bacteria per food unit in comparison to bacterial concentration in quantitative risk assessment: impact on risk estimates.

Science.gov (United States)

Pouillot, Régis; Chen, Yuhuan; Hoelzer, Karin

2015-02-01

When developing quantitative risk assessment models, a fundamental consideration for risk assessors is to decide whether to evaluate changes in bacterial levels in terms of concentrations or in terms of bacterial numbers. Although modeling bacteria in terms of integer numbers may be regarded as a more intuitive and rigorous choice, modeling bacterial concentrations is more popular as it is generally less mathematically complex. We tested three different modeling approaches in a simulation study. The first approach considered bacterial concentrations; the second considered the number of bacteria in contaminated units, and the third considered the expected number of bacteria in contaminated units. Simulation results indicate that modeling concentrations tends to overestimate risk compared to modeling the number of bacteria. A sensitivity analysis using a regression tree suggests that processes which include drastic scenarios consisting of combinations of large bacterial inactivation followed by large bacterial growth frequently lead to a >10-fold overestimation of the average risk when modeling concentrations as opposed to bacterial numbers. Alternatively, the approach of modeling the expected number of bacteria in positive units generates results similar to the second method and is easier to use, thus potentially representing a promising compromise. Published by Elsevier Ltd.
Rate-based modelling and validation of a pilot absorber using MDEA enhanced with carbonic anhydrase (CA)

DEFF Research Database (Denmark)

Gaspar, Jozsef; Gladis, Arne; Woodley, John

2017-01-01

solvent-regeneration energy demand.The focus of this work is to develop a rate-based model for CO2 absorption using MDEA enhanced with CA and to validate it against pilot-scale absorption experiments. In this work, we compare model predictions to measured temperature and CO2 concentration profiles...
Defect chemistry modelling of oxygen-stoichiometry, vacancy concentrations, and conductivity of (La1-xSrx)(y)MnO3 +/-delta

DEFF Research Database (Denmark)

Poulsen, F.W.

2000-01-01

model, based on delocalised electrons, electron holes and all B-ions being trivalent is given in Appendix A. The sequential mathematical method allows us to calculate the high temperature oxygen partial pressure dependent properties of (La1-xSrx)(y)MnO3+/-delta in a unified manner irrespective...... are calculated by the small polaron model containing only ionic species - the B-ion may be Mn-B' (Mn2+), Mn-B(x) (Mn3+), and Mn-B(Mn4+). The A/B-ratio = y greatly influences the oxygen stoichiometry, oxygen ion vacancy- and cation vacancy concentrations and the total conductivity. Calculations are given...
Modeling pollen time series using seasonal-trend decomposition procedure based on LOESS smoothing.

Science.gov (United States)

Rojo, Jesús; Rivero, Rosario; Romero-Morte, Jorge; Fernández-González, Federico; Pérez-Badia, Rosa

2017-02-01

Analysis of airborne pollen concentrations provides valuable information on plant phenology and is thus a useful tool in agriculture-for predicting harvests in crops such as the olive and for deciding when to apply phytosanitary treatments-as well as in medicine and the environmental sciences. Variations in airborne pollen concentrations, moreover, are indicators of changing plant life cycles. By modeling pollen time series, we can not only identify the variables influencing pollen levels but also predict future pollen concentrations. In this study, airborne pollen time series were modeled using a seasonal-trend decomposition procedure based on LOcally wEighted Scatterplot Smoothing (LOESS) smoothing (STL). The data series-daily Poaceae pollen concentrations over the period 2006-2014-was broken up into seasonal and residual (stochastic) components. The seasonal component was compared with data on Poaceae flowering phenology obtained by field sampling. Residuals were fitted to a model generated from daily temperature and rainfall values, and daily pollen concentrations, using partial least squares regression (PLSR). This method was then applied to predict daily pollen concentrations for 2014 (independent validation data) using results for the seasonal component of the time series and estimates of the residual component for the period 2006-2013. Correlation between predicted and observed values was r = 0.79 (correlation coefficient) for the pre-peak period (i.e., the period prior to the peak pollen concentration) and r = 0.63 for the post-peak period. Separate analysis of each of the components of the pollen data series enables the sources of variability to be identified more accurately than by analysis of the original non-decomposed data series, and for this reason, this procedure has proved to be a suitable technique for analyzing the main environmental factors influencing airborne pollen concentrations.
A Mathematical Model for Swallowing of Concentrated Fluids in Oesophagus

OpenAIRE

Pandey, S. K.; Tripathi, Dharmendra

2011-01-01

This model investigates particularly the impact of an integral and a non-integral number of waves on the swallowing of food stuff such as jelly, tomato puree, soup, concentrated fruits juices and honey transported peristaltically through the oesophagus. The fluid is considered as a Casson fluid. Emphasis is on the study of the dependence of local pressure distribution on space and time. Mechanical efficiency, reflux limit and trapping are also discussed. The effect of Casson fluid vis-à-vis N...
Preliminary study on carprofen concentration measurements after transcutaneous treatment with Vetdrop® in a microfracture joint defect model in sheep.

Science.gov (United States)

Sidler, Michèle; Fouché, Nathalie; Meth, Ingmar; von Hahn, Friedrich; von Rechenberg, Brigitte; Kronen, Peter W

2014-12-09

The present preliminary study describes concentration time courses of the NSAID carprofen in the plasma and synovial fluid in a microfrature sheep model after transcutaneous treatments with a novel application device (Vetdrop®). To treat circumscribed inflammatory processes a transcutaneous application device could potentially be beneficial. After transcutaneous application normally lower systemic concentrations are measured which may reduce the incidence of side effects, whereas efficacy is still maintained. In this study carprofen was used based on its capacity to provide analgesia after orthopaedic procedures in sheep and it is considered that it may have a positive influence on the healing of cartilage in low concentrations. In all transcutaneously treated animals, carprofen plasma concentrations exceeded those of synovial fluid, although plasma levels remained significantly reduced (300-fold) as compared to carprofen administered intravenously. Furthermore, in contrast to the intravenously treated animals, a modest accumulation of carprofen in plasma and synovial fluid was observed in the transcutaneously treated animals over the 6-week treatment period. The transcutaneously administered carprofen using the Vetdrop® device penetrated the skin and both, plasma- and synovial concentrations could be measured repeatedly over time. This novel device may be considered a valuable transcutaneous drug delivery system.
Source characterization and exposure modeling of gas-phase polycyclic aromatic hydrocarbon (PAH) concentrations in Southern California

Science.gov (United States)

Masri, Shahir; Li, Lianfa; Dang, Andy; Chung, Judith H.; Chen, Jiu-Chiuan; Fan, Zhi-Hua (Tina); Wu, Jun

2018-03-01

Airborne exposures to polycyclic aromatic hydrocarbons (PAHs) are associated with adverse health outcomes. Because personal air measurements of PAHs are labor intensive and costly, spatial PAH exposure models are useful for epidemiological studies. However, few studies provide adequate spatial coverage to reflect intra-urban variability of ambient PAHs. In this study, we collected 39-40 weekly gas-phase PAH samples in southern California twice in summer and twice in winter, 2009, in order to characterize PAH source contributions and develop spatial models that can estimate gas-phase PAH concentrations at a high resolution. A spatial mixed regression model was constructed, including such variables as roadway, traffic, land-use, vegetation index, commercial cooking facilities, meteorology, and population density. Cross validation of the model resulted in an R2 of 0.66 for summer and 0.77 for winter. Results showed higher total PAH concentrations in winter. Pyrogenic sources, such as fossil fuels and diesel exhaust, were the most dominant contributors to total PAHs. PAH sources varied by season, with a higher fossil fuel and wood burning contribution in winter. Spatial autocorrelation accounted for a substantial amount of the variance in total PAH concentrations for both winter (56%) and summer (19%). In summer, other key variables explaining the variance included meteorological factors (9%), population density (15%), and roadway length (21%). In winter, the variance was also explained by traffic density (16%). In this study, source characterization confirmed the dominance of traffic and other fossil fuel sources to total measured gas-phase PAH concentrations while a spatial exposure model identified key predictors of PAH concentrations. Gas-phase PAH source characterization and exposure estimation is of high utility to epidemiologist and policy makers interested in understanding the health impacts of gas-phase PAHs and strategies to reduce emissions.
Modeling organic aerosol concentrations and properties during winter 2014 in the northwestern Mediterranean region

OpenAIRE

Chrit, Mounir; Sartelet, Karine; Sciare, Jean; Majdi, Marwa; Nicolas, José; Petit, Jean-Eudes; Dulac, François

2018-01-01

Organic aerosols are measured at a remote site (Ersa) on Corsica Cape in the northwestern Mediterranean basin during the Chemistry-Aerosol Mediterranean Experiment (CharMEx) winter campaign of 2014, when high organic concentrations from anthropogenic origin are observed. This work aims at representing the observed organic aerosol concentrations and properties (oxidation state) using the air-quality model Polyphemus with a surrogate approach for secondary organic aerosol (SOA) formation. Becau...

A GIS-based atmospheric dispersion model for pollutants emitted by complex source areas.

Science.gov (United States)

Teggi, Sergio; Costanzini, Sofia; Ghermandi, Grazia; Malagoli, Carlotta; Vinceti, Marco

2018-01-01

Gaussian dispersion models are widely used to simulate the concentrations and deposition fluxes of pollutants emitted by source areas. Very often, the calculation time limits the number of sources and receptors and the geometry of the sources must be simple and without holes. This paper presents CAREA, a new GIS-based Gaussian model for complex source areas. CAREA was coded in the Python language, and is largely based on a simplified formulation of the very popular and recognized AERMOD model. The model allows users to define in a GIS environment thousands of gridded or scattered receptors and thousands of complex sources with hundreds of vertices and holes. CAREA computes ground level, or near ground level, concentrations and dry deposition fluxes of pollutants. The input/output and the runs of the model can be completely managed in GIS environment (e.g. inside a GIS project). The paper presents the CAREA formulation and its applications to very complex test cases. The tests shows that the processing time are satisfactory and that the definition of sources and receptors and the output retrieval are quite easy in a GIS environment. CAREA and AERMOD are compared using simple and reproducible test cases. The comparison shows that CAREA satisfactorily reproduces AERMOD simulations and is considerably faster than AERMOD. Copyright © 2017 Elsevier B.V. All rights reserved.
Cybernetic modeling based on pathway analysis for Penicillium chrysogenum fed-batch fermentation.

Science.gov (United States)

Geng, Jun; Yuan, Jingqi

2010-08-01

A macrokinetic model employing cybernetic methodology is proposed to describe mycelium growth and penicillin production. Based on the primordial and complete metabolic network of Penicillium chrysogenum found in the literature, the modeling procedure is guided by metabolic flux analysis and cybernetic modeling framework. The abstracted cybernetic model describes the transients of the consumption rates of the substrates, the assimilation rates of intermediates, the biomass growth rate, as well as the penicillin formation rate. Combined with the bioreactor model, these reaction rates are linked with the most important state variables, i.e., mycelium, substrate and product concentrations. Simplex method is used to estimate the sensitive parameters of the model. Finally, validation of the model is carried out with 20 batches of industrial-scale penicillin cultivation.
Simulations of organic aerosol concentrations in Mexico City using the WRF-CHEM model during the MCMA-2006/MILAGRO campaign

Directory of Open Access Journals (Sweden)

G. Li

2011-04-01

Full Text Available Organic aerosol concentrations are simulated using the WRF-CHEM model in Mexico City during the period from 24 to 29 March in association with the MILAGRO-2006 campaign. Two approaches are employed to predict the variation and spatial distribution of the organic aerosol concentrations: (1 a traditional 2-product secondary organic aerosol (SOA model with non-volatile primary organic aerosols (POA; (2 a non-traditional SOA model including the volatility basis-set modeling method in which primary organic components are assumed to be semi-volatile and photochemically reactive and are distributed in logarithmically spaced volatility bins. The MCMA (Mexico City Metropolitan Area 2006 official emission inventory is used in simulations and the POA emissions are modified and distributed by volatility based on dilution experiments for the non-traditional SOA model. The model results are compared to the Aerosol Mass Spectrometry (AMS observations analyzed using the Positive Matrix Factorization (PMF technique at an urban background site (T0 and a suburban background site (T1 in Mexico City. The traditional SOA model frequently underestimates the observed POA concentrations during rush hours and overestimates the observations in the rest of the time in the city. The model also substantially underestimates the observed SOA concentrations, particularly during daytime, and only produces 21% and 25% of the observed SOA mass in the suburban and urban area, respectively. The non-traditional SOA model performs well in simulating the POA variation, but still overestimates during daytime in the urban area. The SOA simulations are significantly improved in the non-traditional SOA model compared to the traditional SOA model and the SOA production is increased by more than 100% in the city. However, the underestimation during daytime is still salient in the urban area and the non-traditional model also fails to reproduce the high level of SOA concentrations in the
Data to support "Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations & Biological Condition"

Data.gov (United States)

U.S. Environmental Protection Agency — Spreadsheets are included here to support the manuscript "Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition". This...
Short-term population-based and spatiotemporal nonlinear concentration-response associations between fine particulate matter and children's respiratory clinic visits

Science.gov (United States)

Yu, Hwa-Lung; Chien, Lung-Chang

2014-05-01

Advert health impacts associated with the PM2.5 exposure have been confirmed in mortality and cardiovascular diseases; however, findings of the influence of PM2.5 on respiratory diseases investigated among previous studies are still inconsistent. We investigated the short-term population-based associations between the respiratory clinic visits of children population and the PM2.5 exposure levels with considering both the spatiotemporal distributions of the ambient pollution and clinic visit data. We applied a spatiotemporal structured additive regression model to examine the concentration-response (C-R) association between daily children's respiratory clinic visits and PM2.5 concentrations. The analysis was performed separately on the four selected respiratory disease categories of the population-based dataset, obtained from Taiwan National Health Insurance database, covering the 41 districts in Taipei area during the period of 2005 to 2007. This study reveals a strong nonlinear C-R pattern that the PM2.5 increment can significantly affect respiratory health at PM2.5 concentration ≤ 18.17µg/m3 for both preschool children and schoolchildren. The elevated risks are especially present in the category of acute respiratory infections. PM2.5 increase is mostly non-significant to the more severe respiratory diseases, e.g., COPD and pneumonia, over the ranges of 8.85-92.45µg/m3. The significantly higher relative rate of respiratory clinic visit most likely concentrated at populated areas. We highlight the nonlinearity of the respiratory health impacts of PM2.5 on children's populations from the first study, to our knowledge, to investigate this population-based association. The strong nonlinearity can possibly cause the inconsistency of PM2.5 health impact assessments with linear assumptions.
Effect of concentration of Curcuma longa L. on chitosan-starch based edible coating

Science.gov (United States)

Yusof, N. M.; Jai, J.; Hamzah, F.; Yahya, A.; Pinijsuwan, S.

2017-08-01

The ability of chitosan-starch based coating to extend shelf life of strawberry were studied. The main objectives of this paper is to study the effects of different concentrations (20, 15, 10 and 5 µL) of Curcuma longa L. (CUR) essential oil into chitosan-based edible coating on surface tension in order to increase the effectiveness of the coating. CUR or turmeric is one of the commercially planted herbs in Malaysia for its phytochemical benefits. Application of edible coating using dipping technique has been analysed and evaluated for their effectiveness in extending shelf life of fruits. Surface tension was analysed to investigate the adhesion properties. The best CUR concentration was 15 µL with the optimum surface tension was found to be 31.92 dynes/cm.
Elliptical concentrators.

Science.gov (United States)

Garcia-Botella, Angel; Fernandez-Balbuena, Antonio Alvarez; Bernabeu, Eusebio

2006-10-10

Nonimaging optics is a field devoted to the design of optical components for applications such as solar concentration or illumination. In this field, many different techniques have been used to produce optical devices, including the use of reflective and refractive components or inverse engineering techniques. However, many of these optical components are based on translational symmetries, rotational symmetries, or free-form surfaces. We study a new family of nonimaging concentrators called elliptical concentrators. This new family of concentrators provides new capabilities and can have different configurations, either homofocal or nonhomofocal. Translational and rotational concentrators can be considered as particular cases of elliptical concentrators.
An empirical model for predicting urban roadside nitrogen dioxide concentrations in the UK

International Nuclear Information System (INIS)

Stedman, J.R.; Goodwin, J.W.L.; King, K.; Murrells, T.P.; Bush, T.J.

2001-01-01

An annual mean concentration of 40μgm -3 has been proposed as a limit value within the European Union Air Quality Directives and as a provisional objective within the UK National Air Quality Strategy for 2010 and 2005, respectively. Emissions reduction measures resulting from current national and international policies are likely to deliver significant reductions in emissions of oxides of nitrogen from road traffic in the near future. It is likely that there will still be exceedances of this target value in 2005 and in 2009 if national measures are considered in isolation, particularly at the roadside. It is envisaged that this 'policy gap' will be addressed by implementing local air quality management to reduce concentrations in locations that are at risk of exceeding the objective. Maps of estimated annual mean NO 2 concentrations in both urban background and roadside locations are a valuable resource for the development of UK air quality policy and for the identification of locations at which local air quality management measures may be required. Maps of annual mean NO 2 concentrations at both background and roadside locations for 1998 have been calculated using modelling methods, which make use of four mathematically straightforward, empirically derived linear relationships. Maps of projected concentrations in 2005 and 2009 have also been calculated using an illustrative emissions scenario. For this emissions scenario, annual mean urban background NO 2 concentrations in 2005 are likely to be below 40μgm -3 , in all areas except for inner London, where current national and international policies are expected to lead to concentrations in the range 40-41μgm -3 . Reductions in NO x emissions between 2005 and 2009 are expected to reduce background concentrations to the extent that our modelling results indicate that 40μgm -3 is unlikely to be exceeded in background locations by 2009. Roadside NO 2 concentrations in urban areas in 2005 and 2009 are expected to be
Uncertainty-based calibration and prediction with a stormwater surface accumulation-washoff model based on coverage of sampled Zn, Cu, Pb and Cd field data

DEFF Research Database (Denmark)

Lindblom, Erik Ulfson; Ahlman, S.; Mikkelsen, Peter Steen

2011-01-01

allows identifying a range of behavioral model parameter sets. The small catchment size and nearness of the rain gauge justified excluding the hydrological model parameters from the uncertainty assessment. Uniform, closed prior distributions were heuristically specified for the dry and wet removal...... of accumulated metal available on the conceptual catchment surface. Forward Monte Carlo analysis based on the posterior parameter sets covered 95% of the observed event mean concentrations, and 95% prediction quantiles for site mean concentrations were estimated to 470 μg/l ±20% for Zn, 295 μg/l ±40% for Cu, 20...
Event-Based Conceptual Modeling

DEFF Research Database (Denmark)

Bækgaard, Lars

The paper demonstrates that a wide variety of event-based modeling approaches are based on special cases of the same general event concept, and that the general event concept can be used to unify the otherwise unrelated fields of information modeling and process modeling. A set of event......-based modeling approaches are analyzed and the results are used to formulate a general event concept that can be used for unifying the seemingly unrelated event concepts. Events are characterized as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms...... of information structures. The general event concept can be used to guide systems analysis and design and to improve modeling approaches....
PAH concentrations in lake sediment decline following ban on coal-tar-based pavement sealants in Austin, Texas

Science.gov (United States)

Van Metre, Peter C.; Mahler, Barbara J.

2013-01-01

Recent studies have concluded that coal-tar-based pavement sealants are a major source of polycyclic aromatic hydrocarbons (PAHs) in urban settings in large parts of the United States. In 2006, Austin, TX, became the first jurisdiction in the U.S. to ban the use of coal-tar sealants. We evaluated the effect of Austin’s ban by analyzing PAHs in sediment cores and bottom-sediment samples collected in 1998, 2000, 2001, 2012, and 2014 from Lady Bird Lake, the principal receiving water body for Austin urban runoff. The sum concentration of the 16 EPA Priority Pollutant PAHs (∑PAH16) in dated core intervals and surficial bottom-sediment samples collected from sites in the lower lake declined about 44% from 1998–2005 to 2006–2014 (means of 7980 and 4500 μg kg–1, respectively), and by 2012–2014, the decline was about 58% (mean of 3320 μg kg–1). Concentrations of ∑PAH16 in bottom sediment from two of three mid-lake sites decreased by about 71 and 35% from 2001 to 2014. Concentrations at a third site increased by about 14% from 2001 to 2014. The decreases since 2006 reverse a 40-year (1959–1998) upward trend. Despite declines in PAH concentrations, PAH profiles and source-receptor modeling results indicate that coal-tar sealants remain the largest PAH source to the lake, implying that PAH concentrations likely will continue to decline as stocks of previously applied sealant gradually become depleted.
Modeling annual benzene, toluene, NO2, and soot concentrations on the basis of road traffic characteristics

International Nuclear Information System (INIS)

Carr, David; Ehrenstein, Ondine von; Weiland, Stephan; Wagner, Claudia; Wellie, Oliver; Nicolai, Thomas; Mutius, Erika von

2002-01-01

The investigation of potential adverse health effects of urban traffic-related air pollution is hampered by difficulties encountered with exposure assessment. Usually public measuring sites are few and thereby do not adequately describe spatial variation of pollutant levels over an urban area. In turn, individual monitoring of pollution exposure among study subjects is laborious and expensive. We therefore investigated whether traffic characteristics can be used to adequately predict benzene, NO 2 , and soot concentrations at individual addresses of study subjects in the city area of Munich, Germany. For all road segments with expected traffic volumes of at least 4000 vehicles a day (n=1840), all vehicles were counted manually or a single weekday in 1995. The proportion of vehicles in 'stop-go' mode, n estimate of traffic jam, was determined. Furthermore, annual concentrations of benzene, NO 2 , and soot from 18 high-concentration sites means: 8.7, 65.8, and 12.9 μg/m 3 , respectively) and from 16 school sites with moderate concentrations (means: 2.6, 32.2, and 5.7 μg/m 3 , respectively) were measured from 1996 to 1998. Statistical analysis of the data was performed using components of two different statistical models recently used to predict air pollution levels in comparable settings. Two traffic characteristics, traffic volume and traffic jam percentage, adequately described air pollutant concentrations (R 2 : 0.76-0.80, P=0.0001). This study shows that air pollutant concentrations can be accurately predicted by two traffic characteristics and that these models compare favorably with other more complex models in the literature
Comparison of predicted pesticide concentrations in groundwater from SCI-GROW and PRZM-GW models with historical monitoring data.

Science.gov (United States)

Estes, Tammara L; Pai, Naresh; Winchell, Michael F

2016-06-01

A key factor in the human health risk assessment process for the registration of pesticides by the US Environmental Protection Agency (EPA) is an estimate of pesticide concentrations in groundwater used for drinking water. From 1997 to 2011, these estimates were obtained from the EPA empirical model SCI-GROW. Since 2012, these estimates have been obtained from the EPA deterministic model PRZM-GW, which has resulted in a significant increase in estimated groundwater concentrations for many pesticides. Historical groundwater monitoring data from the National Ambient Water Quality Assessment (NAWQA) Program (1991-2014) were compared with predicted groundwater concentrations from both SCI-GROW (v.2.3) and PRZM-GW (v.1.07) for 66 different pesticides of varying environmental fate properties. The pesticide environmental fate parameters associated with over- and underprediction of groundwater concentrations by the two models were evaluated. In general, SCI-GROW2.3 predicted groundwater concentrations were close to maximum historically observed groundwater concentrations. However, for pesticides with soil organic carbon content values below 1000 L kg(-1) and no simulated hydrolysis, PRZM-GW overpredicted, often by greater than 100 ppb. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.
Modeling hydraulic conductivity and swelling pressure of several kinds of bentonites affected by concentration of saline water

International Nuclear Information System (INIS)

Tanaka, Yukihisa; Hasegawa, Takuma; Nakamura, Kunihiko

2007-01-01

In case of construction of repository for radioactive waste near the coastal area, the effect of brine on hydraulic conductivity of bentonite as an engineering barrier should be considered because it is known that the hydraulic conductivity of bentonite increases with increasing in salt concentration of water. Thus, the effect of salinity of water on hydraulic conductivity of bentonite has been conducted experimentally. However, it is necessary to elucidate and to model the mechanism of the phenomenon because various kinds of bentonites may possibly be placed in various salinity of salt water. In this study, a model for evaluating permeability of compacted bentonite is proposed considering a) increase in number of sheets of montomorillonite crystal because of cohesion, b) decrease in viscosity of water in interlayer between sheets of montmorillonite crystal. Quantitative evaluation method for permeability of several kinds of bentonite under brine is proposed based on the model mentioned above. (author)
Dissolved and labile concentrations of Cd, Cu, Pb, and Zn in the South Fork Coeur d'Alene River, Idaho: Comparisons among chemical equilibrium models and implications for biotic ligand models

Science.gov (United States)

Balistrieri, L.S.; Blank, R.G.

2008-01-01

In order to evaluate thermodynamic speciation calculations inherent in biotic ligand models, the speciation of dissolved Cd, Cu, Pb, and Zn in aquatic systems influenced by historical mining activities is examined using equilibrium computer models and the diffusive gradients in thin films (DGT) technique. Several metal/organic-matter complexation models, including WHAM VI, NICA-Donnan, and Stockholm Humic model (SHM), are used in combination with inorganic speciation models to calculate the thermodynamic speciation of dissolved metals and concentrations of metal associated with biotic ligands (e.g., fish gills). Maximum dynamic metal concentrations, determined from total dissolved metal concentrations and thermodynamic speciation calculations, are compared with labile metal concentrations measured by DGT to assess which metal/organic-matter complexation model best describes metal speciation and, thereby, biotic ligand speciation, in the studied systems. Results indicate that the choice of model that defines metal/organic-matter interactions does not affect calculated concentrations of Cd and Zn associated with biotic ligands for geochemical conditions in the study area, whereas concentrations of Cu and Pb associated with biotic ligands depend on whether the speciation calculations use WHAM VI, NICA-Donnan, or SHM. Agreement between labile metal concentrations and dynamic metal concentrations occurs when WHAM VI is used to calculate Cu speciation and SHM is used to calculate Pb speciation. Additional work in systems that contain wide ranges in concentrations of multiple metals should incorporate analytical speciation methods, such as DGT, to constrain the speciation component of biotic ligand models. ?? 2008 Elsevier Ltd.
SOME STATISTICAL ISSUES RELATED TO MULTIPLE LINEAR REGRESSION MODELING OF BEACH BACTERIA CONCENTRATIONS

Science.gov (United States)

As a fast and effective technique, the multiple linear regression (MLR) method has been widely used in modeling and prediction of beach bacteria concentrations. Among previous works on this subject, however, several issues were insufficiently or inconsistently addressed. Those is...
Validation and implementation of model based control strategies at an industrial wastewater treatment plant.

Science.gov (United States)

Demey, D; Vanderhaegen, B; Vanhooren, H; Liessens, J; Van Eyck, L; Hopkins, L; Vanrolleghem, P A

2001-01-01

In this paper, the practical implementation and validation of advanced control strategies, designed using model based techniques, at an industrial wastewater treatment plant is demonstrated. The plant under study is treating the wastewater of a large pharmaceutical production facility. The process characteristics of the wastewater treatment were quantified by means of tracer tests, intensive measurement campaigns and the use of on-line sensors. In parallel, a dynamical model of the complete wastewater plant was developed according to the specific kinetic characteristics of the sludge and the highly varying composition of the industrial wastewater. Based on real-time data and dynamic models, control strategies for the equalisation system, the polymer dosing and phosphorus addition were established. The control strategies are being integrated in the existing SCADA system combining traditional PLC technology with robust PC based control calculations. The use of intelligent control in wastewater treatment offers a wide spectrum of possibilities to upgrade existing plants, to increase the capacity of the plant and to eliminate peaks. This can result in a more stable and secure overall performance and, finally, in cost savings. The use of on-line sensors has a potential not only for monitoring concentrations, but also for manipulating flows and concentrations. This way the performance of the plant can be secured.
Prediction of a Therapeutic Dose for Buagafuran, a Potent Anxiolytic Agent by Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling Starting from Pharmacokinetics in Rats and Human

Directory of Open Access Journals (Sweden)

Fen Yang

2017-10-01

Full Text Available Physiologically based pharmacokinetic (PBPK/pharmacodynamic (PD models can contribute to animal-to-human extrapolation and therapeutic dose predictions. Buagafuran is a novel anxiolytic agent and phase I clinical trials of buagafuran have been completed. In this paper, a potentially effective dose for buagafuran of 30 mg t.i.d. in human was estimated based on the human brain concentration predicted by a PBPK/PD modeling. The software GastroPlusTM was used to build the PBPK/PD model for buagafuran in rat which related the brain tissue concentrations of buagafuran and the times of animals entering the open arms in the pharmacological model of elevated plus-maze. Buagafuran concentrations in human plasma were fitted and brain tissue concentrations were predicted by using a human PBPK model in which the predicted plasma profiles were in good agreement with observations. The results provided supportive data for the rational use of buagafuran in clinic.
Perturbation based Monte Carlo criticality search in density, enrichment and concentration

International Nuclear Information System (INIS)

Li, Zeguang; Wang, Kan; Deng, Jingkang

2015-01-01

Highlights: • A new perturbation based Monte Carlo criticality search method is proposed. • The method could get accurate results with only one individual criticality run. • The method is used to solve density, enrichment and concentration search problems. • Results show the feasibility and good performances of this method. • The relationship between results’ accuracy and perturbation order is discussed. - Abstract: Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Existing Monte Carlo criticality search methods need large amount of individual criticality runs and may have unstable results because of the uncertainties of criticality results. In this paper, a new perturbation based Monte Carlo criticality search method is proposed and discussed. This method only needs one individual criticality calculation with perturbation tallies to estimate k eff changing function using initial k eff and differential coefficients results, and solves polynomial equations to get the criticality search results. The new perturbation based Monte Carlo criticality search method is implemented in the Monte Carlo code RMC, and criticality search problems in density, enrichment and concentration are taken out. Results show that this method is quite inspiring in accuracy and efficiency, and has advantages compared with other criticality search methods
Optimized dispatch in a first-principles concentrating solar power production model

Energy Technology Data Exchange (ETDEWEB)

Wagner, Michael J.; Newman, Alexandra M.; Hamilton, William T.; Braun, Robert J.

2017-10-01

Concentrating solar power towers, which include a steam-Rankine cycle with molten salt thermal energy storage, is an emerging technology whose maximum effectiveness relies on an optimal operational and dispatch policy. Given parameters such as start-up and shut-down penalties, expected electricity price profiles, solar availability, and system interoperability requirements, this paper seeks a profit-maximizing solution that determines start-up and shut-down times for the power cycle and solar receiver, and the times at which to dispatch stored and instantaneous quantities of energy over a 48-h horizon at hourly fidelity. The mixed-integer linear program (MIP) is subject to constraints including: (i) minimum and maximum rates of start-up and shut-down, (ii) energy balance, including energetic state of the system as a whole and its components, (iii) logical rules governing the operational modes of the power cycle and solar receiver, and (iv) operational consistency between time periods. The novelty in this work lies in the successful integration of a dispatch optimization model into a detailed techno-economic analysis tool, specifically, the National Renewable Energy Laboratory's System Advisor Model (SAM). The MIP produces an optimized operating strategy, historically determined via a heuristic. Using several market electricity pricing profiles, we present comparative results for a system with and without dispatch optimization, indicating that dispatch optimization can improve plant profitability by 5-20% and thereby alter the economics of concentrating solar power technology. While we examine a molten salt power tower system, this analysis is equally applicable to the more mature concentrating solar parabolic trough system with thermal energy storage.

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