WorldWideScience

Sample records for solubility prediction based

  1. Predicting corrosion product transport in nuclear power stations using a solubility-based model for flow-accelerated corrosion

    International Nuclear Information System (INIS)

    Burrill, K.A.; Cheluget, E.L.

    1995-01-01

    A general model of solubility-driven flow-accelerated corrosion of carbon steel was derived based on the assumption that the solubilities of ferric oxyhydroxide and magnetite control the rate of film dissolution. This process involves the dissolution of an oxide film due to fast-flowing coolant unsaturated in iron. The soluble iron is produced by (i) the corrosion of base metal under a porous oxide film and (ii) the dissolution of the oxide film at the fluid-oxide film interface. The iron released at the pipe wall is transferred into the bulk flow by turbulent mass transfer. The model is suitable for calculating concentrations of dissolved iron in feedtrain lines. These iron levels were used to calculate sludge transport rates around the feedtrain. The model was used to predict sludge transport rates due to flow accelerated corrosion of major feedtrain piping in a CANDU reactor. The predictions of the model compare well with plant measurements

  2. Potable NIR spectroscopy predicting soluble solids content of pears based on LEDs

    Energy Technology Data Exchange (ETDEWEB)

    Liu Yande; Liu Wei; Sun Xudong; Gao Rongjie; Pan Yuanyuan; Ouyang Aiguo, E-mail: jxliuyd@163.com [School of Mechatronics Engineering, East China Jiaotong University, Changbei Open and Developing District, Nanchang, 330013 (China)

    2011-01-01

    A portable near-infrared (NIR) instrument was developed for predicting soluble solids content (SSC) of pears equipped with light emitting diodes (LEDs). NIR spectra were collected on the calibration and prediction sets (145:45). Relationships between spectra and SSC were developed by multivariate linear regression (MLR), partial least squares (PLS) and artificial neural networks (ANNs) in the calibration set. The 45 unknown pears were applied to evaluate the performance of them in terms of root mean square errors of prediction (RMSEP) and correlation coefficients (r). The best result was obtained by PLS with RMSEP of 0.62{sup 0}Brix and r of 0.82. The results showed that the SSC of pears could be predicted by the portable NIR instrument.

  3. Potable NIR spectroscopy predicting soluble solids content of pears based on LEDs

    International Nuclear Information System (INIS)

    Liu Yande; Liu Wei; Sun Xudong; Gao Rongjie; Pan Yuanyuan; Ouyang Aiguo

    2011-01-01

    A portable near-infrared (NIR) instrument was developed for predicting soluble solids content (SSC) of pears equipped with light emitting diodes (LEDs). NIR spectra were collected on the calibration and prediction sets (145:45). Relationships between spectra and SSC were developed by multivariate linear regression (MLR), partial least squares (PLS) and artificial neural networks (ANNs) in the calibration set. The 45 unknown pears were applied to evaluate the performance of them in terms of root mean square errors of prediction (RMSEP) and correlation coefficients (r). The best result was obtained by PLS with RMSEP of 0.62 0 Brix and r of 0.82. The results showed that the SSC of pears could be predicted by the portable NIR instrument.

  4. Scoring function to predict solubility mutagenesis

    Directory of Open Access Journals (Sweden)

    Deutsch Christopher

    2010-10-01

    Full Text Available Abstract Background Mutagenesis is commonly used to engineer proteins with desirable properties not present in the wild type (WT protein, such as increased or decreased stability, reactivity, or solubility. Experimentalists often have to choose a small subset of mutations from a large number of candidates to obtain the desired change, and computational techniques are invaluable to make the choices. While several such methods have been proposed to predict stability and reactivity mutagenesis, solubility has not received much attention. Results We use concepts from computational geometry to define a three body scoring function that predicts the change in protein solubility due to mutations. The scoring function captures both sequence and structure information. By exploring the literature, we have assembled a substantial database of 137 single- and multiple-point solubility mutations. Our database is the largest such collection with structural information known so far. We optimize the scoring function using linear programming (LP methods to derive its weights based on training. Starting with default values of 1, we find weights in the range [0,2] so that predictions of increase or decrease in solubility are optimized. We compare the LP method to the standard machine learning techniques of support vector machines (SVM and the Lasso. Using statistics for leave-one-out (LOO, 10-fold, and 3-fold cross validations (CV for training and prediction, we demonstrate that the LP method performs the best overall. For the LOOCV, the LP method has an overall accuracy of 81%. Availability Executables of programs, tables of weights, and datasets of mutants are available from the following web page: http://www.wsu.edu/~kbala/OptSolMut.html.

  5. Predictive value of serum soluble corin in the risk of hyperglycemia: A population-based prospective cohort study in China.

    Science.gov (United States)

    Zhu, Zhengbao; Zhang, Qiu; Peng, Hao; Zhong, Chongke; Guo, Daoxia; Huangfu, Xinfeng; Chao, Xiangqin; Wang, Aili; Jin, Jianhua; Zhang, Yonghong

    2018-04-01

    Serum soluble corin has been suggested to be associated with hyperglycemia by cross-sectional study. However, the prospective relationship between them remains unclear, and whether lipid component influences the relationship between them has not yet been studied. A total of 1961 participants who were free from hyperglycemia were enrolled at baseline in 2010. The serum soluble corin concentrations were measured at baseline and all participants were followed up for hyperglycemia in 2014. The association between serum soluble corin and hyperglycemia incidence was appreciably modified by high density lipoprotein cholesterol (HDL-C) (P interaction  = 0.04). Elevated serum soluble corin was associated with the risk of hyperglycemia only in the HDL-C ≥1.04 mmol/l subgroup rather than all participants. In participants with HDL-C ≥1.04 mmol/l, the adjusted odds ratio (95% CU) of hyperglycemia associated with the fourth quartiles of corin was 1.78 (1.08-2.94) compared with the lowest quartile of serum soluble corin, and there was a positive linear dose-response relationship between them (P for linearity <0.01). The ordinal analysis showed an association between serum soluble corin and hyperglycemia severity (adjusted OR, 1.81; 95% CI, 1.10-2.99; P trend  = 0.02, when 2 extreme quartiles were compared). The addition of serum soluble corin to conventional risk factors improved risk prediction for hyperglycemia (net reclassification index: 0.16; integrated discrimination improvement: 0.01) in participants with HDL-C ≥1.04 mmol/l. Serum soluble corin might be a valuable biomarker in prediction of future hyperglycemia in population with HDL-C ≥1.04 mmol/l, suggesting that corin might play a potential role in glucose metabolism. Copyright © 2018 Elsevier B.V. All rights reserved.

  6. Method for Predicting Solubilities of Solids in Mixed Solvents

    DEFF Research Database (Denmark)

    Ellegaard, Martin Dela; Abildskov, Jens; O'Connell, J. P.

    2009-01-01

    A method is presented for predicting solubilities of solid solutes in mixed solvents, based on excess Henry's law constants. The basis is statistical mechanical fluctuation solution theory for composition derivatives of solute/solvent infinite dilution activity coefficients. Suitable approximatio...

  7. Prediction of the solubility in lipidic solvent mixture: Investigation of the modeling approach and thermodynamic analysis of solubility.

    Science.gov (United States)

    Patel, Shruti V; Patel, Sarsvatkumar

    2015-09-18

    Self-micro emulsifying drug delivery system (SMEDDS) is one of the methods to improve solubility and bioavailability of poorly soluble drug(s). The knowledge of the solubility of pharmaceuticals in pure lipidic solvents and solvent mixtures is crucial for designing the SMEDDS of poorly soluble drug substances. Since, experiments are very time consuming, a model, which allows for solubility predictions in solvent mixtures based on less experimental data is desirable for efficiency. Solvents employed were Labrafil® M1944CS and Labrasol® as lipidic solvents; Capryol-90®, Capryol-PGMC® and Tween®-80 as surfactants; Transcutol® and PEG-400 as co-solvents. Solubilities of both drugs were determined in single solvent systems at temperature (T) range of 283-333K. In present study, we investigated the applicability of the thermodynamic model to understand the solubility behavior of drugs in the lipiodic solvents. By using the Van't Hoff and general solubility theory, the thermodynamic functions like Gibbs free energy, enthalpy and entropy of solution, mixing and solvation for drug in single and mixed solvents were understood. The thermodynamic parameters were understood in the framework of drug-solvent interaction based on their chemical similarity and dissimilarity. Clotrimazole and Fluconazole were used as active ingredients whose solubility was measured in single solvent as a function of temperature and the data obtained were used to derive mathematical models which can predict solubility in multi-component solvent mixtures. Model dependent parameters for each drug were calculated at each temperature. The experimental solubility data of solute in mixed solvent system were measured experimentally and further correlated with the calculates values obtained from exponent model and log-linear model of Yalkowsky. The good correlation was observed between experimental solubility and predicted solubility. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. A bi-layer model for nondestructive prediction of soluble solids content in apple based on reflectance spectra and peel pigments.

    Science.gov (United States)

    Tian, Xi; Li, Jiangbo; Wang, Qingyan; Fan, Shuxiang; Huang, Wenqian

    2018-01-15

    Hyperspectral imaging technology was used to investigate the effect of various peel colors on soluble solids content (SSC) prediction model and build a SSC model insensitive to the color distribution of apple peel. The SSC and peel pigments were measured, effective wavelengths (EWs) of SSC and pigments were selected from the acquired hyperspectral images of the intact and peeled apple samples, respectively. The effect of pigments on the SSC prediction was studied and optimal SSC EWs were selected from the peel-flesh layers spectra after removing the chlorophyll and anthocyanin EWs. Then, the optimal bi-layer model for SSC prediction was built based on the finally selected optimal SSC EWs. Results showed that the correlation coefficient of prediction, root mean square error of prediction and selected bands of the bi-layer model were 0.9560, 0.2528 and 41, respectively, which will be more acceptable for future online SSC prediction of various colors of apple. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Evaluation of the performance and limitations of empirical partition-relations and process based multisurface models to predict trace element solubility in soils

    Energy Technology Data Exchange (ETDEWEB)

    Groenenberg, J.E.; Bonten, L.T.C. [Alterra, Wageningen UR, P.O. Box 47, 6700 AA Wageningen (Netherlands); Dijkstra, J.J. [Energy research Centre of the Netherlands ECN, P.O. Box 1, 1755 ZG Petten (Netherlands); De Vries, W. [Department of Environmental Systems Analysis, Wageningen University, Wageningen UR, P.O. Box 47, 6700 AA Wageningen (Netherlands); Comans, R.N.J. [Department of Soil Quality, Wageningen University, Wageningen UR, P.O. Box 47, 6700 AA Wageningen (Netherlands)

    2012-07-15

    Here we evaluate the performance and limitations of two frequently used model-types to predict trace element solubility in soils: regression based 'partition-relations' and thermodynamically based 'multisurface models', for a large set of elements. For this purpose partition-relations were derived for As, Ba, Cd, Co, Cr, Cu, Mo, Ni, Pb, Sb, Se, V, Zn. The multi-surface model included aqueous speciation, mineral equilibria, sorption to organic matter, Fe/Al-(hydr)oxides and clay. Both approaches were evaluated by their application to independent data for a wide variety of conditions. We conclude that Freundlich-based partition-relations are robust predictors for most cations and can be used for independent soils, but within the environmental conditions of the data used for their derivation. The multisurface model is shown to be able to successfully predict solution concentrations over a wide range of conditions. Predicted trends for oxy-anions agree well for both approaches but with larger (random) deviations than for cations.

  10. Prediction of pH-dependent aqueous solubility of druglike molecules

    DEFF Research Database (Denmark)

    Hansen, Niclas Tue; Kouskoumvekaki, Irene; Jørgensen, Flemming Steen

    2012-01-01

    In the present work, the Henderson-Hasselbalch (HH) equation has been employed for the development of a tool for the prediction of pH-dependent aqueous solubility of drugs and drug candidates. A new prediction method for the intrinsic solubility was developed, based on artificial neural networks...

  11. A fast-running core prediction model based on neural networks for load-following operations in a soluble boron-free reactor

    Energy Technology Data Exchange (ETDEWEB)

    Jang, Jin-wook [Korea Atomic Energy Research Institute, P.O. Box 105, Yusong, Daejon 305-600 (Korea, Republic of)], E-mail: Jinwook@kaeri.re.kr; Seong, Seung-Hwan [Korea Atomic Energy Research Institute, P.O. Box 105, Yusong, Daejon 305-600 (Korea, Republic of)], E-mail: shseong@kaeri.re.kr; Lee, Un-Chul [Department of Nuclear Engineering, Seoul National University, Shinlim-Dong, Gwanak-Gu, Seoul 151-742 (Korea, Republic of)

    2007-09-15

    A fast prediction model for load-following operations in a soluble boron-free reactor has been proposed, which can predict the core status when three or more control rod groups are moved at a time. This prediction model consists of two multilayer feedforward neural network models to retrieve the axial offset and the reactivity, and compensation models to compensate for the reactivity and axial offset arising from the xenon transient. The neural network training data were generated by taking various overlaps among the control rod groups into consideration for training the neural network models, and the accuracy of the constructed neural network models was verified. Validation results of predicting load following operations for a soluble boron-free reactor show that this model has a good capability to predict the positions of the control rods for sustaining the criticality of a core during load-following operations to ensure that the tolerable axial offset band is not exceeded and it can provide enough corresponding time for the operators to take the necessary actions to prevent a deviation from the tolerable operating band.

  12. A fast-running core prediction model based on neural networks for load-following operations in a soluble boron-free reactor

    International Nuclear Information System (INIS)

    Jang, Jin-wook; Seong, Seung-Hwan; Lee, Un-Chul

    2007-01-01

    A fast prediction model for load-following operations in a soluble boron-free reactor has been proposed, which can predict the core status when three or more control rod groups are moved at a time. This prediction model consists of two multilayer feedforward neural network models to retrieve the axial offset and the reactivity, and compensation models to compensate for the reactivity and axial offset arising from the xenon transient. The neural network training data were generated by taking various overlaps among the control rod groups into consideration for training the neural network models, and the accuracy of the constructed neural network models was verified. Validation results of predicting load following operations for a soluble boron-free reactor show that this model has a good capability to predict the positions of the control rods for sustaining the criticality of a core during load-following operations to ensure that the tolerable axial offset band is not exceeded and it can provide enough corresponding time for the operators to take the necessary actions to prevent a deviation from the tolerable operating band

  13. HIGH PRESSURE PHASE EQUILIBRIUM: PREDICTION OF ESSENTIAL OIL SOLUBILITY

    Directory of Open Access Journals (Sweden)

    Lúcio CARDOZO-FILHO

    1997-12-01

    Full Text Available This work describes a method to predict the solubility of essential oils in supercritical carbon dioxide. The method is based on the formulation proposed in 1979 by Asselineau, Bogdanic and Vidal. The Peng-Robinson and Soave-Redlich-Kwong cubic equations of state were used with the van der Waals mixing rules with two interaction parameters. Method validation was accomplished calculating orange essential oil solubility in pressurized carbon dioxide. The solubility of orange essential oil in carbon dioxide calculated at 308.15 K for pressures of 50 to 70 bar varied from 1.7± 0.1 to 3.6± 0.1 mg/g. For same the range of conditions, experimental solubility varied from 1.7± 0.1 to 3.6± 0.1 mg/g. Predicted values were not very sensitive to initial oil composition.Este trabalho descreve uma metodologia para o cálculo da solubilidade de óleos essenciais em dióxido de carbono a altas pressões baseada na formulação proposta em 1979 por Asselineau, Bogdanic e Vidal. Foram utilizadas as equações cúbicas de estado de Peng-Robinson e Soave-Redlich-Kwong com regras de mistura de van der Waals com dois parâmetros de interação. O cálculo da solubilidade do óleo essencial de laranja em dióxido de carbono pressurizado foi usado para validação do método. A solubilidade calculada a 308,15 K para pressões entre 50 e 70 bar variou entre 1,5 e 4,1 mg/g. Valores experimentais para as mesmas condições variam entre 1,7± 0.1 a 3,6± 0.1 mg/g. Os valores preditos não são muito sensíveis à composição inicial do óleo essencial.

  14. Nitrogen solubility in nickel base multicomponent melts

    International Nuclear Information System (INIS)

    Bol'shov, L.A.; Stomakhin, A.Ya.; Sokolov, V.M.; Teterin, V.G.

    1984-01-01

    Applicability of various methods for calculation of nitrogen solubility in high-alloyed nickel base alloys, containing Cr, Fe, W, Mo, Ti, Nb, has been estimated. A possibility is shown to use the formUla, derived for the calculation of nitrogen solubility in iron on the basis of statistical theory for a grid model of solution which does not require limitations for the content of a solvent component. The calculation method has been used for nickel alloys, with the concentration of solvent, iron, being accepted equal to zero, and employing parameters of nitrogen interaction as determined for iron-base alloys

  15. Decision trees to characterise the roles of permeability and solubility on the prediction of oral absorption.

    Science.gov (United States)

    Newby, Danielle; Freitas, Alex A; Ghafourian, Taravat

    2015-01-27

    Oral absorption of compounds depends on many physiological, physiochemical and formulation factors. Two important properties that govern oral absorption are in vitro permeability and solubility, which are commonly used as indicators of human intestinal absorption. Despite this, the nature and exact characteristics of the relationship between these parameters are not well understood. In this study a large dataset of human intestinal absorption was collated along with in vitro permeability, aqueous solubility, melting point, and maximum dose for the same compounds. The dataset allowed a permeability threshold to be established objectively to predict high or low intestinal absorption. Using this permeability threshold, classification decision trees incorporating a solubility-related parameter such as experimental or predicted solubility, or the melting point based absorption potential (MPbAP), along with structural molecular descriptors were developed and validated to predict oral absorption class. The decision trees were able to determine the individual roles of permeability and solubility in oral absorption process. Poorly permeable compounds with high solubility show low intestinal absorption, whereas poorly water soluble compounds with high or low permeability may have high intestinal absorption provided that they have certain molecular characteristics such as a small polar surface or specific topology. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  16. Alternative Bio-Based Solvents for Extraction of Fat and Oils: Solubility Prediction, Global Yield, Extraction Kinetics, Chemical Composition and Cost of Manufacturing

    Directory of Open Access Journals (Sweden)

    Anne-Gaëlle Sicaire

    2015-04-01

    Full Text Available The present study was designed to evaluate the performance of alternative bio-based solvents, more especially 2-methyltetrahydrofuran, obtained from crop’s byproducts for the substitution of petroleum solvents such as hexane in the extraction of fat and oils for food (edible oil and non-food (bio fuel applications. First a solvent selection as well as an evaluation of the performance was made with Hansen Solubility Parameters and the COnductor-like Screening MOdel for Realistic Solvation (COSMO-RS simulations. Experiments were performed on rapeseed oil extraction at laboratory and pilot plant scale for the determination of lipid yields, extraction kinetics, diffusion modeling, and complete lipid composition in term of fatty acids and micronutrients (sterols, tocopherols and tocotrienols. Finally, economic and energetic evaluations of the process were conducted to estimate the cost of manufacturing using 2-methyltetrahydrofuran (MeTHF as alternative solvent compared to hexane as petroleum solvent.

  17. Solubility Temperature Dependence Predicted from 2D Structure

    Directory of Open Access Journals (Sweden)

    Alex Avdeef

    2015-12-01

    Full Text Available The objective of the study was to find a computational procedure to normalize solubility data determined at various temperatures (e.g., 10 – 50 oC to values at a “reference” temperature (e.g., 25 °C. A simple procedure was devised to predict enthalpies of solution, ΔHsol, from which the temperature dependence of intrinsic (uncharged form solubility, log S0, could be calculated. As dependent variables, values of ΔHsol at 25 °C were subjected to multiple linear regression (MLR analysis, using melting points (mp and Abraham solvation descriptors. Also, the enthalpy data were subjected to random forest regression (RFR and recursive partition tree (RPT analyses. A total of 626 molecules were examined, drawing on 2040 published solubility values measured at various temperatures, along with 77 direct calori    metric measurements. The three different prediction methods (RFR, RPT, MLR all indicated that the estimated standard deviations in the enthalpy data are 11-15 kJ mol-1, which is concordant with the 10 kJ mol-1 propagation error estimated from solubility measurements (assuming 0.05 log S errors, and consistent with the 7 kJ mol-1 average reproducibility in enthalpy values from interlaboratory replicates. According to the MLR model, higher values of mp, H‑bond acidity, polarizability/dipolarity, and dispersion forces relate to more positive (endothermic enthalpy values. However, molecules that are large and have high H-bond basicity are likely to possess negative (exothermic enthalpies of solution. With log S0 values normalized to 25 oC, it was shown that the interlaboratory average standard deviations in solubility measurement are reduced to 0.06 ‑ 0.17 log unit, with higher errors for the least-soluble druglike molecules. Such improvements in data mining are expected to contribute to more reliable in silico prediction models of solubility for use in drug discovery.

  18. Can human experts predict solubility better than computers?

    Science.gov (United States)

    Boobier, Samuel; Osbourn, Anne; Mitchell, John B O

    2017-12-13

    In this study, we design and carry out a survey, asking human experts to predict the aqueous solubility of druglike organic compounds. We investigate whether these experts, drawn largely from the pharmaceutical industry and academia, can match or exceed the predictive power of algorithms. Alongside this, we implement 10 typical machine learning algorithms on the same dataset. The best algorithm, a variety of neural network known as a multi-layer perceptron, gave an RMSE of 0.985 log S units and an R 2 of 0.706. We would not have predicted the relative success of this particular algorithm in advance. We found that the best individual human predictor generated an almost identical prediction quality with an RMSE of 0.942 log S units and an R 2 of 0.723. The collection of algorithms contained a higher proportion of reasonably good predictors, nine out of ten compared with around half of the humans. We found that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median generated excellent predictivity. While our consensus human predictor achieved very slightly better headline figures on various statistical measures, the difference between it and the consensus machine learning predictor was both small and statistically insignificant. We conclude that human experts can predict the aqueous solubility of druglike molecules essentially equally well as machine learning algorithms. We find that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median is a powerful way of benefitting from the wisdom of crowds.

  19. Measurement and prediction of the solubility of acid gases in monoethanolamine solutions at low partial pressures

    Energy Technology Data Exchange (ETDEWEB)

    Nasir, P; Mather, A E

    1977-12-01

    An apparatus for the determination of the solubility of hydrogen sulfide, carbon dioxide, and their mixtures in ethanolamine solutions at low pressures is described. With this apparatus, the solubility of H/sub 2/S, CO/sub 2/ and their mixtures in aqueous solutions of monoethanolamine was measured at partial pressures between 0.001 kPa and 9 kPa at temperatures of 80 and 100/sup 0/C. The results for the mixture were compared with two methods of prediction based on a thermodynamic model. 6 figures, 4 tables.

  20. Comparative Study of Different Methods for the Prediction of Drug-Polymer Solubility

    DEFF Research Database (Denmark)

    Knopp, Matthias Manne; Tajber, Lidia; Tian, Yiwei

    2015-01-01

    monomer weight ratios. The drug–polymer solubility at 25 °C was predicted using the Flory–Huggins model, from data obtained at elevated temperature using thermal analysis methods based on the recrystallization of a supersaturated amorphous solid dispersion and two variations of the melting point......, which suggests that this method can be used as an initial screening tool if a liquid analogue is available. The learnings of this important comparative study provided general guidance for the selection of the most suitable method(s) for the screening of drug–polymer solubility....

  1. Soluble L-selectin levels predict survival in sepsis

    DEFF Research Database (Denmark)

    Seidelin, Jakob B; Nielsen, Ole H; Strøm, Jens

    2002-01-01

    To evaluate serum soluble L-selectin as a prognostic factor for survival in patients with sepsis.......To evaluate serum soluble L-selectin as a prognostic factor for survival in patients with sepsis....

  2. Measurement and ANN prediction of pH-dependent solubility of nitrogen-heterocyclic compounds.

    Science.gov (United States)

    Sun, Feifei; Yu, Qingni; Zhu, Jingke; Lei, Lecheng; Li, Zhongjian; Zhang, Xingwang

    2015-09-01

    Based on the solubility of 25 nitrogen-heterocyclic compounds (NHCs) measured by saturation shake-flask method, artificial neural network (ANN) was employed to the study of the quantitative relationship between the structure and pH-dependent solubility of NHCs. With genetic algorithm-multivariate linear regression (GA-MLR) approach, five out of the 1497 molecular descriptors computed by Dragon software were selected to describe the molecular structures of NHCs. Using the five selected molecular descriptors as well as pH and the partial charge on the nitrogen atom of NHCs (QN) as inputs of ANN, a quantitative structure-property relationship (QSPR) model without using Henderson-Hasselbalch (HH) equation was successfully developed to predict the aqueous solubility of NHCs in different pH water solutions. The prediction model performed well on the 25 model NHCs with an absolute average relative deviation (AARD) of 5.9%, while HH approach gave an AARD of 36.9% for the same model NHCs. It was found that QN played a very important role in the description of NHCs and, with QN, ANN became a potential tool for the prediction of pH-dependent solubility of NHCs. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Prediction of non-polar gas solubilities in water, alcohols and aqueous alcohol solutions by the modified ASOG method

    Energy Technology Data Exchange (ETDEWEB)

    Tochigi, K.; Kojima, K.

    1982-07-01

    This study evaluated a technique for predicting gas solubilities based on a modified ASOG group-contribution method, considering water, alcohols, and aqueous alcohol solutions as the solvents. The nonpolar gaseous solutes considered were oxygen, nitrogen, hydrogen, carbon dioxide, argon, methane, ethane, ethylene, propane, and butane. Gas solubilities were correlated and predicted for a partial gas pressure of 1 atm and a temperature range of 50/sup 0/-100/sup 0/F (10/sup 0/-40/sup 0/C) in pure solvents, and then predicted for the same pressure and temperature range in mixed solvents using only the solubility data for the pure solvents. The deviations between the observed and predicted solubilities averaged 6.0% in pure systems and 10.2% in mixed solvents.

  4. Predicting water solubility of congeners: Chloronaphthalenes-A case study

    Energy Technology Data Exchange (ETDEWEB)

    Puzyn, Tomasz, E-mail: puzi@qsar.eu.org [Faculty of Chemistry, University of Gdansk, Sobieskiego 18, 80-952 Gdansk (Poland); Mostrag, Aleksandra; Falandysz, Jerzy [Faculty of Chemistry, University of Gdansk, Sobieskiego 18, 80-952 Gdansk (Poland); Kholod, Yana; Leszczynski, Jerzy [NSF CREST Nanotoxicity Center, Department of Chemistry, Jackson State University, 1325 Lynch St, Jackson, MS 39217-0510 (United States)

    2009-10-30

    Since the important physicochemical data for chloronaphtalenes (PCNs) are still scarce, we have predicted water solubility (log S) of all 75 congeners with the Quantitative Structure-Property Relationship (QSPR) scheme. The values of log S, predicted by the most efficient model, varied from 0.01 to 1660 {mu}g dm{sup -3} (2.85 x 10{sup -11}-1.02 x 10{sup -5} mol dm{sup -3}), depending on the number of chlorine atoms present in the molecule and the substitution pattern. We found that the main factor determining relative differences in solubility between the congeners is the solvent accessible volume related to the cavitation process occurring in the solvent. The results are presented as a case study of QSPR modeling for those Persistent Organic Pollutants (POPs) that exist as families of congeners. By investigating the impact of (i) the way of the molecular descriptors' calculation, (ii) the size of applied database and (iii) chemometric method of modeling (Multiple Linear Regression, MLR, and/or Partial Least Squares regression, PLS) on the quality of the models we proposed general recommendations for dealing with congeners. We found that the combination of the B3LYP functional with 6-311++G(d,p) basis set was the most optimal technique of the molecular descriptors' calculation for congeners when comparing with semi-empirical PM3, ab initio Hartee-Fock (HF), and Moller-Pleset 2 (MP2) method carried out with different-size basis sets. Moreover, the model developed with a larger and more general database that includes chloronaphthalenes, polychlorinated dibezno-p-dioxins, furans and biphenyls predicted the values of log S for PCNs noticeable worse than the model calibrated only on PCNs. In the later case it was possible to obtain satisfactory results by employing even the simplest MLR method and only one molecular descriptor. The values of log S were also calculated with the WSKOWIN and COSMO-RS models as the reference techniques and then compared to our

  5. Predicting water solubility of congeners: Chloronaphthalenes-A case study

    International Nuclear Information System (INIS)

    Puzyn, Tomasz; Mostrag, Aleksandra; Falandysz, Jerzy; Kholod, Yana; Leszczynski, Jerzy

    2009-01-01

    Since the important physicochemical data for chloronaphtalenes (PCNs) are still scarce, we have predicted water solubility (log S) of all 75 congeners with the Quantitative Structure-Property Relationship (QSPR) scheme. The values of log S, predicted by the most efficient model, varied from 0.01 to 1660 μg dm -3 (2.85 x 10 -11 -1.02 x 10 -5 mol dm -3 ), depending on the number of chlorine atoms present in the molecule and the substitution pattern. We found that the main factor determining relative differences in solubility between the congeners is the solvent accessible volume related to the cavitation process occurring in the solvent. The results are presented as a case study of QSPR modeling for those Persistent Organic Pollutants (POPs) that exist as families of congeners. By investigating the impact of (i) the way of the molecular descriptors' calculation, (ii) the size of applied database and (iii) chemometric method of modeling (Multiple Linear Regression, MLR, and/or Partial Least Squares regression, PLS) on the quality of the models we proposed general recommendations for dealing with congeners. We found that the combination of the B3LYP functional with 6-311++G(d,p) basis set was the most optimal technique of the molecular descriptors' calculation for congeners when comparing with semi-empirical PM3, ab initio Hartee-Fock (HF), and Moller-Pleset 2 (MP2) method carried out with different-size basis sets. Moreover, the model developed with a larger and more general database that includes chloronaphthalenes, polychlorinated dibezno-p-dioxins, furans and biphenyls predicted the values of log S for PCNs noticeable worse than the model calibrated only on PCNs. In the later case it was possible to obtain satisfactory results by employing even the simplest MLR method and only one molecular descriptor. The values of log S were also calculated with the WSKOWIN and COSMO-RS models as the reference techniques and then compared to our results.

  6. Predictions of flavonoid solubility in ionic liquids by COSMO-RS: experimental verification, structural elucidation, and solvation characterization

    DEFF Research Database (Denmark)

    Guo, Zheng; Lue, Bena-Marie; Thomsen, Kaj

    2007-01-01

    Predictions of the solubility of flavonoids in a large variety of ionic liquids (ILs) with over 1800 available structures were examined based on COSMO-RS computation. The results show that the solubilities of flavonoids are strongly anion-dependent. Experimental measurement of the solubilities...... of esculin and rutin in 12 ILs with varying anions and cations show that predicted and experimental results generally have a good agreement. Based on the sound physical basis of COSMO-RS, the solubility changes of flavonoids were quantitatively associated with solvation interactions and structural...... characteristics of ILs. COSMO-RS derived parameters, i.e. misfit, H-bonding and van der Waals interaction energy, are shown to be capable of characterizing the complicated multiple interactions in the IL system effectively. H-bonding interaction is the most dominant interaction for ILs (followed by misfit and van...

  7. Investigation of samarium solubility in the magnesium based solid solution

    International Nuclear Information System (INIS)

    Rokhlin, L.L.; Padezhnova, E.M.; Guzej, L.S.

    1976-01-01

    Electric resistance measurements and microscopic analysis were used to investigate the solubility of samarium in a magnesium-based solid solution. The constitutional diagram Mg-Sm on the magnesium side is of an eutectic type with the temperature of the eutectic transformation of 542 deg C. Samarium is partly soluble in solid magnesium, the less so, the lower is the temperature. The maximum solubility of samarium in magnesium (at the eutectic transformation point) is 5.8 % by mass (0.99 at. %). At 200 deg C, the solubility of samarium in magnesium is 0.4 % by mass (0.063 at. %)

  8. Water-soluble resorcin[4]arene based cavitands

    NARCIS (Netherlands)

    Grote gansey, M.H.B.; Grote Gansey, Marcel H.B.; Bakker, Frank K.G.; Feiters, Martinus C.; Geurts, Hubertus P.M.; Verboom, Willem; Reinhoudt, David

    1998-01-01

    Water-soluble resorcin[4]arene based cavitands were obtained in good yields by reaction of bromomethylcavitands with pyridine. Their solubility was determined by conductometry. The behaviour in water depends on the alkyl chain length; the methylcavitand does not aggregate, whereas the pentyl- and

  9. Temperature dependence of nitrogen solubility in iron base multicomponent melts

    International Nuclear Information System (INIS)

    Sokolov, V.M.; Koval'chuk, L.A.

    1986-01-01

    Method for calculating temperature dependence of nitrogen solubility in iron base multicomponent melts is suggested. Application areas of existing methods were determined and advantages of the new method for calculating nitrogen solubility in multicomponent-doped iron melts (Fe-Ni-Cr-Mo, Fe-Ni-Cr-Mn, Fe-Mo-V) at 1773-2073 K are shown

  10. Predicting pear (cv. Clara Frijs) dry matter and soluble solids content with near infrared spectroscopy

    DEFF Research Database (Denmark)

    Travers, Sylvia; Bertelsen, Marianne; Petersen, Karen

    2014-01-01

    Regression models for predicting preharvest dry matter (DM) and soluble solids content (SSC), based on two spectral ranges (680-1000 nm and 1100-2350 nm), were compared. Models based on longer NIR spectra were more successful for both parameters (DM/SSC: R2 = 0.78-0.84; RMECV = 0.78/0.44; LVs = 6....../7). SSC prediction was better than expected considering the presence of starch in fruit. Generally poor SSC prediction in the presence of starch could be related to the inability of models to distinguish between forms of carbohydrate. Variable selection and regression coefficients highlighted...... fruit. Further research is needed to qualify and build on the results presented here....

  11. WHIM-3D-QSPR APPROACH FOR PREDICTING AQUEOUS SOLUBILITY OF CHLORINATED HYDROCARBONS

    Directory of Open Access Journals (Sweden)

    Oman Zuas

    2010-06-01

    Full Text Available The weighted holistic invariant molecular-three dimensional-quantitative structure property relationship (WHIM-3D-QSPR approach has been applied to the study of the aqueous solubility (- log Sw of chlorinated hydrocarbon compounds (CHC's. The obtained QSPR model is predictive and only requires four WHIM-3D descriptors in the calculation. The correlation equation of the model that is based on a training set of 50 CHC's compound has statistical parameters: standard coefficient correlation (R2 = 0.948; cross-validated correlation coefficients (Q2 = 0.935; Standard Error of Validation (SEV = 0.35; and average absolute error (AAE = 0.31. The application of the best model to a testing set of 50 CHC's demonstrates a reliable result with good predictability. Besides, it was possible to construct new model by applying WHIM-3D-QSPR approach without require any experimental physicochemical properties in the calculation of aqueous solubility.   Keywords: WHIM-3D; QSPR; aqueous solubility; - Log Sw, chlorinated hydrocarbons, CHC's

  12. Le Chatelier's Principle and the Prediction Temperature on Solubilities.

    Science.gov (United States)

    Fernandez-Prini, R.

    1982-01-01

    Discusses Le Chatelier's Principle from a thermodynamic perspective and applies it to the effect of temperature on the solubility of gases in liquids. Rationale of this discussion is to evaluate data in a previous article claimed to be contradictory to the Principle. (Author/JN)

  13. Predicting the Solubility of 1,1-Difluoroethane in Polystyrene Using the Perturbed Soft Chain Theory

    DEFF Research Database (Denmark)

    Pretel, Eduardo; Hong, Seong-Uk

    1998-01-01

    In this study, the solubility of 1,1-difluoroethane in polystyrene was correlated and predicted using the Perturbed Soft Chain Theory (PSCT) and compared with experimental data from the literature. For correlation, a binary interaction parameter was determined by using experimental solubility data...

  14. Limitations of polyethylene glycol-induced precipitation as predictive tool for protein solubility during formulation development.

    Science.gov (United States)

    Hofmann, Melanie; Winzer, Matthias; Weber, Christian; Gieseler, Henning

    2018-05-01

    Polyethylene glycol (PEG)-induced protein precipitation is often used to extrapolate apparent protein solubility at specific formulation compositions. The procedure was used for several fields of application such as protein crystal growth but also protein formulation development. Nevertheless, most studies focused on applicability in protein crystal growth. In contrast, this study focuses on applicability of PEG-induced precipitation during high-concentration protein formulation development. In this study, solubility of three different model proteins was investigated over a broad range of pH. Solubility values predicted by PEG-induced precipitation were compared to real solubility behaviour determined by either turbidity or content measurements. Predicted solubility by PEG-induced precipitation was confirmed for an Fc fusion protein and a monoclonal antibody. In contrast, PEG-induced precipitation failed to predict solubility of a single-domain antibody construct. Applicability of PEG-induced precipitation as indicator of protein solubility during formulation development was found to be not valid for one of three model molecules. Under certain conditions, PEG-induced protein precipitation is not valid for prediction of real protein solubility behaviour. The procedure should be used carefully as tool for formulation development, and the results obtained should be validated by additional investigations. © 2017 Royal Pharmaceutical Society.

  15. A review of machine learning methods to predict the solubility of overexpressed recombinant proteins in Escherichia coli.

    Science.gov (United States)

    Habibi, Narjeskhatoon; Mohd Hashim, Siti Z; Norouzi, Alireza; Samian, Mohammed Razip

    2014-05-08

    Over the last 20 years in biotechnology, the production of recombinant proteins has been a crucial bioprocess in both biopharmaceutical and research arena in terms of human health, scientific impact and economic volume. Although logical strategies of genetic engineering have been established, protein overexpression is still an art. In particular, heterologous expression is often hindered by low level of production and frequent fail due to opaque reasons. The problem is accentuated because there is no generic solution available to enhance heterologous overexpression. For a given protein, the extent of its solubility can indicate the quality of its function. Over 30% of synthesized proteins are not soluble. In certain experimental circumstances, including temperature, expression host, etc., protein solubility is a feature eventually defined by its sequence. Until now, numerous methods based on machine learning are proposed to predict the solubility of protein merely from its amino acid sequence. In spite of the 20 years of research on the matter, no comprehensive review is available on the published methods. This paper presents an extensive review of the existing models to predict protein solubility in Escherichia coli recombinant protein overexpression system. The models are investigated and compared regarding the datasets used, features, feature selection methods, machine learning techniques and accuracy of prediction. A discussion on the models is provided at the end. This study aims to investigate extensively the machine learning based methods to predict recombinant protein solubility, so as to offer a general as well as a detailed understanding for researches in the field. Some of the models present acceptable prediction performances and convenient user interfaces. These models can be considered as valuable tools to predict recombinant protein overexpression results before performing real laboratory experiments, thus saving labour, time and cost.

  16. SOLUBILITY PREDICTION OF SULFONAMIDES AT VARIOUS TEMPERATURES USING A SINGLE DETERMINATION

    Directory of Open Access Journals (Sweden)

    JALAL HANAEE

    2005-04-01

    Full Text Available Solubility of sulphamethoxazole, sulphisoxazole and sulphasalazine in six solvents namely water,methanol, ethanol, 1-propanol, acetone and chloroform were determined at 15, 25, 37 and 45 °C. Two models derived from the Hildebrand solubility approach are proposed for solubility prediction at different temperatures using a single determination. The experimental data of the present work as well as data gathered from the literature have been employed to investigate the accuracy and prediction capability of the proposed models. The overall percent deviations between the predicted and experimental values were 10.78 and 14.63% which were comparable to those of the classical two and three parameter models. The proposed models were much superior to the two pure predictive models i.e., the ones which do not require experimental solubility determination, as the overall percent deviations produced by the latter models were 150.09 and 161.00%.

  17. Prediction of the solubility of selected pharmaceuticals in water and alcohols with a group contribution method

    International Nuclear Information System (INIS)

    Pelczarska, Aleksandra; Ramjugernath, Deresh; Rarey, Jurgen; Domańska, Urszula

    2013-01-01

    Highlights: ► The prediction of solubility of pharmaceuticals in water and alcohols was presented. ► Improved group contribution method UNIFAC was proposed for 42 binary mixtures. ► Infinite activity coefficients were used in a model. ► A semi-predictive model with one experimental point was proposed. ► This model qualitatively describes the temperature dependency of Pharms. -- Abstract: An improved group contribution approach using activity coefficients at infinite dilution, which has been proposed by our group, was used for the prediction of the solubility of selected pharmaceuticals in water and alcohols [B. Moller, Activity of complex multifunctional organic compounds in common solvents, PhD Thesis, Chemical Engineering, University of KwaZulu-Natal, 2009]. The solubility of 16 different pharmaceuticals in water, ethanol and octan-1-ol was predicted over a fairly wide range of temperature with this group contribution model. The predicted values, along with values computed with the Schroeder-van Laar equation, are compared to experimental results published by us previously for 42 binary mixtures. The predicted solubility values were lower than those from the experiments for most of the mixtures. In order to improve the prediction method, a semi-predictive calculation using one experimental solubility value was implemented. This one point prediction has given acceptable results when comparison is made to experimental values

  18. Multimodel Predictive System for Carbon Dioxide Solubility in Saline Formation Waters

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Zan; Small, Mitchell J; Karamalidis, Athanasios K

    2013-02-05

    The prediction of carbon dioxide solubility in brine at conditions relevant to carbon sequestration (i.e., high temperature, pressure, and salt concentration (T-P-X)) is crucial when this technology is applied. Eleven mathematical models for predicting CO{sub 2} solubility in brine are compared and considered for inclusion in a multimodel predictive system. Model goodness of fit is evaluated over the temperature range 304–433 K, pressure range 74–500 bar, and salt concentration range 0–7 m (NaCl equivalent), using 173 published CO{sub 2} solubility measurements, particularly selected for those conditions. The performance of each model is assessed using various statistical methods, including the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). Different models emerge as best fits for different subranges of the input conditions. A classification tree is generated using machine learning methods to predict the best-performing model under different T-P-X subranges, allowing development of a multimodel predictive system (MMoPS) that selects and applies the model expected to yield the most accurate CO{sub 2} solubility prediction. Statistical analysis of the MMoPS predictions, including a stratified 5-fold cross validation, shows that MMoPS outperforms each individual model and increases the overall accuracy of CO{sub 2} solubility prediction across the range of T-P-X conditions likely to be encountered in carbon sequestration applications.

  19. Prediction of solubilities for ginger bioactive compounds in hot water by the COSMO-RS method

    Science.gov (United States)

    Zaimah Syed Jaapar, Syaripah; Azian Morad, Noor; Iwai, Yoshio

    2013-04-01

    The solubilities in water of four main ginger bioactives, 6-gingerol, 6-shogaol, 8-gingerol and 10-gingerol, were predicted using a conductor-like screening model for real solvent (COSMO-RS) calculations. This study was conducted since no experimental data are available for ginger bioactive solubilities in hot water. The σ-profiles of these selected molecules were calculated using Gaussian software and the solubilities were calculated using the COSMO-RS method. The solubilities of these ginger bioactives were calculated at 50 to 200 °C. In order to validate the accuracy of the COSMO-RS method, the solubilities of five hydrocarbon molecules were calculated using the COSMO-RS method and compared with the experimental data in the literature. The selected hydrocarbon molecules were 3-pentanone, 1-hexanol, benzene, 3-methylphenol and 2-hydroxy-5-methylbenzaldehyde. The calculated results of the hydrocarbon molecules are in good agreement with the data in the literature. These results confirm that the solubilities of ginger bioactives can be predicted using the COSMO-RS method. The solubilities of the ginger bioactives are lower than 0.0001 at temperatures lower than 130 °C. At 130 to 200 °C, the solubilities increase dramatically with the highest being 6-shogaol, which is 0.00037 mole fraction, and the lowest is 10-gingerol, which is 0.000039 mole fraction at 200 °C.

  20. Prediction of solubilities for ginger bioactive compounds in hot water by the COSMO-RS method

    International Nuclear Information System (INIS)

    Jaapar, Syaripah Zaimah Syed; Iwai, Yoshio; Morad, Noor Azian

    2013-01-01

    The solubilities in water of four main ginger bioactives, 6-gingerol, 6-shogaol, 8-gingerol and 10-gingerol, were predicted using a conductor-like screening model for real solvent (COSMO-RS) calculations. This study was conducted since no experimental data are available for ginger bioactive solubilities in hot water. The σ-profiles of these selected molecules were calculated using Gaussian software and the solubilities were calculated using the COSMO-RS method. The solubilities of these ginger bioactives were calculated at 50 to 200 °C. In order to validate the accuracy of the COSMO-RS method, the solubilities of five hydrocarbon molecules were calculated using the COSMO-RS method and compared with the experimental data in the literature. The selected hydrocarbon molecules were 3-pentanone, 1-hexanol, benzene, 3-methylphenol and 2-hydroxy-5-methylbenzaldehyde. The calculated results of the hydrocarbon molecules are in good agreement with the data in the literature. These results confirm that the solubilities of ginger bioactives can be predicted using the COSMO-RS method. The solubilities of the ginger bioactives are lower than 0.0001 at temperatures lower than 130 °C. At 130 to 200 °C, the solubilities increase dramatically with the highest being 6-shogaol, which is 0.00037 mole fraction, and the lowest is 10-gingerol, which is 0.000039 mole fraction at 200 °C.

  1. Prediction of aqueous and nonaqueous solubilities of chemicals with environmental interest by UNIFAC

    International Nuclear Information System (INIS)

    Kan, A.T.; Tomson, M.B.

    1995-01-01

    This paper is to investigate the accuracy and precision of predicting the aqueous and non-aqueous solubilities of a vast number of chemicals with significant environmental roles using the latest version of UNIFAC group interaction parameters. A few critical measurements to test specific UNIFAC calculations of nonaqueous solubilities are also reported. The chemicals included in the calculation have aqueous solubilities that span eleven orders of magnitude. Good agreement was observed between the UNIFAC predicted and literature reported aqueous solubilities for eleven groups of compounds. Similarly, UNIFAC successfully predicts the co-solvency of PCB in methanol/water solutions. The error between predicted and literature reported aqueous solubilities was larger for three groups of chemicals: long chain alkanes, phthalates, and chlorinated alkenes. The average absolute error in UNIFAC precision of aqueous solubilities is about 0.5 log units, but the average absolute error is only about 0.2 log units for chlorinated aromatic compounds in organic solvents. The application of UNIFAC approach to predict the fate of hydrocarbons and PCBs in soil column flushing, cosolvency and in natural gas pipeline liquids will be discussed

  2. Simulated rat intestinal fluid improves oral exposure prediction for poorly soluble compounds over a wide dose range

    Directory of Open Access Journals (Sweden)

    Joerg Berghausen

    2016-03-01

    Full Text Available Solubility can be the absorption limiting factor for drug candidates and is therefore a very important input parameter for oral exposure prediction of compounds with limited solubility. Biorelevant media of the fasted and fed state have been published for humans, as well as for dogs in the fasted state. In a drug discovery environment, rodents are the most common animal model to assess the oral exposure of drug candidates. In this study a rat simulated intestinal fluid (rSIF is proposed as a more physiologically relevant media to describe drug solubility in rats. Equilibrium solubility in this medium was tested as input parameter for physiologically-based pharmacokinetics (PBPK simulations of oral pharmacokinetics in the rat. Simulations were compared to those obtained using other solubility values as input parameters, like buffer at pH 6.8, human simulated intestinal fluid and a comprehensive dissolution assay based on rSIF. Our study on nine different compounds demonstrates that the incorporation of rSIF equilibrium solubility values into PBPK models of oral drug exposure can significantly improve the reliability of simulations in rats for doses up to 300 mg/kg compared to other media. The comprehensive dissolution assay may help to improve further simulation outcome, but the greater experimental effort as compared to equilibrium solubility may limit its use in a drug discovery environment. Overall, PBPK simulations based on solubility in the proposed rSIF medium can improve prioritizing compounds in drug discovery as well as planning dose escalation studies, e.g. during toxicological investigations.

  3. Soluble L-selectin levels predict survival in sepsis

    DEFF Research Database (Denmark)

    Seidelin, Jakob B; Nielsen, Ole H; Strøm, Jens

    2002-01-01

    OBJECTIVE: To evaluate serum soluble L-selectin as a prognostic factor for survival in patients with sepsis. DESIGN: A prospective study of mortality in patients with sepsis whose serum levels of sL-selectin were measured on admission to an intensive care unit (ICU) and 4 days later. Follow-up data......, and 3 and 12 months after admission. Serum sL-selectin levels were significantly lower in the patients than in the controls. Sepsis nonsurvivors had significantly lower levels than survivors. Efficiency analysis and receiver operation characteristics showed that the ideal cutoff point for s......L-selectin as a test for sepsis survival was 470 ng/ml. The accumulated mortality in patients with subnormal sL-selectin levels on admission was significantly increased. No correlation was found between clinical or paraclinical markers, including SAPS II and sL-selectin, and no relationship to the microbial diagnosis...

  4. The importance of the accuracy of the experimental data for the prediction of solubility

    Directory of Open Access Journals (Sweden)

    SLAVICA ERIĆ

    2010-04-01

    Full Text Available Aqueous solubility is an important factor influencing several aspects of the pharmacokinetic profile of a drug. Numerous publications present different methodologies for the development of reliable computational models for the prediction of solubility from structure. The quality of such models can be significantly affected by the accuracy of the employed experimental solubility data. In this work, the importance of the accuracy of the experimental solubility data used for model training was investigated. Three data sets were used as training sets – data set 1, containing solubility data collected from various literature sources using a few criteria (n = 319, data set 2, created by substituting 28 values from data set 1 with uniformly determined experimental data from one laboratory (n = 319, and data set 3, created by including 56 additional components, for which the solubility was also determined under uniform conditions in the same laboratory, in the data set 2 (n = 375. The selection of the most significant descriptors was performed by the heuristic method, using one-parameter and multi-parameter analysis. The correlations between the most significant descriptors and solubility were established using multi-linear regression analysis (MLR for all three investigated data sets. Notable differences were observed between the equations corresponding to different data sets, suggesting that models updated with new experimental data need to be additionally optimized. It was successfully shown that the inclusion of uniform experimental data consistently leads to an improvement in the correlation coefficients. These findings contribute to an emerging consensus that improving the reliability of solubility prediction requires the inclusion of many diverse compounds for which solubility was measured under standardized conditions in the data set.

  5. Substituted polyfluorene-based hole transport layer with tunable solubility

    NARCIS (Netherlands)

    Craciun, N.I.; Wildeman, J.; Blom, P.W.M.

    2010-01-01

    We report on the synthesis and electrical characterization of polyfluorene-triarylamine-based hole transport layers (HTLs). The solubility of the HTL can be tuned by adjustment of the chemical structure without loss of the charge transport properties. Double-layer polymer light-emitting diodes are

  6. Prediction of soluble solids content and ph in red wine by visible and near infrared spectroscopy

    Science.gov (United States)

    Wang, Li; He, Yong; Wang, Yanyan

    2008-02-01

    Soluble solids content (SSC) and pH are two major characteristic used for assessing quality of red wine, and they are also two important quality indexes in the manufacture of red wine. For rapid detection of SSC and pH in red wine, visible and near infrared (Vis/NIR) transmittance spectroscopy technique combined with partial least squares (PLS) and least squares support vector machines (LS-SVM) were used in this study. First, the near infrared transmittance spectra of 175 red wine samples were obtained using Vis/NIR spectroradiometer, then, PLS was applied for reducing the dimensionality of the original spectra, latent variables (LVs) selected by PLS could be used to replace the complex spectral data. All samples were randomly separated into calibration set and validation set. The LVs (selected by PLS) of each sample in calibration set was used as the inputs to train the LS-SVM model, then the optimal model was used to predict the SSC and pH values of samples in validation set based on their LVs. Standard error prediction (SEP) and determination coefficient (r2) were used as the evaluation standards, and the results indicated that the SEP and r2 for the prediction of SSC were 0.2313 and 0.9348; while 0.0071 and 0.9986 for pH. This prediction model was more accurate compared with the related research.

  7. PON-Sol: prediction of effects of amino acid substitutions on protein solubility.

    Science.gov (United States)

    Yang, Yang; Niroula, Abhishek; Shen, Bairong; Vihinen, Mauno

    2016-07-01

    Solubility is one of the fundamental protein properties. It is of great interest because of its relevance to protein expression. Reduced solubility and protein aggregation are also associated with many diseases. We collected from literature the largest experimentally verified solubility affecting amino acid substitution (AAS) dataset and used it to train a predictor called PON-Sol. The predictor can distinguish both solubility decreasing and increasing variants from those not affecting solubility. PON-Sol has normalized correct prediction ratio of 0.491 on cross-validation and 0.432 for independent test set. The performance of the method was compared both to solubility and aggregation predictors and found to be superior. PON-Sol can be used for the prediction of effects of disease-related substitutions, effects on heterologous recombinant protein expression and enhanced crystallizability. One application is to investigate effects of all possible AASs in a protein to aid protein engineering. PON-Sol is freely available at http://structure.bmc.lu.se/PON-Sol The training and test data are available at http://structure.bmc.lu.se/VariBench/ponsol.php mauno.vihinen@med.lu.se Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  8. Importance of critical micellar concentration for the prediction of solubility enhancement in biorelevant media.

    Science.gov (United States)

    Ottaviani, G; Wendelspiess, S; Alvarez-Sánchez, R

    2015-04-06

    This study evaluated if the intrinsic surface properties of compounds are related to the solubility enhancement (SE) typically observed in biorelevant media like fasted state simulated intestinal fluids (FaSSIF). The solubility of 51 chemically diverse compounds was measured in FaSSIF and in phosphate buffer and the surface activity parameters were determined. This study showed that the compound critical micellar concentration parameter (CMC) correlates strongly with the solubility enhancement (SE) observed in FaSSIF compared to phosphate buffer. Thus, the intrinsic capacity of molecules to form micelles is also a determinant for each compound's affinity to the micelles of biorelevant surfactants. CMC correlated better with SE than lipophilicity (logD), especially over the logD range typically covered by drugs (2 < logD < 4). CMC can become useful to guide drug discovery scientists to better diagnose, improve, and predict solubility in biorelevant media, thereby enhancing oral bioavailability of drug candidates.

  9. Predicting trace metal solubility and fractionation in Urban soils from isotopic exchangeability

    International Nuclear Information System (INIS)

    Mao, L.C.; Young, S.D.; Tye, A.M.; Bailey, E.H.

    2017-01-01

    Metal-salt amended soils (MA, n = 23), and historically-contaminated urban soils from two English cities (Urban, n = 50), were investigated to assess the effects of soil properties and contaminant source on metal lability and solubility. A stable isotope dilution method, with and without a resin purification step, was used to measure the lability of Cd, Cu, Ni, Pb and Zn. For all five metals in MA soils, lability (%E-values) could be reasonably well predicted from soil pH value with a simple logistic equation. However, there was evidence of continuing time-dependent fixation of Cd and Zn in the MA soils, following more than a decade of storage under air-dried conditions, mainly in high pH soils. All five metals in MA soils remained much more labile than in Urban soils, strongly indicating an effect of contaminant source on metal lability in the latter. Metal solubility was predicted for both sets of soil by the geochemical speciation model WHAM-VII, using E-value as an input variable. For soils with low metal solution concentrations, over-estimation of Cd, Ni and Zn solubility was associated with binding to the Fe oxide fraction while accurate prediction of Cu solubility was dependent on humic acid content. Lead solubility was most poorly described, especially in the Urban soils. Generally, slightly poorer estimation of metal solubility was observed in Urban soils, possibly due to a greater incidence of high pH values. The use of isotopically exchangeable metal to predict solubility is appropriate both for historically contaminated soils and where amendment with soluble forms of metal is used, as in toxicological trials. However, the major limitation to predicting solubility may lie with the accuracy of model input variables such as humic acid and Fe oxide contents where there is often a reliance on relatively crude analytical estimations of these variables. Trace metal reactivity in urban soils depends on both soil properties and the original source material

  10. Fast Measurement of Soluble Solid Content in Mango Based on Visible and Infrared Spectroscopy Technique

    Science.gov (United States)

    Yu, Jiajia; He, Yong

    Mango is a kind of popular tropical fruit, and the soluble solid content is an important in this study visible and short-wave near-infrared spectroscopy (VIS/SWNIR) technique was applied. For sake of investigating the feasibility of using VIS/SWNIR spectroscopy to measure the soluble solid content in mango, and validating the performance of selected sensitive bands, for the calibration set was formed by 135 mango samples, while the remaining 45 mango samples for the prediction set. The combination of partial least squares and backpropagation artificial neural networks (PLS-BP) was used to calculate the prediction model based on raw spectrum data. Based on PLS-BP, the determination coefficient for prediction (Rp) was 0.757 and root mean square and the process is simple and easy to operate. Compared with the Partial least squares (PLS) result, the performance of PLS-BP is better.

  11. Predicting Soluble Nickel in Soils Using Soil Properties and Total Nickel.

    Science.gov (United States)

    Zhang, Xiaoqing; Li, Jumei; Wei, Dongpu; Li, Bo; Ma, Yibing

    2015-01-01

    Soil soluble nickel (Ni) concentration is very important for determining soil Ni toxicity. In the present study, the relationships between soil properties, total and soluble Ni concentrations in soils were developed in a wide range of soils with different properties and climate characteristics. The multiple regressions showed that soil pH and total soil Ni concentrations were the most significant parameters in predicting soluble Ni concentrations with the adjusted determination coefficients (Radj2) values of 0.75 and 0.68 for soils spiked with soluble Ni salt and the spiked soils leached with artificial rainwater to mimic field conditions, respectively. However, when the soils were divided into three categories (pH 8), they obtained better predictions with Radj2 values of 0.78-0.90 and 0.79-0.94 for leached and unleached soils, respectively. Meanwhile, the other soil properties, such as amorphous Fe and Al oxides and clay, were also found to be important for determining soluble Ni concentrations, indicating that they were also presented as active adsorbent surfaces. Additionally, the whole soil speciation including bulk soil properties and total soils Ni concentrations were analyzed by mechanistic speciation models WHAM VI and Visual MINTEQ3.0. It was found that WHAM VI provided the best predictions for the soils with pH 8. The Visual MINTEQ3.0 could provide better estimation for pH 8. These results indicated the possibility and applicability of these models to predict soil soluble Ni concentration by soil properties.

  12. Solubility of water in fluorocarbons: Experimental and COSMO-RS prediction results

    International Nuclear Information System (INIS)

    Freire, Mara G.; Carvalho, Pedro J.; Santos, Luis M.N.B.F.; Gomes, Ligia R.; Marrucho, Isabel M.; Coutinho, Joao A.P.

    2010-01-01

    This work aims at providing experimental and theoretical information about the water-perfluorocarbon molecular interactions. For that purpose, experimental solubility results for water in cyclic and aromatic perfluorocarbons (PFCs), over the temperature range between (288.15 and 318.15) K, and at atmospheric pressure, were obtained and are presented. From the experimental solubility dependence on temperature, the partial molar solution and solvation thermodynamic functions such as Gibbs free energy, enthalpy and entropy were determined and are discussed. The process of dissolution of water in PFCs is shown to be spontaneous for cyclic and aromatic compounds. It is demonstrated that the interactions between the non-aromatic PFCs and water are negligible while those between aromatic PFCs and water are favourable. The COSMO-RS predictive capability was explored for the description of the water solubility in PFCs and others substituted fluorocompounds. The COSMO-RS is shown to be a useful model to provide reasonable predictions of the solubility values, as well as to describe their temperature and structural modifications dependence. Moreover, the molar Gibbs free energy and molar enthalpy of solution of water are predicted remarkably well by COSMO-RS while the main deviations appear for the prediction of the molar entropy of solution.

  13. Predicting the equilibrium solubility of solid polycyclic aromatic hydrocarbons and dibenzothiophene using a combination of MOSCED plus molecular simulation or electronic structure calculations

    Science.gov (United States)

    Phifer, Jeremy R.; Cox, Courtney E.; da Silva, Larissa Ferreira; Nogueira, Gabriel Gonçalves; Barbosa, Ana Karolyne Pereira; Ley, Ryan T.; Bozada, Samantha M.; O'Loughlin, Elizabeth J.; Paluch, Andrew S.

    2017-06-01

    Methods to predict the equilibrium solubility of non-electrolyte solids are important for the design of novel separation processes. Here we demonstrate how conventional molecular simulation free energy calculations or electronic structure calculations in a continuum solvent, here SMD or SM8, can be used to predict parameters for the MOdified Separation of Cohesive Energy Density (MOSCED) method. The method is applied to the solutes naphthalene, anthracene, phenanthrene, pyrene and dibenzothiophene, compounds of interested to the petroleum industry and for environmental remediation. Adopting the melting point temperature and enthalpy of fusion of these compounds from experiment, we are able to predict equilibrium solubilities. Comparing to a total of 422 non-aqueous and 193 aqueous experimental solubilities, we find the proposed method is able to well correlate the data. The use of MOSCED is additionally advantageous as it is a solubility parameter-based method useful for intuitive solvent selection and formulation.

  14. Drug Solubility in Fatty Acids as a Formulation Design Approach for Lipid-Based Formulations: A Technical Note.

    Science.gov (United States)

    Lee, Yung-Chi; Dalton, Chad; Regler, Brian; Harris, David

    2018-06-06

    Lipid-based drug delivery systems have been intensively investigated as a means of delivering poorly water-soluble drugs. Upon ingestion, the lipases in the gastrointestinal tract digest lipid ingredients, mainly triglycerides, within the formulation into monoglycerides and fatty acids. While numerous studies have addressed the solubility of drugs in triglycerides, comparatively few publications have addressed the solubility of drugs in fatty acids, which are the end product of digestion and responsible for the solubility of drug within mixed micelles. The objective of this investigation was to explore the solubility of a poorly water-soluble drug in fatty acids and raise the awareness of the importance of drug solubility in fatty acids. The model API (active pharmaceutical ingredient), a weak acid, is considered a BCS II compound with an aqueous solubility of 0.02 μg/mL and predicted partition coefficient >7. The solubility of API ranged from 120 mg/mL to over 1 g/mL in fatty acids with chain lengths across the range C18 to C6. Hydrogen bonding was found to be the main driver of the solubilization of API in fatty acids. The solubility of API was significantly reduced by water uptake in caprylic acid but not in oleic acid. This report demonstrates that solubility data generated in fatty acids can provide an indication of the solubility of the drug after lipid digestion. This report also highlights the importance of measuring the solubility of drugs in fatty acids in the course of lipid formulation development.

  15. Use Of Stream Analyzer For Solubility Predictions Of Selected Hanford Tank Waste

    International Nuclear Information System (INIS)

    Pierson, Kayla; Belsher, Jeremy; Ho, Quynh-dao

    2012-01-01

    The Hanford Tank Waste Operations Simulator (HTWOS) models the mission to manage, retrieve, treat and vitrify Hanford waste for long-term storage and disposal. HTWOS is a dynamic, flowsheet, mass balance model of waste retrieval and treatment activities. It is used to evaluate the impact of changes on long-term mission planning. The project is to create and evaluate the integrated solubility model (ISM). The ISM is a first step in improving the chemistry basis in HTWOS. On principal the ISM is better than the current HTWOS solubility. ISM solids predictions match the experimental data well, with a few exceptions. ISM predictions are consistent with Stream Analyzer predictions except for chromium. HTWOS is producing more realistic results with the ISM

  16. Consideration on thermodynamic data for predicting solubility and chemical species of elements in groundwater. Part 2: Np, Pu

    International Nuclear Information System (INIS)

    Yamaguchi, Tetsuji

    2000-11-01

    The solubility determines the release of a radionuclide from waste form and is used as a source term in radionuclide migration analysis in performance assessment of radioactive waste repository. Complexations of the radionuclide by ligands in groundwater affect the interaction between radionuclides and geologic media, thus affect their migration behavior. It is essential to estimate the solubility and to predict the chemical species for the radionuclide based on thermodynamic data. The thermodynamic data of aqueous species and compounds were reviewed and compiled for Np and Pu. Thermodynamic data were reviewed with emphasis on the hydrolysis and carbonate complexation that can dominate the speciation in groundwater. Thermodynamic data for other species were selected based on existing databases. Thermodynamic data for other important elements are under investigation, thus shown in an appendix for temporary use. (author)

  17. Major Source of Error in QSPR Prediction of Intrinsic Thermodynamic Solubility of Drugs: Solid vs Nonsolid State Contributions?

    Science.gov (United States)

    Abramov, Yuriy A

    2015-06-01

    The main purpose of this study is to define the major limiting factor in the accuracy of the quantitative structure-property relationship (QSPR) models of the thermodynamic intrinsic aqueous solubility of the drug-like compounds. For doing this, the thermodynamic intrinsic aqueous solubility property was suggested to be indirectly "measured" from the contributions of solid state, ΔGfus, and nonsolid state, ΔGmix, properties, which are estimated by the corresponding QSPR models. The QSPR models of ΔGfus and ΔGmix properties were built based on a set of drug-like compounds with available accurate measurements of fusion and thermodynamic solubility properties. For consistency ΔGfus and ΔGmix models were developed using similar algorithms and descriptor sets, and validated against the similar test compounds. Analysis of the relative performances of these two QSPR models clearly demonstrates that it is the solid state contribution which is the limiting factor in the accuracy and predictive power of the QSPR models of the thermodynamic intrinsic solubility. The performed analysis outlines a necessity of development of new descriptor sets for an accurate description of the long-range order (periodicity) phenomenon in the crystalline state. The proposed approach to the analysis of limitations and suggestions for improvement of QSPR-type models may be generalized to other applications in the pharmaceutical industry.

  18. Model evaluation for the prediction of solubility of active pharmaceutical ingredients (APIs to guide solid–liquid separator design

    Directory of Open Access Journals (Sweden)

    Kuveneshan Moodley

    2018-05-01

    Full Text Available The assumptions and models for solubility modelling or prediction in systems using non-polar solvents, or water and complex triterpene and other active pharmaceutical ingredients as solutes aren't well studied. Furthermore, the assumptions concerning heat capacity effects (negligibility, experimental values or approximations are explored, using non-polar solvents (benzene, or water as reference solvents, for systems with solute melting points in the range of 306–528 K and molecular weights in the range of 90–442 g/mol. New empirical estimation methods for the ΔfusCpi of APIs are presented which correlate the solute molecular masses and van der Waals surface areas with ΔfusCpi. Separate empirical parameters were required for oxygenated and non-oxygenated solutes. Subsequently, the predictive capabilities of the various approaches to solubility modelling for complex pharmaceuticals, for which data is limited, are analysed. The solute selection is based on a principal component analysis, considering molecular weights, fusion temperatures, and solubilities in a non-polar solvent, alcohol, and water, where data was available. New NRTL-SAC parameters were determined for selected steroids, by regression. The original UNIFAC, modified UNIFAC (Dortmund, COSMO-RS (OL, and COSMO-SAC activity coefficient predictions are then conducted, based on the availability of group constants and sigma profiles. These are undertaken to assess the predictive capabilities of these models when each assumption concerning heat capacity is employed. The predictive qualities of the models are assessed, based on the mean square deviation and provide guidelines for model selection, and assumptions concerning phase equilibrium, when designing solid–liquid separators for the pharmaceutical industry on process simulation software. The most suitable assumption regarding ΔfusCpi was found to be system specific, with modified UNIFAC (Dortmund performing well in benzene as

  19. Consideration on thermodynamic data for predicting solubility and chemical species of elements in groundwater. Part 1: Tc, U, Am

    Energy Technology Data Exchange (ETDEWEB)

    Yamaguchi, Tetsuji; Takeda, Seiji [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    1999-01-01

    The solubility determines the release of radionuclides from waste form and is used as a source term in radionuclide migration analysis in performance assessment of radioactive waste repository. Complexations of radionuclides by ligands in groundwater affect the interaction between radionuclides and geologic media, thus affect their migration behavior. Thermodynamic data for Tc, Am and U were reviewed and compiled to be used for predicting the solubility and chemical species in groundwater. Thermodynamic data were reviewed with emphasis on the hydrolysis and carbonate complexation that can dominate the speciation in typical groundwater. Thermodynamic data for other species were selected based on existing database. Thermodynamic data for other important elements are under investigation, thus shown in an appendix for temporary use. (author)

  20. High pre-transplant soluble CD30 levels are predictive of the grade of rejection.

    Science.gov (United States)

    Rajakariar, Ravindra; Jivanji, Naina; Varagunam, Mira; Rafiq, Mohammad; Gupta, Arun; Sheaff, Michael; Sinnott, Paul; Yaqoob, M M

    2005-08-01

    In renal transplantation, serum soluble CD30 (sCD30) levels in graft recipients are associated with increased rejection and graft loss. We investigated whether pre-transplant sCD30 concentrations are predictive of the grade of rejection. Pre-transplant sera of 51 patients with tubulointerstitial rejection (TIR), 16 patients with vascular rejection (VR) and an age-matched control group of 41 patients with no rejection (NR) were analyzed for sCD30. The transplant biopsies were immunostained for C4d. The median sCD30 level was significantly elevated in the group with VR (248 Units (U)/mL, range: 92-802) when compared with TIR (103 U/mL, range: 36-309, psCD30 levels compared to NR. Based on C4d staining, a TH2 driven process, the median sCD30 levels were significantly raised in C4d+ patients compared with C4d- group (177 U/mL vs. 120 U/mL, psCD30 levels measured at time of transplantation correlate with the grade of rejection. High pre-transplant levels are associated with antibody-mediated rejection which carries a poorer prognosis. sCD30 could be another tool to assess immunological risk prior to transplantation and enable a patient centered approach to immunosuppression.

  1. Thermodynamic approach to improving solubility prediction of co-crystals in comparison with individual poorly soluble components

    International Nuclear Information System (INIS)

    Perlovich, German L.

    2014-01-01

    Highlights: • Thermodynamic approach for solubility improvement of co-crystal was developed. • The graphical technique for estimation of co-crystal solubility was elaborated. • Hydration enthalpies of some drugs and amino acids were calculated. • Applicability/operability of the approach was exemplified by some drugs and amino acids. - Abstract: A novel thermodynamic approach to compare poorly soluble components (active pharmaceutical ingredient (API)) both in co-crystals and individual compounds was developed. An algorithm of choosing potential co-crystals with improved solubility characteristics on the basis of the known solvation/hydration API and co-former enthalpies is described. The applicability and operability of the algorithm were tested exemplified by some drugs and amino acids

  2. pH-metric solubility. 2: correlation between the acid-base titration and the saturation shake-flask solubility-pH methods.

    Science.gov (United States)

    Avdeef, A; Berger, C M; Brownell, C

    2000-01-01

    The objective of this study was to compare the results of a normal saturation shake-flask method to a new potentiometric acid-base titration method for determining the intrinsic solubility and the solubility-pH profiles of ionizable molecules, and to report the solubility constants determined by the latter technique. The solubility-pH profiles of twelve generic drugs (atenolol, diclofenac.Na, famotidine, flurbiprofen, furosemide, hydrochlorothiazide, ibuprofen, ketoprofen, labetolol.HCl, naproxen, phenytoin, and propranolol.HCl), with solubilities spanning over six orders of magnitude, were determined both by the new pH-metric method and by a traditional approach (24 hr shaking of saturated solutions, followed by filtration, then HPLC assaying with UV detection). The 212 separate saturation shake-flask solubility measurements and those derived from 65 potentiometric titrations agreed well. The analysis produced the correlation equation: log(1/S)titration = -0.063(+/- 0.032) + 1.025(+/- 0.011) log(1/S)shake-flask, s = 0.20, r2 = 0.978. The potentiometrically-derived intrinsic solubilities of the drugs were: atenolol 13.5 mg/mL, diclofenac.Na 0.82 microg/mL, famotidine 1.1 mg/ mL, flurbiprofen 10.6 microg/mL, furosemide 5.9 microg/mL, hydrochlorothiazide 0.70 mg/mL, ibuprofen 49 microg/mL, ketoprofen 118 microg/mL, labetolol.HCl 128 microg/mL, naproxen 14 microg/mL, phenytoin 19 microg/mL, and propranolol.HCl 70 microg/mL. The new potentiometric method was shown to be reliable for determining the solubility-pH profiles of uncharged ionizable drug substances. Its speed compared to conventional equilibrium measurements, its sound theoretical basis, its ability to generate the full solubility-pH profile from a single titration, and its dynamic range (currently estimated to be seven orders of magnitude) make the new pH-metric method an attractive addition to traditional approaches used by preformulation and development scientists. It may be useful even to discovery

  3. Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

    Science.gov (United States)

    Page, Sandra; Birerdinc, Aybike; Estep, Michael; Stepanova, Maria; Afendy, Arian; Petricoin, Emanuel; Younossi, Zobair; Chandhoke, Vikas; Baranova, Ancha

    2013-01-01

    The discovery of biomarkers is often performed using high-throughput proteomics-based platforms and is limited to the molecules recognized by a given set of purified and validated antigens or antibodies. Knowledge-based, or systems biology, approaches that involve the analysis of integrated data, predominantly molecular pathways and networks may infer quantitative changes in the levels of biomolecules not included by the given assay from the levels of the analytes profiled. In this study we attempted to use a knowledge-based approach to predict biomarkers reflecting the changes in underlying protein phosphorylation events using Nonalcoholic Fatty Liver Disease (NAFLD) as a model. Two soluble biomarkers, CCL-2 and FasL, were inferred in silico as relevant to NAFLD pathogenesis. Predictive performance of these biomarkers was studied using serum samples collected from patients with histologically proven NAFLD. Serum levels of both molecules, in combination with clinical and demographic data, were predictive of hepatic fibrosis in a cohort of NAFLD patients. Our study suggests that (1) NASH-specific disruption of the kinase-driven signaling cascades in visceral adipose tissue lead to detectable changes in the levels of soluble molecules released into the bloodstream, and (2) biomarkers discovered in silico could contribute to predictive models for non-malignant chronic diseases.

  4. Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

    Directory of Open Access Journals (Sweden)

    Sandra Page

    Full Text Available The discovery of biomarkers is often performed using high-throughput proteomics-based platforms and is limited to the molecules recognized by a given set of purified and validated antigens or antibodies. Knowledge-based, or systems biology, approaches that involve the analysis of integrated data, predominantly molecular pathways and networks may infer quantitative changes in the levels of biomolecules not included by the given assay from the levels of the analytes profiled. In this study we attempted to use a knowledge-based approach to predict biomarkers reflecting the changes in underlying protein phosphorylation events using Nonalcoholic Fatty Liver Disease (NAFLD as a model. Two soluble biomarkers, CCL-2 and FasL, were inferred in silico as relevant to NAFLD pathogenesis. Predictive performance of these biomarkers was studied using serum samples collected from patients with histologically proven NAFLD. Serum levels of both molecules, in combination with clinical and demographic data, were predictive of hepatic fibrosis in a cohort of NAFLD patients. Our study suggests that (1 NASH-specific disruption of the kinase-driven signaling cascades in visceral adipose tissue lead to detectable changes in the levels of soluble molecules released into the bloodstream, and (2 biomarkers discovered in silico could contribute to predictive models for non-malignant chronic diseases.

  5. Actinide solubility in deep groundwaters - estimates for upper limits based on chemical equilibrium calculations

    International Nuclear Information System (INIS)

    Schweingruber, M.

    1983-12-01

    A chemical equilibrium model is used to estimate maximum upper concentration limits for some actinides (Th, U, Np, Pu, Am) in groundwaters. Eh/pH diagrams for solubility isopleths, dominant dissolved species and limiting solids are constructed for fixed parameter sets including temperature, thermodynamic database, ionic strength and total concentrations of most important inorganic ligands (carbonate, fluoride, phosphate, sulphate, chloride). In order to assess conservative conditions, a reference water is defined with high ligand content and ionic strength, but without competing cations. In addition, actinide oxides and hydroxides are the only solid phases considered. Recommendations for 'safe' upper actinide solubility limits for deep groundwaters are derived from such diagrams, based on the predicted Eh/pH domain. The model results are validated as far as the scarce experimental data permit. (Auth.)

  6. pH-dependent solubility and permeability profiles: A useful tool for prediction of oral bioavailability.

    Science.gov (United States)

    Sieger, P; Cui, Y; Scheuerer, S

    2017-07-15

    pH-dependent solubility - permeability profiles offer a simple way to predict bioavailability after oral application, if bioavailability is only solubility and permeability driven. Combining both pH-dependent solubility and pH-dependent permeability in one diagram provides a pH-window (=ΔpH sol-perm ) from which the conditions for optimal oral bioavailability can be taken. The size of this window is directly proportional to the observed oral bioavailability. A set of 21 compounds, with known absolute human oral bioavailability, was used to establish this correlation. Compounds with ΔpH sol-perm bioavailability (bioavailability typically by approximately 25%. For compounds where ΔpH sol-perm ≥3 but still showing poor bioavailability, most probably other pharmacokinetic aspects (e.g. high clearance), are limiting exposure. Interestingly, the location of this pH-window seems to have a negligible influence on the observed oral bioavailability. In scenarios, where the bioavailability is impaired by certain factors, like for example proton pump inhibitor co-medication or food intake, the exact position of this pH-window might be beneficial for understanding the root cause. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Predicting the solubility of gases in Nitrile Butadiene Rubber in extreme conditions using molecular simulation

    Science.gov (United States)

    Khawaja, Musab; Molinari, Nicola; Sutton, Adrian; Mostofi, Arash

    In the oil and gas industry, elastomer seals play an important role in protecting sensitive monitoring equipment from contamination by gases - a problem that is exacerbated by the high pressures and temperatures found down-hole. The ability to predict and prevent such permeative failure has proved elusive to-date. Nitrile butadiene rubber (NBR) is a common choice of elastomer for seals due to its resistance to heat and fuels. In the conditions found in the well it readily absorbs small molecular weight gases. How this behaviour changes quantitatively for different gases as a function of temperature and pressure is not well-understood. In this work a series of fully atomistic simulations are performed to understand the effect of extreme conditions on gas solubility in NBR. Widom particle insertion is used to compute solubilities. The importance of sampling and allowing structural relaxation upon compression are highlighted, and qualitatively reasonable trends reproduced. Finally, while at STP it has previously been shown that the solubility of CO2 is higher than that of He in NBR, we observe that under the right circumstances it is possible to reverse this trend.

  8. Prediction and experimental determination of the solubility of exotic scales at high temperatures - Zinc sulfide

    DEFF Research Database (Denmark)

    Carolina Figueroa Murcia, Diana; Fosbøl, Philip Loldrup; Thomsen, Kaj

    2016-01-01

    The presence of "exotic" scale such as Zinc Sulfide (ZnS), Lead Sulfide (PbS) and Iron Sulfide (FeS) in HP/HT reservoirs has been identified. "Exotic" scale materials come as a new challenge in HP/HT reservoirs. This has led to the development of more advanced tools to predict their behavior...... at extreme conditions. The aim of this work is to include ZnS into the group of scale materials that can be modeled with the Extended UNIQUAC model. Solubility data for ZnS are scarce in the open literature. In order to improve the available data, we study the experimental behavior of ZnS solubility at high...... temperatures. The determination of the solubility of ZnS is carried out at temperatures up to 250°C. Zinc sulfide (99.99%) and ultra-pure water are placed in a vial in a reduced oxygen atmosphere. The sample is placed in a controlled bath and stirred until equilibrium is attained. The suspension is filtered...

  9. Prediction of pH-dependent aqueous solubility of Histone Deacetylase (HDAC) inhibitors

    DEFF Research Database (Denmark)

    Kouskoumvekaki, Irene; Hansen, Niclas Tue; Bjorkling, F.

    2008-01-01

    on the series of HDAC inhibitors by use of Self-Organizing Maps (SOM) and 2D-projection of the HDAC inhibitors on the chemical space of the training data set of the artificial neural network (ANN) module. The model was refined for the particular chemical space of interest, which led to two modifications...... can develop models that are more accurate in predicting differences in the solubility of structurally very similar compounds than models that have been trained on structurally unbiased, diverse data sets. Such 'tailor-made' models have the potential to become trustworthy enough to replace time...

  10. tPC-PSAFT modeling of gas solubility in imidazolium-based ionic liquids

    DEFF Research Database (Denmark)

    Karakatsani, Eirini; Economou, Ioannis; Kroon, M. C.

    2007-01-01

    The truncated perturbed chain-polar statistical associating fluid theory (tPC-PSAFT) is re-parametrized for imidazolium-based ionic liquids (ILs) by fitting IL density data over a wide temperature range and restricting the model to predict very low vapor pressure values, in agreement with recent...... experimental evidence. The new set of parameters is used for the correlation of carbon dioxide solubility in various ILs using a binary interaction parameter, k(ij). The correlated k(ij) values are much lower than the values used previously for the same mixtures (Kroon et al., J. Phys. Chem. B 2006, 110, 9262...

  11. Measurement and prediction of dabigatran etexilate mesylate Form II solubility in mono-solvents and mixed solvents

    International Nuclear Information System (INIS)

    Xiao, Yan; Wang, Jingkang; Wang, Ting; Ouyang, Jinbo; Huang, Xin; Hao, Hongxun; Bao, Ying; Fang, Wen; Yin, Qiuxiang

    2016-01-01

    Highlights: • Solubility of DEM Form II in mono-solvents and binary solvent mixtures was measured. • Regressed UNIFAC model was used to predict the solubility in solvent mixtures. • The experimental solubility data were correlated by different models. - Abstract: UV spectrometer method was used to measure the solubility data of dabigatran etexilate mesylate (DEM) Form II in five mono-solvents (methanol, ethanol, ethane-1,2-diol, DMF, DMAC) and binary solvent mixtures of methanol and ethanol in the temperature range from 287.37 K to 323.39 K. The experimental solubility data in mono-solvents were correlated with modified Apelblat equation, van’t Hoff equation and λh equation. GSM model and Modified Jouyban-Acree model were employed to correlate the solubility data in mixed solvent systems. And Regressed UNIFAC model was used to predict the solubility of DEM Form II in the binary solvent mixtures. Results showed that the predicted data were consistent with the experimental data.

  12. Predicting the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol mixtures via molecular simulation

    Science.gov (United States)

    Paluch, Andrew S.; Parameswaran, Sreeja; Liu, Shuai; Kolavennu, Anasuya; Mobley, David L.

    2015-01-01

    We present a general framework to predict the excess solubility of small molecular solids (such as pharmaceutical solids) in binary solvents via molecular simulation free energy calculations at infinite dilution with conventional molecular models. The present study used molecular dynamics with the General AMBER Force Field to predict the excess solubility of acetanilide, acetaminophen, phenacetin, benzocaine, and caffeine in binary water/ethanol solvents. The simulations are able to predict the existence of solubility enhancement and the results are in good agreement with available experimental data. The accuracy of the predictions in addition to the generality of the method suggests that molecular simulations may be a valuable design tool for solvent selection in drug development processes.

  13. Alternate source term models for Yucca Mountain performance assessment based on natural analog data and secondary mineral solubility

    International Nuclear Information System (INIS)

    Murphy, W.M.; Codell, R.B.

    1999-01-01

    Performance assessment calculations for the proposed high level radioactive waste repository at Yucca Mountain, Nevada, were conducted using the Nuclear Regulatory Commission Total-System Performance Assessment (TPA 3.2) code to test conceptual models and parameter values for the source term based on data from the Pena Blanca, Mexico, natural analog site and based on a model for coprecipitation and solubility of secondary schoepite. In previous studies the value for the maximum constant oxidative alteration rate of uraninite at the Nopal I uranium body at Pena Blanca was estimated. Scaling this rate to the mass of uranium for the proposed Yucca Mountain repository yields an oxidative alteration rate of 22 kg/y, which was assumed to be an upper limit on the release rate from the proposed repository. A second model was developed assuming releases of radionuclides are based on the solubility of secondary schoepite as a function of temperature and solution chemistry. Releases of uranium are given by the product of uranium concentrations at equilibrium with schoepite and the flow of water through the waste packages. For both models, radionuclides other than uranium and those in the cladding and gap fraction were modeled to be released at a rate proportional to the uranium release rate, with additional elemental solubility limits applied. Performance assessment results using the Pena Blanca oxidation rate and schoepite solubility models for Yucca Mountain were compared to the TPA 3.2 base case model, in which release was based on laboratory studies of spent fuel dissolution, cladding and gap release, and solubility limits. Doses calculated using the release rate based on natural analog data and the schoepite solubility models were smaller than doses generated using the base case model. These results provide a degree of confidence in safety predictions using the base case model and an indication of how conservatism in the base case model may be reduced in future analyses

  14. Alternate source term models for Yucca Mountain performance assessment based on natural analog data and secondary mineral solubility

    Energy Technology Data Exchange (ETDEWEB)

    Murphy, W.M.; Codell, R.B.

    1999-07-01

    Performance assessment calculations for the proposed high level radioactive waste repository at Yucca Mountain, Nevada, were conducted using the Nuclear Regulatory Commission Total-System Performance Assessment (TPA 3.2) code to test conceptual models and parameter values for the source term based on data from the Pena Blanca, Mexico, natural analog site and based on a model for coprecipitation and solubility of secondary schoepite. In previous studies the value for the maximum constant oxidative alteration rate of uraninite at the Nopal I uranium body at Pena Blanca was estimated. Scaling this rate to the mass of uranium for the proposed Yucca Mountain repository yields an oxidative alteration rate of 22 kg/y, which was assumed to be an upper limit on the release rate from the proposed repository. A second model was developed assuming releases of radionuclides are based on the solubility of secondary schoepite as a function of temperature and solution chemistry. Releases of uranium are given by the product of uranium concentrations at equilibrium with schoepite and the flow of water through the waste packages. For both models, radionuclides other than uranium and those in the cladding and gap fraction were modeled to be released at a rate proportional to the uranium release rate, with additional elemental solubility limits applied. Performance assessment results using the Pena Blanca oxidation rate and schoepite solubility models for Yucca Mountain were compared to the TPA 3.2 base case model, in which release was based on laboratory studies of spent fuel dissolution, cladding and gap release, and solubility limits. Doses calculated using the release rate based on natural analog data and the schoepite solubility models were smaller than doses generated using the base case model. These results provide a degree of confidence in safety predictions using the base case model and an indication of how conservatism in the base case model may be reduced in future analyses.

  15. Use of tritium to predict soluble pollutants transport in Ebro River waters (Spain).

    Science.gov (United States)

    Pujol, L; Sanchez-Cabeza, J A

    2000-05-01

    The Ebro River, in Northeast Spain, discharges into the Mediterranean Sea after flowing through several large cities and agricultural, mining and industrial areas. The Ascó nuclear power plant (NPP) is located in its lower section and comprises two pressurised water reactor units, from which low-level liquid radioactive waste is released to river waters under authority control. Tritium routinely released by the NPP was used as a radiotracer to determine the longitudinal dispersion coefficient and velocity of the river waters. Several field experiments, in co-ordination with the NPP, were carried out during 1991 and 1992. During each field experiment, the flow rate was kept constant by dams located upstream from the NPP. After each tritium release, water was sampled downstream at periodic intervals over several hours and tritium was measured with a low-background liquid scintillation counter. Velocity and dispersion coefficient were determined in river waters for several river discharges using an analytical, box-type and numerical approach to solve the one-dimensional advection-diffusion equation. The set of calibrated parameters was used to predict the displacement and dispersion of soluble pollutants in river waters. Velocity was determined as a function of river discharge and river slope, and dispersion coefficient was determined as a function of distance. Finally, sensitivity of the model predictions was studied and uncertainties of the fitted parameters were estimated.

  16. Solubilities of some gases in four immidazolium-based ionic liquids

    International Nuclear Information System (INIS)

    Afzal, Waheed; Liu, Xiangyang; Prausnitz, John M.

    2013-01-01

    Graphical abstract: Experimental apparatus based on the synthetic-volumetric method for measuring solubilities of gases in liquids. Highlights: • We constructed an apparatus for measuring solubilities of sparingly-soluble gases. • We measured solubilities of five gases in four immidazolium-based ionic liquids. • We calculated Henry’s constants for gases in the ionic liquids studied in this work. -- Abstract: The synthetic-volumetric method is used for rapidly measuring solubilities of sparingly-soluble gases in monoethylene glycol and in four ionic liquids. Known molar quantities of solute and solvent are charged into an equilibrium vessel. Measured quantities at equilibrium include: temperature, pressure, quantities of fluids, and volumes of the gas and liquid phases in the equilibrium vessel. These measurements enable calculation of equilibrium compositions using material balances. No sampling or chemical analyses are required. Solubilities are reported for carbon dioxide, krypton, oxygen, and hydrogen in monoethylene glycol, l-n-butyl-3-methylimidazolium tetrafluoroborate [BMIM][BF4], l-n-butyl-3-methylimidazolium hexafluorophosphate [BMIM][PF6], 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide [EMIM][Tf 2 N], or 1-ethyl-3-methylimidazolium acetate [EMIM][AC]. Solubilities were measured over the temperature range (298 to 355) K and for pressures up to about 7 MPa using two different pieces of equipment, both based on the volumetric method: a low-pressure glass apparatus and a high-pressure stainless-steel apparatus. Special emphasis is given to experimental reliability to assure consistent data

  17. Improved prediction of octanol-water partition coefficients from liquid-solute water solubilities and molar volumes

    Science.gov (United States)

    Chiou, C.T.; Schmedding, D.W.; Manes, M.

    2005-01-01

    A volume-fraction-based solvent-water partition model for dilute solutes, in which the partition coefficient shows a dependence on solute molar volume (V??), is adapted to predict the octanol-water partition coefficient (K ow) from the liquid or supercooled-liquid solute water solubility (Sw), or vice versa. The established correlation is tested for a wide range of industrial compounds and pesticides (e.g., halogenated aliphatic hydrocarbons, alkylbenzenes, halogenated benzenes, ethers, esters, PAHs, PCBs, organochlorines, organophosphates, carbamates, and amidesureas-triazines), which comprise a total of 215 test compounds spanning about 10 orders of magnitude in Sw and 8.5 orders of magnitude in Kow. Except for phenols and alcohols, which require special considerations of the Kow data, the correlation predicts the Kow within 0.1 log units for most compounds, much independent of the compound type or the magnitude in K ow. With reliable Sw and V data for compounds of interest, the correlation provides an effective means for either predicting the unavailable log Kow values or verifying the reliability of the reported log Kow data. ?? 2005 American Chemical Society.

  18. Soluble CD30 in renal transplant recipients: is it a good biomarker to predict rejection?

    Science.gov (United States)

    Azarpira, Negar; Aghdaie, Mahdokht Hosein; Malekpour, Zahra

    2010-01-01

    It has been suggested that the serum soluble CD30 (sCD30) level may be a poten-tial marker for the prediction of acute allograft rejection in kidney transplant recipients. Therefore, its serum concentrations might offer a promising non-invasive tool to recognize patients with an increased risk for developing an acute graft rejection. We retrospectively correlate pre and post transplant level on post transplant graft survival, incidence of acute rejection and graft function using stored serum samples. Ninety-nine patients were divided in two separate groups: Group A in whom sample collection was done one day before transplantation and Group B where sample collection was done five days after transplantation. Younger recipients (aged less than 20 years) had higher sCD30 levels (P= 0.02). There was neither significant difference in the incidence of acute rejection nor incomplete response rate after anti rejection therapy in relation to pre transplant or post transplant sCD30. We could not find a significantly inferior graft survival rate in the high sCD30 group. In conclusion, younger patients had higher sCD30 concentrations however no correlation existed between the serum concentrations and occurrence of rejection episodes or graft survival.

  19. Soluble CD30 for the prediction and detection of kidney transplant rejection.

    Science.gov (United States)

    Arjona, Alvaro

    2009-09-01

    Although safer and more effective immunosuppressants as well as enhanced immunosuppressive protocols are continuously being developed in order to increase graft survival, they come at the steep price of drug-related complications and important side effects. In addition, the value of panel reactive antibodies determination, which at present is the single most used indicator of an increased risk of transplant rejection, is now being reevaluated. Therefore, effective tailoring of immunosuppressive therapy minimizing the above-mentioned pitfalls requires the existence of dependable biomarkers that adequately monitor rejection risk both before and after transplantation. Here we review the data yielded by studies assessing the usefulness of measuring soluble CD30 levels (sCD30) in kidney transplant rejection. These data collectively show that sCD30 serum content has a considerable predictive/diagnostic value for acute rejection of renal grafts, particularly when measured a few days after transplantation. Copyright 2009 Prous Science, S.A.U. or its licensors. All rights reserved.

  20. Prediction of solubility and permeability class membership: provisional BCS classification of the world's top oral drugs.

    Science.gov (United States)

    Dahan, Arik; Miller, Jonathan M; Amidon, Gordon L

    2009-12-01

    The Biopharmaceutics Classification System (BCS) categorizes drugs into one of four biopharmaceutical classes according to their water solubility and membrane permeability characteristics and broadly allows the prediction of the rate-limiting step in the intestinal absorption process following oral administration. Since its introduction in 1995, the BCS has generated remarkable impact on the global pharmaceutical sciences arena, in drug discovery, development, and regulation, and extensive validation/discussion/extension of the BCS is continuously published in the literature. The BCS has been effectively implanted by drug regulatory agencies around the world in setting bioavailability/bioequivalence standards for immediate-release (IR) oral drug product approval. In this review, we describe the BCS scientific framework and impact on regulatory practice of oral drug products and review the provisional BCS classification of the top drugs on the global market. The Biopharmaceutical Drug Disposition Classification System and its association with the BCS are discussed as well. One notable finding of the provisional BCS classification is that the clinical performance of the majority of approved IR oral drug products essential for human health can be assured with an in vitro dissolution test, rather than empirical in vivo human studies.

  1. New Dendrimer-Based Nanoparticles Enhance Curcumin Solubility.

    Science.gov (United States)

    Falconieri, Maria Cristina; Adamo, Mauro; Monasterolo, Claudio; Bergonzi, Maria Camilla; Coronnello, Marcella; Bilia, Anna Rita

    2017-03-01

    Curcumin, the main curcuminoid of the popular Indian spice turmeric, is a potent chemopreventive agent and useful in many different diseases. A major limitation of applicability of curcumin as a health promoting and medicinal agent is its extremely low bioavailability due to efficient first pass metabolism, poor gastrointestinal absorption, rapid elimination, and poor aqueous solubility. In the present study, nanotechnology was selected as a choice approach to enhance the bioavailability of the curcuminis. A new polyamidoamine dendrimer (G0.5) was synthesized, characterized, and tested for cytotoxicity in human breast cancer cells (MCF-7). No cytotoxicity of G0.5 was found in the range between 10 -3 and 3 × 10 -8  M. Consequently, G0.5 was used to prepare spherical nanoparticles of ca. 150 nm, which were loaded with curcumin [molar ratio G0.5/curcumin 1 : 1 (formulation 1) and 1 : 0.5 (formulation 2)]. Remarkably, the occurrence of a single population of nanoparticles having an excellent polydispersity index (solubility of curcumin was increased ca. 415 and 150 times with respect to the unformulated drug, respectively, for formulation 1 and formulation 2. The release of curcumin from the nanoparticles showed an interesting prolonged and sustained release profile. Georg Thieme Verlag KG Stuttgart · New York.

  2. Water-soluble, triflate-based, pyrrolidinium ionic liquids

    International Nuclear Information System (INIS)

    Moreno, M.; Montanino, M.; Carewska, M.; Appetecchi, G.B.; Jeremias, S.; Passerini, S.

    2013-01-01

    Highlights: • Water-soluble, pyrrolidinium triflate ILs as solvents for extraction processes. • Electrolyte components for high safety, electrochemical devices. • Effect of the oxygen atom in the alkyl main side chain of pyrrolidinium cation. -- Abstract: The physicochemical and electrochemical properties of the water-soluble, N-methoxyethyl-N-methylpyrrolidinium trifluoromethanesulfonate (PYR 1(2O1) OSO 2 CF 3 ) ionic liquid (IL) were investigated and compared with those of commercial N-butyl-N-methylpyrrolidinium trifluoromethanesulfonate (PYR 14 OSO 2 CF 3 ). The results have shown that the transport properties are well correlated with the rheological and thermal behavior. The incorporation of an oxygen atom in the pyrrolidinium cation aliphatic side chain resulted in enhanced flexibility of the ether side chain, this supporting for the higher ionic conductivity, self-diffusion coefficient and density of PYR 1(2O1) OSO 2 CF 3 with respect to PYR 14 OSO 2 CF 3 , whereas no relevant effect on the crystallization of the ionic liquid was found. Finally, the presence of the ether side chain material in the pyrrolidinium cation led to a reduction in electrochemical stability, particularly on the cathodic verse

  3. NIR calibration of soluble stem carbohydrates for predicting drought tolerance in spring wheat

    Science.gov (United States)

    Soluble stem carbohydrates are a component of drought response in wheat (Triticum aestivum L.) and other grasses. Near-infrared spectroscopy (NIR) can rapidly assay for soluble carbohydrates indirectly, but this requires a statistical model for calibration. The objectives of this study were: (i) to ...

  4. Prediction of acute renal allograft rejection in early post-transplantation period by soluble CD30.

    Science.gov (United States)

    Dong, Wang; Shunliang, Yang; Weizhen, Wu; Qinghua, Wang; Zhangxin, Zeng; Jianming, Tan; He, Wang

    2006-06-01

    To evaluate the feasibility of serum sCD30 for prediction of acute graft rejection, we analyzed clinical data of 231 patients, whose serum levels of sCD30 were detected by ELISA before and after transplantation. They were divided into three groups: acute rejection group (AR, n = 49), uncomplicated course group (UC, n = 171) and delayed graft function group (DGF, n = 11). Preoperative sCD30 levels of three groups were 183 +/- 74, 177 +/- 82 and 168 +/- 53 U/ml, respectively (P = 0.82). Significant decrease of sCD30 was detected in three groups on day 5 and 10 post-transplantation respectively (52 +/- 30 and 9 +/- 5 U/ml respectively, P sCD30 values on day 5 post-transplantation (92 +/- 27 U/ml vs. 41 +/- 20 U/ml and 48 +/- 18 U/ml, P sCD30 levels on day 10 post-transplantation were virtually similar in patients of three groups (P = 0.43). Receiver operating characteristic (ROC) curve demonstrated that sCD30 level on day 5 post-transplantation could differentiate patients who subsequently suffered acute allograft rejection from others (area under ROC curve 0.95). According to ROC curve, 65 U/ml may be the optimal operational cut-off level to predict impending graft rejection (specificity 91.8%, sensitivity 87.1%). Measurement of soluble CD30 on day 5 post-transplantation might offer a noninvasive means to recognize patients at risk of impending acute graft rejection during early post-transplantation period.

  5. A prediction of the inert gas solubilities in stoichiometric molten UO2

    International Nuclear Information System (INIS)

    Gunnerson, F.S.; Cronenberg, A.W.

    1975-01-01

    To analyze the effect of fission gas behaviour on fast reactor fuels during a hypothetical overpower transient, the solubility characteristics of the noble gases in molten UO 2 have been assessed. To accomplish this, a theoretical estimation of such solubilities is made by determining the reversible work required to introduce a hard sphere, the size of the gas atom, into the liquid solvent. Results indicate that the solubility of the noble gases in molten UO 2 is quite low, the molar fraction of gas-to-liquid being approximately 10 -6 . Such a low solubility of fission gases suggests that for preirradiated fuels, added swelling or formation may occur upon melting. In addition, such low solubility potential indicates that the fission gases do not play an appreciable role in the fragmentation of molten UO 2 upon quenching in sodium coolant. (Auth.)

  6. Deep architectures and deep learning in chemoinformatics: the prediction of aqueous solubility for drug-like molecules.

    Science.gov (United States)

    Lusci, Alessandro; Pollastri, Gianluca; Baldi, Pierre

    2013-07-22

    Shallow machine learning methods have been applied to chemoinformatics problems with some success. As more data becomes available and more complex problems are tackled, deep machine learning methods may also become useful. Here, we present a brief overview of deep learning methods and show in particular how recursive neural network approaches can be applied to the problem of predicting molecular properties. However, molecules are typically described by undirected cyclic graphs, while recursive approaches typically use directed acyclic graphs. Thus, we develop methods to address this discrepancy, essentially by considering an ensemble of recursive neural networks associated with all possible vertex-centered acyclic orientations of the molecular graph. One advantage of this approach is that it relies only minimally on the identification of suitable molecular descriptors because suitable representations are learned automatically from the data. Several variants of this approach are applied to the problem of predicting aqueous solubility and tested on four benchmark data sets. Experimental results show that the performance of the deep learning methods matches or exceeds the performance of other state-of-the-art methods according to several evaluation metrics and expose the fundamental limitations arising from training sets that are too small or too noisy. A Web-based predictor, AquaSol, is available online through the ChemDB portal ( cdb.ics.uci.edu ) together with additional material.

  7. SORPTION AND SOLUBILITY OF LOW-SHRINKAGE RESIN-BASED DENTAL COMPOSITES

    Directory of Open Access Journals (Sweden)

    Sevda Yantcheva

    2016-04-01

    Full Text Available Background: Resin-based composites are well-established restorative materials. However, these materials may absorb significant amounts of water when exposed to aqueous environments. Sorption and solubility are affecting composite restorations by two different mechanisms; the first is the up taking of water producing an increased weight and the second is the dissolution of materials in water, leading to a weight reduction of the final conditioned samples. Objective: To measure the water sorption and solubility of different low-shrinkage resin-based composites. Six materials were selected: Filtek P60, Filtek Ultimate, SonicFill, Filtek Silorane, Kalore and Venus Diamond. Materials and methods: Five disc specimens were prepared of each material and polymerized with diode light-curing unit. Water sorption and solubility of the different materials were were calculated by means of weighting the samples before and after water immersion and desiccation. Data were statistically analyzed using Shapiro-Wilk One Way Analysis of Variance followed by the Holm-Sidak comparison test . Results: There were significant differences (p<=0.001 between materials regarding sorption and solubility. Regarding sorption F. Silorane showed lowest values, followed by SonicFill, without significant difference between them. Statistical significant differences exist between F. Silorane and F.P60, F. Ultimate, Kalore. Significant differences exist between SonicFill and F. Ultimate. F.Silorane (-0.018 and Kalore (-0.010 showed lowest values of solubility but there were marginal difference among all composites investigated. Conclusions: 1.The material with lowest values of sorption and solubility was F.Silorane. 2. The attained sorption and solubility values for composites are influenced by the differences in resin matrix composition and filler contend. 3. Modifications of dimethacrylate matrix did not minimize significantly sorption and solubility of composites. 4. Besides water

  8. CO2 Solubilities in Amide-based Brφnsted Acidic Ionic Liquids

    International Nuclear Information System (INIS)

    Palgunadi, Jelliarko; Im, Jin Kyu; Kang, Je Eun; Kim, Hoon Sik; Cheong, Min Serk

    2010-01-01

    A distinguished class of hydrophobic ionic liquids bearing a Brφnsted acidic character derived from amide-like compounds were prepared by a neutralization reaction of N,N-diethylformamide, N,N-dibutylformamide, 1-formylpiperidine, and ε-caprolactam with trifluoroacetic acid and physical absorptions of CO 2 in these ionic liquids were demonstrated and evaluated. CO 2 solubilities in these ionic liquids were influenced by the molecular structure of the cation and were apparently increased with the molar volume. Comparison based on a volume unit reveals that CO 2 solubilities in these liquids are relatively higher than those in imidazolium-based ionic liquids. Henry's coefficients calculated from low-pressure solubility tests at 313 to 333 K were used to derive the thermodynamics quantities. Enthalpy and entropy of solvation may share equal contributions in solubility

  9. High serum soluble CD30 does not predict acute rejection in liver transplant patients.

    Science.gov (United States)

    Matinlauri, I; Höckerstedt, K; Isoniemi, H

    2006-12-01

    Increased pre- and posttransplantation values of soluble CD30 (sCD30) have been shown to be associated with acute kidney transplant rejection. We sought to study whether high sCD30 could predict rejection early after liver transplantation. The study population included 54 consecutive liver transplant patients, whose samples were collected before liver transplantation and at discharge, which was at a mean time of 3 weeks after transplantation. During the first 6 months posttransplantation, 22 patients experienced an acute rejection episode. Serum sCD30 concentrations were measured by an enzyme-linked immunoassay; changes in serum sCD30 levels posttransplantation were also expressed as relative values compared with pretransplantation results. Liver patients before transplantation displayed higher serum sCD30 values compared with healthy controls: mean values +/- SD were 93 +/- 58 IU/mL vs 17 +/- 8 IU/mL, respectively. At 3 weeks after transplantation the mean sCD30 concentration in liver transplant patients decreased to 59 +/- 42 IU/mL (P = .005). The mean pretransplantation serum sCD30 value was slightly lower among rejecting vs nonrejecting patients: 78 +/- 43 IU/mL vs 104 +/- 65 IU/mL (P = NS). Posttransplantation values in both groups decreased significantly: 47 +/- 34 IU/mL in patients with rejection (P = .014) vs 69 +/- 45 IU/mL in patients without rejection (P = .012). The relative value at 3 weeks posttransplantation decreased slightly more among patients with vs without rejection (70% vs 88%; NS). No correlation was found between serum sCD30 and anti-HLA class I antibodies or crossmatch positivity. In conclusion, neither pre- nor posttransplantation sCD30 levels were associated with acute rejection in liver transplant patients.

  10. Soluble CD30 levels in recipients undergoing heart transplantation do not predict post-transplant outcome.

    Science.gov (United States)

    Ypsilantis, Efthymios; Key, Timothy; Bradley, J Andrew; Morgan, C Helen; Tsui, Stephen; Parameshwar, Jayan; Taylor, Craig J

    2009-11-01

    The pre-transplant serum level of soluble CD30 (sCD30), a proteolytic derivative of the lymphocyte surface receptor CD30, has been suggested as a biomarker for immunologic risk after organ transplantation. Pre-transplant serum sCD30 levels were determined in 200 consecutive adult heart transplant recipients undertaken at a single center. Transplant outcome (acute rejection in the first 12 months and patient survival up to 5 years post-transplant) was determined. Patients treated with a left ventricular assist device (LVAD) prior to transplantation (n = 28) had higher levels of sCD30 (median 64 U/ml, range 12 to 112 U/ml) than those (n = 172) with no LVAD (median 36 U/ml, range 1 to 158 U/ml, p sCD30 levels were "low" (lower quartile, 58 U/ml, n = 50). Neither acute rejection nor recipient survival differed according to sCD30 level, with values (mean +/- SEM) of 0.30 +/- 0.04, 0.23 +/- 0.03 and 0.30 +/- 0.05 acute rejection episodes per 100 days in the low, intermediate and high groups, respectively, with recipient survival rates at 1 year of 77.7%, 84.9% and 86% and at 5 years of 73.6%, 67.9% and 75.8%, respectively. Pre-transplant serum sCD30 level does not predict acute allograft rejection or recipient survival after heart transplantation, although sCD30 levels are increased by LVAD, possibly as a result of biomaterial-host immune interaction.

  11. Inkjet Printing of Organic Light-Emitting Diodes Based on Alcohol-Soluble Polyfluorenes

    Science.gov (United States)

    Odod, A. V.; Gadirov, R. M.; Solodova, T. A.; Kurtsevich, A. E.; Il'gach, D. M.; Yakimanskii, A. V.; Burtman, V.; Kopylova, T. N.

    2018-04-01

    Ink compositions for inkjet printing based on poly(9.9-dioctylfluorene) and its alcohol-soluble analog are created. Current-voltage, brightness-voltage, and spectral characteristics are compared for one- and twolayer polymer structures of organic light-emitting diodes. It is shown that the efficiency of the alcohol-soluble polyfluorene analog is higher compared to poly(9.9-dioctylfluorene), and the possibility of viscosity optimization is higher compared to aromatic chlorinated solvents.

  12. Prediction and correlation of high-pressure gas solubility in polymers with simplified PC-SAFT

    DEFF Research Database (Denmark)

    von Solms, Nicolas; Michelsen, Michael Locht; Kontogeorgis, Georgios

    2005-01-01

    Using simplified PC-SAFT we have modeled gas solubilities at high temperatures and pressures for the gases methane and carbon dioxide in each of the three polymers high-density polyethylene (HDPE), nylon polyamide-11 (PA-11), and poly(vinylidene fluoride) (PVDF). In general the results are satisf......Using simplified PC-SAFT we have modeled gas solubilities at high temperatures and pressures for the gases methane and carbon dioxide in each of the three polymers high-density polyethylene (HDPE), nylon polyamide-11 (PA-11), and poly(vinylidene fluoride) (PVDF). In general the results...

  13. Investigation of Cyclodextrin-Based Nanosponges for Solubility and Bioavailability Enhancement of Rilpivirine.

    Science.gov (United States)

    Rao, Monica R P; Chaudhari, Jagruti; Trotta, Francesco; Caldera, Fabrizio

    2018-06-04

    Rilpivrine is BCS class II drug used for treatment of HIV infection. The drug has low aqueous solubility (0.0166 mg/ml) and dissolution rate leading to low bioavailability (32%). Aim of this work was to enhance solubility and dissolution of rilpivirine using beta-cyclodextrin-based nanosponges. These nanosponges are biocompatible nanoporous particles having high loading capacity to form supramolecular inclusion and non-inclusion complexes with hydrophilic and lipophilic drugs for solubility enhancement. Beta-cyclodextrin was crosslinked with carbonyl diimidazole and pyromellitic dianhydride to prepare nanosponges. The nanosponges were loaded with rilpivirine by solvent evaporation method. Binary and ternary complexes of drug with β-CD, HP-β-CD, nanosponges, and tocopherol polyethylene glycol succinate were prepared and characterized by phase solubility, saturation solubility in different media, in vitro dissolution, and in vivo pharmacokinetics. Spectral analysis by Fourier transform infrared spectroscopy, powder X-ray diffraction, and differential scanning calorimetry was performed. Results obtained from spectral characterization confirmed inclusion complexation. Phase solubility studies indicated stable complex formation. Saturation solubility was found to be 10-13-folds higher with ternary complexes in distilled water and 12-14-fold higher in 0.1 N HCl. Solubility enhancement was evident in biorelevant media. Molecular modeling studies revealed possible mode of entrapment of rilpivirine within β-CD cavities. A 3-fold increase in dissolution with ternary complexes was observed. Animal studies revealed nearly 2-fold increase in oral bioavailability of rilpivirine. It was inferred that electronic interactions, hydrogen bonding, and van der Waals forces are involved in the supramolecular interactions.

  14. The Prognostic and Predictive Value of Soluble Type IV Collagen in Colorectal Cancer

    DEFF Research Database (Denmark)

    Rolff, Hans Christian; Christensen, Ib Jarle; Vainer, Ben

    2016-01-01

    PURPOSE: To investigate the prognostic and predictive biomarker value of type IV collagen in colorectal cancer. EXPERIMENTAL DESIGN: Retrospective evaluation of two independent cohorts of patients with colorectal cancer included prospectively in 2004-2005 (training set) and 2006-2008 (validation....... RESULTS: High levels of type IV collagen showed independent prognostic significance in both cohorts with hazard ratios (HRs; for a one-unit change on the log base 2 scale) of 2.25 [95% confidence intervals (CIs), 1.78-2.84; P ... and validation set, respectively. The prognostic impact was present both in patients with metastatic and nonmetastatic disease. The predictive value of the marker was investigated in stage II and III patients. In the training set, type IV collagen was prognostic both in the subsets of patients receiving...

  15. Macrophage activation marker soluble CD163 may predict disease progression in hepatocellular carcinoma

    DEFF Research Database (Denmark)

    Kazankov, Konstantin; Rode, Anthony; Simonsen, Kira Schreiner

    2016-01-01

    BACKGROUND: Tumor associated macrophages are present in hepatocellular carcinoma (HCC) and associated with a poor prognosis. The aim of the present study was to investigate the levels and dynamics of soluble (s)CD163, a specific macrophage activation marker, in patients with HCC. METHODS: In a co...

  16. Predicting the solubility of mixtures of sugars and their replacers using the Flory-Huggins theory

    NARCIS (Netherlands)

    Sman, van der R.G.M.

    2017-01-01

    In this paper we investigate whether the Flory-Huggins theory can describe the thermodynamics of solutions of simple carbohydrates, like sugars and polyols. In particular, we focus on the description of the solubility of the carbohydrates in water. This is investigated for both binary and ternary

  17. Fasting serum soluble CD 163 predicts risk of type 2 diabetes in ...

    African Journals Online (AJOL)

    grade inflammation is believed to play a central role in the evolution of type 2 diabetes. Aim: To assess whether a new macrophage-derived biomarker, soluble CD163, identifies at-risk individuals with metabolic syndrome before overt disease ...

  18. Serum soluble CD163 predicts risk of type 2 diabetes in the general population

    DEFF Research Database (Denmark)

    Møller, Holger Jon; Frikke-Schmidt, Ruth; Moestrup, Søren

    2011-01-01

    Activation of adipose tissue macrophages with concomitant low-grade inflammation is believed to play a central role in the development of type 2 diabetes. We tested whether a new macrophage-derived biomarker, soluble CD163 (sCD163), identifies at-risk individuals before overt disease has developed....

  19. The solubility of solid fission products in carbides and nitrides of uranium and plutonium: Pt.2. Solubility rules based on lattice parameter differences

    International Nuclear Information System (INIS)

    Benedict, U.

    1977-01-01

    The Relative Lattice Parameter Difference (RLPD) is defined for a solute element with respect to cubic carbides and nitrides of uranium and plutonium as solvents. Rules are given for the relationship between the solubility and the RLPD. NaCl type monocarbides with RLPD's from -10.2% to +7.8% are completely miscible with UC and PuC. NaCl type mononitrides with RLPD's from -7.5% to +8.5% are completely miscible with UN and PuN. The solubility in the sesquicarbides increases with decreasing RPLD and becomes complete in Pu 2 C 3 at RLPD = +4%, and in U 2 C 3 at RLPD approximately +1.5%. Solubilities are predicted on the basis of these rules for the cases where no experimental results are available

  20. Bioavailability of elemental iron powders to rats is less than bakery-grade ferrous sulfate and predicted by iron solubility and particle surface area.

    Science.gov (United States)

    Swain, James H; Newman, Samuel M; Hunt, Janet R

    2003-11-01

    Foods are fortified with elemental forms of iron to reduce iron deficiency. However, the nutritional efficacy of current, commercially produced elemental iron powders has not been verified. We determined the bioavailability of six commercial elemental iron powders and examined how physicochemistry influences bioavailability. Relative biological value (RBV) of the iron powders was determined using a hemoglobin repletion/slope ratio method, treating iron-deficient rats with repletion diets fortified with graded quantities of iron powders, bakery-grade ferrous sulfate or no added iron. Iron powders were assessed physicochemically by measuring iron solubility in hydrochloric acid at pH 1.0 and 1.7, surface area by nitrogen gas adsorption and surface microstructure by electron microscopy. Bioavailability from the iron powders, based on absolute iron intake, was significantly less than from FeSO4 (100%; P Electrolytic (54%; A-131, U.S.) > Electrolytic (46%; Electrolytic Iron, India) > H-Reduced (42%; AC-325, U.S.) > Reduced (24%; ATOMET 95SP, Canada) > CO-Reduced (21%; RSI-325, Sweden). Solubility testing of the iron powders resulted in different relative rankings and better RBV predictability with increasing time at pH 1.7 (R2 = 0.65 at 150 min). The prediction was improved with less time and lower pH (R2 = 0.82, pH 1.0 at 30 min). Surface area, ranging from 90 to 370 m2/kg, was also highly predictive of RBV (R2 = 0.80). Bioavailability of iron powders is less than bakery-grade ferrous sulfate and varies up to three times among different commercial forms. Solubility at pH 1.0 and surface area were predictive of iron bioavailability in rats.

  1. Biocompatible choline based ionic salts: Solubility in short-chain alcohols

    International Nuclear Information System (INIS)

    Lopes, Joana M.; Paninho, Ana B.; Môlho, Marta F.; Nunes, Ana V.M.; Rocha, Angelo; Lourenço, Nuno M.T.; Najdanovic-Visak, Vesna

    2013-01-01

    Highlights: • Biocompatible ionic liquids based on choline esters were synthesized in this work. • Solubility of choline and choline esters based ionic salt in alcohols were measured. • Activity coefficients were calculated. • Experimental data were correlated by means of the semi-empirical Grant equation. -- Abstract: In this work, we report data on solubility of choline chloride and choline acetate in short-chain linear alcohols (ethanol, 1-propanol and 1-butanol) at various temperatures. Furthermore, we synthesize two choline derivatives: hydrogen choline chloride glutarate ([CholGlut][Cl]) and hydrogen choline chloride succinate ([CholSucc][Cl]). Their characterization and solubility in short-chain alcohols as a function of temperature are also included. Activity coefficients were calculated and their comparisons with ideal solutions were discussed. The experimental data were correlated successfully by means of the semi-empirical Grant equation

  2. Prediction based on mean subset

    DEFF Research Database (Denmark)

    Øjelund, Henrik; Brown, P. J.; Madsen, Henrik

    2002-01-01

    , it is found that the proposed mean subset method has superior prediction performance than prediction based on the best subset method, and in some settings also better than the ridge regression and lasso methods. The conclusions drawn from the Monte Carlo study is corroborated in an example in which prediction......Shrinkage methods have traditionally been applied in prediction problems. In this article we develop a shrinkage method (mean subset) that forms an average of regression coefficients from individual subsets of the explanatory variables. A Bayesian approach is taken to derive an expression of how...... the coefficient vectors from each subset should be weighted. It is not computationally feasible to calculate the mean subset coefficient vector for larger problems, and thus we suggest an algorithm to find an approximation to the mean subset coefficient vector. In a comprehensive Monte Carlo simulation study...

  3. Decision trees to characterise the roles of permeability and solubility on the prediction of oral absorption

    OpenAIRE

    Newby, Danielle; Freitas, Alex. A.; Ghafourian, Taravat

    2015-01-01

    Oral absorption of compounds depends on many physiological, physiochemical and formulation factors. Two important properties that govern oral absorption are in vitro permeability and solubility, which are commonly used as indicators of human intestinal absorption. Despite this, the nature and exact characteristics of the relationship between these parameters are not well understood. In this study a large dataset of human intestinal absorption was collated along with in vitro permeability, aqu...

  4. Soluble adenylyl cyclase is an acid-base sensor in epithelial base-secreting cells.

    Science.gov (United States)

    Roa, Jinae N; Tresguerres, Martin

    2016-08-01

    Blood acid-base regulation by specialized epithelia, such as gills and kidney, requires the ability to sense blood acid-base status. Here, we developed primary cultures of ray (Urolophus halleri) gill cells to study mechanisms for acid-base sensing without the interference of whole animal hormonal regulation. Ray gills have abundant base-secreting cells, identified by their noticeable expression of vacuolar-type H(+)-ATPase (VHA), and also express the evolutionarily conserved acid-base sensor soluble adenylyl cyclase (sAC). Exposure of cultured cells to extracellular alkalosis (pH 8.0, 40 mM HCO3 (-)) triggered VHA translocation to the cell membrane, similar to previous reports in live animals experiencing blood alkalosis. VHA translocation was dependent on sAC, as it was blocked by the sAC-specific inhibitor KH7. Ray gill base-secreting cells also express transmembrane adenylyl cyclases (tmACs); however, tmAC inhibition by 2',5'-dideoxyadenosine did not prevent alkalosis-dependent VHA translocation, and tmAC activation by forskolin reduced the abundance of VHA at the cell membrane. This study demonstrates that sAC is a necessary and sufficient sensor of extracellular alkalosis in ray gill base-secreting cells. In addition, this study indicates that different sources of cAMP differentially modulate cell biology. Copyright © 2016 the American Physiological Society.

  5. Pre-transplant and post-transplant soluble CD30 for prediction and diagnosis of acute kidney allograft rejection.

    Science.gov (United States)

    Nafar, Mohsen; Farrokhi, Farhat; Vaezi, Mohammad; Entezari, Amir-Ebrahim; Pour-Reza-Gholi, Fatemeh; Firoozan, Ahmad; Eniollahi, Behzad

    2009-01-01

    Serum levels of soluble CD30 (sCD30) have been considered as a predictor of acute kidney allograft rejection. We have evaluated the pre-transplant and post-transplant levels of sCD30 with the aim of determining its value in predicting and diagnosing kidney rejection. We measured sCD30 serum levels before kidney transplantation, 5 days post-operatively, and at creatinine elevation episodes. The predictive value of sCD30 for diagnosing acute rejection (AR) within the first 6 post-operative months was assessed in 203 kidney recipients from living donors. Pre-transplant and post-operative levels of serum sCD30 were 58.10 +/- 52.55 and 51.55 +/- 49.65 U/ml, respectively (P = 0.12). Twenty-three patients experienced biopsy-proven acute rejection, and 28 had acute allograft dysfunction due to non-immunologic diseases. The pre-transplant sCD30 level was not different between patients with and without AR. However, post-transplant sCD30 was higher in the AR group. The median serum level of post-transplant sCD30 was 52 U/ml in the AR group and 26.3 U/ml in a control group (P sCD30 on day 5 were higher in patients with AR (P = 0.003). Based on post-transplant sCD30 levels, we were able to differentiate between kidney recipients who experienced an AR within 6 months post-surgery and those without an AR (cutoff value 41 U/ml; sensitivity 70%; specificity 71.7%). The level of sCD30 during periods of elevated serum creatinine was not independently associated with the diagnosis of AR. Post-transplant sCD30 levels and their relative changes are higher in patients experiencing AR. We propose further studies on the post-transplant trend of this marker for the prediction of AR.

  6. Lipid-based formulations for oral administration of poorly water-soluble drugs

    DEFF Research Database (Denmark)

    Mu, Huiling; Holm, René; Müllertz, Anette

    2013-01-01

    Lipid-based drug delivery systems have shown great potentials in oral delivery of poorly water-soluble drugs, primarily for lipophilic drugs, with several successfully marketed products. Pre-dissolving drugs in lipids, surfactants, or mixtures of lipids and surfactants omits the dissolving....../dissolution step, which is a potential rate limiting factor for oral absorption of poorly water-soluble drugs. Lipids not only vary in structures and physiochemical properties, but also in their digestibility and absorption pathway; therefore selection of lipid excipients and dosage form has a pronounced effect...

  7. Activity-Based Approach for Teaching Aqueous Solubility, Energy, and Entropy

    Science.gov (United States)

    Eisen, Laura; Marano, Nadia; Glazier, Samantha

    2014-01-01

    We describe an activity-based approach for teaching aqueous solubility to introductory chemistry students that provides a more balanced presentation of the roles of energy and entropy in dissolution than is found in most general chemistry textbooks. In the first few activities, students observe that polar substances dissolve in water, whereas…

  8. Evaluation Of The Integrated Solubility Model, A Graded Approach For Predicting Phase Distribution In Hanford Tank Waste

    International Nuclear Information System (INIS)

    Pierson, Kayla L.; Belsher, Jeremy D.; Seniow, Kendra R.

    2012-01-01

    The mission of the DOE River Protection Project (RPP) is to store, retrieve, treat and dispose of Hanford's tank waste. Waste is retrieved from the underground tanks and delivered to the Waste Treatment and Immobilization Plant (WTP). Waste is processed through a pretreatment facility where it is separated into low activity waste (LAW), which is primarily liquid, and high level waste (HLW), which is primarily solid. The LAW and HLW are sent to two different vitrification facilities and glass canisters are then disposed of onsite (for LAW) or shipped off-site (for HLW). The RPP mission is modeled by the Hanford Tank Waste Operations Simulator (HTWOS), a dynamic flowsheet simulator and mass balance model that is used for mission analysis and strategic planning. The integrated solubility model (ISM) was developed to improve the chemistry basis in HTWOS and better predict the outcome of the RPP mission. The ISM uses a graded approach to focus on the components that have the greatest impact to the mission while building the infrastructure for continued future improvement and expansion. Components in the ISM are grouped depending upon their relative solubility and impact to the RPP mission. The solubility of each group of components is characterized by sub-models of varying levels of complexity, ranging from simplified correlations to a set of Pitzer equations used for the minimization of Gibbs Energy

  9. Evaluation Of The Integrated Solubility Model, A Graded Approach For Predicting Phase Distribution In Hanford Tank Waste

    Energy Technology Data Exchange (ETDEWEB)

    Pierson, Kayla L.; Belsher, Jeremy D.; Seniow, Kendra R.

    2012-10-19

    The mission of the DOE River Protection Project (RPP) is to store, retrieve, treat and dispose of Hanford's tank waste. Waste is retrieved from the underground tanks and delivered to the Waste Treatment and Immobilization Plant (WTP). Waste is processed through a pretreatment facility where it is separated into low activity waste (LAW), which is primarily liquid, and high level waste (HLW), which is primarily solid. The LAW and HLW are sent to two different vitrification facilities and glass canisters are then disposed of onsite (for LAW) or shipped off-site (for HLW). The RPP mission is modeled by the Hanford Tank Waste Operations Simulator (HTWOS), a dynamic flowsheet simulator and mass balance model that is used for mission analysis and strategic planning. The integrated solubility model (ISM) was developed to improve the chemistry basis in HTWOS and better predict the outcome of the RPP mission. The ISM uses a graded approach to focus on the components that have the greatest impact to the mission while building the infrastructure for continued future improvement and expansion. Components in the ISM are grouped depending upon their relative solubility and impact to the RPP mission. The solubility of each group of components is characterized by sub-models of varying levels of complexity, ranging from simplified correlations to a set of Pitzer equations used for the minimization of Gibbs Energy.

  10. A Fluid Membrane-Based Soluble Ligand Display System for Live CellAssays

    Energy Technology Data Exchange (ETDEWEB)

    Nam, Jwa-Min; Nair, Pradeep N.; Neve, Richard M.; Gray, Joe W.; Groves, Jay T.

    2005-10-14

    Cell communication modulates numerous biological processes including proliferation, apoptosis, motility, invasion and differentiation. Correspondingly, there has been significant interest in the development of surface display strategies for the presentation of signaling molecules to living cells. This effort has primarily focused on naturally surface-bound ligands, such as extracellular matrix components and cell membranes. Soluble ligands (e.g. growth factors and cytokines) play an important role in intercellular communications, and their display in a surface-bound format would be of great utility in the design of array-based live cell assays. Recently, several cell microarray systems that display cDNA, RNAi, or small molecules in a surface array format were proven to be useful in accelerating high-throughput functional genetic studies and screening therapeutic agents. These surface display methods provide a flexible platform for the systematic, combinatorial investigation of genes and small molecules affecting cellular processes and phenotypes of interest. In an analogous sense, it would be an important advance if one could display soluble signaling ligands in a surface assay format that allows for systematic, patterned presentation of soluble ligands to live cells. Such a technique would make it possible to examine cellular phenotypes of interest in a parallel format with soluble signaling ligands as one of the display parameters. Herein we report a ligand-modified fluid supported lipid bilayer (SLB) assay system that can be used to functionally display soluble ligands to cells in situ (Figure 1A). By displaying soluble ligands on a SLB surface, both solution behavior (the ability to become locally enriched by reaction-diffusion processes) and solid behavior (the ability to control the spatial location of the ligands in an open system) could be combined. The method reported herein benefits from the naturally fluid state of the supported membrane, which allows

  11. Solubility of fragrance raw materials in water: Experimental study, correlations, and Mod. UNIFAC (Do) predictions

    Energy Technology Data Exchange (ETDEWEB)

    Domanska, Urszula, E-mail: ula@ch.pw.edu.p [Department of Physical Chemistry, Faculty of Chemistry, Warsaw University of Technology, Noakowskiego 3, 00-664 Warsaw (Poland); Paduszynski, Kamil; Niszczota, Zaneta K. [Department of Physical Chemistry, Faculty of Chemistry, Warsaw University of Technology, Noakowskiego 3, 00-664 Warsaw (Poland)

    2011-01-15

    The (liquid + liquid) and (solid + liquid) phase equilibria of nine binary mixtures containing fragrance raw materials (FRM) such as aliphatic ketones and compounds based on cyclohexane with water were investigated. The systems {l_brace}2-heptanone, or 2-nonanone, or 2-undecanone, or 2-tridecanone, or cyclohexyl carboxylic acid (CCA), or cyclohexyl acetic acid (CAA), or 2-cyclohexyl ethanol (2CE) or cyclohexyl acetate (CA), or 2-cyclohexyl ethyl acetate (2CEA) + water (2){r_brace} have been measured by a dynamic method in wide range of temperatures from (290 to 360) K and ambient pressure. For all systems immiscibility in the liquid phase was detected. The experimental data was correlated by means of the NRTL equation, utilizing parameters derived from the (liquid + liquid) equilibrium. Additionally, the binary mixtures were predicted with the Mod. UNIFAC (Do) model, with known from literature parameters, with very good results.

  12. Solubility of fragrance raw materials in water: Experimental study, correlations, and Mod. UNIFAC (Do) predictions

    International Nuclear Information System (INIS)

    Domanska, Urszula; Paduszynski, Kamil; Niszczota, Zaneta K.

    2011-01-01

    The (liquid + liquid) and (solid + liquid) phase equilibria of nine binary mixtures containing fragrance raw materials (FRM) such as aliphatic ketones and compounds based on cyclohexane with water were investigated. The systems {2-heptanone, or 2-nonanone, or 2-undecanone, or 2-tridecanone, or cyclohexyl carboxylic acid (CCA), or cyclohexyl acetic acid (CAA), or 2-cyclohexyl ethanol (2CE) or cyclohexyl acetate (CA), or 2-cyclohexyl ethyl acetate (2CEA) + water (2)} have been measured by a dynamic method in wide range of temperatures from (290 to 360) K and ambient pressure. For all systems immiscibility in the liquid phase was detected. The experimental data was correlated by means of the NRTL equation, utilizing parameters derived from the (liquid + liquid) equilibrium. Additionally, the binary mixtures were predicted with the Mod. UNIFAC (Do) model, with known from literature parameters, with very good results.

  13. Acid-base equilibria and solubility of loratadine and desloratadine in water and micellar media.

    Science.gov (United States)

    Popović, Gordana; Cakar, Mira; Agbaba, Danica

    2009-01-15

    Acid-base equilibria in homogeneous and heterogeneous systems of two antihistaminics, loratadine and desloratadine were studied spectrophotometrically in Britton-Robinson's buffer at 25 degrees C. Acidity constant of loratadine was found to be pK(a) 5.25 and those of desloratadine pK(a1) 4.41 and pK(a2) 9.97. The values of intrinsic solubilities of loratadine and desloratadine were 8.65x10(-6) M and 3.82x10(-4) M, respectively. Based on the pK(a) values and intrinsic solubilities, solubility curves of these two drugs as a function of pH were calculated. The effects of anionic, cationic and non-ionic surfactants applied in the concentration exceeding critical micelle concentration (cmc) on acid-base properties of loratadine and desloratadine, as well as on intrinsic solubility of loratadine were also examined. The results revealed a shift of pK(a) values in micellar media comparing to the values obtained in water. These shifts (DeltapK(a)) ranged from -2.24 to +1.24.

  14. Determination of water-soluble vitamins using a colorimetric microbial viability assay based on the reduction of water-soluble tetrazolium salts.

    Science.gov (United States)

    Tsukatani, Tadayuki; Suenaga, Hikaru; Ishiyama, Munetaka; Ezoe, Takatoshi; Matsumoto, Kiyoshi

    2011-07-15

    A method for the determination of water-soluble vitamins using a colorimetric microbial viability assay based on the reduction of the tetrazolium salt {2-(2-methoxy-4-nitrophenyl)-3-(4-nitrophenyl)-5-(2,4-disulfophenyl)-2H-tetrazolium, monosodium salt (WST-8)} via 2-methyl-1,4-napthoquinone (NQ) was developed. Measurement conditions were optimized for the microbiological determination of water-soluble vitamins, such as vitamin B(6), biotin, folic acid, niacin, and pantothenic acid, using microorganisms that have a water-soluble vitamin requirement. A linear relationship between absorbance and water-soluble vitamin concentration was obtained. The proposed method was applied to determine the concentration of vitamin B(6) in various foodstuffs. There was good agreement between vitamin B(6) concentrations determined after 24h using the WST-8 colorimetric method and those obtained after 48h using a conventional method. The results suggest that the WST-8 colorimetric assay is a useful method for the rapid determination of water-soluble vitamins in a 96-well microtiter plate. Copyright © 2011 Elsevier Ltd. All rights reserved.

  15. Enhanced solubility and bioavailability of sibutramine base by solid dispersion system with aqueous medium.

    Science.gov (United States)

    Li, Dong Xun; Jang, Ki-Young; Kang, Wonku; Bae, Kyoungjin; Lee, Mann Hyung; Oh, Yu-Kyoung; Jee, Jun-Pil; Park, Young-Joon; Oh, Dong Hoon; Seo, Youn Gee; Kim, Young Ran; Kim, Jong Oh; Woo, Jong Soo; Yong, Chul Soon; Choi, Han-Gon

    2010-01-01

    To develop a novel sibutramine base-loaded solid dispersion with improved solubility bioavailability, various solid dispersions were prepared with water, hydroxypropylmethyl cellulose (HPMC), poloxamer and citric acid using spray-drying technique. The effect of HPMC, poloxamer and citric acid on the aqueous solubility of sibutramine was investigated. The physicochemical properties of solid dispersion were investigated using scanning electron microscopy (SEM), differential scanning calorimetry (DSC) and X-ray powder diffraction. The dissolution and pharmacokinetics in rats of solid dispersion were evaluated compared to the sibutramine hydrochloride monohydrate-loaded commercial product (Reductil). The sibutramine base-loaded solid dispersion gave two type forms. Like conventional solid dispersion system, one type appeared as a spherical shape with smooth surface, as the carriers and drug with relatively low melting point were soluble in water and formed it. The other appeared as an irregular form with relatively rough surface. Unlike conventional solid dispersion system, this type changed no crystalline form of drug. Our results suggested that this type was formed by attaching hydrophilic carriers to the surface of drug without crystal change, resulting from changing the hydrophobic drug to hydrophilic form. The sibutramine-loaded solid dispersion at the weight ratio of sibutramine base/HPMC/poloxamer/citric acid of 5/3/3/0.2 gave the maximum drug solubility of about 3 mg/ml. Furthermore, it showed the similar plasma concentration, area under the curve (AUC) and C(max) of parent drug, metabolite I and II to the commercial product, indicating that it might give the similar drug efficacy compared to the sibutramine hydrochloride monohydrate-loaded commercial product in rats. Thus, this solid dispersion system would be useful to deliver poorly water-soluble sibutramine base with enhanced bioavailability.

  16. Macrophage serum markers in pneumococcal bacteremia: Prediction of survival by soluble CD163

    DEFF Research Database (Denmark)

    Møller, Holger Jon; K. Moestrup, Søren; Weis, Nina Margrethe

    2006-01-01

    OBJECTIVE: Soluble CD163 (sCD163) is a new macrophage-specific serum marker. This study investigated sCD163 and other markers of macrophage activation (neopterin, ferritin, transcobalamin, and soluble urokinase plasminogen activator receptor [suPAR]) as prognostic factors in patients...... analyses at the time of first positive blood culture. MEASUREMENTS AND MAIN RESULTS: sCD163 was highly correlated with other macrophage markers and was significantly elevated (median [25-75 percentiles], 4.6 mg/L [2.8-8.9]) compared with healthy controls (2.7 mg/L [2.1-3.3], p ..., all macrophage markers were increased in patients who died from their infection compared with survivors, whereas no change was observed in any of the markers in the very old age. At cutoff levels of 9.5 mg/L (sCD163) and 1650 nmol/L (C-reactive protein), the relative risk for fatal outcome in patients...

  17. Chasing equilibrium: measuring the intrinsic solubility of weak acids and bases.

    Science.gov (United States)

    Stuart, Martin; Box, Karl

    2005-02-15

    A novel procedure is described for rapid (20-80 min) measurement of intrinsic solubility values of organic acids, bases, and ampholytes. In this procedure, a quantity of substance was first dissolved at a pH where it exists predominantly in its ionized form, and then a precipitate of the neutral (un-ionized) species was formed by changing the pH. Subsequently, the rate of change of pH due to precipitation or dissolution was monitored and strong acid and base titrant were added to adjust the pH to discover its equilibrium conditions, and the intrinsic solubility of the neutral form of the compound could then be determined. The procedure was applied to a variety of monoprotic and diprotic pharmaceutical compounds. The results were highly repeatable and had a good correlation to available published values. Data collected during the procedure provided good diagnostic information. Kinetic solubility data were also collected but provided a poor guide to the intrinsic solubility.

  18. Prediction of response to medical therapy by serum soluble (pro)renin receptor levels in Graves' disease.

    Science.gov (United States)

    Mizuguchi, Yuki; Morimoto, Satoshi; Kimura, Shihori; Takano, Noriyoshi; Yamashita, Kaoru; Seki, Yasufumi; Bokuda, Kanako; Yatabe, Midori; Yatabe, Junichi; Watanabe, Daisuke; Ando, Takashi; Ichihara, Atsuhiro

    2018-01-01

    Antithyroid drugs are generally selected as the first-line treatment for Graves' Disease (GD); however, the existence of patients showing resistance or severe side effects to these drugs is an important issue to be solved. The (pro)renin receptor [(P)RR] is a multi-functional protein that activates the tissue renin-angiotensin system and is an essential constituent of vacuolar H+-ATPase, necessary for the autophagy-lysosome pathway. (P)RR is cleaved to soluble (s)(P)RR, which reflects the status of (P)RR expression. In this retrospective study, we aimed to investigate whether serum s(P)RR concentration can be used as a biomarker to predict the outcome of antithyroid drug treatment in GD patients. Serum s(P)RR levels were measured in 54 untreated GD patients and 47 control participants. Effects of medical treatment with antithyroid drugs on these levels were investigated in GD patients. Serum s(P)RR levels were significantly higher in patients with Graves' disease than in control subjects (PGraves' disease. High serum s(P)RR levels were associated with resistance to antithyroid drug treatment, suggesting that serum s(P)RR concentration can be used as a useful biomarker to predict the outcome of antithyroid drug treatment in these patients. Patients with Graves' disease with low body mass index showed higher levels of serum soluble (pro)renin receptor levels than those with high body mass index. In addition, in patients with Graves' disease, serum triglyceride levels were negatively correlated with serum soluble (pro)renin receptor levels. All these data indicated an association between low nutrient condition due to hyperthyroidism and increased (pro)renin receptor expression in these patients, suggesting that (pro)renin receptor expression could be increased in the process of stimulating intracellular energy production via activating autophagy function to compensate energy loss.

  19. Prediction of response to medical therapy by serum soluble (pro)renin receptor levels in Graves’ disease

    Science.gov (United States)

    Kimura, Shihori; Takano, Noriyoshi; Yamashita, Kaoru; Seki, Yasufumi; Bokuda, Kanako; Yatabe, Midori; Yatabe, Junichi; Watanabe, Daisuke; Ando, Takashi

    2018-01-01

    Antithyroid drugs are generally selected as the first-line treatment for Graves’ Disease (GD); however, the existence of patients showing resistance or severe side effects to these drugs is an important issue to be solved. The (pro)renin receptor [(P)RR] is a multi-functional protein that activates the tissue renin-angiotensin system and is an essential constituent of vacuolar H+-ATPase, necessary for the autophagy-lysosome pathway. (P)RR is cleaved to soluble (s)(P)RR, which reflects the status of (P)RR expression. In this retrospective study, we aimed to investigate whether serum s(P)RR concentration can be used as a biomarker to predict the outcome of antithyroid drug treatment in GD patients. Serum s(P)RR levels were measured in 54 untreated GD patients and 47 control participants. Effects of medical treatment with antithyroid drugs on these levels were investigated in GD patients. Serum s(P)RR levels were significantly higher in patients with Graves’ disease than in control subjects (Pantithyroid drug treatment, suggesting that serum s(P)RR concentration can be used as a useful biomarker to predict the outcome of antithyroid drug treatment in these patients. Patients with Graves’ disease with low body mass index showed higher levels of serum soluble (pro)renin receptor levels than those with high body mass index. In addition, in patients with Graves’ disease, serum triglyceride levels were negatively correlated with serum soluble (pro)renin receptor levels. All these data indicated an association between low nutrient condition due to hyperthyroidism and increased (pro)renin receptor expression in these patients, suggesting that (pro)renin receptor expression could be increased in the process of stimulating intracellular energy production via activating autophagy function to compensate energy loss. PMID:29621332

  20. Weak bases and formation of a less soluble lauryl sulfate salt/complex in sodium lauryl sulfate (SLS) containing media.

    Science.gov (United States)

    Bhattachar, Shobha N; Risley, Donald S; Werawatganone, Pornpen; Aburub, Aktham

    2011-06-30

    This work reports on the solubility of two weakly basic model compounds in media containing sodium lauryl sulfate (SLS). Results clearly show that the presence of SLS in the media (e.g. simulated gastric fluid or dissolution media) can result in an underestimation of solubility of some weak bases. We systematically study this phenomenon and provide evidence (chromatography and pXRD) for the first time that the decrease in solubility is likely due to formation of a less soluble salt/complex between the protonated form of the weak base and lauryl sulfate anion. Copyright © 2011 Elsevier B.V. All rights reserved.

  1. Micro-scale prediction method for API-solubility in polymeric matrices and process model for forming amorphous solid dispersion by hot-melt extrusion.

    Science.gov (United States)

    Bochmann, Esther S; Neumann, Dirk; Gryczke, Andreas; Wagner, Karl G

    2016-10-01

    A new predictive micro-scale solubility and process model for amorphous solid dispersions (ASDs) by hot-melt extrusion (HME) is presented. It is based on DSC measurements consisting of an annealing step and a subsequent analysis of the glass transition temperature (Tg). The application of a complex mathematical model (BCKV-equation) to describe the dependency of Tg on the active pharmaceutical ingredient (API)/polymer ratio, enables the prediction of API solubility at ambient conditions (25°C). Furthermore, estimation of the minimal processing temperature for forming ASDs during HME trials could be defined and was additionally confirmed by X-ray powder diffraction data. The suitability of the DSC method was confirmed with melt rheological trials (small amplitude oscillatory system). As an example, ball milled physical mixtures of dipyridamole, indomethacin, itraconazole and nifedipine in poly(vinylpyrrolidone-co-vinylacetate) (copovidone) and polyvinyl caprolactam-polyvinyl acetate-polyethylene glycol graft copolymer (Soluplus®) were used. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Serum soluble CD163 predicts risk of type 2 diabetes in the general population

    DEFF Research Database (Denmark)

    Møller, Holger J; Frikke-Schmidt, Ruth; Moestrup, Søren K

    2011-01-01

    has developed. METHODS: A prospective cohort study of 8849 study participants from the general population, the Copenhagen City Heart Study, was followed for 18 years for incidence of type 2 diabetes. Risk of disease was calculated according to age- and sex-adjusted percentile categories of serum s......BACKGROUND: Activation of adipose tissue macrophages with concomitant low-grade inflammation is believed to play a central role in the development of type 2 diabetes. We tested whether a new macrophage-derived biomarker, soluble CD163 (sCD163), identifies at-risk individuals before overt disease......CD163 concentrations: 0%-33%, 34%-66%, 67%-90%, 91%-95%, and 96%-100%. RESULTS: A total of 568 participants developed type 2 diabetes. The cumulative incidence increased with increasing baseline sCD163 (trend P

  3. Prediction of Permeation Resistance of Protective Gloves, etc. from Solubility Parameters

    DEFF Research Database (Denmark)

    Henriksen, H. Risvig; Madsen, Jørgen Øgaard

    1997-01-01

    ). A starting point was the authoritative conclusion (Coletta et al., 1978), that permeation in protective clothing could not be predicted. As a spin off, the predictive concept indicated that new types of polymers sometimes should be incorporated to reach a reasonable (long) breakthrough time and (low...

  4. The Solubility of Aluminum in Cryolite-Based Electrolyte-Containing KF

    Science.gov (United States)

    Zhang, Yu; Yu, Jiangyu; Gao, Bingliang; Liu, Yibai; Hu, Xianwei; Shi, Zhongning; Wang, Zhaowen

    2016-04-01

    The solubility of aluminum in NaF-AlF3-CaF2-KF-A12O3 electrolyte system at 1253 K (980 °C) has been measured by the analysis of quenched samples saturated with aluminum. The content of the dissolved metal in the quenched melt was determined by collecting the volume of hydrogen gas when a finely crushed sample is treated with HCl. Addition of 0 to 5 pct KF has no obvious effect on the solubility of aluminum in cryolite-based melts with molar ratio of NaF/AlF3 (cryolite ratio) ranging from 2.2 to 3.0. The solubility of aluminum increases from 0.015 to 0.026 wt pct with cryolite ratio increases from 2.2 to 4.0 in the NaF-AlF3-5 wt pct CaF2-3 wt pct A12O3 electrolyte at 1253 K (980 °C). Aluminum solubility was affected by both chemical replacement reaction of Al + 3NaF = AlF3 + 3Na and physical dissolution.

  5. Gas release during salt-well pumping: Model predictions and laboratory validation studies for soluble and insoluble gases

    International Nuclear Information System (INIS)

    Peurrung, L.M.; Caley, S.M.; Gauglitz, P.A.

    1997-08-01

    The Hanford Site has 149 single-shell tanks (SSTs) containing radioactive wastes that are complex mixes of radioactive and chemical products. Of these, 67 are known or suspected to have leaked liquid from the tanks into the surrounding soil. Salt-well pumping, or interim stabilization, is a well-established operation for removing drainable interstitial liquid from SSTs. The overall objective of this ongoing study is to develop a quantitative understanding of the release rates and cumulative releases of flammable gases from SSTs as a result of salt-well pumping. The current study is an extension of the previous work reported by Peurrung et al. (1996). The first objective of this current study was to conduct laboratory experiments to quantify the release of soluble and insoluble gases. The second was to determine experimentally the role of characteristic waste heterogeneities on the gas release rates. The third objective was to evaluate and validate the computer model STOMP (Subsurface Transport over Multiple Phases) used by Peurrung et al. (1996) to predict the release of both soluble (typically ammonia) and insoluble gases (typically hydrogen) during and after salt-well pumping. The fourth and final objective of the current study was to predict the gas release behavior for a range of typical tank conditions and actual tank geometry. In these models, the authors seek to include all the pertinent salt-well pumping operational parameters and a realistic range of physical properties of the SST wastes. For predicting actual tank behavior, two-dimensional (2-D) simulations were performed with a representative 2-D tank geometry

  6. Design of Chitosan and Its Water Soluble Derivatives-Based Drug Carriers with Polyelectrolyte Complexes

    Directory of Open Access Journals (Sweden)

    Qing-Xi Wu

    2014-12-01

    Full Text Available Chitosan, the cationic polysaccharide derived from the natural polysaccharide chitin, has been studied as a biomaterial for more than two decades. As a polycationic polymer with favorable properties, it has been widely used to form polyelectrolyte complexes with polyanions for various applications in drug delivery fields. In recent years, a growing number of studies have been focused on the preparation of polyelectrolyte complexes based on chitosan and its water soluble derivatives. They have been considered well-suited as biomaterials for a number of vital drug carriers with targeted/controlled release profiles, e.g., films, capsules, microcapsules. In this work, an overview highlights not only the favorable properties of chitosan and its water soluble derivatives but also the good performance of the polyelectrolyte complexes produced based on chitosan. Their various types of applications as drug carriers are reviewed in detail.

  7. Design of chitosan and its water soluble derivatives-based drug carriers with polyelectrolyte complexes.

    Science.gov (United States)

    Wu, Qing-Xi; Lin, Dong-Qiang; Yao, Shan-Jing

    2014-12-19

    Chitosan, the cationic polysaccharide derived from the natural polysaccharide chitin, has been studied as a biomaterial for more than two decades. As a polycationic polymer with favorable properties, it has been widely used to form polyelectrolyte complexes with polyanions for various applications in drug delivery fields. In recent years, a growing number of studies have been focused on the preparation of polyelectrolyte complexes based on chitosan and its water soluble derivatives. They have been considered well-suited as biomaterials for a number of vital drug carriers with targeted/controlled release profiles, e.g., films, capsules, microcapsules. In this work, an overview highlights not only the favorable properties of chitosan and its water soluble derivatives but also the good performance of the polyelectrolyte complexes produced based on chitosan. Their various types of applications as drug carriers are reviewed in detail.

  8. Design of Chitosan and Its Water Soluble Derivatives-Based Drug Carriers with Polyelectrolyte Complexes

    Science.gov (United States)

    Wu, Qing-Xi; Lin, Dong-Qiang; Yao, Shan-Jing

    2014-01-01

    Chitosan, the cationic polysaccharide derived from the natural polysaccharide chitin, has been studied as a biomaterial for more than two decades. As a polycationic polymer with favorable properties, it has been widely used to form polyelectrolyte complexes with polyanions for various applications in drug delivery fields. In recent years, a growing number of studies have been focused on the preparation of polyelectrolyte complexes based on chitosan and its water soluble derivatives. They have been considered well-suited as biomaterials for a number of vital drug carriers with targeted/controlled release profiles, e.g., films, capsules, microcapsules. In this work, an overview highlights not only the favorable properties of chitosan and its water soluble derivatives but also the good performance of the polyelectrolyte complexes produced based on chitosan. Their various types of applications as drug carriers are reviewed in detail. PMID:25532565

  9. Design of Chitosan and Its Water Soluble Derivatives-Based Drug Carriers with Polyelectrolyte Complexes

    OpenAIRE

    Wu, Qing-Xi; Lin, Dong-Qiang; Yao, Shan-Jing

    2014-01-01

    Chitosan, the cationic polysaccharide derived from the natural polysaccharide chitin, has been studied as a biomaterial for more than two decades. As a polycationic polymer with favorable properties, it has been widely used to form polyelectrolyte complexes with polyanions for various applications in drug delivery fields. In recent years, a growing number of studies have been focused on the preparation of polyelectrolyte complexes based on chitosan and its water soluble derivatives. They have...

  10. Ferricyanide-based analysis of aqueous lignin suspension revealed sequestration of water-soluble lignin moieties

    OpenAIRE

    Joshua, CJ; Simmons, BA; Singer, SW

    2016-01-01

    © 2016 The Royal Society of Chemistry. This study describes the application of a ferricyanide-based assay as a simple and inexpensive assay for rapid analysis of aqueous lignin samples. The assay measures the formation of Prussian blue from the redox reaction between a mixture of potassium ferricyanide and ferric chloride, and phenolic hydroxyl groups of lignin or lignin-derived phenolic moieties. This study revealed that soluble lignin moieties exhibited stronger ferricyanide reactivity than...

  11. Soluble CD163 predicts incident chronic lung, kidney and liver disease in HIV infection

    DEFF Research Database (Denmark)

    Kirkegaard-Klitbo, Ditte M; Mejer, Niels; Knudsen, Troels B

    2017-01-01

    OBJECTIVE: To examine if monocyte and macrophage activity may be on the mechanistic pathway to non-AIDS comorbidity by investigating the associations between plasma-soluble CD163 (sCD163) and incident non-AIDS comorbidities in well treated HIV-infected individuals. DESIGN: Prospective single...... was examined using multivariable Cox proportional hazards models adjusted for pertinent covariates. RESULTS: In HIV-1-infected individuals (n = 799), the highest quartile of plasma sCD163 was associated with incident chronic lung disease [adjusted hazard ratio (aHR), 3.2; 95% confidence interval (CI): 1.34; 7.......46] and incident chronic kidney disease (aHR, 10.94; 95% CI: 2.32; 51.35), when compared with lowest quartiles. Further, (every 1 mg) increase in plasma sCD163 was positively correlated with incident liver disease (aHR, 1.12; 95% CI: 1.05; 1.19). The sCD163 level was not associated with incident cancer...

  12. Elevated soluble urokinase plasminogen activator receptor (suPAR) predicts mortality in Staphylococcus aureus bacteremia

    DEFF Research Database (Denmark)

    Mölkänen, T; Ruotsalainen, E; Thorball, C W

    2011-01-01

    The soluble form of urokinase-type plasminogen activator receptor (suPAR) is a new inflammatory marker. High suPAR levels have been shown to associate with mortality in cancer and in chronic infections like HIV and tuberculosis, but reports on the role of suPAR in acute bacteremic infections...... are scarce. To elucidate the role of suPAR in a common bacteremic infection, the serum suPAR levels in 59 patients with Staphylococcus aureus bacteremia (SAB) were measured using the suPARnostic ELISA assay and associations to 1-month mortality and with deep infection focus were analyzed. On day three, after...... the first positive blood culture for S. aureus, suPAR levels were higher in 19 fatalities (median 12.3; range 5.7-64.6 ng/mL) than in 40 survivors (median 8.4; range 3.7-17.6 ng/mL, p = 0.002). This difference persisted for 10 days. The presence of deep infection focus was not associated with elevated su...

  13. Increased serum concentrations of soluble ST2 predict mortality after burn injury.

    Science.gov (United States)

    Hacker, Stefan; Dieplinger, Benjamin; Werba, Gregor; Nickl, Stefanie; Roth, Georg A; Krenn, Claus G; Mueller, Thomas; Ankersmit, Hendrik J; Haider, Thomas

    2018-06-27

    Large burn injuries induce a systemic response in affected patients. Soluble ST2 (sST2) acts as a decoy receptor for interleukin-33 (IL-33) and has immunosuppressive effects. sST2 has been described previously as a prognostic serum marker. Our aim was to evaluate serum concentrations of sST2 and IL-33 after thermal injury and elucidate whether sST2 is associated with mortality in these patients. We included 32 burn patients (total body surface area [TBSA] >10%) admitted to our burn intensive care unit and compared them to eight healthy probands. Serum concentrations of sST2 and IL-33 were measured serially using an enzyme-linked immunosorbent assay (ELISA) technique. The mean TBSA was 32.5%±19.6%. Six patients (18.8%) died during the hospital stay. Serum analyses showed significantly increased concentrations of sST2 and reduced concentrations of IL-33 in burn patients compared to healthy controls. In our study cohort, higher serum concentrations of sST2 were a strong independent predictor of mortality. Burn injuries cause an increment of sST2 serum concentrations with a concomitant reduction of IL-33. Higher concentrations of sST2 are associated with increased in-hospital mortality in burn patients.

  14. Preterm delivery predicted by soluble CD163 and CRP in women with symptoms of preterm delivery

    DEFF Research Database (Denmark)

    Vogel, Ida; Grove, Jakob; Thorsen, Poul

    2005-01-01

    : High levels of sCD163 or CRP are associated with an increased risk of preterm delivery in women with symptoms of delivery. Good prediction of preterm delivery before 34 weeks of gestation was obtained by a combination of preterm prelabour rupture of membranes (PPROM), overweight, relaxin, CRP and s...

  15. Nanotechnology Based Approaches for Enhancing Oral Bioavailability of Poorly Water Soluble Antihypertensive Drugs

    Directory of Open Access Journals (Sweden)

    Mayank Sharma

    2016-01-01

    Full Text Available Oral administration is the most convenient route among various routes of drug delivery as it offers high patient compliance. However, the poor aqueous solubility and poor enzymatic/metabolic stability of drugs are major limitations in successful oral drug delivery. There are several approaches to improve problems related to hydrophobic drugs. Among various approaches, nanotechnology based drug delivery system has potential to overcome the challenges associated with the oral route of administration. Novel drug delivery systems are available in many areas of medicine. The application of these systems in the treatment of hypertension continues to broaden. The present review focuses on various nanocarriers available in oral drug administration for improving solubility profile, dissolution, and consequently bioavailability of hydrophobic antihypertensive drugs.

  16. Soluble CD30 and Hepatocyte growth factor as predictive markers of antibody-mediated rejection of the kidney allograft.

    Science.gov (United States)

    Pavlova, Yelena; Viklicky, Ondrej; Slatinska, Janka; Bürgelova, Marcela; Süsal, Caner; Skibova, Jelena; Honsová, Eva; Striz, Ilja; Kolesar, Libor; Slavcev, Antonij

    2011-07-01

    Our retrospective study was aimed to assess the relevance of pre- and post-transplant measurements of serum concentrations of the soluble CD30 molecule (soluble CD30, sCD30) and the cytokine Hepatocyte growth factor (HGF) for prediction of the risk for development of antibody-mediated rejection (AMR) in kidney transplant patients. Evaluation of sCD30, HGF levels and the presence of HLA-specific antibodies in a cohort of 205 patients was performed before, 2weeks and 6months after transplantation. Patients were followed up for kidney graft function and survival for two years. We found a tendency of higher incidence of AMR in retransplanted patients with elevated pre-transplant sCD30 (≥100U/ml) (p=0.051), however no such correlation was observed in first-transplant patients. Kidney recipients with simultaneously high sCD30 and HLA-specific antibodies (sCD30+/Ab+) before transplantation had significantly lower AMR-free survival compared to the other patient groups (psCD30 showed increased incidence of AMR in recipients with elevated pretransplant sCD30 and low HGF levels. the predictive value of pretransplant sCD30 for the development of antibody-mediated rejection after transplantation is significantly potentiated by the co-presence of HLA specific antibodies. The role of HGF as a rejection-protective factor in patients with high pretransplant HGF levels would need further investigation. Copyright © 2011 Elsevier B.V. All rights reserved.

  17. Serum Soluble Fms-Like Tyrosine Kinase 1 (sFlt-1 Predicts the Severity of Acute Pancreatitis

    Directory of Open Access Journals (Sweden)

    Paulina Dumnicka

    2016-12-01

    Full Text Available Organ failure is the most important determinant of the severity of acute pancreatitis (AP. Soluble fms-like tyrosine kinase 1 (sFlt-1 is positively associated with organ failure in sepsis. Our aim was to evaluate the diagnostic utility of automated sFlt-1 measurements for early prediction of AP severity. Adult patients (66 with AP were recruited, including 46 with mild (MAP, 15 with moderately-severe (MSAP and 5 with severe AP (SAP. Serum and urine samples were collected twice. Serum sFlt-1 was measured with automated electrochemiluminescence immunoassay. Serum concentrations of sFlt-1 were significantly higher in patients with MSAP and SAP as compared to MAP. SAP patients had the highest concentrations. At 24 and 48 h, sFlt-1 positively correlated with inflammatory markers (leukocyte count, C-reactive protein, kidney function (creatinine, urea, cystatin C, serum and urine neutrophil gelatinase-associated lipocalin, urine albumin/creatinine ratio, D-dimer and angiopoietin-2. sFlt-1 positively correlated with the bedside index of severity in AP (BISAP score and the duration of hospital stay. Serum sFlt-1 above 139 pg/mL predicted more severe AP (MSAP + SAP. In the early phase of AP, sFlt-1 is positively associated with the severity of AP and predicts organ failure, in particular kidney failure. Serum sFlt-1 may be a practical way to improve early assessment of AP severity.

  18. The solvation radius of silicate melts based on the solubility of noble gases and scaled particle theory

    International Nuclear Information System (INIS)

    Ottonello, Giulio; Richet, Pascal

    2014-01-01

    The existing solubility data on noble gases in high-temperature silicate melts have been analyzed in terms of Scaling Particle Theory coupled with an ab initio assessment of the electronic, dispersive, and repulsive energy terms based on the Polarized Continuum Model (PCM). After a preliminary analysis of the role of the contracted Gaussian basis sets and theory level in reproducing appropriate static dipole polarizabilities in a vacuum, we have shown that the procedure returns Henry's law constants consistent with the values experimentally observed in water and benzene at T = 25 °C and P = 1 bar for the first four elements of the series. The static dielectric constant (ε) of the investigated silicate melts and its optical counterpart (ε ∞ ) were then resolved through the application of a modified form of the Clausius-Mossotti relation. Argon has been adopted as a probe to depict its high-T solubility in melts through an appropriate choice of the solvent diameter σ s , along the guidelines already used in the past for simple media such as water or benzene. The σ s obtained was consistent with a simple functional form based on the molecular volume of the solvent. The solubility calculations were then extended to He, Ne, and Kr, whose dispersive and repulsive coefficients are available from theory and we have shown that their ab initio Henry's constants at high T reproduce the observed increase with the static polarizability of the series element with reasonable accuracy. At room temperature (T = 25 °C) the calculated Henry's constants of He, Ne, Ar, and Kr in the various silicate media predict higher solubilities than simple extrapolations (i.e., Arrhenius plots) based on high-T experiments and give rise to smooth trends not appreciably affected by the static polarizabilities of the solutes. The present investigation opens new perspectives on a wider application of PCM theory which can be extended to materials of great industrial interest at the core of

  19. The solvation radius of silicate melts based on the solubility of noble gases and scaled particle theory

    Energy Technology Data Exchange (ETDEWEB)

    Ottonello, Giulio, E-mail: giotto@dipteris.unige.it [DISTAV, Università di Genova, Corso Europa 26, 16132 Genova (Italy); Richet, Pascal [Institut de Physique du Globe, Rue Jussieu 2, 75005 Paris (France)

    2014-01-28

    The existing solubility data on noble gases in high-temperature silicate melts have been analyzed in terms of Scaling Particle Theory coupled with an ab initio assessment of the electronic, dispersive, and repulsive energy terms based on the Polarized Continuum Model (PCM). After a preliminary analysis of the role of the contracted Gaussian basis sets and theory level in reproducing appropriate static dipole polarizabilities in a vacuum, we have shown that the procedure returns Henry's law constants consistent with the values experimentally observed in water and benzene at T = 25 °C and P = 1 bar for the first four elements of the series. The static dielectric constant (ε) of the investigated silicate melts and its optical counterpart (ε{sup ∞}) were then resolved through the application of a modified form of the Clausius-Mossotti relation. Argon has been adopted as a probe to depict its high-T solubility in melts through an appropriate choice of the solvent diameter σ{sub s}, along the guidelines already used in the past for simple media such as water or benzene. The σ{sub s} obtained was consistent with a simple functional form based on the molecular volume of the solvent. The solubility calculations were then extended to He, Ne, and Kr, whose dispersive and repulsive coefficients are available from theory and we have shown that their ab initio Henry's constants at high T reproduce the observed increase with the static polarizability of the series element with reasonable accuracy. At room temperature (T = 25 °C) the calculated Henry's constants of He, Ne, Ar, and Kr in the various silicate media predict higher solubilities than simple extrapolations (i.e., Arrhenius plots) based on high-T experiments and give rise to smooth trends not appreciably affected by the static polarizabilities of the solutes. The present investigation opens new perspectives on a wider application of PCM theory which can be extended to materials of great

  20. The solvation radius of silicate melts based on the solubility of noble gases and scaled particle theory.

    Science.gov (United States)

    Ottonello, Giulio; Richet, Pascal

    2014-01-28

    The existing solubility data on noble gases in high-temperature silicate melts have been analyzed in terms of Scaling Particle Theory coupled with an ab initio assessment of the electronic, dispersive, and repulsive energy terms based on the Polarized Continuum Model (PCM). After a preliminary analysis of the role of the contracted Gaussian basis sets and theory level in reproducing appropriate static dipole polarizabilities in a vacuum, we have shown that the procedure returns Henry's law constants consistent with the values experimentally observed in water and benzene at T = 25 °C and P = 1 bar for the first four elements of the series. The static dielectric constant (ɛ) of the investigated silicate melts and its optical counterpart (ɛ(∞)) were then resolved through the application of a modified form of the Clausius-Mossotti relation. Argon has been adopted as a probe to depict its high-T solubility in melts through an appropriate choice of the solvent diameter σs, along the guidelines already used in the past for simple media such as water or benzene. The σs obtained was consistent with a simple functional form based on the molecular volume of the solvent. The solubility calculations were then extended to He, Ne, and Kr, whose dispersive and repulsive coefficients are available from theory and we have shown that their ab initio Henry's constants at high T reproduce the observed increase with the static polarizability of the series element with reasonable accuracy. At room temperature (T = 25 °C) the calculated Henry's constants of He, Ne, Ar, and Kr in the various silicate media predict higher solubilities than simple extrapolations (i.e., Arrhenius plots) based on high-T experiments and give rise to smooth trends not appreciably affected by the static polarizabilities of the solutes. The present investigation opens new perspectives on a wider application of PCM theory which can be extended to materials of great industrial interest at the core of

  1. Clinical studies with oral lipid based formulations of poorly soluble compounds

    DEFF Research Database (Denmark)

    Fatouros, Dimitrios; Karpf, Ditte M; Nielsen, Flemming S

    2007-01-01

    . Several drug products intended for oral administration have been marketed utilizing lipid and surfactant based formulations. Sandimmune((R)) and Sandimmune Neoral((R)) (cyclosporin A, Novartis), Norvir((R)) (ritonavir), and Fortovase((R)) (saquinavir) have been formulated in self-emulsifying drug delivery...... systems (SEDDS). This review summarizes published pharmacokinetic studies of orally administered lipid based formulations of poorly aqueous soluble drugs in human subjects. Special attention has been paid to the physicochemical characteristics of the formulations, when available and the impact...

  2. A Novel Solubility-Enhanced Rubusoside-Based Micelles for Increased Cancer Therapy

    Science.gov (United States)

    Zhang, Meiying; Dai, Tongcheng; Feng, Nianping

    2017-04-01

    Many anti-cancer drugs have a common problem of poor solubility. Increasing the solubility of the drugs is very important for its clinical applications. In the present study, we revealed that the solubility of insoluble drugs was significantly enhanced by adding rubusoside (RUB). Further, it was demonstrated that RUB could form micelles, which was well characterized by Langmuir monolayer investigation, transmission electron microscopy, atomic-force microscopy, and cryogenic transmission electron microscopy. The RUB micelles were ellipsoid with the horizontal distance of 25 nm and vertical distance of 1.2 nm. Insoluble synergistic anti-cancer drugs including curcumin and resveratrol were loaded in RUB to form anti-cancer micelles RUB/CUR + RES. MTT assay showed that RUB/CUR + RES micelles had more significant toxicity on MCF-7 cells compared to RUB/CUR micelles + RUB/RES micelles. More importantly, it was confirmed that RUB could load other two insoluble drugs together for remarkably enhanced anti-cancer effect compared to that of RUB/one drug + RUB/another drug. Overall, we concluded that RUB-based micelles could efficiently load insoluble drugs for enhanced anti-cancer effect.

  3. Data-Based Predictive Control with Multirate Prediction Step

    Science.gov (United States)

    Barlow, Jonathan S.

    2010-01-01

    Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

  4. Plasma Levels of Soluble HLA-E and HLA-F at Diagnosis May Predict Overall Survival of Neuroblastoma Patients

    Directory of Open Access Journals (Sweden)

    Fabio Morandi

    2013-01-01

    Full Text Available The purpose of this study was to identify the plasma/serum biomarkers that are able to predict overall survival (OS of neuroblastoma (NB patients. Concentration of soluble (s biomarkers was evaluated in plasma (sHLA-E, sHLA-F, chromogranin, and B7H3 or serum (calprotectin samples from NB patients or healthy children. The levels of biomarkers that were significantly higher in NB patients were then analyzed considering localized or metastatic subsets. Finally, biomarkers that were significantly different in these two subsets were correlated with patient’s outcome. With the exception of B7H3, levels of all molecules were significantly higher in NB patients than those in controls. However, only chromogranin, sHLA-E, and sHLA-F levels were different between patients with metastatic and localized tumors. sHLA-E and -F levels correlated with each other but not chromogranin. Chromogranin levels correlated with different event-free survival (EFS, whereas sHLA-E and -F levels also correlated with different OS. Association with OS was also detected considering only patients with metastatic disease. In conclusion, low levels of sHLA-E and -F significantly associated with worse EFS/OS in the whole cohort of NB patients and in patients with metastatic NB. Thus, these molecules deserve to be tested in prospective studies to evaluate their predictive power for high-risk NB patients.

  5. Evaluation of pre- and posttransplantation serum interferon-gamma and soluble CD30 for predicting liver allograft rejection.

    Science.gov (United States)

    Kim, K H; Oh, E-J; Jung, E-S; Park, Y-J; Choi, J Y; Kim, D-G; Lee, K Y; Kang, C S

    2006-06-01

    The aim of the present study was to identify whether the serum interferon-gamma (IFNgamma), a Th1 cytokine, or soluble CD30 (sCD30), a marker for activation of Th2 cytokine-producing T cells, predict acute cellular rejection episodes among liver graft patients. Pretransplant and posttransplant sera from 32 living donor liver transplant recipients obtained on days 1, 3, and 7 after surgery were tested for serum IFNgamma and sCD30 concentrations using commercial enzyme-linked immunosorbent assay kits. Recipients with an acute rejection episode (ARE) (n=14) displayed significantly higher IFNgamma concentrations pretransplant than did the patients with no ARE (n=18) (PsCD30 were not different between the non-ARE and ARE groups. However, in comparison with the non-ARE group, who showed steadily decreasing serum sCD30 levels after transplantation, 12 among the 14 patients in the ARE group showed increasing sCD30 levels from day 1 to day 3 after transplantation (PsCD30 increment during the early period after liver transplantation affects the immune response of rejection. This observation emphasizes the clinical relevance of serum sCD30, in addition to serum IFNgamma, as predictive markers for acute liver graft rejection.

  6. A solar rechargeable flow battery based on photoregeneration of two soluble redox couples.

    Science.gov (United States)

    Liu, Ping; Cao, Yu-liang; Li, Guo-Ran; Gao, Xue-Ping; Ai, Xin-Ping; Yang, Han-Xi

    2013-05-01

    Storable sunshine, reusable rays: A solar rechargeable redox flow battery is proposed based on the photoregeneration of I(3)(-)/I(-) and [Fe(C(10)H(15))(2)](+)/Fe(C(10)H(15))(2) soluble redox couples, which can be regenerated by flowing from a discharged redox flow battery (RFB) into a dye-sensitized solar cell (DSSC) and then stored in tanks for subsequent RFB applications This technology enables effective solar-to-chemical energy conversion. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. A sorption model for alkalis in cement-based materials - Correlations with solubility and electrokinetic properties

    Science.gov (United States)

    Henocq, Pierre

    2017-06-01

    In cement-based materials, radionuclide uptake is mainly controlled by calcium silicate hydrates (C-S-H). This work presents an approach for defining a unique set of parameters of a surface complexation model describing the sorption behavior of alkali ions on the C-S-H surface. Alkali sorption processes are modeled using the CD-MUSIC function integrated in the Phreeqc V.3.0.6 geochemical code. Parameterization of the model was performed based on (1) retention, (2) zeta potential, and (3) solubility experimental data from the literature. This paper shows an application of this model to sodium ions. It was shown that retention, i.e. surface interactions, and solubility are closely related, and a consistent sorption model for radionuclides in cement-based materials requires a coupled surface interaction/chemical equilibrium model. In case of C-S-H with low calcium-to-silicon ratios, sorption of sodium ions on the C-S-H surface strongly influences the chemical equilibrium of the C-S-H + NaCl system by significantly increasing the aqueous calcium concentration. The close relationship between sorption and chemical equilibrium was successfully illustrated by modeling the effect of the solid-to-liquid ratio on the calcium content in solution in the case of C-S-H + NaCl systems.

  8. Soluble Suppression of Tumorigenicity-2 Predicts Hospital Mortality in Burn Patients: An Observational Prospective Cohort Pilot Study.

    Science.gov (United States)

    Ruiz-Castilla, Mireia; Bosacoma, Pau; Dos Santos, Bruce; Baena, Jacinto; Guilabert, Patricia; Marin-Corral, Judith; Masclans, Joan R; Roca, Oriol; Barret, Juan P

    2018-04-10

    The IL33/ST2 pathway has been implicated in the pathogenesis of different inflammatory diseases. Our aim was to analyze whether plasma levels of biomarkers involved in the IL33/ST2 axis might help to predict mortality in burn patients. Single-center prospective observational cohort pilot study performed at the Burns Unit of the Plastic and Reconstructive Surgery Department of the Vall d'Hebron University Hospital (Barcelona). All patients aged ≥18 years old with second or third-degree burns requiring admission to the Burns Unit were considered for inclusion. Blood samples were taken to measure levels of interleukins (IL)6, IL8, IL33, and soluble suppression of tumorigenicity-2 (sST2) within 24 h of admission to the Burns Unit and at day 3. Results are expressed as medians and interquartile ranges or as frequencies and percentages. Sixty-nine patients (58 [84.1%] male, mean age 52 [35-63] years, total body surface area burned 21% [13%-30%], Abbreviated Burn Severity Index 6 [4-8]) were included. Thirteen (18.8%) finally died in the Burns Unit. Plasma levels of sST2 measured at day 3 after admission demonstrated the best prediction accuracy for survival (area under the ROC curve 0.85 [0.71-0.99]; P < 0.001). The best cutoff point for the AUROC index was estimated to be 2,561. In the Cox proportional hazards model, after adjusting for potential confounding, a plasma sST2 level ≥2,561 measured at day 3 was significantly associated with mortality (HR 6.94 [1.73-27.74]; P = 0.006). Plasma sST2 at day 3 predicts hospital mortality in burn patients.

  9. Enhancing production and cytotoxic activity of polymeric soluble FasL-based chimeric proteins by concomitant expression of soluble FasL.

    Directory of Open Access Journals (Sweden)

    Aurore Morello

    Full Text Available Membrane FasL is the natural trigger of Fas-mediated apoptosis. A soluble homotrimeric counterpart (sFasL also exists which is very weakly active, and needs oligomerization beyond its trimeric state to induce apoptosis. We recently generated a soluble FasL chimera by fusing the immunoglobulin-like domain of the leukemia inhibitory factor receptor gp190 to the extracellular region of human FasL, which enabled spontaneous dodecameric homotypic polymerization of FasL. This polymeric soluble human FasL (pFasL displayed anti-tumoral activity in vitro and in vivo without systemic cytotoxicity in mouse. In the present work, we focused on the improvement of pFasL, with two complementary objectives. First, we developed more complex pFasL-based chimeras that contained a cell-targeting module. Secondly, we attempted to improve the production and/or the specific activity of pFasL and of the cell-targeting chimeras. We designed two chimeras by fusing to pFasL the extracellular portions of the HLA-A2 molecule or of a human gamma-delta TCR, and analyzed the consequences of co-expressing these molecules or pFasL together with sFasL on their heterotopic cell production. This strategy significantly enhanced the production of pFasL and of the two chimeras, as well as the cytotoxic activity of the two chimeras but not of pFasL. These results provide the proof of concept for an optimization of FasL-based chimeric proteins for a therapeutic use.

  10. Application of mixture experimental design to simvastatin apparent solubility predictions in the microemulsifion formed by self-microemulsifying.

    Science.gov (United States)

    Meng, Jian; Zheng, Liangyuan

    2007-09-01

    Self-microemulsifying drug delivery systems (SMEDDS) are useful to improve the bioavailability of poorly water-soluble drugs by increasing their apparent solubility through solubilization. However, very few studies, to date, have systematically examined the level of drug apparent solubility in o/w microemulsion formed by self-microemulsifying. In this study, a mixture experimental design was used to simulate the influence of the compositions on simvastatin apparent solubility quantitatively through an empirical model. The reduced cubic polynomial equation successfully modeled the evolution of simvastatin apparent solubility. The results were presented using an analysis of response surface showing a scale of possible simvastatin apparent solubility between 0.0024 ~ 29.0 mg/mL. Moreover, this technique showed that simvastatin apparent solubility was mainly influenced by microemulsion concentration and, suggested that the drug would precipitate in the gastrointestinal tract due to dilution by gastrointestinal fluids. Furthermore, the model would help us design the formulation to maximize the drug apparent solubility and avoid precipitation of the drug.

  11. Soluble CD30 does not predict late acute rejection or safe tapering of immunosuppression in renal transplantation.

    Science.gov (United States)

    Valke, Lars L F G; van Cranenbroek, Bram; Hilbrands, Luuk B; Joosten, Irma

    2015-01-01

    Previous reports revealed the potential value of the soluble CD30 level (sCD30) as biomarker for the risk of acute rejection and graft failure after renal transplantation, here we examined its use for the prediction of safe tapering of calcineurin inhibitors as well as late acute rejection. In a cohort of renal transplant patients receiving triple immunosuppressive therapy we examined whether sCD30 can be used as a marker for safe (rejection-free) discontinuation of tacrolimus at six months after transplantation (TDS cohort: 24 rejectors and 44 non-rejecting controls). Also, in a second cohort of patients (n=22, rejectors n=11 and non-rejectors n=11), participating in a clinical trial of rituximab as induction therapy after renal transplantation (RITS cohort), we examined whether sCD30 could predict the occurrence of late (>3months post-transplant) acute rejection episodes. sCD30 was measured by ELISA in serum taken before and at several time points after transplantation. Overall, in the TDS cohort sCD30 decreased after transplantation. No difference in sCD30 was observed between rejectors and non-rejecting controls at any of the time points measured. In addition, in the RITS cohort, sCD30 measured at three months after transplantation were not indicative for the occurrence of late acute rejection. In two prospectively followed cohorts of renal transplant patients we found no association between sCD30 and the occurrence of either late acute rejection or acute rejection after reduction of immunosuppression. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. Predicting the solubility and lability of Zn, Cd, and Pb in soils from a minespoil-contaminated catchment by stable isotopic exchange

    Science.gov (United States)

    Marzouk, E. R.; Chenery, S. R.; Young, S. D.

    2013-12-01

    The Rookhope catchment of Weardale, England, has a diverse legacy of contaminated soils due to extensive lead mining activity over four centuries. We measured the isotopically exchangeable content of Pb, Cd and Zn (E-values) in a large representative subset of the catchment soils (n = 246) using stable isotope dilution. All three metals displayed a wide range of %E-values (c. 1-100%) but relative lability followed the sequence Cd > Pb > Zn. A refinement of the stable isotope dilution approach also enabled detection of non-reactive metal contained within suspended sub-micron (dilution, in a diverse range of soil ecosystems within the catchment of an old Pb/Zn mining area. Assess the controlling influences of soil properties on metal lability and develop predictive algorithms for metal lability in the contaminated catchment based on simple soil properties (such as pH, organic matter (LOI), and total metal content). Examine the incidence of non-isotopically-exchangeable metal held within suspended colloidal particles (SCP-metal) in filtered soil solutions (<0.22 μm) by comparing E-values from isotopic abundance in solutions equilibrated with soil and in a resin phase equilibrated with the separated solution. Assess the ability of a geochemical speciation model, WHAM(VII), to predict metal solubility using isotopically exchangeable metal as an input variable.

  13. Predicting Liaison: an Example-Based Approach

    NARCIS (Netherlands)

    Greefhorst, A.P.M.; Bosch, A.P.J. van den

    2016-01-01

    Predicting liaison in French is a non-trivial problem to model. We compare a memory-based machine-learning algorithm with a rule-based baseline. The memory-based learner is trained to predict whether liaison occurs between two words on the basis of lexical, orthographic, morphosyntactic, and

  14. Thorium oxalate solubility and morphology

    International Nuclear Information System (INIS)

    Monson, P.R. Jr.; Hall, R.

    1981-10-01

    Thorium was used as a stand-in for studying the solubility and precipitation of neptunium and plutonium oxalates. Thorium oxalate solubility was determined over a range of 0.001 to 10.0 in the concentration parameter [H 2 C 2 O 4 ]/[HNO 3 ] 2 . Morphology of thorium oxide made from the oxalate precipitates was characterized by scanning electron microscopy. The different morphologies found for oxalate-lean and oxalate-rich precipitations were in agreement with predictions based on precipitation theory

  15. Automatic Carbon Dioxide-Methane Gas Sensor Based on the Solubility of Gases in Water

    Directory of Open Access Journals (Sweden)

    Raúl O. Cadena-Pereda

    2012-08-01

    Full Text Available Biogas methane content is a relevant variable in anaerobic digestion processing where knowledge of process kinetics or an early indicator of digester failure is needed. The contribution of this work is the development of a novel, simple and low cost automatic carbon dioxide-methane gas sensor based on the solubility of gases in water as the precursor of a sensor for biogas quality monitoring. The device described in this work was used for determining the composition of binary mixtures, such as carbon dioxide-methane, in the range of 0–100%. The design and implementation of a digital signal processor and control system into a low-cost Field Programmable Gate Array (FPGA platform has permitted the successful application of data acquisition, data distribution and digital data processing, making the construction of a standalone carbon dioxide-methane gas sensor possible.

  16. Automatic carbon dioxide-methane gas sensor based on the solubility of gases in water.

    Science.gov (United States)

    Cadena-Pereda, Raúl O; Rivera-Muñoz, Eric M; Herrera-Ruiz, Gilberto; Gomez-Melendez, Domingo J; Anaya-Rivera, Ely K

    2012-01-01

    Biogas methane content is a relevant variable in anaerobic digestion processing where knowledge of process kinetics or an early indicator of digester failure is needed. The contribution of this work is the development of a novel, simple and low cost automatic carbon dioxide-methane gas sensor based on the solubility of gases in water as the precursor of a sensor for biogas quality monitoring. The device described in this work was used for determining the composition of binary mixtures, such as carbon dioxide-methane, in the range of 0-100%. The design and implementation of a digital signal processor and control system into a low-cost Field Programmable Gate Array (FPGA) platform has permitted the successful application of data acquisition, data distribution and digital data processing, making the construction of a standalone carbon dioxide-methane gas sensor possible.

  17. Soluble Forms of Intercellular and Vascular Cell Adhesion Molecules Independently Predict Progression to Type 2 Diabetes in Mexican American Families.

    Directory of Open Access Journals (Sweden)

    Hemant Kulkarni

    Full Text Available While the role of type 2 diabetes (T2D in inducing endothelial dysfunction is fairly well-established the etiological role of endothelial dysfunction in the onset of T2D is still a matter of debate. In the light of conflicting evidence in this regard, we conducted a prospective study to determine the association of circulating levels of soluble intercellular adhesion molecule 1 (sICAM-1 and soluble vessel cell adhesion molecule 1 (sVCAM-1 with incident T2D.Data from this study came from 1,269 Mexican Americans of whom 821 initially T2D-free individuals were longitudinally followed up in the San Antonio Family Heart Study. These individuals were followed for 9752.95 person-years for development of T2D. Prospective association of sICAM-1 and sVCAM-1 with incident T2D was studied using Kaplan-Meier survival plots and mixed effects Cox proportional hazards modeling to account for relatedness among study participants. Incremental value of adhesion molecule biomarkers was studied using integrated discrimination improvement (IDI and net reclassification improvement (NRI indexes.Decreasing median values for serum concentrations of sICAM-1 and sVCAM-1 were observed in the following groups in this order: individuals with T2D at baseline, individuals who developed T2D during follow-up, individuals with prediabetes at baseline and normal glucose tolerant (NGT individuals who remained T2D-free during follow-up. Top quartiles for sICAM-1 and sVCAM-1 were strongly and significantly associated with homeostatic model of assessment--insulin resistance (HOMA-IR. Mixed effects Cox proportional hazards modeling revealed that after correcting for important clinical confounders, high sICAM-1 and sVCAM-1 concentrations were associated with 2.52 and 1.99 times faster progression to T2D as compared to low concentrations, respectively. Individuals with high concentrations for both sICAM-1 and sVCAM-1 progressed to T2D 3.42 times faster than those with low values for both

  18. Soluble Receptor for Advanced Glycation End-Products Predicts Impaired Alveolar Fluid Clearance in Acute Respiratory Distress Syndrome.

    Science.gov (United States)

    Jabaudon, Matthieu; Blondonnet, Raiko; Roszyk, Laurence; Bouvier, Damien; Audard, Jules; Clairefond, Gael; Fournier, Mathilde; Marceau, Geoffroy; Déchelotte, Pierre; Pereira, Bruno; Sapin, Vincent; Constantin, Jean-Michel

    2015-07-15

    Levels of the soluble form of the receptor for advanced glycation end-products (sRAGE) are elevated during acute respiratory distress syndrome (ARDS) and correlate with severity and prognosis. Alveolar fluid clearance (AFC) is necessary for the resolution of lung edema but is impaired in most patients with ARDS. No reliable marker of this process has been investigated to date. To verify whether sRAGE could predict AFC during ARDS. Anesthetized CD-1 mice underwent orotracheal instillation of hydrochloric acid. At specified time points, lung injury was assessed by analysis of blood gases, alveolar permeability, lung histology, AFC, and plasma/bronchoalveolar fluid measurements of proinflammatory cytokines and sRAGE. Plasma sRAGE and AFC rates were also prospectively assessed in 30 patients with ARDS. The rate of AFC was inversely correlated with sRAGE levels in the plasma and the bronchoalveolar fluid of acid-injured mice (Spearman's ρ = -0.73 and -0.69, respectively; P < 10(-3)), and plasma sRAGE correlated with AFC in patients with ARDS (Spearman's ρ = -0.59; P < 10(-3)). Similarly, sRAGE levels were significantly associated with lung injury severity, and decreased over time in mice, whereas AFC was restored and lung injury resolved. Our results indicate that sRAGE levels could be a reliable predictor of impaired AFC during ARDS, and should stimulate further studies on the pathophysiologic implications of RAGE axis in the mechanisms leading to edema resolution. Clinical trial registered with www.clinicaltrials.gov (NCT 00811629).

  19. Neptunium (IV) oxalate solubility

    International Nuclear Information System (INIS)

    Luerkens, D.W.

    1983-07-01

    The equilibrium solubility of neptunium (IV) oxalate in nitric/oxalic acid solutions was determined at 22 0 C, 45 0 C, and 60 0 C. The concentrations of nitric/oxalic acid solutions represented a wide range of free oxalate ion concentration. A mathematical solubility model was developed which is based on the formation of the known complexes of neptunium (IV) oxalate. the solubility model uses a simplified concentration parameter which is proportional to the free oxalate ion concentration. The solubility model can be used to estimate the equilibrium solubility of neptunium (IV) oxalate over a wide range of oxalic and nitric acid concentrations at each temperature

  20. Carbohydrate composition, viscosity, solubility, and sensory acceptance of sweetpotato- and maize-based complementary foods

    Science.gov (United States)

    Amagloh, Francis Kweku; Mutukumira, Anthony N.; Brough, Louise; Weber, Janet L.; Hardacre, Allan; Coad, Jane

    2013-01-01

    Background Cereal-based complementary foods from non-malted ingredients form a relatively high viscous porridge. Therefore, excessive dilution, usually with water, is required to reduce the viscosity to be appropriate for infant feeding. The dilution invariably leads to energy and nutrient thinning, that is, the reduction of energy and nutrient densities. Carbohydrate is the major constituent of food that significantly influences viscosity when heated in water. Objectives To compare the sweetpotato-based complementary foods (extrusion-cooked ComFa, roller-dried ComFa, and oven-toasted ComFa) and enriched Weanimix (maize-based formulation) regarding their 1) carbohydrate composition, 2) viscosity and water solubility index (WSI), and 3) sensory acceptance evaluated by sub-Sahara African women as model caregivers. Methods The level of simple sugars/carbohydrates was analysed by spectrophotometry, total dietary fibre by enzymatic-gravimetric method, and total carbohydrate and starch levels estimated by calculation. A Rapid Visco™ Analyser was used to measure viscosity. WSI was determined gravimetrically. A consumer sensory evaluation was used to evaluate the product acceptance of the roller-dried ComFa, oven-toasted ComFa, and enriched Weanimix. Results The sweetpotato-based complementary foods were, on average, significantly higher in maltose, sucrose, free glucose and fructose, and total dietary fibre, but they were markedly lower in starch content compared with the levels in the enriched Weanimix. Consequently, the sweetpotato-based complementary foods had relatively low apparent viscosity, and high WSI, than that of enriched Weanimix. The scores of sensory liking given by the caregivers were highest for the roller-dried ComFa, followed by the oven-toasted ComFa, and, finally, the enriched Weanimix. Conclusion The sweetpotato-based formulations have significant advantages as complementary food due to the high level of endogenous sugars and low starch content that

  1. Carbon dioxide solubilities in decanoic acid-based hydrophobic deep eutectic solvents

    NARCIS (Netherlands)

    Zubeir, Lawien F.; Van Osch, Dannie J.G.P.; Rocha, Marisa A.A.; Banat, Fawzi; Kroon, Maaike C.

    2018-01-01

    The solubility of CO2 in hydrophobic deep eutectic solvents (DESs) has been measured for the first time. Six different hydrophobic DESs are studied in the temperature range from 298 to 323 K and at CO2 pressures up to 2 MPa. The results are evaluated by comparing the solubility data with existing

  2. Study of solubility of akaline earth metals in liquid iron and in alloys on its base

    International Nuclear Information System (INIS)

    Ageev, Yu.A.; Archugov, S.A.

    1985-01-01

    Solubility of magnesium, calcium, strontium and barium in liquid iron and its alloys with aluminium, silicon, nickel, chromium and carbon at 1600 deg C has been measured. Interaction parameters taking account of the effect of added elements on alkaline earth metal solubility in liquid iron have been estimated

  3. Modelling uranium solubilities in aqueous solutions: Validation of a thermodynamic data base for the EQ3/6 geochemical codes

    International Nuclear Information System (INIS)

    Puigdomenech, I.; Bruno, J.

    1988-01-01

    Experimental solubilities of U 4+ and UO 2 2+ that are reported in the literature have been collected. Data on oxides, hydroxides and carbonates have been selected for this work. They include results both at 25 degrees C and at higher temperatures. The literature data have been compared with calculated uranium solubilities obtained with the EQ3/6 geochemical modelling programs and an uranium thermodynamic data base selected for the Swedish nuclear waste management program. This verification/validiation exercise has shown that more experimental data is needed to determine the chemical composition of anionic uranyl hydroxo complexes as well as their equilibrium constants of formation. There is also a need for more solubility data on well characterised alkaline or alkaline-earth uranates. For the uranyl carbonate system, the calculated results agree reasonably well with the experimental literature values, which span over a wide range of pH, (CO 3 2- ) T , CO 2 (g)-pressure, and T. The experimental solubility of UO 2 (s) agrees also well with the EQ3/6 calculations for pH greater than 6. However, in more acidic solutions the experimental solubilities are higher than the calculated values. This is due to the formation of polynuclear hydroxo complexes of uranium, which are not well characterised, and are not included in the thermodynamic data base used in this study. (authors)

  4. Occurrence of urea-based soluble epoxide hydrolase inhibitors from the plants in the order Brassicales.

    Directory of Open Access Journals (Sweden)

    Seiya Kitamura

    Full Text Available Recently, dibenzylurea-based potent soluble epoxide hydrolase (sEH inhibitors were identified in Pentadiplandra brazzeana, a plant in the order Brassicales. In an effort to generalize the concept, we hypothesized that plants that produce benzyl glucosinolates and corresponding isothiocyanates also produce these dibenzylurea derivatives. Our overall aim here was to examine the occurrence of urea derivatives in Brassicales, hoping to find biologically active urea derivatives from plants. First, plants in the order Brassicales were analyzed for the presence of 1, 3-dibenzylurea (compound 1, showing that three additional plants in the order Brassicales produce the urea derivatives. Based on the hypothesis, three dibenzylurea derivatives with sEH inhibitory activity were isolated from maca (Lepidium meyenii roots. Topical application of one of the identified compounds (compound 3, human sEH IC50 = 222 nM effectively reduced pain in rat inflammatory pain model, and this compound was bioavailable after oral administration in mice. The biosynthetic pathway of these urea derivatives was investigated using papaya (Carica papaya seed as a model system. Finally, a small collection of plants from the Brassicales order was grown, collected, extracted and screened for sEH inhibitory activity. Results show that several plants of the Brassicales order could be potential sources of urea-based sEH inhibitors.

  5. Trust-based collective view prediction

    CERN Document Server

    Luo, Tiejian; Xu, Guandong; Zhou, Jia

    2013-01-01

    Collective view prediction is to judge the opinions of an active web user based on unknown elements by referring to the collective mind of the whole community. Content-based recommendation and collaborative filtering are two mainstream collective view prediction techniques. They generate predictions by analyzing the text features of the target object or the similarity of users' past behaviors. Still, these techniques are vulnerable to the artificially-injected noise data, because they are not able to judge the reliability and credibility of the information sources. Trust-based Collective View

  6. Prediction of crude protein digestibility of animal by-product meals for dogs by the protein solubility in pepsin method.

    Science.gov (United States)

    Kawauchi, Iris M; Sakomura, Nilva K; Pontieri, Cristiana F F; Rebelato, Aline; Putarov, Thaila C; Malheiros, Euclides B; Gomes, Márcia de O S; Castrillo, Carlos; Carciofi, Aulus C

    2014-01-01

    Animal by-product meals have large variability in crude protein (CP) content and digestibility. In vivo digestibility procedures are precise but laborious, and in vitro methods could be an alternative to evaluate and classify these ingredients. The present study reports prediction equations to estimate the CP digestibility of meat and bone meal (MBM) and poultry by-product meal (PM) using the protein solubility in pepsin method (PSP). Total tract CP digestibility of eight MBM and eight PM samples was determined in dogs by the substitution method. A basal diet was formulated for dog maintenance, and sixteen diets were produced by mixing 70 % of the basal diet and 30 % of each tested meal. Six dogs per diet were used to determine ingredient digestibility. In addition, PSP of the MBM and PM samples was determined using three pepsin concentrations: 0·02, 0·002 and 0·0002 %. The CP content of MBM and PM ranged from 39 to 46 % and 57 to 69 %, respectively, and their mean CP digestibility by dogs was 76 (2·4) and 85 (2·6) %, respectively. The pepsin concentration with higher Pearson correlation coefficients with the in vivo results were 0·0002 % for MBM (r 0·380; P = 0·008) and 0·02 % for PM (r 0·482; P = 0·005). The relationship between the in vivo and in vitro results was better explained by the following equations: CP digestibility of MBM = 61·7 + 0·2644 × PSP at 0·0002 % (P = 0·008; R (2) 0·126); and CP digestibility of PM = 54·1 + 0·3833 × PSP at 0·02 % (P = 0·005; R (2) 0·216). Although significant, the coefficients of determination were low, indicating that the models were weak and need to be used with caution.

  7. A FUNDAMENTAL STUDY ON SOLUBILITY OF HEAVY METAL OXIDES IN AMMONIUM AND PHOSPHONIUM BASED DEEP EUTECTIC SOLVENTS

    Directory of Open Access Journals (Sweden)

    SHANGGARY RAJENDRAN

    2016-02-01

    Full Text Available Water pollution has become increasingly prevalent in our daily lives and has caused a serious threat at a global level. Among the various pollutants that exist,heavy metal pollution has become an issue of great concern due to their high toxicity, greater bioaccumulation in human body and food chain, nonbiodegradability nature, and carcinogenic effects to humans. This study aims to address the heavy metal ion contamination in wastewater by providing a low cost and efficient removal technique using DESs. In this investigation, the solubility of CuO and ZnO heavy metal oxide ions with concentration of 20g/L was studied in ammonium and phosphonium based DESs. The samples were left to stir at 250 rpm at 28, 45 and 65°C respectively for four hours in an incubator orbital shaker and the solubility of the heavy metal ions were analysed using Atomic Absorption Spectrometer (AAS using serial dilution technique. Phosphonium based DES which contain Methyl Triphenyl Phosphonium Bromide (MTPB showed higher solubility of CuO and ZnO ions. Based on the results obtained, DES 6 (MTPB: Glycerol has the highest solubility of CuO, 0.197 mg/L at 65°C and the solubility of ZnO was found to be the highest in DES 7 (MTPB: Glycerol, 1.225 mg/L at 65°C. Higher solubility was observed in samples containing ZnO as they are more ionic compared to CuO.

  8. The serum level of soluble urokinase receptor is elevated in tuberculosis patients and predicts mortality during treatment: a community study from Guinea-Bissau

    DEFF Research Database (Denmark)

    Eugen-Olsen, Jesper; Gustafson, P; Sidenius, N

    2002-01-01

    OBJECTIVE: To investigate whether the serum level of soluble urokinase plasminogen activator receptor (suPAR) carries prognostic information in individuals infected with Mycobacterium tuberculosis. DESIGN: suPAR was measured by ELISA in 262 individuals at the time of enrolment into a cohort based...

  9. Manufacturing of Dysprosium-Iron Alloys by Electrolysis in Fluoride-Based Electrolytes: Oxide Solubility Determinations

    Science.gov (United States)

    Martinez, Ana Maria; Støre, Anne; Osen, Karen Sende

    2018-04-01

    Electrolytic production of light rare earth elements and alloys takes place in a fluoride-based electrolyte using rare earth oxides as raw material. The optimization of this method, mainly in terms of the energy efficiency and environmental impact control, is rather challenging. Anode effects, evolution of fluorine-containing compounds, and side cathode reactions could largely be minimized by a good control of the amount of rare earth oxide species dissolved in the fluoride-based electrolyte and their dissolution rate. The oxide content of the fluoride melts REF3-LiF (RE = Nd, Dy) at different compositions and temperatures were experimentally determined by carbothermal analysis of melt samples. The highest solubility values of oxide species, added as Dy2O3 and Dy2(CO3)3, were obtained to be of ca. 3 wt pct (expressed as Dy2O3) in the case of the equimolar DyF3-LiF melt at 1323 K (1050 °C). The oxide saturation values increased with the amount of REF3 present in the molten bath and the working temperature.

  10. Validity of Scientific Based Chemistry Android Module to Empower Science Process Skills (SPS) in Solubility Equilibrium

    Science.gov (United States)

    Antrakusuma, B.; Masykuri, M.; Ulfa, M.

    2018-04-01

    Evolution of Android technology can be applied to chemistry learning, one of the complex chemistry concept was solubility equilibrium. this concept required the science process skills (SPS). This study aims to: 1) Characteristic scientific based chemistry Android module to empowering SPS, and 2) Validity of the module based on content validity and feasibility test. This research uses a Research and Development approach (RnD). Research subjects were 135 s1tudents and three teachers at three high schools in Boyolali, Central of Java. Content validity of the module was tested by seven experts using Aiken’s V technique, and the module feasibility was tested to students and teachers in each school. Characteristics of chemistry module can be accessed using the Android device. The result of validation of the module contents got V = 0.89 (Valid), and the results of the feasibility test Obtained 81.63% (by the student) and 73.98% (by the teacher) indicates this module got good criteria.

  11. Study of methane solubility in oil base used in oil base drilling fluid; Estudo da solubilidade de metano em base oleo utilizada em fluido de perfuracao base oleo

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Carolina Teixeira da; Mariolani, Jose Ricardo Lenzi [Universidade Estadual de Campinas, SP (Brazil); Ribeiro, Paulo Roberto; Lomba, Rosana Fatima Teixeira; Bonet, Euclides Jose

    2004-07-01

    During drilling a well, it is necessary to prevent and control high pressurized zones because while drilling on those zones, could occur a kick if the formation pressure were higher then downhole pressure, allowing the entering of undesirables fluids from the formation to the wellbore. If the well is not controlled this kick could became a blowout, generating damages to the environment, to the equipment and the human life. When drilling using oil-based mud, the concern related to the well control would be higher due the gas solubility in the mud, which could make it hard to detect the kick, especially in deep and ultra deep waters. In this work we have studied the interaction between methane and organic liquids used in drilling fluids, and the measurement and analysis of the thermodynamic properties of those gas liquid mixtures. There have been measured parameters like the oil formation volume factor (FVF{sub o}), bubble pressure, solubility (Rs) and the density of the saturated liquid in function of methane mole fraction and temperature. The results have shown that the gas solubility, at downhole conditions and during kick circulation, is a factor very important to the safety during well drilling in deep and ultra deep waters. (author)

  12. Monoglyceride-based self-assembling copolymers as carriers for poorly water-soluble drugs.

    Science.gov (United States)

    Rouxhet, L; Dinguizli, M; Latere Dwan'isa, J P; Ould-Ouali, L; Twaddle, P; Nathan, A; Brewster, M E; Rosenblatt, J; Ariën, A; Préat, V

    2009-12-01

    To develop self-assembling polymers forming polymeric micelles and increasing the solubility of poorly soluble drugs, amphiphilic polymers containing a hydrophilic PEG moiety and a hydrophobic moiety derived from monoglycerides and polyethers were designed. The biodegradable copolymers were obtained via a polycondensation reaction of polyethylene glycol (PEG), monooleylglyceride (MOG) and succinic anhydride (SA). Polymers with molecular weight below 10,000 g/mol containing a minimum of 40 mol% PEG and a maximum of 10 mol% MOG self-assembled spontaneously in aqueous media upon gentle mixing. They formed particles with a diameter of 10 nm although some aggregation was evident. The critical micellar concentration varied between 3x10(-4) and 4x10(-3) g/ml, depending on the polymer. The cloud point (> or = 66 degrees C) and flocculation point (> or = 0.89 M) increased with the PEG chain length. At a 1% concentration, the polymers increased the solubility of poorly water-soluble drug candidates up to 500-fold. Drug solubility increased as a function of the polymer concentration. HPMC capsules filled with these polymers disintegrated and released model drugs rapidly. Polymer with long PEG chains had a lower cytotoxicity (MTT test) on Caco-2 cells. All of these data suggest that the object polymers, in particular PEG1000/MOG/SA (45/5/50) might be potential candidates for improving the oral biopharmaceutical performance of poorly soluble drugs.

  13. Solubility of amphotericin B in water-lecithin-dispersions and lecithin-based submicron emulsions.

    Science.gov (United States)

    Salerno, Claudia; Perez, Sebastian; Monteagudo, Ezequiel; Carlucci, Adriana; Bregni, Carlos

    2013-01-01

    The aim of this work was to evaluate water-lecithin-dispersions (WLDs) as carriers for amphotericin B (AmB) and to compare the drug solubility in WLDs and O/W lecithin-based submicron emulsions (SMEs) in order to evaluate the influence of lecithin content on the dosage form solubilization of the active compound. WLDs and different SMEs with either 1.2 or 2.4% of lecithin were prepared. WLD with 2.4% lecithin show a 10-fold increase in solubilization of AmB compared with 1.2% lecithin WLD. SMEs with 1.2% lecithin show an increase of over 400 times in solubilization compared with WLD containing the same concentration of lecithin, whereas SMEs with 2.4% lecithin show an increase of over 40 times compared with the corresponding WLD. Drug solubilization in SMEs with 2.4% lecithin is not significantly greater than in those containing 1.2% lecithin. The content of surfactant Brij 97 ® had a significant influence on drug solubilization in SMEs (P < 0.05). Results indicate that indicate that SMEs are proper systems to solubilize AmB. It can be assumed that solubilization is due to the formulation microstructure and not to the separate components themselves.

  14. Reverse micelle-based water-soluble nanoparticles for simultaneous bioimaging and drug delivery.

    Science.gov (United States)

    Chen, Ying; Liu, Yong; Yao, Yongchao; Zhang, Shiyong; Gu, Zhongwei

    2017-04-11

    With special confined water pools, reverse micelles (RMs) have shown potential for a wide range of applications. However, the inherent water-insolubility of RMs hinders their further application prospects, especially for applications related to biology. We recently reported the first successful transfer of RMs from organic media to an aqueous phase without changing the smart water pools by the hydrolysis of an arm-cleavable interfacial cross-linked reverse micelles. Herein, we employed another elaborate amphiphile 1 to construct new acrylamide-based cross-linked water-soluble nanoparticles (ACW-NPs) under much gentler conditions. The special property of the water pools of the ACW-NPs was confirmed by both the Förster resonance energy transfer (FRET) between 5-((2-aminoethyl)amino)naphthalene-1-sulfonic acid (1,5-EDANS) and benzoic acid, 4-[2-[4-(dimethylamino)phenyl]diazenyl] (DABCYL) and satisfactory colloidal stability in 10% fetal bovine serum. Importantly, featured by the gentle synthetic strategy, confined water pool, and carboxylic acid-functionalized surface, the new ACW-NPs are well suitable for biological applications. As an example, the fluorescent reagent 8-hydroxy-1,3,6-pyrenetrisulfonic acid trisodium salt (HPTS) was encapsulated in the core and simultaneously, the anticancer drug gemcitabine (Gem) was covalently conjugated onto the surface exterior. As expected, the resulting multifunctional ACW-NPs@HPTS@Gem exhibits a high imaging effect and anticancer activity for non-small lung cancer cells.

  15. Highly Selective Enrichment of Glycopeptides Based on Zwitterionically Functionalized Soluble Nanopolymers

    Science.gov (United States)

    Cao, Weiqian; Huang, Jiangming; Jiang, Biyun; Gao, Xing; Yang, Pengyuan

    2016-07-01

    Efficient glycopeptides enrichment prior to mass spectrometry analysis is essential for glycoproteome study. ZIC-HILIC (zwitterionic hydrophilic interaction liquid chromatography) based glycopeptides enrichment approaches have been attracting more attention for several benefits like easy operating, high enrichment specificity and intact glycopeptide retained. In this study, Poly (amidoamine) dendrimer (PAMAM) was adopted for the synthesis of zwitterionically functionalized (ZICF) materials for glycopeptide enrichment. The multiple branched structure and good solubility of ZICF-PAMAM enables a sufficient interaction with glycopeptides. The ZICF-PAMAM combined with the FASP-mode enrichment strategy exhibits more superior performance compared with the existing methods. It has the minimum detectable concentration of femtomolar level and high recovery rate of over 90.01%, and can efficiently enrich glycopeptides from complex biological samples even for merely 0.1 μL human serum. The remarkable glycopeptides enrichment capacity of ZICF-PAMAM highlights the potential application in in-depth glycoproteome research, which may open up new opportunities for the development of glycoproteomics.

  16. Electrochemical and optical properties of new soluble dithienylpyrroles based on azo dyes

    International Nuclear Information System (INIS)

    Cihaner, Atilla; Algi, Fatih

    2009-01-01

    Two dithienylpyrroles based on azo dyes, namely 2,5'-dimethyl-[4-(2,5-di-thiophen-2-yl-pyrrol-1-yl)-phenyl]azobenzene (SNS-AB2) and 2,5'-dimethyloxy-[4-(2,5-di-thiophen-2-yl-pyrrol-1-yl)-phenyl]azobenzene (SNS-AB3), were synthesized and their corresponding polymers (PSNS-AB2 and PSNS-AB3) were successfully obtained via electropolymerization. The monomers have lower oxidation potentials (0.75 V and 0.80 V vs. Ag/AgCl for SNS-AB2 and SNS-AB3, respectively) when compared to their analogous. Both monomers exhibited photoisomerism properties under irradiation at 360 nm. During the irradiation process, for example, the color of SNS-AB3 changes from yellow to greenish yellow. The electroactive polymer films have well defined and reversible redox couples with a good cycle stability in both aqueous and organic solutions. The polymer films also exhibited electrochromic behaviors; color changes from yellowish green to dark green for the PSNS-AB2 (λ max = 435 nm and E g = 2.31 eV) and from mustard color to green for PSNS-AB3 (λ max = 430 nm and E g = 2.34 eV). Furthermore, the soluble polymers demonstrated different hues of yellow and green colors

  17. One-step enzymatic synthesis of nucleosides from low water-soluble purine bases in non-conventional media.

    Science.gov (United States)

    Fernández-Lucas, Jesús; Fresco-Taboada, Alba; de la Mata, Isabel; Arroyo, Miguel

    2012-07-01

    The effect of several water-miscible cosolvents on activity and stability of soluble and immobilized 2'-deoxyribosyltransferase from Lactobacillus reuteri on Sepabeads® has been studied in order to establish optimal conditions for enzymatic synthesis of nucleosides using purine bases with low solubility in aqueous buffer. As a rule of thumb, there was a general reduction of soluble enzyme activity when cosolvent content was gradually increased in reaction medium. In contrast, immobilized enzyme activity was enhanced 1.2-1.4-fold at 20% of methanol, ethanol, 2-propanol, diethylene glycol, and acetone; and at 10% and 30% acetonitrile. Likewise, highest increased activity (1.8-fold) was also obtained in presence of 20% acetonitrile. Immobilized enzyme was successfully used in the synthesis of 2'-deoxyxanthosine and 2'-deoxyguanosine using 2'-deoxyuridine as sugar donor and the corresponding poor water-soluble base in the presence of 30% of methanol, ethanol, 2-propanol, ethylene glycol, acetonitrile, and DMSO, giving high nucleoside yields at 4h. Copyright © 2011 Elsevier Ltd. All rights reserved.

  18. Characterization of water sorption, solubility, and roughness of silorane- and methacrylate-based composite resins.

    Science.gov (United States)

    Giannini, M; Di Francescantonio, M; Pacheco, R R; Cidreira Boaro, L C; Braga, R R

    2014-01-01

    The objective of this study was to evaluate the surface roughness (SR), water sorption (WS), and solubility (SO) of four composite resins after finishing/polishing and after one year of water storage. Two low-shrinkage composites (Filtek Silorane [3M ESPE] and Aelite LS [Bisco Inc]) and two composites of conventional formulations (Heliomolar and Tetric N-Ceram [Ivoclar Vivadent]) were tested. Their respective finishing and polishing systems (Sof-Lex Discs, 3M ESPE; Finishing Discs Kit, Bisco Inc; and Astropol F, P, HP, Ivoclar Vivadent) were used according to the manufacturers' instructions. Ten disc-shaped specimens of each composite resin were made for each evaluation. Polished surfaces were analyzed using a profilometer after 24 hours and one year. For the WS and SO, the discs were stored in desiccators until constant mass was achieved. Specimens were then stored in water for seven days or one year, at which time the mass of each specimen was measured. The specimens were dried again and dried specimen mass determined. The WS and SO were calculated from these measurements. Data were analyzed by two-way analysis of variance and Tukey post hoc test (α=0.05). Filtek Silorane showed the lowest SR, WS, and SO means. Water storage for one year increased the WS means for all composite resins tested. The silorane-based composite resin results were better than those obtained for methacrylate-based resins. One-year water storage did not change the SR and SO properties in any of the composite resins.

  19. Thermodynamic models to predict gas-liquid solubilities in the methanol synthesis, the methanol-higher alcohol synthesis, and the Fischer-Tropsch synthesis via gas-slurry processes

    NARCIS (Netherlands)

    Breman, B.B; Beenackers, A.A C M

    1996-01-01

    Various thermodynamic models were tested concerning their applicability to predict gas-liquid solubilities, relevant for synthesis gas conversion to methanol, higher alcohols, and hydrocarbons via gas-slurry processes. Without any parameter optimization the group contribution equation of state

  20. Speech Intelligibility Prediction Based on Mutual Information

    DEFF Research Database (Denmark)

    Jensen, Jesper; Taal, Cees H.

    2014-01-01

    This paper deals with the problem of predicting the average intelligibility of noisy and potentially processed speech signals, as observed by a group of normal hearing listeners. We propose a model which performs this prediction based on the hypothesis that intelligibility is monotonically related...... to the mutual information between critical-band amplitude envelopes of the clean signal and the corresponding noisy/processed signal. The resulting intelligibility predictor turns out to be a simple function of the mean-square error (mse) that arises when estimating a clean critical-band amplitude using...... a minimum mean-square error (mmse) estimator based on the noisy/processed amplitude. The proposed model predicts that speech intelligibility cannot be improved by any processing of noisy critical-band amplitudes. Furthermore, the proposed intelligibility predictor performs well ( ρ > 0.95) in predicting...

  1. Calorimeter prediction based on multiple exponentials

    International Nuclear Information System (INIS)

    Smith, M.K.; Bracken, D.S.

    2002-01-01

    Calorimetry allows very precise measurements of nuclear material to be carried out, but it also requires relatively long measurement times to do so. The ability to accurately predict the equilibrium response of a calorimeter would significantly reduce the amount of time required for calorimetric assays. An algorithm has been developed that is effective at predicting the equilibrium response. This multi-exponential prediction algorithm is based on an iterative technique using commercial fitting routines that fit a constant plus a variable number of exponential terms to calorimeter data. Details of the implementation and the results of trials on a large number of calorimeter data sets will be presented

  2. Prediction of Starch, Soluble Sugars and Amino Acids in Potatoes (Solanum tuberosum L.) Using Hyperspectral Imaging, Dielectric and LF-NMR Methodologies

    DEFF Research Database (Denmark)

    Kjær, Anders; Nielsen, Glenn; Stærke, Søren

    2016-01-01

    Handling and processing of potatoes is performed in increasingly large and more automated facilities, and the industry calls for more automated machinery for quality assessment and sorting by concentration of starch, soluble sugars, protein, amino acids etc. of the potato tubers. The present study...... cultivars were simultaneously sampled for analyses of content and scanned by the five different scanning methods. The resulting multivariate dataset was used to estimate the prediction ability of the individual scanning methods on starch-related parameters, selected simple sugars, selected amino acids......, conductivity of pressed cell sap and cell sizes. Results showed that most types of spectral analyses had relatively high potential for predicting the starch-related parameters and medium potential for predicting the concentration of the reducing sugars fructose and glucose. Most methods showed medium potential...

  3. Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems

    International Nuclear Information System (INIS)

    Kovalenko, Andriy

    2014-01-01

    Cellulose Nanocrysals (CNC) is a renewable biodegradable biopolymer with outstanding mechanical properties made from highly abundant natural source, and therefore is very attractive as reinforcing additive to replace petroleum-based plastics in biocomposite materials, foams, and gels. Large-scale applications of CNC are currently limited due to its low solubility in non-polar organic solvents used in existing polymerization technologies. The solvation properties of CNC can be improved by chemical modification of its surface. Development of effective surface modifications has been rather slow because extensive chemical modifications destabilize the hydrogen bonding network of cellulose and deteriorate the mechanical properties of CNC. We employ predictive multiscale theory, modeling, and simulation to gain a fundamental insight into the effect of CNC surface modifications on hydrogen bonding, CNC crystallinity, solvation thermodynamics, and CNC compatibilization with the existing polymerization technologies, so as to rationally design green nanomaterials with improved solubility in non-polar solvents, controlled liquid crystal ordering and optimized extrusion properties. An essential part of this multiscale modeling approach is the statistical- mechanical 3D-RISM-KH molecular theory of solvation, coupled with quantum mechanics, molecular mechanics, and multistep molecular dynamics simulation. The 3D-RISM-KH theory provides predictive modeling of both polar and non-polar solvents, solvent mixtures, and electrolyte solutions in a wide range of concentrations and thermodynamic states. It properly accounts for effective interactions in solution such as steric effects, hydrophobicity and hydrophilicity, hydrogen bonding, salt bridges, buffer, co-solvent, and successfully predicts solvation effects and processes in bulk liquids, solvation layers at solid surface, and in pockets and other inner spaces of macromolecules and supramolecular assemblies. This methodology

  4. Predictive Multiscale Modeling of Nanocellulose Based Materials and Systems

    Science.gov (United States)

    Kovalenko, Andriy

    2014-08-01

    Cellulose Nanocrysals (CNC) is a renewable biodegradable biopolymer with outstanding mechanical properties made from highly abundant natural source, and therefore is very attractive as reinforcing additive to replace petroleum-based plastics in biocomposite materials, foams, and gels. Large-scale applications of CNC are currently limited due to its low solubility in non-polar organic solvents used in existing polymerization technologies. The solvation properties of CNC can be improved by chemical modification of its surface. Development of effective surface modifications has been rather slow because extensive chemical modifications destabilize the hydrogen bonding network of cellulose and deteriorate the mechanical properties of CNC. We employ predictive multiscale theory, modeling, and simulation to gain a fundamental insight into the effect of CNC surface modifications on hydrogen bonding, CNC crystallinity, solvation thermodynamics, and CNC compatibilization with the existing polymerization technologies, so as to rationally design green nanomaterials with improved solubility in non-polar solvents, controlled liquid crystal ordering and optimized extrusion properties. An essential part of this multiscale modeling approach is the statistical- mechanical 3D-RISM-KH molecular theory of solvation, coupled with quantum mechanics, molecular mechanics, and multistep molecular dynamics simulation. The 3D-RISM-KH theory provides predictive modeling of both polar and non-polar solvents, solvent mixtures, and electrolyte solutions in a wide range of concentrations and thermodynamic states. It properly accounts for effective interactions in solution such as steric effects, hydrophobicity and hydrophilicity, hydrogen bonding, salt bridges, buffer, co-solvent, and successfully predicts solvation effects and processes in bulk liquids, solvation layers at solid surface, and in pockets and other inner spaces of macromolecules and supramolecular assemblies. This methodology

  5. Unchanged Levels of Soluble CD14 and IL-6 Over Time Predict Serious Non-AIDS Events in HIV-1-Infected People

    Science.gov (United States)

    Sunil, Meena; Nigalye, Maitreyee; Somasunderam, Anoma; Martinez, Maria Laura; Yu, Xiaoying; Arduino, Roberto C.; Bell, Tanvir K.

    2016-01-01

    Abstract HIV-1-infected persons have increased risk of serious non-AIDS events (SNAEs) despite suppressive antiretroviral therapy. Increased circulating levels of soluble CD14 (sCD14), soluble CD163 (sCD163), and interleukin-6 (IL-6) at a single time point have been associated with SNAEs. However, whether changes in these biomarker levels predict SNAEs in HIV-1-infected persons is unknown. We hypothesized that greater decreases in inflammatory biomarkers would be associated with fewer SNAEs. We identified 39 patients with SNAEs, including major cardiovascular events, end stage renal disease, decompensated cirrhosis, non-AIDS-defining malignancies, and death of unknown cause, and age- and sex-matched HIV-1-infected controls. sCD14, sCD163, and IL-6 were measured at study enrollment (T1) and proximal to the event (T2) or equivalent duration in matched controls. Over ∼34 months, unchanged rather than decreasing levels of sCD14 and IL-6 predicted SNAEs. Older age and current illicit substance abuse, but not HCV coinfection, were associated with SNAEs. In a multivariate analysis, older age, illicit substance use, and unchanged IL-6 levels remained significantly associated with SNAEs. Thus, the trajectories of sCD14 and IL-6 levels predict SNAEs. Interventions to decrease illicit substance use may decrease the risk of SNAEs in HIV-1-infected persons. PMID:27344921

  6. Energy based prediction models for building acoustics

    DEFF Research Database (Denmark)

    Brunskog, Jonas

    2012-01-01

    In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...... on underlying basic assumptions, such as diffuse fields, high modal overlap, resonant field being dominant, etc., and the consequences of these in terms of limitations in the theory and in the practical use of the models....

  7. High variation of individual soluble serum CD30 levels of pre-transplantation patients: sCD30 a feasible marker for prediction of kidney allograft rejection?

    Science.gov (United States)

    Altermann, Wolfgang; Schlaf, Gerald; Rothhoff, Anita; Seliger, Barbara

    2007-10-01

    Previous studies have suggested that the pre-transplant levels of the soluble CD30 molecule (sCD30) represent a non-invasive tool which can be used as a biomarker for the prediction of kidney allograft rejections. In order to evaluate the feasibility of sCD30 for pre-transplantation monitoring the sera of potential kidney recipients (n = 652) were collected four times in a 3 months interval. Serum from healthy blood donors (n = 203) served as controls. The sCD30 concentrations of all samples were determined using a commercially available ELISA. This strategy allowed the detection of possible variations of individual sCD30 levels over time. Heterogeneous sCD30 concentrations were found in the samples obtained from individual putative kidney transplant recipients when quarterly measured over 1 year. Total 95% of serum samples obtained from healthy controls exhibited sCD30 values 30 U/ml). Total 524 patients (80.4%) constantly exhibited serum concentrations of sCD30 values >100 U/ml was significantly lower than that previously reported. The high degree of variation does not allow the stratification of patients into high and low immunological risk groups based on a single sCD30 value > 100 U/ml. Due to the heterogeneity of sCD30 levels during time course and the high values of SD, its implementation as a pre-transplant marker cannot be justified to generate special provisions for the organ allocation to patients with single sCD30 values > 100 U/ml.

  8. Soluble CD30 and ELISA-detected human leukocyte antigen antibodies for the prediction of acute rejection in pediatric renal transplant recipients.

    Science.gov (United States)

    Billing, Heiko; Sander, Anja; Süsal, Caner; Ovens, Jörg; Feneberg, Reinhard; Höcker, Britta; Vondrak, Karel; Grenda, Ryszard; Friman, Stybjorn; Milford, David V; Lucan, Mihai; Opelz, Gerhard; Tönshoff, Burkhard

    2013-03-01

    Biomarker-based post-transplant immune monitoring for the prediction of impending graft rejection requires validation in specific patient populations. Serum of 28 pediatric renal transplant recipients within the framework of a well-controlled prospective randomized trial was analyzed pre- and post-transplant for soluble CD30 (sCD30), a biomarker reflecting mainly T-cell reactivity, and anti-human leukocyte antigen (anti-HLA) antibody reactivity, a biomarker for B-cell activation. A sCD30 concentration ≥40.3 U/ml on day 14 was able to discriminate between patients with or without biopsy-proven acute rejection (BPAR) with a sensitivity of 100% and a specificity of 76%. Six of seven patients (86%) with BPAR showed a sCD30 above this cut-off, whereas only 3/21 patients (14%) without BPAR had a sCD30 above this cut-off (P = 0.004). For pre- and post-transplant anti-HLA class II reactivities by enzyme-linked immunosorbent assay, a cut-off value of 140 optical density was able to discriminate rejecters from nonrejecters with a sensitivity of 86% or 71% and a specificity of 81% or 90%, respectively. Withdrawal of steroids was associated with a approximately twofold higher serum sCD30 compared to controls, but did not affect anti-HLA reactivities. An increased post-transplant sCD30 serum concentration and positive pre- and post-transplant anti-HLA class II reactivities are informative biomarkers for impending BPAR in pediatric renal transplant recipients. (TWIST, Clinical Trial No: FG-506-02-43). © 2012 The Authors Transplant International © 2012 European Society for Organ Transplantation. Published by Blackwell Publishing Ltd.

  9. A Phase Blending Study on Rubber Blends Based on the Solubility Preference of Curatives

    NARCIS (Netherlands)

    Guo, R.; Talma, Auke; Datta, Rabin; Dierkes, Wilma K.; Noordermeer, Jacobus W.M.

    2009-01-01

    Using previously obtained data on the solubilities of curatives in SBR, EPDM and in NBR, different mixing procedures were performed on 50/50 SBR/EPDM and NBR/EPDM blends. In contrast to a previous phase-mixing study, the curatives were added to separate phases before final blending, in an attempt to

  10. Plutonium solubilities

    International Nuclear Information System (INIS)

    Puigdomnech, I.; Bruno, J.

    1991-02-01

    Thermochemical data has been selected for plutonium oxide, hydroxide, carbonate and phosphate equilibria. Equilibrium constants have been evaluated in the temperature range 0 to 300 degrees C at a pressure of 1 bar to T≤100 degrees C and at the steam saturated pressure at higher temperatures. Measured solubilities of plutonium that are reported in the literature for laboratory experiments have been collected. Solubility data on oxides, hydroxides, carbonates and phosphates have been selected. No solubility data were found at temperatures higher than 60 degrees C. The literature solubility data have been compared with plutonium solubilities calculated with the EQ3/6 geochemical modelling programs, using the selected thermodynamic data for plutonium. (authors)

  11. Knowledge-based Fragment Binding Prediction

    Science.gov (United States)

    Tang, Grace W.; Altman, Russ B.

    2014-01-01

    Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. PMID:24762971

  12. Predicting Learned Helplessness Based on Personality

    Science.gov (United States)

    Maadikhah, Elham; Erfani, Nasrollah

    2014-01-01

    Learned helplessness as a negative motivational state can latently underlie repeated failures and create negative feelings toward the education as well as depression in students and other members of a society. The purpose of this paper is to predict learned helplessness based on students' personality traits. The research is a predictive…

  13. In vitro solubility of calcium, iron and zinc in relation to phytic acid levels in rice-based consumer products in China

    NARCIS (Netherlands)

    Liang, J.; Han, B.Z.; Nout, M.J.R.; Hamer, R.J.

    2010-01-01

    In vitro solubility of calcium, iron and zinc in relation to phytic acid (PA) levels in 30 commercial rice-based foods from China was studied. Solubility of minerals and molar ratios of PA to minerals varied with degrees of processing. In primary products, [PA]/[Ca] values were less than 5 and

  14. Uranium solubility and speciation in ground water

    International Nuclear Information System (INIS)

    Ollila, K.

    1985-04-01

    The purpose of this study has been to assess the solubility and possible species of uranium in groundwater at the disposal conditions of spent fuel. The effects of radiolysis and bentonite are considered. The assessment is based on the theoretical calculations found in the literature. The Finnish experimental results are included. The conservative estimate for uranium solubility under the oxidizing conditions caused by alpha radiolysis is based on the oxidation of uranium to the U(VI) state and formation of carbonate complex. For the groundwater with the typical carbonate content of 275 mg/l and the high carbonate content of 485 mg/l due to bentonite, the solubility values of 360 mg u/l and 950 mg U/l, are obtained, respectively. The experimental results predict considerably lower values, 0.5-20 mg U/l. The solubility of uranium under the undisturbed reducing conditions may be calculated based on the hydrolysis, carbonate complexation and redox reactions. The results vary considerably depending on the thermodynamic data used. The wide ranges of the most important groundwater parameters are seen in the solubility values. The experimental results show the same trends. As a conservative value for the solubility in reducing groundwater 50-500 μg U/l is estimated. (author)

  15. Structure-solubility relationships in fluoride-containing phosphate based bioactive glasses

    Science.gov (United States)

    Shaharyar, Yaqoot

    The dissolution of fluoride-containing bioactive glasses critically affects their biomedical applications. Most commercial fluoride-releasing bioactive glasses have been designed in the soda-lime-silica system. However, their relatively slow chemical dissolution and the adverse effect of fluoride on their bioactivity are stimulating the study of novel biodegradable materials with higher bioactivity, such as biodegradable phosphate-based bioactive glasses, which can be a viable alternative for applications where a fast release of active ions is sought. In order to design new biomaterials with controlled degradability and high bioactivity, it is essential to understand the connection between chemical composition, molecular structure, and solubility in physiological fluids.Accordingly, in this work we have combined the strengths of various experimental techniques with Molecular Dynamics (MD) simulations, to elucidate the impact of fluoride ions on the structure and chemical dissolution of bioactive phosphate glasses in the system: 10Na2O - (45-x) CaO - 45P2O5 - xCaF2, where x varies between 0 -- 10 mol.%. NMR and MD data reveal that the medium-range atomic-scale structure of thse glasses is dominated by Q2 phosphate units followed by Q1 units, and the MD simulations further show that fluoride tends to associate with network modifier cations to form alkali/alkaline-earth rich ionic aggregates. On a macroscopic scale, we find that incorporating fluoride in phosphate glasses does not affect the rate of apatite formation on the glass surface in simulated body fluid (SBF). However, fluoride has a marked favorable impact on the glass dissolution in deionized water. Similarly, fluoride incorporation in the glasses results in significant weight gain due to adsorption of water (in the form of OH ions). These macroscopic trends are discussed on the basis of the F effect on the atomistic structure of the glasses, such as the F-induced phosphate network re-polymerization, in a

  16. High mobility organic field-effect transistor based on water-soluble deoxyribonucleic acid via spray coating

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Wei; Han, Shijiao; Huang, Wei; Yu, Junsheng, E-mail: jsyu@uestc.edu.cn [State Key Laboratory of Electronic Thin Films and Integrated Devices, School of Optoelectronic Information, University of Electronic Science and Technology of China (UESTC), Chengdu 610054 (China)

    2015-01-26

    High mobility organic field-effect transistors (OFETs) by inserting water-soluble deoxyribonucleic acid (DNA) buffer layer between electrodes and pentacene film through spray coating process were fabricated. Compared with the OFETs incorporated with DNA in the conventional organic solvents of ethanol and methanol: water mixture, the water-soluble DNA based OFET exhibited an over four folds enhancement of field-effect mobility from 0.035 to 0.153 cm{sup 2}/Vs. By characterizing the surface morphology and the crystalline structure of pentacene active layer through atomic force microscope and X-ray diffraction, it was found that the adoption of water solvent in DNA solution, which played a key role in enhancing the field-effect mobility, was ascribed to both the elimination of the irreversible organic solvent-induced bulk-like phase transition of pentacene film and the diminution of a majority of charge trapping at interfaces in OFETs.

  17. Serum markers of macrophage activation in pre-eclampsia: no predictive value of soluble CD163 and neopterin

    DEFF Research Database (Denmark)

    Kronborg, Camilla S; Knudsen, Ulla Breth; Moestrup, Søren K

    2007-01-01

    BACKGROUND: Alternatively activated macrophages expressing the CD163 and CD206 surface receptors are the dominant immune-cell type found in the placenta. The placental number and distribution of macrophages is altered in pre-eclampsia, and the generalised inflammatory reaction associated with pre-eclampsia...... might lead to shedding of soluble CD163 into the circulation. METHODS: Serum samples from 18 women with pre-eclampsia and 90 normal pregnancies were obtained from a longitudinal study of 955 pregnant women at Randers County Hospital, Denmark. sCD163 and Neopterin were measured by ELISA on samples....... Neopterin increased throughout pregnancy in both healthy (from median 5.4 to 6.7 nmol/l, ppre-eclampsia...

  18. Beyond liposomes: Recent advances on lipid based nanostructures for poorly soluble/poorly permeable drug delivery.

    Science.gov (United States)

    Teixeira, M C; Carbone, C; Souto, E B

    2017-10-01

    Solid lipid nanoparticle (SLN), nanostructured lipid carriers (NLC) and hybrid nanoparticles, have gained increasing interest as drug delivery systems because of their potential to load and release drugs from the Biopharmaceutical classification system (BCS) of class II (low solubility and high permeability) and of class IV (low solubility and low permeability). Lipid properties (e.g. high solubilizing potential, biocompatibility, biotolerability, biodegradability and distinct route of absorption) contribute for the improvement of the bioavailability of these drugs for a set of administration routes. Their interest continues to grow, as translated by the number of patents being field worldwide. This paper discusses the recent advances on the use of SLN, NLC and lipid-polymer hybrid nanoparticles for the loading of lipophilic, poorly water-soluble and poorly permeable drugs, being developed for oral, topical, parenteral and ocular administration, also discussing the industrial applications of these systems. A review of the patents filled between 2014 and 2017, concerning the original inventions of lipid nanocarriers, is also provided. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Combining in vitro and in silico methods for better prediction of surfactant effects on the absorption of poorly water soluble drugs-a fenofibrate case example.

    Science.gov (United States)

    Berthelsen, Ragna; Sjögren, Erik; Jacobsen, Jette; Kristensen, Jakob; Holm, René; Abrahamsson, Bertil; Müllertz, Anette

    2014-10-01

    The aim of this study was to develop a sensitive and discriminative in vitro-in silico model able to simulate the in vivo performance of three fenofibrate immediate release formulations containing different surfactants. In addition, the study was designed to investigate the effect of dissolution volume when predicting the oral bioavailability of the formulations. In vitro dissolution studies were carried out using the USP apparatus 2 or a mini paddle assembly, containing 1000 mL or 100mL fasted state biorelevant medium, respectively. In silico simulations of small intestinal absorption were performed using the GI-Sim absorption model. All simulation runs were performed twice adopting either a total small intestinal volume of 533 mL or 105 mL, in order to examine the implication of free luminal water volumes for the in silico predictions. For the tested formulations, the use of a small biorelevant dissolution volume was critical for in vitro-in silico prediction of drug absorption. Good predictions, demonstrating rank order in vivo-in vitro-in silico correlations for Cmax, were obtained with in silico predictions utilizing a 105 mL estimate for the human intestinal water content combined with solubility and dissolution data performed in a mini paddle apparatus with 100mL fasted state simulated media. Copyright © 2014. Published by Elsevier B.V.

  20. Simultaneous separation of water- and fat-soluble vitamins in isocratic pressure-assisted capillary electrochromatography using a methacrylate-based monolithic column.

    Science.gov (United States)

    Yamada, Hiroki; Kitagawa, Shinya; Ohtani, Hajime

    2013-06-01

    A method of simultaneous separation of water- and fat-soluble vitamins using pressure-assisted CEC with a methacrylate-based capillary monolithic column was developed. In the proposed method, water-soluble vitamins were mainly separated electrophoretically, while fat soluble-ones were separated chromatographically by the interaction with a methacrylate-based monolith. A mixture of six water-soluble and four fat-soluble vitamins was separated simultaneously within 20 min with an isocratic elution using 1 M formic acid (pH 1.9)/acetonitrile (30:70, v/v) containing 10 mM ammonium formate as a mobile phase. When the method was applied to a commercial multivitamin tablet and a spiked one, the vitamins were successfully analyzed, and no influence of the matrix contained in the tablet was observed. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Highway traffic noise prediction based on GIS

    Science.gov (United States)

    Zhao, Jianghua; Qin, Qiming

    2014-05-01

    Before building a new road, we need to predict the traffic noise generated by vehicles. Traditional traffic noise prediction methods are based on certain locations and they are not only time-consuming, high cost, but also cannot be visualized. Geographical Information System (GIS) can not only solve the problem of manual data processing, but also can get noise values at any point. The paper selected a road segment from Wenxi to Heyang. According to the geographical overview of the study area and the comparison between several models, we combine the JTG B03-2006 model and the HJ2.4-2009 model to predict the traffic noise depending on the circumstances. Finally, we interpolate the noise values at each prediction point and then generate contours of noise. By overlaying the village data on the noise contour layer, we can get the thematic maps. The use of GIS for road traffic noise prediction greatly facilitates the decision-makers because of GIS spatial analysis function and visualization capabilities. We can clearly see the districts where noise are excessive, and thus it becomes convenient to optimize the road line and take noise reduction measures such as installing sound barriers and relocating villages and so on.

  2. Argon solubility in liquid steel

    NARCIS (Netherlands)

    Boom, R; Dankert, O; Van Veen, A; Kamperman, AA

    2000-01-01

    Experiments have been performed to establish the solubility of argon in liquid interstitial-free steel. The solubility appears to be lower than 0.1 at ppb, The results are in line with argon solubilities reported in the literature on liquid iron. Semiempirical theories and calculations based on the

  3. Dst Prediction Based on Solar Wind Parameters

    Directory of Open Access Journals (Sweden)

    Yoon-Kyung Park

    2009-12-01

    Full Text Available We reevaluate the Burton equation (Burton et al. 1975 of predicting Dst index using high quality hourly solar wind data supplied by the ACE satellite for the period from 1998 to 2006. Sixty magnetic storms with monotonously decreasing main phase are selected. In order to determine the injection term (Q and the decay time (tau of the equation, we examine the relationships between Dst* and VB_s, Delta Dst* and VB_s, and Delta Dst* and Dst* during the magnetic storms. For this analysis, we take into account one hour of the propagation time from the ACE satellite to the magnetopause, and a half hour of the response time of the magnetosphere/ring current to the solar wind forcing. The injection term is found to be Q({nT}/h=-3.56VB_s for VB_s>0.5mV/m and Q({nT}/h=0 for VB_s leq0.5mV/m. The tau (hour is estimated as 0.060 Dst* + 16.65 for Dst*>-175nT and 6.15 hours for Dst* leq -175nT. Based on these empirical relationships, we predict the 60 magnetic storms and find that the correlation coefficient between the observed and predicted Dst* is 0.88. To evaluate the performance of our prediction scheme, the 60 magnetic storms are predicted again using the models by Burton et al. (1975 and O'Brien & McPherron (2000a. The correlation coefficients thus obtained are 0.85, the same value for both of the two models. In this respect, our model is slightly improved over the other two models as far as the correlation coefficients is concerned. Particularly our model does a better job than the other two models in predicting intense magnetic storms (Dst* lesssim -200nT.

  4. Wavelet-based prediction of oil prices

    International Nuclear Information System (INIS)

    Yousefi, Shahriar; Weinreich, Ilona; Reinarz, Dominik

    2005-01-01

    This paper illustrates an application of wavelets as a possible vehicle for investigating the issue of market efficiency in futures markets for oil. The paper provides a short introduction to the wavelets and a few interesting wavelet-based contributions in economics and finance are briefly reviewed. A wavelet-based prediction procedure is introduced and market data on crude oil is used to provide forecasts over different forecasting horizons. The results are compared with data from futures markets for oil and the relative performance of this procedure is used to investigate whether futures markets are efficiently priced

  5. Predictive value of elevated soluble CD40 ligand in patients undergoing primary angioplasty for ST-segment elevation myocardial infarction.

    Science.gov (United States)

    Pusuroglu, Hamdi; Akgul, Ozgur; Erturk, Mehmet; Uyarel, Huseyin; Bulut, Umit; Akkaya, Emre; Buturak, Ali; Surgit, Ozgur; Fuat, Ali; Cetin, Mustafa; Yldrm, Aydn

    2014-11-01

    The aim of this study was to evaluate the prognostic value of soluble CD40 ligand (sCD40L) in patients with ST-segment elevation myocardial infarction (STEMI) undergoing a primary percutaneous coronary intervention (PCI). The prognostic value of sCD40L has been documented in patients with acute coronary syndrome; however, its value in acute STEMI remains unclear. We prospectively enrolled 499 consecutive STEMI patients (397 men, 102 women) undergoing primary PCI. The study population was divided into tertiles on the basis of admission sCD40L values. The high sCD40L group (n=168) included patients with a value in the third tertile (≥0.947 mg/l) and the low sCD40L group (n=331) included patients with a value in the lower two tertiles (0.947 mg/l) is a powerful independent predictor of 1-year all-cause mortality (odds ratio: 3.68; 95% confidence interval: 1.54-8.77; P=0.003). The results of this study suggest that a high sCD40L level at admission is associated with increased in-hospital and 1-year all-cause mortality rates in patients with STEMI undergoing primary PCI.

  6. Gas Permeation Properties of Soluble Aromatic Polyimides Based on 4-Fluoro-4,4'-Diaminotriphenylmethane

    Directory of Open Access Journals (Sweden)

    Diego Guzmán-Lucero

    2015-04-01

    Full Text Available A series of new organic polyimides were synthesized from 4-fluoro-4'4"-diaminotriphenylmethane and four different aromatic dianhydrides through a one-step, high-temperature, direct polycondensation in m-cresol at 180–200 °C, resulting in the formation of high-molecular-weight polyimides (inherent viscosities ~ 1.0–1.3 dL/g. All the resulting polyimides exhibited good thermal stability with initial decomposition temperatures above 434 °C, glass-transition temperatures between 285 and 316 °C, and good solubility in polar aprotic solvents. Wide-angle X-ray scattering data indicated that the polyimides were amorphous. Dense membranes were prepared by solution casting and solvent evaporation to evaluate their gas transport properties (permeability, diffusivity, and solubility coefficients toward pure hydrogen, helium, oxygen, nitrogen, methane, and carbon dioxide gases. In general, the gas permeability was increased as both the fractional free volume and d-spacing were also increased. A good combination of permeability and selectivity was promoted efficiently by the bulky hexafluoroisopropylidene and 4-fluoro-phenyl groups introduced into the polyimides. The results indicate that the gas transport properties of these films depend on both the structure of the anhydride moiety, which controls the intrinsic intramolecular rigidity, and the 4-fluoro-phenyl pendant group, which disrupts the intermolecular packing.

  7. High serum soluble tumor necrosis factor receptor 1 predicts poor treatment response in acute-stage schizophrenia.

    Science.gov (United States)

    Nishimon, Shohei; Ohnuma, Tohru; Takebayashi, Yuto; Katsuta, Narimasa; Takeda, Mayu; Nakamura, Toru; Sannohe, Takahiro; Higashiyama, Ryoko; Kimoto, Ayako; Shibata, Nobuto; Gohda, Tomohito; Suzuki, Yusuke; Yamagishi, Sho-Ichi; Tomino, Yasuhiko; Arai, Heii

    2017-06-02

    Inflammation may be involved in the pathophysiology of schizophrenia. However, few cross-sectional or longitudinal studies have examined changes in biomarker expression to evaluate diagnostic and prognostic efficacy in acute-stage schizophrenia. We compared serum inflammatory biomarker concentrations in 87 patients with acute-stage schizophrenia on admission to 105 age-, sex-, and body mass index (BMI)-matched healthy controls. The measured biomarkers were soluble tumor necrosis factor receptor 1 (sTNFR1) and adiponectin, which are associated with inflammatory responses, and pigment epithelium-derived factor (PEDF), which has anti-inflammatory properties. We then investigated biomarker concentrations and associations with clinical factors in 213 patients (including 42 medication-free patients) and 110 unmatched healthy controls to model conditions typical of clinical practice. Clinical symptoms were assessed using the Brief Psychiatric Rating Scale and Global Assessment of Function. In 121 patients, biomarker levels and clinical status were evaluated at both admission and discharge. Serum sTNFR1 was significantly higher in patients with acute-stage schizophrenia compared to matched controls while no significant group differences were observed for the other markers. Serum sTNFR1 was also significantly higher in the 213 patients compared to unmatched controls. The 42 unmedicated patients had significantly lower PEDF levels compared to controls. Between admission and discharge, sTNFR1 levels decreased significantly; however, biomarker changes did not correlate with clinical symptoms. The discriminant accuracy of sTNFR1 was 93.2% between controls and patients, showing no symptom improvement during care. Inflammation and a low-level anti-inflammatory state may be involved in both schizophrenia pathogenesis and acute-stage onset. High serum sTNFR1 in the acute stage could be a useful prognostic biomarker for treatment response in clinical practice. Copyright © 2017

  8. Link prediction based on nonequilibrium cooperation effect

    Science.gov (United States)

    Li, Lanxi; Zhu, Xuzhen; Tian, Hui

    2018-04-01

    Link prediction in complex networks has become a common focus of many researchers. But most existing methods concentrate on neighbors, and rarely consider degree heterogeneity of two endpoints. Node degree represents the importance or status of endpoints. We describe the large-degree heterogeneity as the nonequilibrium between nodes. This nonequilibrium facilitates a stable cooperation between endpoints, so that two endpoints with large-degree heterogeneity tend to connect stably. We name such a phenomenon as the nonequilibrium cooperation effect. Therefore, this paper proposes a link prediction method based on the nonequilibrium cooperation effect to improve accuracy. Theoretical analysis will be processed in advance, and at the end, experiments will be performed in 12 real-world networks to compare the mainstream methods with our indices in the network through numerical analysis.

  9. Incorporating Pitzer equations in a new thermodynamic model for the prediction of acid gases solubility in aqueous alkanolamine solutions

    NARCIS (Netherlands)

    Alhseinat, E.; Mota Martinez, M.; Peters, C.J.; Banat, F.

    2014-01-01

    In gas sweetening, acid gases such as CO2 and/or H2S are usually removed by "chemical" absorption through aqueous amine solutions such as N-Methyldiethanolamine (MDEA) solution. Reliable prediction of equilibrium properties (vapor–liquid equilibrium and species distribution) is needed for a rigorous

  10. [Application of the concetrations ratio of soluble receptor tyrosine kinase type 1, and placental growth factor for short-term prediction and diagnosis of preeclampsia].

    Science.gov (United States)

    Bubeníková, Š; Cíchová, A; Roubalová, L; Durdová, V; Vlk, R

    Bring a comprehensive overview of the available information about applications of the concetration ratio of soluble receptor tyrosine kinase type 1 (sFlt-1), and placental growth factor for short-term prediction and diagnosis of preeclampsia. Overview study. Department of Midwifery, Faculty of Health Sciences, Olomouc; Department of Clinical Biochemistry, University Hospital Olomouc; Department of Obstetrics and Gynecology, University Hospital Olomouc; Department of Obstetrics and Gynecology, 2nd Faculty of Medicine, Charles University in Prague and Motol University Hospital. Analysis of literary sources and databases Ovid, Medline (2001-2016). Preeclampsia is a multisystem disease with not fully understood etiology. This disease occurs in 2-5% of pregnant women. Preeclampsia is one of the main causes of global maternal and perinatal morbidity and mortality. It manifests itself as a newborn hypertension and proteinuria after 20 weeks of pregnancy in previously normotensive women. The only effective treatment is the delivery of the child. Diagnosis of preeclampsia comprises measuring blood pressure and proteinuria. These indicators have low diagnostic sensitivity and specificity. In preeclampsia, there is a decrease of serum levels of placental growth factor (PlGF). Soluble receptor tyrosine kinase type 1 (sFlt-1) is an antagonist of PlGF. Increased levels of sFlt-1 in proportion to the reduced level of PlGF are associated with an increased risk of preeclampsia. The sFlt-1/PlGF ratio can be a better predictive marker in the diagnosis of pre-eclampsia after 20 weeks of gestation.

  11. Wavelet neural network modeling in QSPR for prediction of solubility of 25 anthraquinone dyes at different temperatures and pressures in supercritical carbon dioxide.

    Science.gov (United States)

    Tabaraki, R; Khayamian, T; Ensafi, A A

    2006-09-01

    A wavelet neural network (WNN) model in quantitative structure property relationship (QSPR) was developed for predicting solubility of 25 anthraquinone dyes in supercritical carbon dioxide over a wide range of pressures (70-770 bar) and temperatures (291-423 K). A large number of descriptors were calculated with Dragon software and a subset of calculated descriptors was selected from 18 classes of Dragon descriptors with a stepwise multiple linear regression (MLR) as a feature selection technique. Six calculated and two experimental descriptors, pressure and temperature, were selected as the most feasible descriptors. The selected descriptors were used as input nodes in a wavelet neural network (WNN) model. The wavelet neural network architecture and its parameters were optimized simultaneously. The data was randomly divided to the training, prediction and validation sets. The predictive ability of the model was evaluated using validation data set. The root mean squares error (RMSE) and mean absolute errors were 0.339 and 0.221, respectively, for the validation data set. The performance of the WNN model was also compared with artificial neural network (ANN) model and the results showed the superiority of the WNN over ANN model.

  12. Modeling how soluble microbial products (SMP) support heterotrophic bacteria in autotroph-based biofilms

    DEFF Research Database (Denmark)

    Merkey, Brian; Rittmann, Bruce E.; Chopp, David L.

    2009-01-01

    . In this paper, we develop and use a mathematical model to describe a model biofilm system that includes autotrophic and heterotrophic bacteria and the key products produced by the bacteria. The model combines the methods of earlier multi-species models with a multi-component biofilm model in order to explore...... the interaction between species via exchange of soluble microbial products (SMP). We show that multiple parameter sets are able to describe the findings of experimental studies, and that heterotrophs growing on autotrophically produced SMP may pursue either r- or K-strategies to sustain themselves when SMP...... is their only substrate. We also show that heterotrophs can colonize some distance from the autotrophs and still be sustained by autotrophically produced SMP. This work defines the feasible range of parameters for utilization of SMP by heterotrophs and the nature of the interactions between autotrophs...

  13. Water-soluble thin film transistors and circuits based on amorphous indium-gallium-zinc oxide.

    Science.gov (United States)

    Jin, Sung Hun; Kang, Seung-Kyun; Cho, In-Tak; Han, Sang Youn; Chung, Ha Uk; Lee, Dong Joon; Shin, Jongmin; Baek, Geun Woo; Kim, Tae-il; Lee, Jong-Ho; Rogers, John A

    2015-04-22

    This paper presents device designs, circuit demonstrations, and dissolution kinetics for amorphous indium-gallium-zinc oxide (a-IGZO) thin film transistors (TFTs) comprised completely of water-soluble materials, including SiNx, SiOx, molybdenum, and poly(vinyl alcohol) (PVA). Collections of these types of physically transient a-IGZO TFTs and 5-stage ring oscillators (ROs), constructed with them, show field effect mobilities (∼10 cm2/Vs), on/off ratios (∼2×10(6)), subthreshold slopes (∼220 mV/dec), Ohmic contact properties, and oscillation frequency of 5.67 kHz at supply voltages of 19 V, all comparable to otherwise similar devices constructed in conventional ways with standard, nontransient materials. Studies of dissolution kinetics for a-IGZO films in deionized water, bovine serum, and phosphate buffer saline solution provide data of relevance for the potential use of these materials and this technology in temporary biomedical implants.

  14. Solubility of flue gas components in NaOH based scrubber solutions

    Energy Technology Data Exchange (ETDEWEB)

    Sandelin, K; Backman, R

    1997-11-01

    The work reported here is a thermodynamic study on the solubility of flue gas components in aqueous solutions containing sodium salts. The result of the work is an equilibrium model. The model presented here includes sodium hydroxide and sodium salts that makes it possible to study simultaneous absorption of flue gas components in alkaline scrubber solutions. The model is applied on the absorption of a flue gas into a NaOH scrubber solution. The calculations show that it is possible to simultaneously absorb sulfur dioxide, sulfuric acid, and ammonia without carbon dioxide co-absorption. The calculations also show that gaseous NO and N{sub 2}O cannot be scrubbed unless they are oxidized to nitrate or reduced to ammonia. (author) SIHTI 2 Research Programme. 59 refs.

  15. Evaluation of chitosan–anionic polymers based tablets for extended-release of highly water-soluble drugs

    Directory of Open Access Journals (Sweden)

    Yang Shao

    2015-02-01

    Full Text Available The objective of this study is to develop chitosan–anionic polymers based extended-release tablets and test the feasibility of using this system for the sustained release of highly water-soluble drugs with high drug loading. Here, the combination of sodium valproate (VPS and valproic acid (VPA were chosen as the model drugs. Anionic polymers studied include xanthan gum (XG, carrageenan (CG, sodium carboxymethyl cellulose (CMC-Na and sodium alginate (SA. The tablets were prepared by wet granulation method. In vitro drug release was carried out under simulated gastrointestinal condition. Drug release mechanism was studied. Compared with single polymers, chitosan–anionic polymers based system caused a further slowdown of drug release rate. Among them, CS–xanthan gum matrix system exhibited the best extended-release behavior and could extend drug release for up to 24 h. Differential scanning calorimetry (DSC and Fourier transform infrared spectroscopy (FTIR studies demonstrated that polyelectrolyte complexes (PECs were formed on the tablet surface, which played an important role on retarding erosion and swelling of the matrix in the later stage. In conclusion, this study demonstrated that it is possible to develop highly water-soluble drugs loaded extended-release tablets using chitosan–anionic polymers based system.

  16. TWT transmitter fault prediction based on ANFIS

    Science.gov (United States)

    Li, Mengyan; Li, Junshan; Li, Shuangshuang; Wang, Wenqing; Li, Fen

    2017-11-01

    Fault prediction is an important component of health management, and plays an important role in the reliability guarantee of complex electronic equipments. Transmitter is a unit with high failure rate. The cathode performance of TWT is a common fault of transmitter. In this dissertation, a model based on a set of key parameters of TWT is proposed. By choosing proper parameters and applying adaptive neural network training model, this method, combined with analytic hierarchy process (AHP), has a certain reference value for the overall health judgment of TWT transmitters.

  17. Solubility-pH profiles of a free base and its salt: sibutramine as a case study

    Directory of Open Access Journals (Sweden)

    Diego Lucero-Borja

    2017-12-01

    Full Text Available In the present study the solubility-pH profiles of sibutramine free base and its hydrochloride salt were determined in the pH range between 2.0 and 9.5 by means of the recommended shake-flask method, and the solids collected were dried and studied by X-ray diffraction in order to elucidate their free base or salt structure. Above pHmax (or Gibbs pKa the solid collected was always identified as free base, whatever the sibutramine species (free base or hydrochloride salt initially solved. However, in the pH range below pHmax different solids were isolated depending on the buffers employed.

  18. Enzymatic production of dietary nucleotides from low-soluble purine bases by an efficient, thermostable and alkali-tolerant biocatalyst.

    Science.gov (United States)

    Del Arco, J; Cejudo-Sanches, J; Esteban, I; Clemente-Suárez, V J; Hormigo, D; Perona, A; Fernández-Lucas, J

    2017-12-15

    Traditionally, enzymatic synthesis of nucleoside-5'-monophosphates (5'-NMPs) using low water-soluble purine bases has been described as less efficient due to their low solubility in aqueous media. The use of enzymes from extremophiles, such as thermophiles or alkaliphiles, offers the potential to increase solubilisation of these bases by employing high temperatures or alkaline pH. This study describes the cloning, expression and purification of hypoxanthine-guanine-xanthine phosphoribosyltransferase from Thermus thermophilus (TtHGXPRT). Biochemical characterization indicates TtHGXPRT as a homotetramer with excellent activity and stability across a broad range of temperatures (50-90°C) and ionic strengths (0-500mMNaCl), but it also reveals an unusually high activity and stability under alkaline conditions (pH range 8-11). In order to explore the potential of TtHGXPRT as an industrial biocatalyst, enzymatic production of several dietary 5'-NMPs, such as 5'-GMP and 5'-IMP, was carried out at high concentrations of guanine and hypoxanthine. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. A thermodynamic data base for Tc to calculate equilibrium solubilities at temperatures up to 300 deg C

    International Nuclear Information System (INIS)

    Puigdomenech, I.; Bruno, J.

    1995-04-01

    Thermodynamic data has been selected for solids and aqueous species of technetium. Equilibrium constants have been calculated in the temperature range 0 to 300 deg C at a pressure of 1 bar for T r Cdeg pm values for mononuclear hydrolysis reactions. The formation constants for chloro complexes of Tc(V) and Tc(IV), whose existence is well established, have been estimated. The majority of entropy and heat capacity values in the data base have also been estimated, and therefore temperature extrapolations are largely based on estimations. The uncertainties derived from these calculations are described. Using the data base developed in this work, technetium solubilities have been calculated as a function of temperature for different chemical conditions. The implications for the mobility of Tc under nuclear repository conditions are discussed. 70 refs

  20. Seasonal changes in Fe species and soluble Fe concentration in the atmosphere in the Northwest Pacific region based on the analysis of aerosols collected in Tsukuba, Japan

    Directory of Open Access Journals (Sweden)

    Y. Takahashi

    2013-08-01

    mineral dust concentrations during spring in East Asia. However, this factor does not contribute to the amount of soluble Fe to a larger degree than the effect of Fe speciation, or more strictly speaking the presence of Fe(III sulfate. Therefore, based on these results, the most significant factor influencing the amount of soluble Fe in the North Pacific region is the concentration of anthropogenic Fe species such as Fe(III sulfate that can be emitted from megacities in Eastern Asia.

  1. A framework for API solubility modelling

    DEFF Research Database (Denmark)

    Conte, Elisa; Gani, Rafiqul; Crafts, Peter

    . In addition, most of the models are not predictive and requires experimental data for the calculation of the needed parameters. This work aims at developing an efficient framework for the solubility modelling of Active Pharmaceutical Ingredients (API) in water and organic solvents. With this framework......-SAFT) are used for solubility calculations when the needed interaction parameters or experimental data are available. The CI-UNIFAC is instead used when the previous models lack interaction parameters or when solubility data are not available. A new GC+ model for APIs solvent selection based...... on the hydrophobicity, hydrophilicity and polarity information of the API and solvent is also developed, for performing fast solvent selection and screening. Eventually, all the previous developments are integrated in a framework for their efficient and integrated use. Two case studies are presented: the first...

  2. Structure-Based Optimization of Arylamides as Inhibitors of Soluble Epoxide Hydrolase

    Energy Technology Data Exchange (ETDEWEB)

    Eldrup, Anne B.; Soleymanzadeh, Fariba; Taylor, Steven J.; Muegge, Ingo; Farrow, Neil A.; Joseph, David; McKellop, Keith; Man, Chuk C.; Kukulka, Alison; De Lombaert, Stephane; (Boehringer)

    2009-11-04

    Inhibition of soluble epoxide hydrolase (sEH) is hypothesized to lead to an increase in circulating levels of epoxyeicosatrienoic acids, resulting in the potentiation of their in vivo pharmacological properties. As part of an effort to identify inhibitors of sEH with high and sustained plasma exposure, we recently performed a high throughput screen of our compound collection. The screen identified N-(3,3-diphenyl-propyl)-nicotinamide as a potent inhibitor of sEH. Further profiling of this lead revealed short metabolic half-lives in microsomes and rapid clearance in the rat. Consistent with these observations, the determination of the in vitro metabolic profile of N-(3,3-diphenyl-propyl)-nicotinamide in rat liver microsomes revealed extensive oxidative metabolism and a propensity for metabolite switching. Lead optimization, guided by the analysis of the solid-state costructure of N-(3,3-diphenyl-propyl)-nicotinamide bound to human sEH, led to the identification of a class of potent and selective inhibitors. An inhibitor from this class displayed an attractive in vitro metabolic profile and high and sustained plasma exposure in the rat after oral administration.

  3. Supramolecular Host-Guest System as Ratiometric Fe3+ Ion Sensor Based on Water-Soluble Pillar[5]arene.

    Science.gov (United States)

    Yao, Qianfang; Lü, Baozhong; Ji, Chendong; Cai, Yang; Yin, Meizhen

    2017-10-18

    Developing a specific, ratiometric, and reversible detection method for metal ions is significant to guard against the threat of metal-caused environmental pollution and organisms poisoning. Here a supramolecular host-guest system (WP5⊃G) based on water-soluble pillar[5]arene (WP5) and water-soluble quaternized perylene diimide derivative (G) was constructed. Morphological transformation was achieved during the process of adding WP5 into G aqueous solution, and a fluorescence "turn-off" phenomenon was observed which was caused by supramolecular photoinduced electron transfer (PET). Meanwhile, hydrophobic effect and electrostatic interaction played important roles in this supramolecular process, which was confirmed by isothermal titration calorimeter (ITC) and ζ potential experiments. Furthermore, the supramolecular host-guest system could be a "turn-on" fluorescent probe for Fe 3+ ion detection through the process of interdicting supramolecular PET. Moreover, the Fe 3+ ion detection showed specific, ratiometric, and reversible performances with a detection limit of 2.13 × 10 -7 M, which might have great potentials in biological and environmental monitoring.

  4. Fluorescent water-Soluble Probes Based on Ammonium Cation Peg Substituted Perylenepisimides: Synthesis, Photophysical Properties, and Live Cell Images

    Science.gov (United States)

    Yang, Wei; Cai, Jiaxuan; Zhang, Shuchen; Yi, Xuegang; Gao, Baoxiang

    2018-01-01

    To synthesize perylenbisimides (PBI) fluorescent probes that will improve the water-soluble ability and the cytocompatibility, the synthesis and properties of fluorescent water-soluble probes based on dendritic ammonium cation polyethylene glycol (PEG) substituted perylenebisimides(GPDIs) are presented. As we expected, with increased ammonium cation PEG, the aggregation of the PBI in an aqueous solution is completely suppressed by the hydrophilic ammonium cation PEG groups. And the fluorescence quantum yield increases from 25% for GPDI-1 to 62% for GPDI-2. When incubated with Hela cells for 48 h, the viabilities are 71% (for GPDI-1) and 76% (for GPDI-2). Live cell imaging shows that these probes are efficiently internalized by HeLa cells. The study of the photophysical properties indicated increasing the ammonium cation PEG generation can increase the fluorescence quantum yield. Live cell imaging shows that with the ammonium cation PEG chains of perylenebisimides has high biocompatibility. The exceptionally low cytotoxicity is ascribed to the ammonium cation PEG chains, which protect the dyes from nonspecifically interacting with the extracellular proteins. Live cell imaging shows that ammonium cations PEG chains can promote the internalization of these probes.

  5. Autohydrolysis processing as an alternative to enhance cellulose solubility and preparation of its regenerated bio-based materials

    Energy Technology Data Exchange (ETDEWEB)

    Gan, Sinyee, E-mail: gansinyee@hotmail.com; Zakaria, Sarani, E-mail: szakaria@ukm.edu.my; Chen, Ruey Shan; Chia, Chin Hua; Padzil, Farah Nadia Mohammad; Moosavi, Seyedehmaryam

    2017-05-01

    Kenaf core pulp has been successfully autohydrolysed using an autoclave heated in oil bath at various reaction temperature at 100, 120 and 140 °C. Membranes, hydrogels and aerogels were then prepared from autohydrolysed kenaf in urea/alkaline medium by casting on the glass plate, by using epichlorohydrin (ECH) as cross-linker via stirring and freeze-drying method, respectively. The autohydrolysis process reduced the molecular weight of cellulose and enhanced cellulose solubility and viscosity. Structure and properties of the regenerated products were measured with Field emission scanning electron microscope (FESEM), X-ray diffraction (XRD), Ultraviolet–visible (UV–Vis) spectrophotometer and swelling testing. As the autohydrolysis temperature increased, the porosity of cellulose membranes (as seen from the morphology) increased. The autohydrolysis process improved the swelling porperties and transparency of regenerated cellulose hydrogels. This finding is expected to be useful in reducing molecular weight of cellulose in order to produce regenerated bio-based cellulose materials. - Highlights: • Autohydrolysis temperature is negatively correlated to cellulose molecular weight. • Cellulose solubility and viscosity are improved after cellulose pretreatment. • Autohydrolysis improved the properties of regenerated cellulose materials.

  6. Discovery of potent inhibitors of soluble epoxide hydrolase by combinatorial library design and structure-based virtual screening.

    Science.gov (United States)

    Xing, Li; McDonald, Joseph J; Kolodziej, Steve A; Kurumbail, Ravi G; Williams, Jennifer M; Warren, Chad J; O'Neal, Janet M; Skepner, Jill E; Roberds, Steven L

    2011-03-10

    Structure-based virtual screening was applied to design combinatorial libraries to discover novel and potent soluble epoxide hydrolase (sEH) inhibitors. X-ray crystal structures revealed unique interactions for a benzoxazole template in addition to the conserved hydrogen bonds with the catalytic machinery of sEH. By exploitation of the favorable binding elements, two iterations of library design based on amide coupling were employed, guided principally by the docking results of the enumerated virtual products. Biological screening of the libraries demonstrated as high as 90% hit rate, of which over two dozen compounds were single digit nanomolar sEH inhibitors by IC(50) determination. In total the library design and synthesis produced more than 300 submicromolar sEH inhibitors. In cellular systems consistent activities were demonstrated with biochemical measurements. The SAR understanding of the benzoxazole template provides valuable insights into discovery of novel sEH inhibitors as therapeutic agents.

  7. Based on BP Neural Network Stock Prediction

    Science.gov (United States)

    Liu, Xiangwei; Ma, Xin

    2012-01-01

    The stock market has a high profit and high risk features, on the stock market analysis and prediction research has been paid attention to by people. Stock price trend is a complex nonlinear function, so the price has certain predictability. This article mainly with improved BP neural network (BPNN) to set up the stock market prediction model, and…

  8. Pluronic-Functionalized Silica-Lipid Hybrid Microparticles: Improving the Oral Delivery of Poorly Water-Soluble Weak Bases.

    Science.gov (United States)

    Rao, Shasha; Richter, Katharina; Nguyen, Tri-Hung; Boyd, Ben J; Porter, Christopher J H; Tan, Angel; Prestidge, Clive A

    2015-12-07

    A Pluronic-functionalized silica-lipid hybrid (Plu-SLH) microparticle system for the oral delivery of poorly water-soluble, weak base drugs is reported for the first time. A highly effective Plu-SLH microparticle system was composed of Labrasol as the lipid phase, Pluronic F127 as the polymeric precipitation inhibitor (PPI), and silica nanoparticles as the solid carrier. For the model drug cinnarizine (CIN), the Plu-SLH delivery system was shown to offer significant biopharmaceutical advantages in comparison with unformulated drug and drug in the silica-lipid hybrid (SLH) system. In vitro two-phase dissolution studies illustrated significantly reduced pH provoked CIN precipitation and an 8- to 14-fold improvement in the extent of dissolution in intestinal conditions. In addition, under simulated intestinal digesting conditions, the Plu-SLH provided approximately three times more drug solubilization than the SLH. Oral administration in rats resulted in superior bioavailability for Plu-SLH microparticles, i.e., 1.6- and 2.1-fold greater than the SLH and the unformulated CIN, respectively. A physical mixture of Pluronic and SLH (Plu&SLH), having the same composition as Plu-SLH, was also evaluated, but showed no significant increase in CIN absorption when compared to unmodified CIN or SLH. This work represents the first study where different methods of incorporating PPI to formulate solid-state lipid-based formulations were compared for the impact on the biopharmaceutical performance. The data suggest that the novel physicochemical properties and structure of the fabricated Plu-SLH microparticle delivery system play an important role in facilitating the synergistic advantage of Labrasol and Pluronic F127 in preventing drug precipitation, and the Plu-SLH provides efficient oral delivery of poorly water-soluble weak bases.

  9. Combined Effects of Supersaturation Rates and Doses on the Kinetic-Solubility Profiles of Amorphous Solid Dispersions Based on Water-Insoluble Poly(2-hydroxyethyl methacrylate) Hydrogels.

    Science.gov (United States)

    Schver, Giovanna C R M; Lee, Ping I

    2018-05-07

    Under nonsink dissolution conditions, the kinetic-solubility profiles of amorphous solid dispersions (ASDs) based on soluble carriers typically exhibit so-called "spring-and-parachute" concentration-time behaviors. However, the kinetic-solubility profiles of ASDs based on insoluble carriers (including hydrogels) are known to show sustained supersaturation during nonsink dissolution through a matrix-regulated diffusion mechanism by which the supersaturation of the drug is built up gradually and sustained over an extended period without any dissolved polymers acting as crystallization inhibitors. Despite previous findings demonstrating the interplay between supersaturation rates and total doses on the kinetic-solubility profiles of soluble amorphous systems (including ASDs based on dissolution-regulated releases from soluble polymer carriers), the combined effects of supersaturation rates and doses on the kinetic-solubility profiles of ASDs based on diffusion-regulated releases from water-insoluble carriers have not been investigated previously. Thus, the objective of this study is to examine the impacts of total doses and supersaturation-generation rates on the resulting kinetic-solubility profiles of ASDs based on insoluble hydrogel carriers. We employed a previously established ASD-carrier system based on water-insoluble-cross-linked-poly(2-hydroxyethyl methacrylate) (PHEMA)-hydrogel beads and two poorly water soluble model drugs: the weakly acidic indomethacin (IND) and the weakly basic posaconazole (PCZ). Our results show clearly for the first time that by using the smallest-particle-size fraction and a high dose (i.e., above the critical dose), it is indeed possible to significantly shorten the duration of sustained supersaturation in the kinetic-solubility profile of an ASD based on a water-insoluble hydrogel carrier, such that it resembles the spring-and-parachute dissolution profiles normally associated with ASDs based on soluble carriers. This generates

  10. Synthesis and optical properties of water-soluble biperylene-based dendrimers.

    Science.gov (United States)

    Shao, Pin; Jia, Ningyang; Zhang, Shaojuan; Bai, Mingfeng

    2014-05-30

    We report the synthesis and photophysical properties of three biperylene-based dendrimers, which show red fluorescence in water. A fluorescence microscopy study demonstrated uptake of biperylene-based dendrimers in living cells. Our results indicate that these biperylene-based dendrimers are promising candidates in fluorescence imaging applications with the potential as therapeutic carriers.

  11. Nitroolefin-based BODIPY as a novel water-soluble ratiometric fluorescent probe for detection of endogenous thiols

    Science.gov (United States)

    Kang, Jin; Huo, Fangjun; Chao, Jianbin; Yin, Caixia

    2018-04-01

    Small molecule biothiols, including cysteine (Cys), homocysteine (Hcy), and glutathione (GSH), play many crucial roles in physiological processes. In this work, we have prepared a nitroolefin-based BODIPY fluorescent probe with excellent water solubility for detection thiols, which displayed ratiometric fluorescent signal for thiols. Incorporation of a nitroolefin unit to the BODIPY dye would transform it into a strong Michael acceptor, which would be highly susceptible to sulfhydryl nucleophiles. This probe shows an obvious ratio change upon response with thiols, an increase of the emission at 517 nm along with a concomitant decrease of fluorescence peak at 573 nm. Moreover, these successes of intracellular imaging experiments in A549 cells indicated that this probe is suitable for imaging of ex-/endogenous thiols in living cells.

  12. Circulating ghrelin, leptin, and soluble leptin receptor concentrations and cardiometabolic risk factors in a community-based sample.

    Science.gov (United States)

    Ingelsson, Erik; Larson, Martin G; Yin, Xiaoyan; Wang, Thomas J; Meigs, James B; Lipinska, Izabella; Benjamin, Emelia J; Keaney, John F; Vasan, Ramachandran S

    2008-08-01

    The conjoint effects and relative importance of ghrelin, leptin, and soluble leptin receptor (sOB-R), adipokines involved in appetite control and energy expenditure in mediating cardiometabolic risk, is unknown. The objective of the study was to study the cross-sectional relations of these adipokines to cardiometabolic risk factors in a community-based sample. We measured circulating ghrelin, leptin, and sOB-R in 362 participants (mean age 45 yr; 54% women) of the Framingham Third Generation Cohort. Body mass index, waist circumference (WC), blood pressure, lipid measures, fasting glucose, smoking, and metabolic syndrome (MetS) were measured. Ghrelin and leptin concentrations were significantly higher in women (P risk.

  13. The Solubility Parameters of Ionic Liquids

    Science.gov (United States)

    Marciniak, Andrzej

    2010-01-01

    The Hildebrand’s solubility parameters have been calculated for 18 ionic liquids from the inverse gas chromatography measurements of the activity coefficients at infinite dilution. Retention data were used for the calculation. The solubility parameters are helpful for the prediction of the solubility in the binary solvent mixtures. From the solubility parameters, the standard enthalpies of vaporization of ionic liquids were estimated. PMID:20559495

  14. The Solubility Parameters of Ionic Liquids

    Directory of Open Access Journals (Sweden)

    Andrzej Marciniak

    2010-04-01

    Full Text Available The Hildebrand’s solubility parameters have been calculated for 18 ionic liquids from the inverse gas chromatography measurements of the activity coefficients at infinite dilution. Retention data were used for the calculation. The solubility parameters are helpful for the prediction of the solubility in the binary solvent mixtures. From the solubility parameters, the standard enthalpies of vaporization of ionic liquids were estimated.

  15. Solubility of Carbon in Nanocrystalline -Iron

    OpenAIRE

    Alexander Kirchner; Bernd Kieback

    2012-01-01

    A thermodynamic model for nanocrystalline interstitial alloys is presented. The equilibrium solid solubility of carbon in -iron is calculated for given grain size. Inside the strained nanograins local variation of the carbon content is predicted. Due to the nonlinear relation between strain and solubility, the averaged solubility in the grain interior increases with decreasing grain size. The majority of the global solubility enhancement is due to grain boundary enrichment however. Therefor...

  16. DMol3/COSMO-RS prediction of aqueous solubility and reactivity of selected Azo dyes: Effect of global orbital cut-off and COSMO segment variation

    CSIR Research Space (South Africa)

    Wahab, OO

    2018-01-01

    Full Text Available Aqueous solubility and reactivity of four azo dyes were investigated by DMol3/COSMO-RS calculation to examine the effects of global orbital cut-off and COSMO segment variation on the accuracies of theoretical solubility and reactivity. The studied...

  17. Diagnostic accuracy of soluble urokinase plasminogen activator receptor (suPAR) for prediction of bacteremia in patients with systemic inflammatory response syndrome.

    Science.gov (United States)

    Hoenigl, Martin; Raggam, Reinhard B; Wagner, Jasmin; Valentin, Thomas; Leitner, Eva; Seeber, Katharina; Zollner-Schwetz, Ines; Krammer, Werner; Prüller, Florian; Grisold, Andrea J; Krause, Robert

    2013-02-01

    Soluble urokinase plasminogen activator receptor (suPAR) serum concentrations have recently been described to reflect the severity status of systemic inflammation. In this study, the diagnostic accuracy of suPAR, C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6) to predict bacteremia in patients with systemic inflammatory response syndrome (SIRS) was compared. A total of 132 patients with SIRS were included. In 55 patients blood cultures had resulted positive (study group 1, Gram positive bacteria: Staphylococcus aureus and Streptococcus spp., n=15; study group 2, Gram-negative bacteria, n=40) and 77 patients had negative blood culture results (control group, n=77). Simultaneously with blood cultures suPAR, CRP, PCT, IL-6 and white blood count (WBC) were determined. SuPAR values were significantly higher in study group 1 (median 8.11; IQR 5.78-15.53; p=0.006) and study group 2 (median 9.62; IQR 6.52-11.74; p<0.001) when compared with the control group (median 5.65; IQR 4.30-7.83). ROC curve analysis revealed an AUC of 0.726 for suPAR in differentiating SIRS patients with bacteremia from those without. The biomarkers PCT and IL-6 showed comparable results. Regarding combinations of biomarkers multiplying suPAR, PCT and IL-6 was most promising and resulted in an AUC value of 0.804. Initial suPAR serum concentrations were significantly higher (p=0.028) in patients who died within 28 days than in those who survived. No significant difference was seen for PCT, IL-6 and CRP. In conclusion, suPAR, IL-6 and PCT may contribute to predicting bacteremia in SIRS patients. Copyright © 2012 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  18. Prediction of mortality based on facial characteristics

    Directory of Open Access Journals (Sweden)

    Arnaud Delorme

    2016-05-01

    Full Text Available Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person’s photograph. To test this claim, we invited 12 such individuals to see if they could determine if a person was alive or dead based solely on a brief examination of facial photographs. All photos used in the experiment were transformed into a uniform gray scale and then counterbalanced across eight categories: gender, age, gaze direction, glasses, head position, smile, hair color, and image resolution. Participants examined 404 photographs displayed on a computer monitor, one photo at a time, each shown for a maximum of 8 seconds. Half of the individuals in the photos were deceased, and half were alive at the time the experiment was conducted. Participants were asked to press a button if they thought the person in a photo was living or deceased. Overall mean accuracy on this task was 53.8%, where 50% was expected by chance (p < 0.004, two-tail. Statistically significant accuracy was independently obtained in 5 of the 12 participants. We also collected 32-channel electrophysiological recordings and observed a robust difference between images of deceased individuals correctly vs. incorrectly classified in the early event related potential at 100 ms post-stimulus onset. Our results support claims of individuals who report that some as-yet unknown features of the face predict mortality. The results are also compatible with claims about clairvoyance and warrants further investigation.

  19. Extending Theory-Based Quantitative Predictions to New Health Behaviors.

    Science.gov (United States)

    Brick, Leslie Ann D; Velicer, Wayne F; Redding, Colleen A; Rossi, Joseph S; Prochaska, James O

    2016-04-01

    Traditional null hypothesis significance testing suffers many limitations and is poorly adapted to theory testing. A proposed alternative approach, called Testing Theory-based Quantitative Predictions, uses effect size estimates and confidence intervals to directly test predictions based on theory. This paper replicates findings from previous smoking studies and extends the approach to diet and sun protection behaviors using baseline data from a Transtheoretical Model behavioral intervention (N = 5407). Effect size predictions were developed using two methods: (1) applying refined effect size estimates from previous smoking research or (2) using predictions developed by an expert panel. Thirteen of 15 predictions were confirmed for smoking. For diet, 7 of 14 predictions were confirmed using smoking predictions and 6 of 16 using expert panel predictions. For sun protection, 3 of 11 predictions were confirmed using smoking predictions and 5 of 19 using expert panel predictions. Expert panel predictions and smoking-based predictions poorly predicted effect sizes for diet and sun protection constructs. Future studies should aim to use previous empirical data to generate predictions whenever possible. The best results occur when there have been several iterations of predictions for a behavior, such as with smoking, demonstrating that expected values begin to converge on the population effect size. Overall, the study supports necessity in strengthening and revising theory with empirical data.

  20. Optimization of two methods based on ultrasound energy as alternative to European standards for soluble salts extraction from building materials.

    Science.gov (United States)

    Prieto-Taboada, N; Gómez-Laserna, O; Martinez-Arkarazo, I; Olazabal, M A; Madariaga, J M

    2012-11-01

    The Italian recommendation NORMAL 13/83, later replaced by the UNI 11087/2003 norm, were used as standard for soluble salts extraction from construction materials. These standards are based on long-time stirring (72 and 2h, respectively) of the sample in deionized water. In this work two ultrasound based methods were optimized in order to reduce the extraction time while efficiency is improved. The instrumental variables involved in the extraction assisted by ultrasound bath and focused ultrasounds were optimized by experimental design. As long as it was possible, the same non-instrumental parameters values as those of standard methods were used in order to compare the results obtained on a mortar sample showing a black crust by the standards and the optimized methods. The optimal extraction time for the ultrasounds bath was found to be of two hours. Although the extraction time was equal to the standard UNI 11087/2003, the obtained extraction recovery was improved up to 119%. The focused ultrasound system achieved also better recoveries (up to 106%) depending on the analyte in 1h treatment time. The repeatabilities of the proposed ultrasound based methods were comparables to those of the standards. Therefore, the selection of one or the other of the ultrasound based methods will depend on topics such as laboratory facilities or number of samples, and not in aspects related with their quality parameters. Copyright © 2012 Elsevier B.V. All rights reserved.

  1. A thermodynamic data base for Tc to calculate equilibrium solubilities at temperatures up to 300 deg C

    Energy Technology Data Exchange (ETDEWEB)

    Puigdomenech, I [Studsvik AB, Nykoeping (Sweden); Bruno, J [Intera Information Technologies SL, Cerdanyola (Spain)

    1995-04-01

    Thermodynamic data has been selected for solids and aqueous species of technetium. Equilibrium constants have been calculated in the temperature range 0 to 300 deg C at a pressure of 1 bar for T<100 deg C and at the steam saturated pressure at higher temperatures. For aqueous species, the revised Helgeson-Kirkham-Flowers model is used for temperature extrapolations. The data base contains a large amount of estimated data, and the methods used for these estimations are described in detail. A new equation is presented that allows the estimation of {Delta}{sub r}Cdeg{sub pm} values for mononuclear hydrolysis reactions. The formation constants for chloro complexes of Tc(V) and Tc(IV), whose existence is well established, have been estimated. The majority of entropy and heat capacity values in the data base have also been estimated, and therefore temperature extrapolations are largely based on estimations. The uncertainties derived from these calculations are described. Using the data base developed in this work, technetium solubilities have been calculated as a function of temperature for different chemical conditions. The implications for the mobility of Tc under nuclear repository conditions are discussed. 70 refs.

  2. In vitro solubility of calcium, iron and zinc in relation to phytic acid levels in rice-based consumer products in China.

    Science.gov (United States)

    Liang, Jianfen; Han, Bei-Zhong; Nout, M J Robert; Hamer, Robert J

    2010-02-01

    In vitro solubility of calcium, iron and zinc in relation to phytic acid (PA) levels in 30 commercial rice-based foods from China was studied. Solubility of minerals and molar ratios of PA to minerals varied with degrees of processing. In primary products, [PA]/[Ca] values were less than 5 and [PA]/[Fe] and [PA]/[Zn] similarly ranged between 5 and 74, with most values between 20 and 30. [PA]/[mineral] molar ratios in intensively processed products were lower. Solubility of calcium ranged from 0% to 87%, with the lowest in brown rice (12%) and the highest in infant foods (50%). Iron solubility in two-thirds of samples was lower than 30%, and that of zinc narrowly ranged from 6% to 30%. Solubility of minerals was not significantly affected by [PA]/[mineral]. At present, neither primary nor intensively processed rice-based products are good dietary sources of minerals. Improvements should be attempted by dephytinization, mineral fortification or, preferably, combination of both.

  3. Protein structure based prediction of catalytic residues.

    Science.gov (United States)

    Fajardo, J Eduardo; Fiser, Andras

    2013-02-22

    Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific reference databases.

  4. Water soluble chromone Schiff base derivatives as fluorescence receptor for aluminium(III)

    Czech Academy of Sciences Publication Activity Database

    Jakubek, M.; Kejík, Z.; Parchaňský, Václav; Kaplánek, R.; Vasina, L.; Martásek, P.; Král, V.

    2017-01-01

    Roč. 29, č. 1 (2017), s. 1-7 ISSN 1061-0278 R&D Projects: GA TA ČR(CZ) TE01020028 Institutional support: RVO:61388963 Keywords : aluminium sensing * chelator * chromone * fluorescence * Schiff base Subject RIV: CF - Physical ; Theoretical Chemistry OBOR OECD: Physical chemistry Impact factor: 1.264, year: 2016

  5. Solubility of Oxygen in Liquid Sodium and the Interpretation of Predictions for the Corrosion Rate of Stainless Steels in Liquid Sodium

    International Nuclear Information System (INIS)

    Claxton, K. T.

    1979-01-01

    A statistical analysis of all oxygen in sodium solubility data has been made. The results indicate a real difference. between levels of oxygen reported by UK und US workers. Analysis using sub-sets of culled data to derive a compromise solubility function are considered less than adequate. It is considered preferable and more realistic to distinguish data sub-sets by the analytical technique employed. The vacuum distillation method yields results differing amongst them selves by up to a factor of five at cold trap temperatures of relevance to fast reactor operation. The vanadium wire and electrochemical cell techniques give the lowest solubility values. (Author) 51 refs

  6. Anodic solubility and electrochemical machining of hard alloys on the base of chromium and titanium carbides

    Energy Technology Data Exchange (ETDEWEB)

    Davydov, A D; Klepikov, A N; Malofeeva, A N; Moroz, I I

    1985-01-01

    The regularities of anodic behaviour and electrochemical machining (ECM) of the samples of three materials with the following compositions: 25% of Cr/sub 3/C/sub 2/, 15% of Ni, 70% of TiC, 25% of Ni, 5% of Cr, 70% of TiC, 15% of Ni, 15% of Mo are investigated. It is shown that the electrochemical method is applicable to hard alloys machining on the base of chromium and titanium carbides, the machining of which mechanically meets serious difficulties. The alloys machining rate by a mobile cathode constitutes about 0.5 mm/min.

  7. Validation of photodynamic action via photobleaching of a new curcumin-based composite with enhanced water solubility.

    Science.gov (United States)

    Rego-Filho, Francisco G; de Araujo, Maria T; de Oliveira, Kleber T; Bagnato, Vanderlei S

    2014-09-01

    Motivated by the photochemical and photophysical properties of curcumin-based composites, the characteristics of a new curcumin-based water-soluble salt were investigated via absorption and fluorescence spectroscopy. Photobleaching was investigated using a set of LEDs in three different wavelengths (405 nm, 450 nm and 470 nm) to illuminate an aqueous solution of curcumin, evaluating its degradation for five different exposure times (0, 5, 15, 45 and 105 minutes). The results were compared with equivalent measurements of dark degradation and illumination in the presence of a singlet-oxygen quencher. Three solution concentrations (50, 100 and 150 μg/ml) were studied. To measure the fluorescence, it was used low power 405 nm excitation laser source. Time dependent photodegradation of curcumin was observed, as compared to the natural degradation of samples maintained on a dark environment. Two main absorption peaks were detected and their relation responded to both concentration and wavelength of the illumination source. A spectral correlation between absorption of curcumin and the emission bands of the sources showed an optimal spectral overlap for the 450 nm LED. For this source, photobleaching showed a less intense degradation on the presence of singlet oxygen quencher. This last result confirmed singlet oxygen production in vitro, indicating a strong potential of this composite to be used as a blue-light-activated photosensitizer.

  8. The Precipitation Behavior of Poorly Water-Soluble Drugs with an Emphasis on the Digestion of Lipid Based Formulations.

    Science.gov (United States)

    Khan, Jamal; Rades, Thomas; Boyd, Ben

    2016-03-01

    An increasing number of newly discovered drugs are poorly water-soluble and the use of natural and synthetic lipids to improve the oral bioavailability of these drugs by utilizing the digestion pathway in-vivo has proved an effective formulation strategy. The mechanisms responsible for lipid digestion and drug solubilisation during gastrointestinal transit have been explored in detail, but the implications of drug precipitation beyond the potential adverse effect on bioavailability have received attention only in recent years. Specifically, these implications are that different solid forms of drug on precipitation may affect the total amount of drug absorbed in-vivo through their different physico-chemical properties, and the possibility that the dynamic environment of the small intestine may afford re-dissolution of precipitated drug if present in a high-energy form. This review describes the events that lead to drug precipitation during the dispersion and digestion of lipid based formulations, common methods used to inhibit precipitation, as well as conventional and newly emerging characterization techniques for studying the solid state form of the precipitated drug. Moreover, selected case studies are discussed where drug precipitation has ensued from the digestion of lipid based formulations, as well as the apparent link between drug ionisability and altered solid forms on precipitation, culminating in a discussion about the importance of the solid form on precipitation with relevance to the total drug absorbed.

  9. Supramolecular Drug Delivery Systems Based on Water-Soluble Pillar[n]arenes.

    Science.gov (United States)

    Wu, Xuan; Gao, Lei; Hu, Xiao-Yu; Wang, Leyong

    2016-06-01

    Supramolecular drug delivery systems (SDDSs), including various kinds of nanostructures that are assembled by reversible noncovalent interactions, have attracted considerable attention as ideal drug carriers owing to their fascinating ability to undergo dynamic switching of structure, morphology, and function in response to various external stimuli, which provides a flexible and robust platform for designing and developing functional and smart supramolecular nano-drug carriers. Pillar[n]arenes represent a new generation of macrocyclic hosts, which have unique structures and excellent properties in host-guest chemistry. This account describes recent progress in our group to develop pillararene-based stimuli-responsive supramolecular nanostructures constructed by reversible host-guest interactions for controllable anticancer drug delivery. The potential applications of these supramolecular drug carriers in cancer treatment and the fundamental questions facing SDDSs are also discussed. © 2016 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Prediction-based dynamic load-sharing heuristics

    Science.gov (United States)

    Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.

    1993-01-01

    The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.

  11. Molecular model for solubility of gases in flexible polymers

    DEFF Research Database (Denmark)

    Neergaard, Jesper; Hassager, Ole; Szabo, Peter

    1999-01-01

    We propose a model for a priori prediction of the solubility of gases in flexible polymers. The model is based on the concept of ideal solubility of gases in liquids. According to this concept, the mole fraction of gases in liquids is given by Raoult's law with the total pressure and the vapor...... pressure of the gas, where the latter may have to be extrapolated. However, instead of considering each polymer molecule as a rigid structure, we estimate the effective number of degrees of freedom from an equivalent freely jointed bead-rod model for the flexible polymer. In this model, we associate...... the length of the rods with the molecular weight corresponding to a Kuhn step. The model provides a tool for crude estimation of the gas solubility on the basis of only the monomer unit of the polymer and properties of the gas. A comparison with the solubility data for several gases in poly...

  12. Use of two-phase aqueous systems based on water-soluble polymers in thin-layer and extraction chromatography for recovery and separtion of actinides

    International Nuclear Information System (INIS)

    Molochnikova, N.P.; Shkinev, V.M.; Myasoedov, B.F.

    1995-01-01

    The feasibility has been demonstrated of using two-phase aqueous systems based on water-soluble polymers, polyethylene glycol and dextran sulfate, in thin-layer and extraction chromatography for recovery and separation of actinides. A convenient method has been proposed for continuous recovery of 239 Np from 243 Am, originating from differences in sorption of tri- and pentavalent actinides from sulfate solutions containing potassium phosphotungstate by silica gel impregnated with polyethylene glycol. New plates for thin-layer chromatography using water-soluble polymers have been developed. These plates were used to study behavior of americium in various oxidation states in thin sorbent layers

  13. Medical expert system for assessment of coronary heart disease destabilization based on the analysis of the level of soluble vascular adhesion molecules

    Science.gov (United States)

    Serkova, Valentina K.; Pavlov, Sergey V.; Romanava, Valentina A.; Monastyrskiy, Yuriy I.; Ziepko, Sergey M.; Kuzminova, Nanaliya V.; Wójcik, Waldemar; DzierŻak, RóŻa; Kalizhanova, Aliya; Kashaganova, Gulzhan

    2017-08-01

    Theoretical and practical substantiation of the possibility of the using the level of soluble vascular adhesion molecules (sVCAM) is performed. Expert system for the assessment of coronary heart disease (CHD) destabilization on the base of the analysis of soluble vascular adhesion molecules level is developed. Correlation between the increase of VCAM level and C-reactive protein (CRP) in patients with different variants of CHD progression is established. Association of chronic nonspecific vascular inflammation activation and CHD destabilization is shown. The expedience of parallel determination of sVCAM and CRP levels for diagnostics of CHD destabilization and forecast elaboration is noted.

  14. SITE-94. Radionuclide solubilities for SITE-94

    Energy Technology Data Exchange (ETDEWEB)

    Arthur, R.; Apted, M. [QuantiSci, Denver, CO (United States)

    1996-12-01

    In this report, solubility constraints are evaluated on radioelement source-term concentrations supporting the SITE-94 performance assessment. Solubility models are based on heterogeneous-equilibrium, mass- and charge-balance constraints incorporated into the EQ3/6 geochemical software package, which is used to calculate the aqueous speciation behavior and solubilities of U, Th, Pu, Np, Am, Ni, Ra, Se, Sn, Sr, Tc and Zr in site groundwaters and near-field solutions. The chemical evolution of the near field is approximated using EQ3/6 in terms of limiting conditions at equilibrium, or steady state, in three closed systems representing fully saturated bentonite, Fe{sup o} corrosion products of the canister, and spent fuel. The calculations consider both low-temperature (15 deg C) and high-temperature (80 deg C) conditions in the near field, and the existence of either reducing or strongly oxidizing conditions in each of the bentonite, canister, and spent-fuel barriers. Heterogeneities in site characteristics are evaluated through consideration of a range of initial groundwaters and their interactions with engineered barriers. Aqueous speciation models for many radioelements are constrained by thermodynamic data that are estimated with varying degrees of accuracy. An important question, however, is how accurate do these models need to be for purposes of estimating source-term concentrations? For example, it is unrealistic to expect a high degree of accuracy in speciation models if such models predict solubilities that are below the analytical detection limit for a given radioelement. From a practical standpoint, such models are irrelevant if calculated solubilities cannot be tested by direct comparison to experimental data. In the absence of models that are both accurate and relevant for conditions of interest, the detection limit could define a pragmatic upper limit on radioelement solubility 56 refs, 25 tabs, 10 figs

  15. SITE-94. Radionuclide solubilities for SITE-94

    International Nuclear Information System (INIS)

    Arthur, R.; Apted, M.

    1996-12-01

    In this report, solubility constraints are evaluated on radioelement source-term concentrations supporting the SITE-94 performance assessment. Solubility models are based on heterogeneous-equilibrium, mass- and charge-balance constraints incorporated into the EQ3/6 geochemical software package, which is used to calculate the aqueous speciation behavior and solubilities of U, Th, Pu, Np, Am, Ni, Ra, Se, Sn, Sr, Tc and Zr in site groundwaters and near-field solutions. The chemical evolution of the near field is approximated using EQ3/6 in terms of limiting conditions at equilibrium, or steady state, in three closed systems representing fully saturated bentonite, Fe o corrosion products of the canister, and spent fuel. The calculations consider both low-temperature (15 deg C) and high-temperature (80 deg C) conditions in the near field, and the existence of either reducing or strongly oxidizing conditions in each of the bentonite, canister, and spent-fuel barriers. Heterogeneities in site characteristics are evaluated through consideration of a range of initial groundwaters and their interactions with engineered barriers. Aqueous speciation models for many radioelements are constrained by thermodynamic data that are estimated with varying degrees of accuracy. An important question, however, is how accurate do these models need to be for purposes of estimating source-term concentrations? For example, it is unrealistic to expect a high degree of accuracy in speciation models if such models predict solubilities that are below the analytical detection limit for a given radioelement. From a practical standpoint, such models are irrelevant if calculated solubilities cannot be tested by direct comparison to experimental data. In the absence of models that are both accurate and relevant for conditions of interest, the detection limit could define a pragmatic upper limit on radioelement solubility

  16. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  17. Water swelling, brine soluble imidazole based zwitterionic polymers-synthesis and study of reversible UCST behaviour and gel-sol transitions

    NARCIS (Netherlands)

    Vasantha, Vivek Arjunan; Jana, Satyasankar; Parthiban, Anbanandam; Vancso, Julius G.

    2014-01-01

    New vinylbenzene substituted imidazole based zwitterionic polymers with unique characteristics like swelling in water and solubility in concentrated brine solution in which they exhibited a reversible upper critical solution temperature (UCST) and gel-sol transitions are reported herein. © 2014 The

  18. Circulating Ghrelin, Leptin, and Soluble Leptin Receptor Concentrations and Cardiometabolic Risk Factors in a Community-Based Sample

    OpenAIRE

    Ingelsson, Erik; Larson, Martin G.; Yin, Xiaoyan; Wang, Thomas J.; Meigs, James B.; Lipinska, Izabella; Benjamin, Emelia J.; Keaney, John F.; Vasan, Ramachandran S.

    2008-01-01

    Context: The conjoint effects and relative importance of ghrelin, leptin, and soluble leptin receptor (sOB-R), adipokines involved in appetite control and energy expenditure in mediating cardiometabolic risk, is unknown.

  19. Theoretical bases analysis of scientific prediction on marketing principles

    OpenAIRE

    A.S. Rosohata

    2012-01-01

    The article presents an overview categorical apparatus of scientific predictions and theoretical foundations results of scientific forecasting. They are integral part of effective management of economic activities. The approaches to the prediction of scientists in different fields of Social science and the categories modification of scientific prediction, based on principles of marketing are proposed.

  20. Speaker Prediction based on Head Orientations

    NARCIS (Netherlands)

    Rienks, R.J.; Poppe, Ronald Walter; van Otterlo, M.; Poel, Mannes; Poel, M.; Nijholt, A.; Nijholt, Antinus

    2005-01-01

    To gain insight into gaze behavior in meetings, this paper compares the results from a Naive Bayes classifier, Neural Networks and humans on speaker prediction in four-person meetings given solely the azimuth head angles. The Naive Bayes classifier scored 69.4% correctly, Neural Networks 62.3% and

  1. Compositional Dependence of Solubility/Retention of Molybdenum Oxides in Aluminoborosilicate-Based Model Nuclear Waste Glasses.

    Science.gov (United States)

    Brehault, Antoine; Patil, Deepak; Kamat, Hrishikesh; Youngman, Randall E; Thirion, Lynn M; Mauro, John C; Corkhill, Claire L; McCloy, John S; Goel, Ashutosh

    2018-02-08

    Molybdenum oxides are an integral component of the high-level waste streams being generated from the nuclear reactors in several countries. Although borosilicate glass has been chosen as the baseline waste form by most of the countries to immobilize these waste streams, molybdate oxyanions (MoO 4 2- ) exhibit very low solubility (∼1 mol %) in these glass matrices. In the past three to four decades, several studies describing the compositional and structural dependence of molybdate anions in borosilicate and aluminoborosilicate glasses have been reported in the literature, providing a basis for our understanding of fundamental science that governs the solubility and retention of these species in the nuclear waste glasses. However, there are still several open questions that need to be answered to gain an in-depth understanding of the mechanisms that control the solubility and retention of these oxyanions in glassy waste forms. This article is focused on finding answers to two such questions: (1) What are the solubility and retention limits of MoO 3 in aluminoborosilicate glasses as a function of chemical composition? (2) Why is there a considerable increase in the solubility of MoO 3 with incorporation of rare-earth oxides (for example, Nd 2 O 3 ) in aluminoborosilicate glasses? Accordingly, three different series of aluminoborosilicate glasses (compositional complexity being added in a tiered approach) with varying MoO 3 concentrations have been synthesized and characterized for their ability to accommodate molybdate ions in their structure (solubility) and as a glass-ceramic (retention). The contradictory viewpoints (between different research groups) pertaining to the impact of rare-earth cations on the structure of aluminoborosilicate glasses are discussed, and their implications on the solubility of MoO 3 in these glasses are evaluated. A novel hypothesis explaining the mechanism governing the solubility of MoO 3 in rare-earth containing aluminoborosilicate

  2. Solubility and partitioning of hydrogen in meta-stable ZR-based alloys used in the nuclear industry

    International Nuclear Information System (INIS)

    Khatamian, D.

    1998-11-01

    Terminal solubility and partitioning of hydrogen in Zr-Nb alloys with different Nb concentrations were examined using differential scanning calorimetry and hot vacuum extraction mass spectrometry. Specimens were charged to different concentrations of hydrogen and annealed at 1123 K to generate a two-phase structure consisting of α-Zr (Zr-0.6 wt.% Nb) and meta-stable β-Zr (Zr-20 wt.% Nb) within the alloy. Specimens were aged at 673 and 773 K for up to 1000 h to evaluate the effect of the decomposition of the meta-stable β-Zr to α-Zr + β-Nb on the solubility limit. The results show that the solubility limit for hydrogen in the annealed Zr-Nb alloys is higher than in unalloyed Zr and that the solubility limit increases with the Nb concentration of the alloy. They also show that the hydrogen solubility limits of the completely aged Zr-Nb alloys are similar and approach the values for pure α-Zr. The solubility ratio of hydrogen in β-Zr (Zr-20 wt.% Nb) to that in α-Zr (Zr-0.6 wt.% Nb) was found to range from 9 to 7 within the temperature range of 520 to 580 K. (author)

  3. Co-extraction of soluble and insoluble sugars from energy sorghum based on a hydrothermal hydrolysis process.

    Science.gov (United States)

    Yu, Qiang; Tan, Xuesong; Zhuang, Xinshu; Wang, Qiong; Wang, Wen; Qi, Wei; Zhou, Guixiong; Luo, Yu; Yuan, Zhenhong

    2016-12-01

    A process for co-extraction of soluble and insoluble sugars from energy sorghum (ES) was developed based on hydrothermal hydrolysis (HH). Two series of ES were investigated: one (N) with a high biomass yield displayed a higher recalcitrance to sugar release, whereas the second (T) series was characterized by high sugar extraction. The highest total xylose recoveries of 87.2% and 98.7% were obtained for N-11 and T-106 under hydrolysis conditions of 180°C for 50min and 180°C for 30min, respectively. Moreover, the T series displayed higher enzymatic digestibility (ED) than the N series. The high degree of branching (arabinose/xylose ratio) and acetyl groups in the hemicellulose chains of T-106 would be expected to accelerate sugar release during the HH process. In addition, negative correlations between ED and the lignin content, crystallinity index (CrI) and syringyl/guaiacyl (S/G) lignin ratio were observed. Furthermore, finding ways to overcome the thickness of the cell wall and heterogeneity of its chemical composition distribution would make cellulose more accessible to the enzyme. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Selective and Sensitive Detection of Cyanide Based on the Displacement Strategy Using a Water-Soluble Fluorescent Probe

    Science.gov (United States)

    La, Ming; Hao, Yuanqiang; Wang, Zhaoyang; Han, Guo-Cheng; Qu, Lingbo

    2016-01-01

    A water-soluble fluorescent probe (C-GGH) was used for the highly sensitive and selective detection of cyanide (CN−) in aqueous media based on the displacement strategy. Due to the presence of the recognition unit GGH (Gly-Gly-His), the probe C-GGH can coordinate with Cu2+ and consequently display ON-OFF type fluorescence response. Furthermore, the in situ formed nonfluorescent C-GGH-Cu2+ complex can act as an effective OFF-ON type fluorescent probe for sensing CN− anion. Due to the strong binding affinity of CN− to Cu2+, CN− can extract Cu2+ from C-GGH-Cu2+ complex, leading to the release of C-GGH and the recovery of fluorescent emission of the system. The probe C-GGH-Cu2+ allowed detection of CN− in aqueous solution with a LOD (limit of detection) of 0.017 μmol/L which is much lower than the maximum contaminant level (1.9 μmol/L) for CN− in drinking water set by the WHO (World Health Organization). The probe also displayed excellent specificity for CN− towards other anions, including F−, Cl−, Br−, I−, SCN−, PO4 3−, N3 −, NO3 −, AcO−, SO4 2−, and CO3 2−. PMID:26881185

  5. A sensitive electrochemical aptasensor based on water soluble CdSe quantum dots (QDs) for thrombin determination

    Energy Technology Data Exchange (ETDEWEB)

    Li Yanfen; Han Min [Jiangsu Laboratory of New Power Batteries, Jiangsu Key Laboratory of Biofuctional Materials, College of Chemistry and Materials Science, Nanjing Normal University, Nanjing 210097 (China); Bai Hongyan [Jiangsu Laboratory of New Power Batteries, Jiangsu Key Laboratory of Biofuctional Materials, College of Chemistry and Materials Science, Nanjing Normal University, Nanjing 210097 (China); College of Biological and Chemical Engineering, Jiaxing College, Jiaxing 314001 (China); Wu Yong [Jiangsu Laboratory of New Power Batteries, Jiangsu Key Laboratory of Biofuctional Materials, College of Chemistry and Materials Science, Nanjing Normal University, Nanjing 210097 (China); Dai Zhihui, E-mail: daizhihuii@njnu.edu.cn [Jiangsu Laboratory of New Power Batteries, Jiangsu Key Laboratory of Biofuctional Materials, College of Chemistry and Materials Science, Nanjing Normal University, Nanjing 210097 (China); Bao Jianchun, E-mail: baojianchun@njnu.edu.cn [Jiangsu Laboratory of New Power Batteries, Jiangsu Key Laboratory of Biofuctional Materials, College of Chemistry and Materials Science, Nanjing Normal University, Nanjing 210097 (China)

    2011-08-01

    A novel aptamer biosensor with easy operation and good sensitivity, specificity, stability and reproducibility was developed by immobilizing the aptamer on water soluble CdSe quantum dots (QDs) modified on the top of the glassy carbon electrode (GCE). Methylene blue (MB) was intercalated into the aptamer sequence and used as an electrochemical marker. CdSe QDs improved the electrochemical signal because of their larger surface area and ion centers of CdSe QDs may also had a major role on amplifying the signal. The higher ion concentration caused more combination of aptamer which caused larger signal. The thrombin was detected by differential pulse voltammetry (DPV) quantitatively. Under optimal conditions, the two linear ranges were obtained from 3 to 13 {mu}g mL{sup -1} and from 14 to 31 {mu}g mL{sup -1}, respectively. The detection limit was 0.08 {mu}g mL{sup -1} at 3{sigma}. The constructed biosensor had better responses compared with that in the absence of the CdSe QDs immobilizing. The control experiment was also carried out by using BSA, casein and IgG in the absence of thrombin. The results showed that the aptasensor had good specificity, stability and reproducibility to the thrombin. Moreover, the aptasensor could be used for detection of real sample with consistent results in comparison with those obtained by fluorescence method which could provide a promising platform for fabrication of aptamer based biosensors.

  6. Selective and Sensitive Detection of Cyanide Based on the Displacement Strategy Using a Water-Soluble Fluorescent Probe

    Directory of Open Access Journals (Sweden)

    Ming La

    2016-01-01

    Full Text Available A water-soluble fluorescent probe (C-GGH was used for the highly sensitive and selective detection of cyanide (CN− in aqueous media based on the displacement strategy. Due to the presence of the recognition unit GGH (Gly-Gly-His, the probe C-GGH can coordinate with Cu2+ and consequently display ON-OFF type fluorescence response. Furthermore, the in situ formed nonfluorescent C-GGH-Cu2+ complex can act as an effective OFF-ON type fluorescent probe for sensing CN− anion. Due to the strong binding affinity of CN− to Cu2+, CN− can extract Cu2+ from C-GGH-Cu2+ complex, leading to the release of C-GGH and the recovery of fluorescent emission of the system. The probe C-GGH-Cu2+ allowed detection of CN− in aqueous solution with a LOD (limit of detection of 0.017 μmol/L which is much lower than the maximum contaminant level (1.9 μmol/L for CN− in drinking water set by the WHO (World Health Organization. The probe also displayed excellent specificity for CN− towards other anions, including F−, Cl−, Br−, I−, SCN−, PO43-, N3-, NO3-, AcO−, SO42-, and CO32-.

  7. A Novel Water-soluble Ratiometric Fluorescent Probe Based on FRET for Sensing Lysosomal pH.

    Science.gov (United States)

    Song, Guang-Jie; Bai, Su-Yun; Luo, Jing; Cao, Xiao-Qun; Zhao, Bao-Xiang

    2016-11-01

    A new ratiometric fluorescent probe based on Förster resonance energy transfer (FRET) for sensing lysosomal pH has been developed. The probe (RMPM) was composed of imidazo[1,5-α]pyridine quaternary ammonium salt fluorophore as the FRET donor and the rhodamine moiety as the FRET acceptor. It's the first time to report that imidazo[1,5-α]pyridine quaternary ammonium salt acts as the FRET donor. The ratio of fluorescence intensity of the probe at two wavelengths (I 424 /I 581 ) changed significantly and responded linearly toward minor pH changes in the range of 5.4-6.6. It should be noted that it's rare to report that a ratiometric pH probe could detect so weak acidic pH with pKa = 6.31. In addition, probe RMPM exhibited excellent water-solubility, fast-response, all-right selectivity and brilliant reversibility. Moreover, RMPM has been successfully applied to sensing lysosomal pH in HeLa cells and has low cytotoxicity.

  8. A water-soluble and retrievable ruthenium-based probe for colorimetric recognition of Hg(II) and Cys.

    Science.gov (United States)

    Cui, Yali; Hao, Yuanqiang; Zhang, Yintang; Liu, Baoxia; Zhu, Xu; Qu, Peng; Li, Deliang; Xu, Maotian

    2016-08-05

    A new ruthenium-based complex 1 [(bis(4,4'-dimethylphosphonic-2,2'-bipyridine) dithiocyanato ruthenium (II))] was developed as a colorimetric probe for the detection of Hg(II) and Cys (Cysteine). The obtained compound 1 can give interconversional color changes upon the alternating addition of Hg(II) and Cys in 100% aqueous solution. The specific coordination between NCS groups with Hg(II) can lead to the formation of 1-Hg(2+) complex, which can induce a remarkable spectral changes of probe 1. Afterwards the formed 1-Hg(2+) complex can act as effective colorimetric sensor for Cys. Owing to the stronger binding affinity of sulfhydryl group to Hg(2+), Cys can extract Hg(2+) from 1-Hg(2+) complex resulting in the release of 1 and the revival of absorption profile of the probe 1. By introducing the hydrophilic phosphonic acid groups, the proposed probe exhibited excellent water solubility. The limits of detection (LODs) of the assay for Hg(2+) and Cys are calculated to be 15nM and 200nM, respectively. Copyright © 2016. Published by Elsevier B.V.

  9. Preparation of Essential Oil-Based Microemulsions for Improving the Solubility, pH Stability, Photostability, and Skin Permeation of Quercetin.

    Science.gov (United States)

    Lv, Xia; Liu, Tiantian; Ma, Huipeng; Tian, Yan; Li, Lei; Li, Zhen; Gao, Meng; Zhang, Jianbin; Tang, Zeyao

    2017-11-01

    Quercetin can bring many benefits to skin based on its various bioactivities. However, the therapeutic effect of quercetin is limited due to the poor water solubility, pH instability, light instability, and skin permeation. The aim of the present work was applying essential oil-based microemulsions to improve the solubility, pH stability, photostability, and skin permeation of quercetin for topical application. Peppermint oil (PO-ME), clove oil (CO-ME), and rosemary oil (RMO-ME) were selected as model essential oils. Microemulsions composed of Cremophor EL/1,2-propanediol/essential oils (47:23:30, w/w) were selected as model formulations, based on the pseudo-ternary phase diagram and the characterizations. In the solubility study, the solubility of quercetin was improved dozens of times by microemulsions. Quercetin was found instable under alkaline condition, with 50% degraded in the solution of pH 13. However, PO-ME, CO-ME, and RMO-ME could protect quercetin from the hydroxide ions, with 47, 9, and 12% of quercetin degraded. In the photostability study, the essential oil-based microemulsions showed the capability of protecting quercetin from degradation under UV radiation. Where more than 67% of quercetin was degraded in aqueous solution, while less than 7% of quercetin degraded in microemulsions. At last, the in vitro skin permeation study showed that the essential oil-based microemulsions could enhance the permeation capacity of quercetin by 2.5-3 times compared to the aqueous solution. Hence, the prepared essential oil microemulsions could improve the solubility, pH stability, photostability, and skin permeation of quercetin, which will be beneficial for its topical application.

  10. Geothermal-brine modeling - prediction of mineral solubilities in natural waters: the Na-K-Mg-Ca-H-Cl-SO{sub 4}-OH-HCO{sub 3} CO{sub 3}-CO{sub 2}-H{sub 2}O system to high ionic strengths at 25{sup 0}C

    Energy Technology Data Exchange (ETDEWEB)

    Weare, J.H.

    1981-01-01

    The mineral solubility model of Harvie and Weare (1980) is extended to the eight component system, Na-K-Ca-Mg-H-Cl-SO{sub 4}-OH-HCO{sub 3}-CO{sub 3}-CO{sub 2}-H{sub 2}O at 25{sup 0}C to high concentrations. The model is based on the semi-empirical equations of Pitzer (1973) and co-workers for the thermodynamics of aqueous electrolyte solutions. The model is parameterized using many of the available isopiestic, electromotive force, and solubility data available for many of the subsystems. The predictive abilities of the model are demonstrated by comparison to experimental data in systems more complex than those used in parameterization. The essential features of a chemical model for aqueous electrolyte solutions and the relationship between pH and the equilibrium properties of a solution are discussed.

  11. Prediction-error of Prediction Error (PPE)-based Reversible Data Hiding

    OpenAIRE

    Wu, Han-Zhou; Wang, Hong-Xia; Shi, Yun-Qing

    2016-01-01

    This paper presents a novel reversible data hiding (RDH) algorithm for gray-scaled images, in which the prediction-error of prediction error (PPE) of a pixel is used to carry the secret data. In the proposed method, the pixels to be embedded are firstly predicted with their neighboring pixels to obtain the corresponding prediction errors (PEs). Then, by exploiting the PEs of the neighboring pixels, the prediction of the PEs of the pixels can be determined. And, a sorting technique based on th...

  12. Poloxamer-Based Thermoreversible Gel for Topical Delivery of Emodin: Influence of P407 and P188 on Solubility of Emodin and Its Application in Cellular Activity Screening

    Directory of Open Access Journals (Sweden)

    Eunmi Ban

    2017-02-01

    Full Text Available Emodin is a component in a Chinese herb, Rheum officinale Baill, traditionally used for diabetes and anticancer. Its poor solubility is one of the major challenges to pharmaceutical scientists. We previously reported on thermoreversible gel formulations based on poloxamer for the topical delivery of emodin. The present study was to understand the effect of poloxamer type on emodin solubility and its application in cellular activity screening. Various gel formulations composed of poloxamer 407 (P407, poloxamer 188 (P188 and PEG400 were prepared and evaluated. Major evaluation parameters were the gelation temperature (Tgel and solubility of emodin. The emodin solubility increased with increasing poloxamer concentration and the Tgel was modulated by the proper combination of P407. In particular, this study showed that the amount of P407 in thermoreversible poloxamer gel (PG was the dominant factor in enhancing solubility and P188 was effective at fixing gelation temperature in the desired range. A thermoreversible emodin PG was selected as the proper composition with the liquid state at room temperature and gel state at body temperature. The gel showed the solubility enhancement of emodin at least 100-fold compared to 10% ethanol or water. The thermoreversible formulation was applied for in vitro cellular activity screening in the human dermal fibroblast cell line and DLD-1 colon cancer cell line after dilution with cell culture media. The thermoreversible gel formulation remained as a clear solution in the microplate, which allowed reliable cellular activity screening. In contrast, emodin solution in ethanol or DMSO showed precipitation at the corresponding emodin concentration, complicating data interpretation. In conclusion, the gel formulation is proposed as a useful prototype topical formulation for testing emodin in vivo as well as in vitro.

  13. Students’ misconceptions on solubility equilibrium

    Science.gov (United States)

    Setiowati, H.; Utomo, S. B.; Ashadi

    2018-05-01

    This study investigated the students’ misconceptions of the solubility equilibrium. The participants of the study consisted of 164 students who were in the science class of second year high school. Instrument used is two-tier diagnostic test consisting of 15 items. Responses were marked and coded into four categories: understanding, misconception, understand little without misconception, and not understanding. Semi-structured interviews were carried out with 45 students according to their written responses which reflected different perspectives, to obtain a more elaborated source of data. Data collected from multiple methods were analyzed qualitatively and quantitatively. Based on the data analysis showed that the students misconceptions in all areas in solubility equilibrium. They had more misconceptions such as in the relation of solubility and solubility product, common-ion effect and pH in solubility, and precipitation concept.

  14. Hydrotropic solubilization of lipophilic drugs for oral delivery: The effects of urea and nicotinamide on carbamazepine solubility-permeability interplay

    Directory of Open Access Journals (Sweden)

    Avital Beig

    2016-10-01

    Full Text Available Hydrotropy refers to increasing the water solubility of otherwise poorly soluble compound by the presence of small organic molecules. While it can certainly increase the apparent solubility of a lipophilic drug, the effect of hydrotropy on the drugs' permeation through the intestinal membrane has not been studied. The purpose of this work was to investigate the solubility-permeability interplay when using hydrotropic drug solubilization. The concentration-dependent effects of the commonly used hydrotropes urea and nicotinamide, on the solubility and the permeability of the lipophilic antiepileptic drug carbamazepine were studied. Then, the solubility-permeability interplay was mathematically modeled, and was compared to the experimental data. Both hydrotropes allowed significant concentration-dependent carbamazepine solubility increase (up to ~30-fold. A concomitant permeability decrease was evident both in-vitro and in-vivo (~17-fold for nicotinamide and ~9-fold for urea, revealing a solubility-permeability tradeoff when using hydrotropic drug solubilization. A relatively simplified simulation approach based on proportional opposite correlation between the solubility increase and the permeability decrease at a given hydrotrope concentration allowed excellent prediction of the overall solubility-permeability tradeoff. In conclusion, when using hydrotropic drug solubilization it is prudent to not focus solely on solubility, but to account for the permeability as well; achieving optimal solubility-permeability balance may promote the overall goal of the formulation to maximize oral drug exposure.

  15. A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction.

    Science.gov (United States)

    Deng, Lei; Fan, Chao; Zeng, Zhiwen

    2017-12-28

    Direct prediction of the three-dimensional (3D) structures of proteins from one-dimensional (1D) sequences is a challenging problem. Significant structural characteristics such as solvent accessibility and contact number are essential for deriving restrains in modeling protein folding and protein 3D structure. Thus, accurately predicting these features is a critical step for 3D protein structure building. In this study, we present DeepSacon, a computational method that can effectively predict protein solvent accessibility and contact number by using a deep neural network, which is built based on stacked autoencoder and a dropout method. The results demonstrate that our proposed DeepSacon achieves a significant improvement in the prediction quality compared with the state-of-the-art methods. We obtain 0.70 three-state accuracy for solvent accessibility, 0.33 15-state accuracy and 0.74 Pearson Correlation Coefficient (PCC) for the contact number on the 5729 monomeric soluble globular protein dataset. We also evaluate the performance on the CASP11 benchmark dataset, DeepSacon achieves 0.68 three-state accuracy and 0.69 PCC for solvent accessibility and contact number, respectively. We have shown that DeepSacon can reliably predict solvent accessibility and contact number with stacked sparse autoencoder and a dropout approach.

  16. The wind power prediction research based on mind evolutionary algorithm

    Science.gov (United States)

    Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina

    2018-04-01

    When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.

  17. A prediction method for the wax deposition rate based on a radial basis function neural network

    Directory of Open Access Journals (Sweden)

    Ying Xie

    2017-06-01

    Full Text Available The radial basis function neural network is a popular supervised learning tool based on machinery learning technology. Its high precision having been proven, the radial basis function neural network has been applied in many areas. The accumulation of deposited materials in the pipeline may lead to the need for increased pumping power, a decreased flow rate or even to the total blockage of the line, with losses of production and capital investment, so research on predicting the wax deposition rate is significant for the safe and economical operation of an oil pipeline. This paper adopts the radial basis function neural network to predict the wax deposition rate by considering four main influencing factors, the pipe wall temperature gradient, pipe wall wax crystal solubility coefficient, pipe wall shear stress and crude oil viscosity, by the gray correlational analysis method. MATLAB software is employed to establish the RBF neural network. Compared with the previous literature, favorable consistency exists between the predicted outcomes and the experimental results, with a relative error of 1.5%. It can be concluded that the prediction method of wax deposition rate based on the RBF neural network is feasible.

  18. Solubility of cobalt in primary circuit solutions

    International Nuclear Information System (INIS)

    Lambert, I.; Joyer, F.

    1992-01-01

    The solubility of cobalt ferrite (CoFe 2 O 4 ) was measured in PWR primary circuit conditions, in the temperature range 250-350 deg C, and the results were compared with the ones obtained on magnetite and nickel ferrite. As in the former cases, it was found that, in the prevailing primary circuit conditions, the solubility of the cobalt ferrite was minimum at temperatures around 300 deg C, for cobalt as well as for iron. The equilibrium iron concentration is significantly lower than in the case of magnetite. The results are discussed in relation with the POTHY code, based only on thermodynamic laws and data, used for the prediction of the primary circuit chemistry

  19. Senior high school students’ need analysis of Three-Tier Multiple Choice (3TMC) diagnostic test about acid-base and solubility equilibrium

    Science.gov (United States)

    Ardiansah; Masykuri, M.; Rahardjo, S. B.

    2018-05-01

    Students’ conceptual understanding is the most important comprehension to obtain related comprehension. However, they held their own conception. With this need analysis, we will elicit student need of 3TMC diagnostic test to measure students’ conception about acid-base and solubility equilibrium. The research done by a mixed method using questionnaire analysis based on descriptive of quantitative and qualitative. The research subject was 96 students from 4 senior high schools and 4 chemistry teachers chosen by random sampling technique. Data gathering used a questionnaire with 10 questions for student and 28 questions for teachers. The results showed that 97% of students stated that the development this instrument is needed. In addition, there were several problems obtained in this questionnaire include learning activity, teacher’s test and guessing. In conclusion, this is necessary to develop the 3TMC instrument that can diagnose and measure the student’s conception in acid-base and solubility equilibrium.

  20. Water-soluble egg membrane enhances the immunoactivating properties of an Aloe vera-based extract of Nerium oleander leaves

    Directory of Open Access Journals (Sweden)

    Benson KF

    2016-11-01

    Full Text Available Kathleen F Benson,1 Robert A Newman,2,3 Gitte S Jensen1 1NIS Labs, Klamath Falls, OR, 2Department of Experimental Therapeutics, University of Texas MD Anderson Cancer Center, Houston, 3Nerium Biotechnology Inc, San Antonio, TX, USA Objective: To evaluate a blend of two natural ingredients on immune parameters relevant for their current topical use and potential support of microcirculation in skin tissue. Materials and methods: A blend (BL of Aloe vera-based Nerium oleander extract (NAE-8i, oleandrin-free and hydrolyzed water-soluble egg membrane (WSEM was applied to human whole-blood cultures for 24 hours, with each separate ingredient serving as a control. Immune-cell subsets were analyzed for expression levels of the activation markers CD69 and CD25. Culture supernatants were analyzed for cytokines, chemokines, and immunoregulating peptides. Results: BL increased CD69 expression on lymphocytes, monocytes, and CD3–CD56+ natural killer cells, and CD25 expression on natural killer cells. The number of CD69+CD25+ lymphocytes increased in cultures treated with BL and the separate ingredients. BL triggered production of multiple cytokines and chemokines, where CC chemokines MIP1α and MIP3α, as well as cytokines involved in wound healing – Groα, Groβ, ENA78, and fractalkine – reached levels manyfold above treatment with either NAE-8i or WSEM alone. Conclusion: Data on BL showed that WSEM strongly enhanced NAE-8i’s effects on immunoactivation in vitro. This has potential relevance for support of immunity in skin tissue, including antibacterial and antiviral defense mechanisms, wrinkle reduction, and wound care. Keywords: chemokines, cytokines, leukocyte activation

  1. Highly efficient inverted polymer solar cells based on a cross-linkable water-/alcohol-soluble conjugated polymer interlayer.

    Science.gov (United States)

    Zhang, Kai; Zhong, Chengmei; Liu, Shengjian; Mu, Cheng; Li, Zhengke; Yan, He; Huang, Fei; Cao, Yong

    2014-07-09

    A cross-linkable water/alcohol soluble conjugated polymer (WSCP) material poly[9,9-bis(6'-(N,N-diethylamino)propyl)-fluorene-alt-9,9-bis(3-ethyl(oxetane-3-ethyloxy)-hexyl) fluorene] (PFN-OX) was designed. The cross-linkable nature of PFN-OX is good for fabricating inverted polymer solar cells (PSCs) with well-defined interface and investigating the detailed working mechanism of high-efficiency inverted PSCs based on poly[4,8-bis(2-ethylhexyloxyl)benzo[1,2-b:4,5-b']dithio-phene-2,6-diyl-alt-ethylhexyl-3-fluorothithieno[3,4-b]thiophene-2-carboxylate-4,6-diyl] (PTB7) and (6,6)-phenyl-C71-butyric acid methyl ester (PC71BM) blend active layer. The detailed working mechanism of WSCP materials in high-efficiency PSCs were studied and can be summarized into the following three effects: a) PFN-OX tunes cathode work function to enhance open-circuit voltage (Voc); b) PFN-OX dopes PC71BM at interface to facilitate electron extraction; and c) PFN-OX extracts electrons and blocks holes to enhance fill factor (FF). On the basis of this understanding, the hole-blocking function of the PFN-OX interlayer was further improved with addition of a ZnO layer between ITO and PFN-OX, which led to inverted PSCs with a power conversion efficiency of 9.28% and fill factor high up to 74.4%.

  2. Size-based predictions of food web patterns

    DEFF Research Database (Denmark)

    Zhang, Lai; Hartvig, Martin; Knudsen, Kim

    2014-01-01

    We employ size-based theoretical arguments to derive simple analytic predictions of ecological patterns and properties of natural communities: size-spectrum exponent, maximum trophic level, and susceptibility to invasive species. The predictions are brought about by assuming that an infinite number...... of species are continuously distributed on a size-trait axis. It is, however, an open question whether such predictions are valid for a food web with a finite number of species embedded in a network structure. We address this question by comparing the size-based predictions to results from dynamic food web...... simulations with varying species richness. To this end, we develop a new size- and trait-based food web model that can be simplified into an analytically solvable size-based model. We confirm existing solutions for the size distribution and derive novel predictions for maximum trophic level and invasion...

  3. Base Oils Biodegradability Prediction with Data Mining Techniques

    Directory of Open Access Journals (Sweden)

    Malika Trabelsi

    2010-02-01

    Full Text Available In this paper, we apply various data mining techniques including continuous numeric and discrete classification prediction models of base oils biodegradability, with emphasis on improving prediction accuracy. The results show that highly biodegradable oils can be better predicted through numeric models. In contrast, classification models did not uncover a similar dichotomy. With the exception of Memory Based Reasoning and Decision Trees, tested classification techniques achieved high classification prediction. However, the technique of Decision Trees helped uncover the most significant predictors. A simple classification rule derived based on this predictor resulted in good classification accuracy. The application of this rule enables efficient classification of base oils into either low or high biodegradability classes with high accuracy. For the latter, a higher precision biodegradability prediction can be obtained using continuous modeling techniques.

  4. Soluble form of membrane attack complex independently predicts mortality and cardiovascular events in patients with ST-elevation myocardial infarction treated with primary percutaneous coronary intervention

    DEFF Research Database (Denmark)

    Lindberg, Søren; Pedersen, Sune H; Mogelvang, Rasmus

    2012-01-01

    The complement system is an important mediator of inflammation, which plays a pivotal role in atherosclerosis and acute myocardial infarction (AMI). Animal studies suggest that activation of the complement cascade resulting in the formation of soluble membrane attack complex (sMAC), contributes...

  5. Enhanced Iron Solubility at Low pH in Global Aerosols

    Directory of Open Access Journals (Sweden)

    Ellery D. Ingall

    2018-05-01

    Full Text Available The composition and oxidation state of aerosol iron were examined using synchrotron-based iron near-edge X-ray absorption spectroscopy. By combining synchrotron-based techniques with water leachate analysis, impacts of oxidation state and mineralogy on aerosol iron solubility were assessed for samples taken from multiple locations in the Southern and the Atlantic Oceans; and also from Noida (India, Bermuda, and the Eastern Mediterranean (Crete. These sampling locations capture iron-containing aerosols from different source regions with varying marine, mineral dust, and anthropogenic influences. Across all locations, pH had the dominating influence on aerosol iron solubility. When aerosol samples were approximately neutral pH, iron solubility was on average 3.4%; when samples were below pH 4, the iron solubility increased to 35%. This observed aerosol iron solubility profile is consistent with thermodynamic predictions for the solubility of Fe(III oxides, the major iron containing phase in the aerosol samples. Source regions and transport paths were also important factors affecting iron solubility, as samples originating from or passing over populated regions tended to contain more soluble iron. Although the acidity appears to affect aerosol iron solubility globally, a direct relationship for all samples is confounded by factors such as anthropogenic influence, aerosol buffer capacity, mineralogy and physical processes.

  6. Copula-based prediction of economic movements

    Science.gov (United States)

    García, J. E.; González-López, V. A.; Hirsh, I. D.

    2016-06-01

    In this paper we model the discretized returns of two paired time series BM&FBOVESPA Dividend Index and BM&FBOVESPA Public Utilities Index using multivariate Markov models. The discretization corresponds to three categories, high losses, high profits and the complementary periods of the series. In technical terms, the maximal memory that can be considered for a Markov model, can be derived from the size of the alphabet and dataset. The number of parameters needed to specify a discrete multivariate Markov chain grows exponentially with the order and dimension of the chain. In this case the size of the database is not large enough for a consistent estimation of the model. We apply a strategy to estimate a multivariate process with an order greater than the order achieved using standard procedures. The new strategy consist on obtaining a partition of the state space which is constructed from a combination, of the partitions corresponding to the two marginal processes and the partition corresponding to the multivariate Markov chain. In order to estimate the transition probabilities, all the partitions are linked using a copula. In our application this strategy provides a significant improvement in the movement predictions.

  7. Bankruptcy Prediction Based on the Autonomy Ratio

    Directory of Open Access Journals (Sweden)

    Daniel Brîndescu Olariu

    2016-11-01

    Full Text Available The theory and practice of the financial ratio analysis suggest the existence of a negative correlation between the autonomy ratio and the bankruptcy risk. Previous studies conducted on a sample of companies from Timis County (largest county in Romania confirm this hypothesis and recommend the autonomy ratio as a useful tool for measuring the bankruptcy risk two years in advance. The objective of the current research was to develop a methodology for measuring the bankruptcy risk that would be applicable for the companies from the Timis County (specific methodologies are considered necessary for each region. The target population consisted of all the companies from Timis County with annual sales of over 10,000 lei (aprox. 2,200 Euros. The research was performed over all the target population. The study has thus included 53,252 yearly financial statements from the period 2007 – 2010. The results of the study allow for the setting of benchmarks, as well as the configuration of a methodology of analysis. The proposed methodology cannot predict with perfect accuracy the state of the company, but it allows for a valuation of the risk level to which the company is subjected.

  8. Prediction of pipeline corrosion rate based on grey Markov models

    International Nuclear Information System (INIS)

    Chen Yonghong; Zhang Dafa; Peng Guichu; Wang Yuemin

    2009-01-01

    Based on the model that combined by grey model and Markov model, the prediction of corrosion rate of nuclear power pipeline was studied. Works were done to improve the grey model, and the optimization unbiased grey model was obtained. This new model was used to predict the tendency of corrosion rate, and the Markov model was used to predict the residual errors. In order to improve the prediction precision, rolling operation method was used in these prediction processes. The results indicate that the improvement to the grey model is effective and the prediction precision of the new model combined by the optimization unbiased grey model and Markov model is better, and the use of rolling operation method may improve the prediction precision further. (authors)

  9. Churn prediction based on text mining and CRM data analysis

    OpenAIRE

    Schatzmann, Anders; Heitz, Christoph; Münch, Thomas

    2014-01-01

    Within quantitative marketing, churn prediction on a single customer level has become a major issue. An extensive body of literature shows that, today, churn prediction is mainly based on structured CRM data. However, in the past years, more and more digitized customer text data has become available, originating from emails, surveys or scripts of phone calls. To date, this data source remains vastly untapped for churn prediction, and corresponding methods are rarely described in literature. ...

  10. Statistical model based gender prediction for targeted NGS clinical panels

    Directory of Open Access Journals (Sweden)

    Palani Kannan Kandavel

    2017-12-01

    The reference test dataset are being used to test the model. The sensitivity on predicting the gender has been increased from the current “genotype composition in ChrX” based approach. In addition, the prediction score given by the model can be used to evaluate the quality of clinical dataset. The higher prediction score towards its respective gender indicates the higher quality of sequenced data.

  11. ESPRIT: an automated, library-based method for mapping and soluble expression of protein domains from challenging targets.

    Science.gov (United States)

    Yumerefendi, Hayretin; Tarendeau, Franck; Mas, Philippe J; Hart, Darren J

    2010-10-01

    Expression of sufficient quantities of soluble protein for structural biology and other applications is often a very difficult task, especially when multimilligram quantities are required. In order to improve yield, solubility or crystallisability of a protein, it is common to subclone shorter genetic constructs corresponding to single- or multi-domain fragments. However, it is not always clear where domain boundaries are located, especially when working on novel targets with little or no sequence similarity to other proteins. Several methods have been described employing aspects of directed evolution to the recombinant expression of challenging proteins. These combine the construction of a random library of genetic constructs of a target with a screening or selection process to identify solubly expressing protein fragments. Here we review several datasets from the ESPRIT (Expression of Soluble Proteins by Random Incremental Truncation) technology to provide a view on its capabilities. Firstly, we demonstrate how it functions using the well-characterised NF-kappaB p50 transcription factor as a model system. Secondly, application of ESPRIT to the challenging PB2 subunit of influenza polymerase has led to several novel atomic resolution structures; here we present an overview of the screening phase of that project. Thirdly, analysis of the human kinase TBK1 is presented to show how the ESPRIT technology rapidly addresses the compatibility of challenging targets with the Escherichia coli expression system.

  12. Modeling gas solubilities in imidazolium based ionic liquids with the [Tf2N] anion using the GC-EoS

    NARCIS (Netherlands)

    Pereda, Selva; Raeissi, Sonia; Andreatta, A.E. (Alfonsina); Bottini, Susana B.; Kroon, Maaike; Peters, Cor

    2016-01-01

    The group contribution equation of state (GC-EoS) is extended to model gas solubilities in the homologous 1-alkyl-3-methylimidazolium bis(trifluoromethyl-sulfonyl) imide family. The gases considered in this work are CO2, CO, H2, CH4, and C2H6. The model parameters were estimated on the basis of 1400

  13. Hydrogen solubility in austenite of Fe-Ni-Cr alloys

    International Nuclear Information System (INIS)

    Zhirnova, V.V.; Mogutnov, B.M.; Tomilin, I.A.

    1981-01-01

    Hydrogen solubility in Fe-Ni-Cr alloys at 600-1000 deg C is determined. Hydrogen solubility in ternary alloys can not be predicted on the basis of the data on its solubility in binary Fe-Ni, Fe-Cr alloys. Chromium and nickel effect on hydrogen solubility in iron is insignificant in comparison with the effect of these elements on carbon or nitrogen solubility [ru

  14. Power Load Prediction Based on Fractal Theory

    OpenAIRE

    Jian-Kai, Liang; Cattani, Carlo; Wan-Qing, Song

    2015-01-01

    The basic theories of load forecasting on the power system are summarized. Fractal theory, which is a new algorithm applied to load forecasting, is introduced. Based on the fractal dimension and fractal interpolation function theories, the correlation algorithms are applied to the model of short-term load forecasting. According to the process of load forecasting, the steps of every process are designed, including load data preprocessing, similar day selecting, short-term load forecasting, and...

  15. Prediction of residential radon exposure of the whole Swiss population: comparison of model-based predictions with measurement-based predictions.

    Science.gov (United States)

    Hauri, D D; Huss, A; Zimmermann, F; Kuehni, C E; Röösli, M

    2013-10-01

    Radon plays an important role for human exposure to natural sources of ionizing radiation. The aim of this article is to compare two approaches to estimate mean radon exposure in the Swiss population: model-based predictions at individual level and measurement-based predictions based on measurements aggregated at municipality level. A nationwide model was used to predict radon levels in each household and for each individual based on the corresponding tectonic unit, building age, building type, soil texture, degree of urbanization, and floor. Measurement-based predictions were carried out within a health impact assessment on residential radon and lung cancer. Mean measured radon levels were corrected for the average floor distribution and weighted with population size of each municipality. Model-based predictions yielded a mean radon exposure of the Swiss population of 84.1 Bq/m(3) . Measurement-based predictions yielded an average exposure of 78 Bq/m(3) . This study demonstrates that the model- and the measurement-based predictions provided similar results. The advantage of the measurement-based approach is its simplicity, which is sufficient for assessing exposure distribution in a population. The model-based approach allows predicting radon levels at specific sites, which is needed in an epidemiological study, and the results do not depend on how the measurement sites have been selected. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  16. Ensemble-based prediction of RNA secondary structures.

    Science.gov (United States)

    Aghaeepour, Nima; Hoos, Holger H

    2013-04-24

    Accurate structure prediction methods play an important role for the understanding of RNA function. Energy-based, pseudoknot-free secondary structure prediction is one of the most widely used and versatile approaches, and improved methods for this task have received much attention over the past five years. Despite the impressive progress that as been achieved in this area, existing evaluations of the prediction accuracy achieved by various algorithms do not provide a comprehensive, statistically sound assessment. Furthermore, while there is increasing evidence that no prediction algorithm consistently outperforms all others, no work has been done to exploit the complementary strengths of multiple approaches. In this work, we present two contributions to the area of RNA secondary structure prediction. Firstly, we use state-of-the-art, resampling-based statistical methods together with a previously published and increasingly widely used dataset of high-quality RNA structures to conduct a comprehensive evaluation of existing RNA secondary structure prediction procedures. The results from this evaluation clarify the performance relationship between ten well-known existing energy-based pseudoknot-free RNA secondary structure prediction methods and clearly demonstrate the progress that has been achieved in recent years. Secondly, we introduce AveRNA, a generic and powerful method for combining a set of existing secondary structure prediction procedures into an ensemble-based method that achieves significantly higher prediction accuracies than obtained from any of its component procedures. Our new, ensemble-based method, AveRNA, improves the state of the art for energy-based, pseudoknot-free RNA secondary structure prediction by exploiting the complementary strengths of multiple existing prediction procedures, as demonstrated using a state-of-the-art statistical resampling approach. In addition, AveRNA allows an intuitive and effective control of the trade-off between

  17. High-pressure solubility of carbon dioxide in pyrrolidinium-based ionic liquids: [bmpyr][dca] and [bmpyr][Tf{sub 2}N

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Byung-Chul; Nam, Sang Gyu [Hannam University, Daejeon (Korea, Republic of)

    2015-03-15

    Solubility data of carbon dioxide (CO{sub 2}) in two pyrrolidinium-based ionic liquids: 1-butyl-1-methylpyrrolidinium dicyanamide ([bmpyr][dca]) and 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide ([bmpyr] [Tf{sub 2}N]) are presented at pressures up to about 30MPa and temperatures from 303..2 K to 343.2 K. The solubility was determined by measuring bubble or cloud point pressures of mixtures of CO{sub 2} and ionic liquid using a high-pressure equilibrium apparatus equipped with a variable-volume view cell. The CO{sub 2} solubility in the ionic liquid in terms of the mole fraction or the molality increased with the increase of the equilibrium pressure at a given temperature, but decreased with the increase of temperature at a given pressure. At a given temperature, the mole fraction of CO{sub 2} dissolved in the ionic liquid increased rapidly as pressure increased. CO{sub 2} solubility in the mole fraction almost reached saturation around 0.65 for [bmpyr][dca] and around 0..8 for [bmpyr][Tf{sub 2}N], respectively. The experimental data for the CO{sub 2}+ionic liquid systems were correlated using the Peng-Robinson equation of state (PR-EoS). The mixing rules of the Wong-Sandler type rather than the classical mixing rules of the van der Waals type were coupled with the PR-EoS. The resulting modeling approach proved to be able to correlate the CO{sub 2} solubilities in aforementioned ionic liquids over the aforementioned range of temperature and pressure within 5% average deviations.

  18. Estimation of aqueous solubility of TODGA using group contribution method

    International Nuclear Information System (INIS)

    Balasubramonian, S.; Kumar, Shekhar; Sampath, M.; Sivakumar, D.; Kamachi Mudali, U.

    2017-01-01

    The aqueous solubility of N, N, N', N'-tetraoctyl-3-oxapentanediamide normally referred as TODGA is experimentally measured. The aqueous solubility was also predicted using Marrero and Gani group contribution method. The modification of original Marrero and Gani method was proposed to accurately predict TODGA solubility. The predicted solubility of TODGA using original Marrero and Gani method, Modified Marrero and Gani method and UNIFAC Model was compared. The predicted solubility of TODGA using modified Marrero and Gani method is 0.0237 g/l against the experimentally measured value of 0.0226 g/l. (author)

  19. A novel osmotic pump-based controlled delivery system consisting of pH-modulated solid dispersion for poorly soluble drug flurbiprofen: in vitro and in vivo evaluation.

    Science.gov (United States)

    Li, Shujuan; Wang, Xiaoyu; Wang, Yingying; Zhao, Qianqian; Zhang, Lina; Yang, Xinggang; Liu, Dandan; Pan, Weisan

    2015-01-01

    In this study, a novel controlled release osmotic pump capsule consisting of pH-modulated solid dispersion for poorly soluble drug flurbiprofen (FP) was developed to improve the solubility and oral bioavailability of FP and to minimize the fluctuation of plasma concentration. The pH-modulated solid dispersion containing FP, Kollidon® 12 PF and Na2CO3 at a weight ratio of 1/4.5/0.02 was prepared using the solvent evaporation method. The osmotic pump capsule was assembled by semi-permeable capsule shell of cellulose acetate (CA) prepared by the perfusion method. Then, the solid dispersion, penetration enhancer, and suspending agents were tableted and filled into the capsule. Central composite design-response surface methodology was used to evaluate the influence of factors on the responses. A second-order polynomial model and a multiple linear model were fitted to correlation coefficient of drug release profile and ultimate cumulative release in 12 h, respectively. The actual response values were in good accordance with the predicted ones. The optimized formulation showed a complete drug delivery and zero-order release rate. Beagle dogs were used to be conducted in the pharmacokinetic study. The in vivo study indicated that the relative bioavailability of the novel osmotic pump system was 133.99% compared with the commercial preparation. The novel controlled delivery system with combination of pH-modulated solid dispersion and osmotic pump system is not only a promising strategy to improve the solubility and oral bioavailability of poorly soluble ionizable drugs but also an effective way to reduce dosing frequency and minimize the plasma fluctuation.

  20. Model-based uncertainty in species range prediction

    DEFF Research Database (Denmark)

    Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel

    2006-01-01

    Aim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions...

  1. Prediction based chaos control via a new neural network

    International Nuclear Information System (INIS)

    Shen Liqun; Wang Mao; Liu Wanyu; Sun Guanghui

    2008-01-01

    In this Letter, a new chaos control scheme based on chaos prediction is proposed. To perform chaos prediction, a new neural network architecture for complex nonlinear approximation is proposed. And the difficulty in building and training the neural network is also reduced. Simulation results of Logistic map and Lorenz system show the effectiveness of the proposed chaos control scheme and the proposed neural network

  2. Moment based model predictive control for systems with additive uncertainty

    NARCIS (Netherlands)

    Saltik, M.B.; Ozkan, L.; Weiland, S.; Ludlage, J.H.A.

    2017-01-01

    In this paper, we present a model predictive control (MPC) strategy based on the moments of the state variables and the cost functional. The statistical properties of the state predictions are calculated through the open loop iteration of dynamics and used in the formulation of MPC cost function. We

  3. A supramolecular photosensitizer system based on the host-guest complexation between water-soluble pillar[6]arene and methylene blue for durable photodynamic therapy.

    Science.gov (United States)

    Yang, Kui; Wen, Jia; Chao, Shuang; Liu, Jing; Yang, Ke; Pei, Yuxin; Pei, Zhichao

    2018-06-05

    A supramolecular photosensitizer system WP6-MB was synthesized based on water-soluble pillar[6]arene and the photosensitizer methylene blue (MB) via host-guest interaction. MB can complex with WP6 directly with a high complex constant without further modification. In particular, WP6-MB can reduce the dark toxicity of MB remarkably. Furthermore, it can efficiently overcome photobleaching and extend the time for singlet oxygen production of MB upon light irradiation, which is significant for durable photodynamic therapy.

  4. Slope Deformation Prediction Based on Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Lei JIA

    2013-07-01

    Full Text Available This paper principally studies the prediction of slope deformation based on Support Vector Machine (SVM. In the prediction process,explore how to reconstruct the phase space. The geological body’s displacement data obtained from chaotic time series are used as SVM’s training samples. Slope displacement caused by multivariable coupling is predicted by means of single variable. Results show that this model is of high fitting accuracy and generalization, and provides reference for deformation prediction in slope engineering.

  5. Protein-Based Urine Test Predicts Kidney Transplant Outcomes

    Science.gov (United States)

    ... News Releases News Release Thursday, August 22, 2013 Protein-based urine test predicts kidney transplant outcomes NIH- ... supporting development of noninvasive tests. Levels of a protein in the urine of kidney transplant recipients can ...

  6. Predicting response to incretin-based therapy

    Directory of Open Access Journals (Sweden)

    Agrawal N

    2011-04-01

    Full Text Available Sanjay Kalra1, Bharti Kalra2, Rakesh Sahay3, Navneet Agrawal41Department of Endocrinology, 2Department of Diabetology, Bharti Hospital, Karnal, India; 3Department of Endocrinology, Osmania Medical College, Hyderabad, India; 4Department of Medicine, GR Medical College, Gwalior, IndiaAbstract: There are two important incretin hormones, glucose-dependent insulin tropic polypeptide (GIP and glucagon-like peptide-1 (GLP-1. The biological activities of GLP-1 include stimulation of glucose-dependent insulin secretion and insulin biosynthesis, inhibition of glucagon secretion and gastric emptying, and inhibition of food intake. GLP-1 appears to have a number of additional effects in the gastrointestinal tract and central nervous system. Incretin based therapy includes GLP-1 receptor agonists like human GLP-1 analogs (liraglutide and exendin-4 based molecules (exenatide, as well as DPP-4 inhibitors like sitagliptin, vildagliptin and saxagliptin. Most of the published studies showed a significant reduction in HbA1c using these drugs. A critical analysis of reported data shows that the response rate in terms of target achievers of these drugs is average. One of the first actions identified for GLP-1 was the glucose-dependent stimulation of insulin secretion from islet cell lines. Following the detection of GLP-1 receptors on islet beta cells, a large body of evidence has accumulated illustrating that GLP-1 exerts multiple actions on various signaling pathways and gene products in the ß cell. GLP-1 controls glucose homeostasis through well-defined actions on the islet ß cell via stimulation of insulin secretion and preservation and expansion of ß cell mass. In summary, there are several factors determining the response rate to incretin therapy. Currently minimal clinical data is available to make a conclusion. Key factors appear to be duration of diabetes, obesity, presence of autonomic neuropathy, resting energy expenditure, plasma glucagon levels and

  7. Microarray-based cancer prediction using soft computing approach.

    Science.gov (United States)

    Wang, Xiaosheng; Gotoh, Osamu

    2009-05-26

    One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.

  8. Deep-Learning-Based Approach for Prediction of Algal Blooms

    Directory of Open Access Journals (Sweden)

    Feng Zhang

    2016-10-01

    Full Text Available Algal blooms have recently become a critical global environmental concern which might put economic development and sustainability at risk. However, the accurate prediction of algal blooms remains a challenging scientific problem. In this study, a novel prediction approach for algal blooms based on deep learning is presented—a powerful tool to represent and predict highly dynamic and complex phenomena. The proposed approach constructs a five-layered model to extract detailed relationships between the density of phytoplankton cells and various environmental parameters. The algal blooms can be predicted by the phytoplankton density obtained from the output layer. A case study is conducted in coastal waters of East China using both our model and a traditional back-propagation neural network for comparison. The results show that the deep-learning-based model yields better generalization and greater accuracy in predicting algal blooms than a traditional shallow neural network does.

  9. Modeling of Complex Life Cycle Prediction Based on Cell Division

    Directory of Open Access Journals (Sweden)

    Fucheng Zhang

    2017-01-01

    Full Text Available Effective fault diagnosis and reasonable life expectancy are of great significance and practical engineering value for the safety, reliability, and maintenance cost of equipment and working environment. At present, the life prediction methods of the equipment are equipment life prediction based on condition monitoring, combined forecasting model, and driven data. Most of them need to be based on a large amount of data to achieve the problem. For this issue, we propose learning from the mechanism of cell division in the organism. We have established a moderate complexity of life prediction model across studying the complex multifactor correlation life model. In this paper, we model the life prediction of cell division. Experiments show that our model can effectively simulate the state of cell division. Through the model of reference, we will use it for the equipment of the complex life prediction.

  10. Thermodynamic Solubility Profile of Carbamazepine-Cinnamic Acid Cocrystal at Different pH.

    Science.gov (United States)

    Keramatnia, Fatemeh; Shayanfar, Ali; Jouyban, Abolghasem

    2015-08-01

    Pharmaceutical cocrystal formation is a direct way to dramatically influence physicochemical properties of drug substances, especially their solubility and dissolution rate. Because of their instability in the solution, thermodynamic solubility of cocrystals could not be determined in the common way like other compounds; therefore, the thermodynamic solubility is calculated through concentration of their components in the eutectic point. The objective of this study is to investigate the effect of an ionizable coformer in cocrystal with a nonionizable drug at different pH. Carbamazepine (CBZ), a nonionizable drug with cinnamic acid (CIN), which is an acidic coformer, was selected to prepare CBZ-CIN cocrystal and its thermodynamic solubility was studied in pH range 2-7. Instead of HPLC that is a costly and time-consuming method, a chemometric-based approach, net analyte signal standard addition method, was selected for simultaneous determination of CBZ and CIN in solution. The result showed that, as pH increases, CIN ionization leads to change in CBZ-CIN cocrystal solubility and stability in solution. In addition, the results of this study indicated that there is no significant difference between intrinsic solubility of CBZ and cocrystal despite the higher ideal solubility of cocrystal. This verifies that ideal solubility is not good parameter to predict cocrystal solubility. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

  11. Researches of fruit quality prediction model based on near infrared spectrum

    Science.gov (United States)

    Shen, Yulin; Li, Lian

    2018-04-01

    With the improvement in standards for food quality and safety, people pay more attention to the internal quality of fruits, therefore the measurement of fruit internal quality is increasingly imperative. In general, nondestructive soluble solid content (SSC) and total acid content (TAC) analysis of fruits is vital and effective for quality measurement in global fresh produce markets, so in this paper, we aim at establishing a novel fruit internal quality prediction model based on SSC and TAC for Near Infrared Spectrum. Firstly, the model of fruit quality prediction based on PCA + BP neural network, PCA + GRNN network, PCA + BP adaboost strong classifier, PCA + ELM and PCA + LS_SVM classifier are designed and implemented respectively; then, in the NSCT domain, the median filter and the SavitzkyGolay filter are used to preprocess the spectral signal, Kennard-Stone algorithm is used to automatically select the training samples and test samples; thirdly, we achieve the optimal models by comparing 15 kinds of prediction model based on the theory of multi-classifier competition mechanism, specifically, the non-parametric estimation is introduced to measure the effectiveness of proposed model, the reliability and variance of nonparametric estimation evaluation of each prediction model to evaluate the prediction result, while the estimated value and confidence interval regard as a reference, the experimental results demonstrate that this model can better achieve the optimal evaluation of the internal quality of fruit; finally, we employ cat swarm optimization to optimize two optimal models above obtained from nonparametric estimation, empirical testing indicates that the proposed method can provide more accurate and effective results than other forecasting methods.

  12. Enhancement of Solubility and Antioxidant Activity of Some Flavonoids Based on the Inclusion Complexation with Sulfobutylether β-Cyclodextrin

    International Nuclear Information System (INIS)

    Kwon, Yong Eun; Kim, Hyun Myung; Jung, Seun Ho; Park, Se Yeon

    2010-01-01

    β-CD and SBE-β-CD functioned as a solubilizing agent against three flavonoids. SBE-β-CD is more efficient than native β-CD in solubility enhancement of tested flavonoids. All three tested flavonoids have antioxidant ability. Flavonoid-CD complex positively affected the antioxidant activity comparing with free flavonoids. Throughout this research, SBE-β-CD showed better complexation capacity for the solubility enhancement and bioavailability of tested flavonoids comparing with native β-CD. Flavonoids are polyphenolic photochemicals generally found in plants, foods, and beverages. They contribute to plant colors in fruit, leaves providing a wide spectrum of color from red to blue in flowers. Flavonoids have many good physiological activities such as the antioxidant, antitumor, and antibacterial activities which have been a focus of the attention of many researchers. There are four subgroups of flavonoids, flavone, flavonol, flavanone, and isoflavone, according to their chemical structure

  13. Water soluble nano-scale transient material germanium oxide for zero toxic waste based environmentally benign nano-manufacturing

    KAUST Repository

    Almuslem, A. S.

    2017-02-14

    In the recent past, with the advent of transient electronics for mostly implantable and secured electronic applications, the whole field effect transistor structure has been dissolved in a variety of chemicals. Here, we show simple water soluble nano-scale (sub-10 nm) germanium oxide (GeO) as the dissolvable component to remove the functional structures of metal oxide semiconductor devices and then reuse the expensive germanium substrate again for functional device fabrication. This way, in addition to transiency, we also show an environmentally friendly manufacturing process for a complementary metal oxide semiconductor (CMOS) technology. Every year, trillions of complementary metal oxide semiconductor (CMOS) electronics are manufactured and billions are disposed, which extend the harmful impact to our environment. Therefore, this is a key study to show a pragmatic approach for water soluble high performance electronics for environmentally friendly manufacturing and bioresorbable electronic applications.

  14. Design of tablets for the delayed and complete release of poorly water-soluble weak base drugs using SBE7M-β-CD as a solubilizing agent.

    Science.gov (United States)

    Rao, Venkatramana M; Zannou, Erika A; Stella, Valentino J

    2011-04-01

    The challenge of designing a delayed-release oral dosage form is significantly increased when the drug substance is poorly water soluble. This manuscript describes the design and characterization of a novel controlled-release film-coated tablet for the pH-triggered delayed and complete release of poorly water-soluble weak base drugs. Delivery of weak bases is specifically highlighted with the use of dipyridamole and prazosin as model compounds. Tailored delayed release is achieved with a combination of an insoluble but semipermeable polymer and an enteric polymer, such as cellulose acetate and hydroxypropyl cellulose phthalate, respectively, as coatings. The extent of the time lag prior to complete release depends on the film-coating composition and thickness. Complete release is achieved by the addition of a cyclodextrin, namely SBE7M-β-CD with or without a pH modifier added to the tablet core to ensure complete solubilization and release of the drug substance. The film-coating properties allow the complex formation/solubilization to occur in situ. Additionally, the drug release rate can be modulated on the basis of the cyclodextrin to drug molar ratio. This approach offers a platform technology for delayed release of potent but poorly soluble drugs and the release can be modulated by adjusting the film-coating composition and thickness and/or the cyclodextrin and pH modifier, if necessary. Copyright © 2010 Wiley-Liss, Inc.

  15. Quantification of the level of fat-soluble vitamins in feed based on the novel microemulsion electrokinetic chromatography (MEEKC) method.

    Science.gov (United States)

    Olędzka, Ilona; Kowalski, Piotr; Bałuch, Alicja; Bączek, Tomasz; Paradziej-Łukowicz, Jolanta; Taciak, Marcin; Pastuszewska, Barbara

    2014-02-01

    Simultaneous quantification of liposoluble vitamins is not a new area of interest, since these compounds co-determine the nutritional quality of food and feed, a field widely explored in the human and animal diet. However, the development of appropriate methods is still a matter of concern, especially when the vitamin composition is highly complex, as is the case with feed designated for laboratory animals, representing a higher health and microbiological status. A method combining microemulsion electrokinetic chromatography (MEEKC) with liquid-liquid extraction was developed for the determination of four fat-soluble vitamins in animal feed. A separation medium consisting of 25 mmol L⁻¹ phosphate buffer (pH 2.5), 2-propanol, 1-butanol, sodium dodecyl sulfate and octane allowed the simultaneous determination of vitamins A, D, E and K within a reasonable time of 25 min. The polarity of the separation voltage was reversed in view of the strongly suppressed electro-osmotic flow, and the applied voltage was set at 12 kV. The fat-soluble vitamins were separated in the order of decreasing hydrophobicity. It was proved that the proposed MEEKC method was sufficiently specific and sensitive for screening fat-soluble vitamins in animal feed samples after their sterilization. © 2013 Society of Chemical Industry.

  16. Retrograde curves of solidus and solubility

    International Nuclear Information System (INIS)

    Vasil'ev, M.V.

    1979-01-01

    The investigation was concerned with the constitutional diagrams of the eutectic type with ''retrograde solidus'' and ''retrograde solubility curve'' which must be considered as diagrams with degenerate monotectic transformation. The solidus and the solubility curves form a retrograde curve with a common retrograde point representing the solubility maximum. The two branches of the Aetrograde curve can be described with the aid of two similar equations. Presented are corresponding equations for the Cd-Zn system and shown is the possibility of predicting the run of the solubility curve

  17. Uncertainties in model-based outcome predictions for treatment planning

    International Nuclear Information System (INIS)

    Deasy, Joseph O.; Chao, K.S. Clifford; Markman, Jerry

    2001-01-01

    Purpose: Model-based treatment-plan-specific outcome predictions (such as normal tissue complication probability [NTCP] or the relative reduction in salivary function) are typically presented without reference to underlying uncertainties. We provide a method to assess the reliability of treatment-plan-specific dose-volume outcome model predictions. Methods and Materials: A practical method is proposed for evaluating model prediction based on the original input data together with bootstrap-based estimates of parameter uncertainties. The general framework is applicable to continuous variable predictions (e.g., prediction of long-term salivary function) and dichotomous variable predictions (e.g., tumor control probability [TCP] or NTCP). Using bootstrap resampling, a histogram of the likelihood of alternative parameter values is generated. For a given patient and treatment plan we generate a histogram of alternative model results by computing the model predicted outcome for each parameter set in the bootstrap list. Residual uncertainty ('noise') is accounted for by adding a random component to the computed outcome values. The residual noise distribution is estimated from the original fit between model predictions and patient data. Results: The method is demonstrated using a continuous-endpoint model to predict long-term salivary function for head-and-neck cancer patients. Histograms represent the probabilities for the level of posttreatment salivary function based on the input clinical data, the salivary function model, and the three-dimensional dose distribution. For some patients there is significant uncertainty in the prediction of xerostomia, whereas for other patients the predictions are expected to be more reliable. In contrast, TCP and NTCP endpoints are dichotomous, and parameter uncertainties should be folded directly into the estimated probabilities, thereby improving the accuracy of the estimates. Using bootstrap parameter estimates, competing treatment

  18. Meta-path based heterogeneous combat network link prediction

    Science.gov (United States)

    Li, Jichao; Ge, Bingfeng; Yang, Kewei; Chen, Yingwu; Tan, Yuejin

    2017-09-01

    The combat system-of-systems in high-tech informative warfare, composed of many interconnected combat systems of different types, can be regarded as a type of complex heterogeneous network. Link prediction for heterogeneous combat networks (HCNs) is of significant military value, as it facilitates reconfiguring combat networks to represent the complex real-world network topology as appropriate with observed information. This paper proposes a novel integrated methodology framework called HCNMP (HCN link prediction based on meta-path) to predict multiple types of links simultaneously for an HCN. More specifically, the concept of HCN meta-paths is introduced, through which the HCNMP can accumulate information by extracting different features of HCN links for all the six defined types. Next, an HCN link prediction model, based on meta-path features, is built to predict all types of links of the HCN simultaneously. Then, the solution algorithm for the HCN link prediction model is proposed, in which the prediction results are obtained by iteratively updating with the newly predicted results until the results in the HCN converge or reach a certain maximum iteration number. Finally, numerical experiments on the dataset of a real HCN are conducted to demonstrate the feasibility and effectiveness of the proposed HCNMP, in comparison with 30 baseline methods. The results show that the performance of the HCNMP is superior to those of the baseline methods.

  19. Comparison of Simple Versus Performance-Based Fall Prediction Models

    Directory of Open Access Journals (Sweden)

    Shekhar K. Gadkaree BS

    2015-05-01

    Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “ any fall ” and “ recurrent falls .” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.

  20. NAPR: a Cloud-Based Framework for Neuroanatomical Age Prediction.

    Science.gov (United States)

    Pardoe, Heath R; Kuzniecky, Ruben

    2018-01-01

    The availability of cloud computing services has enabled the widespread adoption of the "software as a service" (SaaS) approach for software distribution, which utilizes network-based access to applications running on centralized servers. In this paper we apply the SaaS approach to neuroimaging-based age prediction. Our system, named "NAPR" (Neuroanatomical Age Prediction using R), provides access to predictive modeling software running on a persistent cloud-based Amazon Web Services (AWS) compute instance. The NAPR framework allows external users to estimate the age of individual subjects using cortical thickness maps derived from their own locally processed T1-weighted whole brain MRI scans. As a demonstration of the NAPR approach, we have developed two age prediction models that were trained using healthy control data from the ABIDE, CoRR, DLBS and NKI Rockland neuroimaging datasets (total N = 2367, age range 6-89 years). The provided age prediction models were trained using (i) relevance vector machines and (ii) Gaussian processes machine learning methods applied to cortical thickness surfaces obtained using Freesurfer v5.3. We believe that this transparent approach to out-of-sample evaluation and comparison of neuroimaging age prediction models will facilitate the development of improved age prediction models and allow for robust evaluation of the clinical utility of these methods.

  1. Gas solubilities widespread applications

    CERN Document Server

    Gerrard, William

    1980-01-01

    Gas Solubilities: Widespread Applications discusses several topics concerning the various applications of gas solubilities. The first chapter of the book reviews Henr's law, while the second chapter covers the effect of temperature on gas solubility. The third chapter discusses the various gases used by Horiuti, and the following chapters evaluate the data on sulfur dioxide, chlorine data, and solubility data for hydrogen sulfide. Chapter 7 concerns itself with solubility of radon, thoron, and actinon. Chapter 8 tackles the solubilities of diborane and the gaseous hydrides of groups IV, V, and

  2. Mechanism and kinetics of the loss of poorly soluble drugs from liposomal carriers studied by a novel flow field-flow fractionation-based drug release-/transfer-assay.

    Science.gov (United States)

    Hinna, Askell Hvid; Hupfeld, Stefan; Kuntsche, Judith; Bauer-Brandl, Annette; Brandl, Martin

    2016-06-28

    Liposomes represent a versatile drug formulation approach e.g. for improving the water-solubility of poorly soluble drugs but also to achieve drug targeting and controlled release. For the latter applications it is essential that the drug remains associated with the liposomal carrier during transit in the vascular bed. A range of in vitro test methods has been suggested over the years for prediction of the release of drug from liposomal carriers. The majority of these fail to give a realistic prediction for poorly water-soluble drugs due to the intrinsic tendency of such compounds to remain associated with liposome bilayers even upon extensive dilution. Upon i.v. injection, in contrast, rapid drug loss often occurs due to drug transfer from the liposomal carriers to endogenous lipophilic sinks such as lipoproteins, plasma proteins or membranes of red blood cells and endothelial cells. Here we report on the application of a recently introduced in vitro predictive drug transfer assay based on incubation of the liposomal drug carrier with large multilamellar liposomes, the latter serving as a biomimetic model sink, using flow field-flow fractionation as a tool to separate the two types of liposomes. By quantifying the amount of drug remaining associated with the liposomal drug carrier as well as that transferred to the acceptor liposomes at distinct times of incubation, both the kinetics of drug transfer and release to the water phase could be established for the model drug p-THPP (5,10,15,20-tetrakis(4-hydroxyphenyl)21H,23H-porphine). p-THPP is structurally similar to temoporfin, a photosensitizer which is under clinical evaluation in a liposomal formulation. Mechanistic insights were gained by varying the donor-to-acceptor lipid mass ratio, size and lamellarity of the liposomes. Drug transfer kinetics from one liposome to another was found rate determining as compared to redistribution from the outermost to the inner concentric bilayers, such that the overall

  3. Implementation of neural network based non-linear predictive

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1998-01-01

    The paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems including open loop unstable and non-minimum phase systems, but has also been proposed extended for the control of non......-linear systems. GPC is model-based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis on an efficient Quasi......-Newton optimization algorithm. The performance is demonstrated on a pneumatic servo system....

  4. A novel water-based process produces eco-friendly bio-adhesive made from green cross-linked soybean soluble polysaccharide and soy protein.

    Science.gov (United States)

    Yuan, Cheng; Chen, Mingsong; Luo, Jing; Li, Xiaona; Gao, Qiang; Li, Jianzhang

    2017-08-01

    In this study, an eco-friendly soy protein adhesive was developed that utilized two components from soybean meal without addition of any toxic material. A plant-based, water-soluble and inexpensive soybean soluble polysaccharide was used as the novel renewable material to combine with soy protein to produce a soy protein adhesive. Three-plywood was fabricated with the resulting adhesive, and its wet shear strength was measured. The results showed the wet shear strength of plywood bonded by the adhesive reached 0.99MPa, meeting the water resistance requirement for interior use panels. This improvement was attributed to the following reasons: (1) Combination of cross-linked soybean soluble polysaccharide and soy protein formed an interpenetrating network structure, improving the thermal stability and water resistance of the cured adhesive. (2) Adding CL-SSPS decreased the adhesive viscosity to 15.14Pas, which increased the amount of the adhesive that penetrate the wood's surface and formed more interlocks. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Prediction-based Dynamic Energy Management in Wireless Sensor Networks

    Science.gov (United States)

    Wang, Xue; Ma, Jun-Jie; Wang, Sheng; Bi, Dao-Wei

    2007-01-01

    Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

  6. Prediction-based Dynamic Energy Management in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Dao-Wei Bi

    2007-03-01

    Full Text Available Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

  7. Development of an irrigation control device based on solar radiation and its adaptability for cultivation of high soluble solid tomato fruit in root zone restriction culture

    International Nuclear Information System (INIS)

    Nitta, M.; Shibuya, K.; Kubai, K.; Komatsu, H.; Hosokawa, T.; Nakamura, K.

    2009-01-01

    An irrigation control device based on solar radiation was developed to allow automatic irrigation management for high soluble solid tomato fruit production in root zone restriction culture. Its adaptability for long-term cultivation (planting carried out in early September and harvesting ending in late June) of high soluble solid tomato fruit in root zone restriction culture was examined. The following results were obtained: 1. The control device was composed of generally available electronic parts. A change of setting was possible for the irrigation starting point, the irrigation time period, and the once amount of irrigation. For the first irrigation of the day, one of two irrigation control modes can be chosen; the first determines irrigation dependent on the solar radiation after the irrigated time of the previous day. The second mode irrigates at a set time. 2. The correlation between the total integrated solar radiation and the evapotranspiration rate of tomato plants were investigated. Positive correlations were observed for each month from October to June. Moreover, total integrated solar radiation per unit evapotranspiration was different for each month. 3. In long-term cultivation of tomato fruit using this device, the marketable yield of high soluble solid tomato fruit (more than Brix 8%) was 9.7t/10a. 4. This device exhibited the necessary adaptability for use in long-term cultivation of high soluble solid tomato fruit in root zone restriction culture, by changing the set value of the irrigation starting point and the irrigation time period in accordance with the growth period

  8. Analysis of americium, plutonium and technetium solubility in groundwater

    International Nuclear Information System (INIS)

    Takeda, Seiji

    1999-08-01

    Safety assessments for geologic disposal of radioactive waste generally use solubilities of radioactive elements as the parameter restricting the dissolution of the elements from a waste matrix. This study evaluated americium, plutonium and technetium solubilities under a variety of geochemical conditions using the geochemical model EQ3/6. Thermodynamic data of elements used in the analysis were provided in the JAERI-data base. Chemical properties of both natural groundwater and interstitial water in buffer materials (bentonite and concrete) were investigated to determine the variations in Eh, pH and ligand concentrations (CO 3 2- , F - , PO 4 3- , SO 4 2- , NO 3 - and NH 4 + ). These properties can play an important role in the complexation of radioactive elements. Effect of the groundwater chemical properties on the solubility and formation of chemical species for americium, plutonium and technetium was predicted based on the solubility analyses under a variety of geochemical conditions. The solubility and speciation of the radioactive elements were estimated, taking into account the possible range of chemical compositions determined from the groundwater investigation. (author)

  9. Time-sensitive Customer Churn Prediction based on PU Learning

    OpenAIRE

    Wang, Li; Chen, Chaochao; Zhou, Jun; Li, Xiaolong

    2018-01-01

    With the fast development of Internet companies throughout the world, customer churn has become a serious concern. To better help the companies retain their customers, it is important to build a customer churn prediction model to identify the customers who are most likely to churn ahead of time. In this paper, we propose a Time-sensitive Customer Churn Prediction (TCCP) framework based on Positive and Unlabeled (PU) learning technique. Specifically, we obtain the recent data by shortening the...

  10. Cloud Based Metalearning System for Predictive Modeling of Biomedical Data

    Directory of Open Access Journals (Sweden)

    Milan Vukićević

    2014-01-01

    Full Text Available Rapid growth and storage of biomedical data enabled many opportunities for predictive modeling and improvement of healthcare processes. On the other side analysis of such large amounts of data is a difficult and computationally intensive task for most existing data mining algorithms. This problem is addressed by proposing a cloud based system that integrates metalearning framework for ranking and selection of best predictive algorithms for data at hand and open source big data technologies for analysis of biomedical data.

  11. Accurate Multisteps Traffic Flow Prediction Based on SVM

    Directory of Open Access Journals (Sweden)

    Zhang Mingheng

    2013-01-01

    Full Text Available Accurate traffic flow prediction is prerequisite and important for realizing intelligent traffic control and guidance, and it is also the objective requirement for intelligent traffic management. Due to the strong nonlinear, stochastic, time-varying characteristics of urban transport system, artificial intelligence methods such as support vector machine (SVM are now receiving more and more attentions in this research field. Compared with the traditional single-step prediction method, the multisteps prediction has the ability that can predict the traffic state trends over a certain period in the future. From the perspective of dynamic decision, it is far important than the current traffic condition obtained. Thus, in this paper, an accurate multi-steps traffic flow prediction model based on SVM was proposed. In which, the input vectors were comprised of actual traffic volume and four different types of input vectors were compared to verify their prediction performance with each other. Finally, the model was verified with actual data in the empirical analysis phase and the test results showed that the proposed SVM model had a good ability for traffic flow prediction and the SVM-HPT model outperformed the other three models for prediction.

  12. Gene function prediction based on Gene Ontology Hierarchy Preserving Hashing.

    Science.gov (United States)

    Zhao, Yingwen; Fu, Guangyuan; Wang, Jun; Guo, Maozu; Yu, Guoxian

    2018-02-23

    Gene Ontology (GO) uses structured vocabularies (or terms) to describe the molecular functions, biological roles, and cellular locations of gene products in a hierarchical ontology. GO annotations associate genes with GO terms and indicate the given gene products carrying out the biological functions described by the relevant terms. However, predicting correct GO annotations for genes from a massive set of GO terms as defined by GO is a difficult challenge. To combat with this challenge, we introduce a Gene Ontology Hierarchy Preserving Hashing (HPHash) based semantic method for gene function prediction. HPHash firstly measures the taxonomic similarity between GO terms. It then uses a hierarchy preserving hashing technique to keep the hierarchical order between GO terms, and to optimize a series of hashing functions to encode massive GO terms via compact binary codes. After that, HPHash utilizes these hashing functions to project the gene-term association matrix into a low-dimensional one and performs semantic similarity based gene function prediction in the low-dimensional space. Experimental results on three model species (Homo sapiens, Mus musculus and Rattus norvegicus) for interspecies gene function prediction show that HPHash performs better than other related approaches and it is robust to the number of hash functions. In addition, we also take HPHash as a plugin for BLAST based gene function prediction. From the experimental results, HPHash again significantly improves the prediction performance. The codes of HPHash are available at: http://mlda.swu.edu.cn/codes.php?name=HPHash. Copyright © 2018 Elsevier Inc. All rights reserved.

  13. The effect of genealogy-based haplotypes on genomic prediction

    DEFF Research Database (Denmark)

    Edriss, Vahid; Fernando, Rohan L.; Su, Guosheng

    2013-01-01

    on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. Methods A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using...... local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (pi) of the haplotype covariates had zero effect......, i.e. a Bayesian mixture method. Results About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some...

  14. Pure Phase Solubility Limits: LANL

    International Nuclear Information System (INIS)

    C. Stockman

    2001-01-01

    , complex stability constants, and redox potentials for radionuclides in different oxidation states, form the underlying database to be used for those calculations. The potentially low solubilities of many radionuclides in natural waters constitute the first barrier for their migration from the repository into the environment. Evaluation of this effect requires a knowledge of the site-specific water chemistry and the expected spatial and temporal ranges of its variability. Quantitative determinations of radionuclide solubility in waters within the range of chemistry must be made. Speciation and molecular complexation must be ascertained to interpret and apply solubility results. The solubilities thus determined can be used to assess the effectiveness of solubility in limiting radionuclide migration. These solubilities can also be used to evaluate the effectiveness of other retardation processes expected to occur once dissolution of the source material and migration begin. Understanding the solubility behavior of radionuclides will assist in designing valuable sorption experiments that must be conducted below the solubility limit since only soluble species participate in surface reactions and sorption processes. The present strategy for radionuclide solubility tasks has been to provide a solubility model from bulk-experiments that attempt to bracket the estimate made for this Analysis and Modeling Report (AMR) of water conditions on site. The long-term goal must be to develop a thermodynamic database for solution speciation and solid-state determination as a prerequisite for transport calculations and interpretation of empirical solubility data. The model has to be self-consistent and tested against known solubility studies in order to predict radionuclide solubilities over the continuous distribution ranges of potential water compositions for performance assessment of the site. Solubility studies upper limits for radionuclide concentrations in natural waters. The

  15. Pure Phase Solubility Limits: LANL

    Energy Technology Data Exchange (ETDEWEB)

    C. Stockman

    2001-01-26

    products, complex stability constants, and redox potentials for radionuclides in different oxidation states, form the underlying database to be used for those calculations. The potentially low solubilities of many radionuclides in natural waters constitute the first barrier for their migration from the repository into the environment. Evaluation of this effect requires a knowledge of the site-specific water chemistry and the expected spatial and temporal ranges of its variability. Quantitative determinations of radionuclide solubility in waters within the range of chemistry must be made. Speciation and molecular complexation must be ascertained to interpret and apply solubility results. The solubilities thus determined can be used to assess the effectiveness of solubility in limiting radionuclide migration. These solubilities can also be used to evaluate the effectiveness of other retardation processes expected to occur once dissolution of the source material and migration begin. Understanding the solubility behavior of radionuclides will assist in designing valuable sorption experiments that must be conducted below the solubility limit since only soluble species participate in surface reactions and sorption processes. The present strategy for radionuclide solubility tasks has been to provide a solubility model from bulk-experiments that attempt to bracket the estimate made for this Analysis and Modeling Report (AMR) of water conditions on site. The long-term goal must be to develop a thermodynamic database for solution speciation and solid-state determination as a prerequisite for transport calculations and interpretation of empirical solubility data. The model has to be self-consistent and tested against known solubility studies in order to predict radionuclide solubilities over the continuous distribution ranges of potential water compositions for performance assessment of the site. Solubility studies upper limits for radionuclide concentrations in natural waters. The

  16. Photoswitchable and Water-Soluble Fluorescent Nano-Aggregates Based on a Diarylethene-Dansyl Dyad and Liposome.

    Science.gov (United States)

    Cheng, Hongbo; Ma, Pin; Wang, Yanan; Hu, Guofei; Fang, Shibi; Fang, Yanyan; Lin, Yuan

    2017-01-17

    In this work, a unique approach is developed to generate photoswitchable and water-soluble fluorescent nano-aggregates. Initially, a new light-controlled diarylethene-dansyl dyad DAE 1 is formed by linking two dansyl fluorophores covalently to a symmetrical dithienylethene backbone, whose photophysical properties can be reversibly switched by optical stimuli. Subsequently, the water insolubility of the molecular switch 1 is overcome by incorporating it into the bilayer of liposome DPPC (1,2-dihexadecanoyl-sn-glycero-3-phosphocholine) in water. This strategy creates stable fluorescent nano-aggregates OF-1@DPPC (≈25 nm diameter) that are soluble in an aqueous medium. The nano-aggregates OF-1@DPPC retain and even improve the photoswitchable fluorescence properties of DAE 1. More importantly, OF-1@DPPC exhibits a remarkable photostability and fatigue resistance after 5 cycles of irradiation with UV and visible light, which is crucial for its practical application. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...... and related to the uncertainty of the impulse response coefficients. The simulations can be used to benchmark l2 MPC against FIR based robust MPC as well as to estimate the maximum performance improvements by robust MPC....

  18. Comparisons of Faulting-Based Pavement Performance Prediction Models

    Directory of Open Access Journals (Sweden)

    Weina Wang

    2017-01-01

    Full Text Available Faulting prediction is the core of concrete pavement maintenance and design. Highway agencies are always faced with the problem of lower accuracy for the prediction which causes costly maintenance. Although many researchers have developed some performance prediction models, the accuracy of prediction has remained a challenge. This paper reviews performance prediction models and JPCP faulting models that have been used in past research. Then three models including multivariate nonlinear regression (MNLR model, artificial neural network (ANN model, and Markov Chain (MC model are tested and compared using a set of actual pavement survey data taken on interstate highway with varying design features, traffic, and climate data. It is found that MNLR model needs further recalibration, while the ANN model needs more data for training the network. MC model seems a good tool for pavement performance prediction when the data is limited, but it is based on visual inspections and not explicitly related to quantitative physical parameters. This paper then suggests that the further direction for developing the performance prediction model is incorporating the advantages and disadvantages of different models to obtain better accuracy.

  19. Static Formation Temperature Prediction Based on Bottom Hole Temperature

    Directory of Open Access Journals (Sweden)

    Changwei Liu

    2016-08-01

    Full Text Available Static formation temperature (SFT is required to determine the thermophysical properties and production parameters in geothermal and oil reservoirs. However, it is not easy to determine SFT by both experimental and physical methods. In this paper, a mathematical approach to predicting SFT, based on a new model describing the relationship between bottom hole temperature (BHT and shut-in time, has been proposed. The unknown coefficients of the model were derived from the least squares fit by the particle swarm optimization (PSO algorithm. Additionally, the ability to predict SFT using a few BHT data points (such as the first three, four, or five points of a data set was evaluated. The accuracy of the proposed method to predict SFT was confirmed by a deviation percentage less than ±4% and a high regression coefficient R2 (>0.98. The proposed method could be used as a practical tool to predict SFT in both geothermal and oil wells.

  20. Prediction on carbon dioxide emissions based on fuzzy rules

    Science.gov (United States)

    Pauzi, Herrini; Abdullah, Lazim

    2014-06-01

    There are several ways to predict air quality, varying from simple regression to models based on artificial intelligence. Most of the conventional methods are not sufficiently able to provide good forecasting performances due to the problems with non-linearity uncertainty and complexity of the data. Artificial intelligence techniques are successfully used in modeling air quality in order to cope with the problems. This paper describes fuzzy inference system (FIS) to predict CO2 emissions in Malaysia. Furthermore, adaptive neuro-fuzzy inference system (ANFIS) is used to compare the prediction performance. Data of five variables: energy use, gross domestic product per capita, population density, combustible renewable and waste and CO2 intensity are employed in this comparative study. The results from the two model proposed are compared and it is clearly shown that the ANFIS outperforms FIS in CO2 prediction.

  1. Relative reductions in soluble CD30 levels post-transplant predict acute graft function in islet allograft recipients receiving three different immunosuppression protocols.

    Science.gov (United States)

    Hire, Kelly; Hering, Bernhard; Bansal-Pakala, Pratima

    2010-08-01

    Despite advances in islet transplantation, challenges remain in monitoring for anti-islet immune responses. Soluble CD30 (sCD30) has been investigated as a predictor of acute rejection in kidney, lung, and heart transplantation as well as in a single study in human islet cell recipients. In this study, sCD30 levels were retrospectively assessed in 19 allograft recipients treated with three different immunosuppression induction therapies. Soluble CD30 levels were assessed at pre-transplant; early post-transplant (day 4-day 7); one-month post-transplant; and late post-transplant (day 90-day 120) and then correlated with eventual graft outcomes at 1-year follow-up. Results showed no correlation between mean serum sCD30 levels at any point in time pre- or post-transplant and graft function at 1-year follow-up. However, analysis demonstrated that mean sCD30 levels at day 28 or day 90-day 120 decreased from pre-transplant levels in recipients with long-term islet allograft function compared to recipients with partial or non-graft function (a decrease of 43.6+/-25.6% compared to 16.7+/-35.2%, psCD30 levels post-transplant overall. A larger reduction post-transplant correlated with full graft function. The results demonstrate that a relative reduction in sCD30 levels post-transplant may be applicable as a biomarker to monitor graft function in islet allograft recipients. Additionally, knowledge of the impact of various immunosuppression protocols on the timing and extent of changes in post-transplant sCD30 levels could aid in patient-specific tailoring of immunosuppression. Copyright © 2010 Elsevier B.V. All rights reserved.

  2. Warning system based on theoretical-experimental study of dispersion of soluble pollutants in rivers Sistema de alerta com base em estudo teórico-experimental de dispersão de poluentes solúveis em rios

    Directory of Open Access Journals (Sweden)

    Celso B. de M. Ribeiro

    2011-10-01

    Full Text Available Information about capacity of transport and dispersion of soluble pollutants in natural streams are important in the management of water resources, especially in planning preventive measures to minimize the problems caused by accidental or intentional waste, in public health and economic activities that depend on the use of water. Considering this importance, this study aimed to develop a warning system for rivers, based on experimental techniques using tracers and analytical equations of one-dimensional transport of soluble pollutants conservative, to subsidizing the decision-making in the management of water resources. The system was development in JAVA programming language and MySQL database can predict the travel time of pollutants clouds from a point of eviction and graphically displays the temporal distribution of concentrations of passage clouds, in a particular location, downstream from the point of its launch.Informações sobre a capacidade de transporte e dispersão de poluentes solúveis em cursos de água naturais são importantes no gerenciamento dos recursos hídricos, principalmente no planejamento preventivo de medidas que visem a minimizar problemas à saúde pública e às atividades econômicas que dependem do uso da água, ocasionados por despejos acidentais ou intencionais. Considerando tal importância, este trabalho teve como objetivo desenvolver um sistema de alerta para rios, com base em resultados experimentais, utilizando técnicas de traçadores e equações analíticas de transporte unidimensional de poluentes solúveis conservativos, visando a subsidiar a tomada de decisão no gerenciamento dos recursos hídricos. O sistema desenvolvido em linguagem de programação JAVA e banco de dados MySQL permite prever o tempo de percurso da nuvem de poluentes a partir de um ponto de despejo de um poluente e apresenta, graficamente, a distribuição temporal de concentrações da passagem da nuvem, em um determinado local,

  3. Drug-target interaction prediction from PSSM based evolutionary information.

    Science.gov (United States)

    Mousavian, Zaynab; Khakabimamaghani, Sahand; Kavousi, Kaveh; Masoudi-Nejad, Ali

    2016-01-01

    The labor-intensive and expensive experimental process of drug-target interaction prediction has motivated many researchers to focus on in silico prediction, which leads to the helpful information in supporting the experimental interaction data. Therefore, they have proposed several computational approaches for discovering new drug-target interactions. Several learning-based methods have been increasingly developed which can be categorized into two main groups: similarity-based and feature-based. In this paper, we firstly use the bi-gram features extracted from the Position Specific Scoring Matrix (PSSM) of proteins in predicting drug-target interactions. Our results demonstrate the high-confidence prediction ability of the Bigram-PSSM model in terms of several performance indicators specifically for enzymes and ion channels. Moreover, we investigate the impact of negative selection strategy on the performance of the prediction, which is not widely taken into account in the other relevant studies. This is important, as the number of non-interacting drug-target pairs are usually extremely large in comparison with the number of interacting ones in existing drug-target interaction data. An interesting observation is that different levels of performance reduction have been attained for four datasets when we change the sampling method from the random sampling to the balanced sampling. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Multi-Objective Predictive Balancing Control of Battery Packs Based on Predictive Current

    Directory of Open Access Journals (Sweden)

    Wenbiao Li

    2016-04-01

    Full Text Available Various balancing topology and control methods have been proposed for the inconsistency problem of battery packs. However, these strategies only focus on a single objective, ignore the mutual interaction among various factors and are only based on the external performance of the battery pack inconsistency, such as voltage balancing and state of charge (SOC balancing. To solve these problems, multi-objective predictive balancing control (MOPBC based on predictive current is proposed in this paper, namely, in the driving process of an electric vehicle, using predictive control to predict the battery pack output current the next time. Based on this information, the impact of the battery pack temperature caused by the output current can be obtained. Then, the influence is added to the battery pack balancing control, which makes the present degradation, temperature, and SOC imbalance achieve balance automatically due to the change of the output current the next moment. According to MOPBC, the simulation model of the balancing circuit is built with four cells in Matlab/Simulink. The simulation results show that MOPBC is not only better than the other traditional balancing control strategies but also reduces the energy loss in the balancing process.

  5. Histidine-functionalized water-soluble nanoparticles for biomimetic nucleophilic/general-base catalysis under acidic conditions.

    Science.gov (United States)

    Chadha, Geetika; Zhao, Yan

    2013-10-21

    Cross-linking the micelles of 4-dodecyloxybenzyltripropargylammonium bromide by 1,4-diazidobutane-2,3-diol in the presence of azide-functionalized imidazole derivatives yielded surface-cross-linked micelles (SCMs) with imidazole groups on the surface. The resulting water-soluble nanoparticles were found, by fluorescence spectroscopy, to contain hydrophobic binding sites. The imidazole groups promoted the photo-deprotonation of 2-naphthol at pH 6 and catalyzed the hydrolysis of p-nitrophenylacetate (PNPA) in aqueous solution at pH ≥ 4. Although the overall hydrolysis rate slowed down with decreasing solution pH, the catalytic effect of the imidazole became stronger because the reactions catalyzed by unfunctionalized SCMs slowed down much more. The unusual ability of the imidazole–SCMs to catalyze the hydrolysis of PNPA under acidic conditions was attributed to the local hydrophobicity and the positive nature of the SCMs.

  6. Seawater-Soluble Pigments and Their Potential Use in Self-Polishing Antifouling Paints: Simulation-based Screening Tool

    DEFF Research Database (Denmark)

    Kiil, Søren; Dam-Johansen, Kim; Erik Weinell, Claus

    2002-01-01

    This work concerns the on-going development of efficient and environmentally friendly antifouling paints for biofouling control on large ocean-going ships. It is illustrated how a detailed mathematical model for a self-polishing antifouling paint exposed to seawater can be used as a product...... solubility and seawater diffusivity of dissolved pigment species have a significant influence on the polishing and leaching behaviour of a typical self-polishing paint system. The pigment size distribution, on the other hand, only has a minor influence on the paint-seawater interaction. Simulations also...... indicate that only compounds which are effective against biofouling at very low seawater concentrations are useful as active antifouling paint ingredients. The need for model verification and exploration of practical issues, subsequent a given pigment has been found of interest, is discussed. The model...

  7. Study on properties of UV-curable films based on alkali-soluble photosensitive polysiloxane urethane acrylate oligomer

    International Nuclear Information System (INIS)

    Sun Fang; Zhang Nan; Du Hongguang; Jiang Shengling

    2011-01-01

    A UV-curable alkali-soluble polysiloxane urethane acrylate (APSUA) for solder mask was designed and synthesized in this work. The effect of composition of APSUA on physical and mechanical properties of UV curing APSUA materials including water resistance, volume shrinkage, hardness, tensile strength, elongation and heat resistance, was investigated in this paper. The results showed that reactive monomers with hydroxyl bonding could increase water absorption of the APSUA. The water absorption of the APSUA decreased with increasing crosslinking yields. The volume shrinkage of the APSUA decreased with increasing APSUA concentrations in the system and the volume shrinkage of investigated APSUA was lower than 6%. Multi-functional monomer and acrylate monomer with rigid structure could improve hardness of APSUA. When functionality of reactive monomer increased the heat resistance of APSUA could enhanced. The APSUA possesses excellent compatibility with most of acrylate monomers. (authors)

  8. Mechanism and kinetics of the loss of poorly soluble drugs from liposomal carriers studied by a novel flow field-flow fractionation-based drug release-/transfer-assay

    DEFF Research Database (Denmark)

    Hinna, Askell Hvid; Hupfeld, Stefan; Kuntsche, Judith

    2016-01-01

    Liposomes represent a versatile drug formulation approach e.g. for improving the water-solubility of poorly soluble drugs but also to achieve drug targeting and controlled release. For the latter applications it is essential that the drug remains associated with the liposomal carrier during transit...... in the vascular bed. A range of in vitro test methods has been suggested over the years for prediction of the release of drug from liposomal carriers. The majority of these fail to give a realistic prediction for poorly water-soluble drugs due to the intrinsic tendency of such compounds to remain associated...... the amount of drug remaining associated with the liposomal drug carrier as well as that transferred to the acceptor liposomes at distinct times of incubation, boththe kinetics of drug transfer and release to the water phase could be established for the model drug p-THPP (5,10,15,20-tetrakis(4-hydroxyphenyl...

  9. State-based Communication on Time-predictable Multicore Processors

    DEFF Research Database (Denmark)

    Sørensen, Rasmus Bo; Schoeberl, Martin; Sparsø, Jens

    2016-01-01

    Some real-time systems use a form of task-to-task communication called state-based or sample-based communication that does not impose any flow control among the communicating tasks. The concept is similar to a shared variable, where a reader may read the same value multiple times or may not read...... a given value at all. This paper explores time-predictable implementations of state-based communication in network-on-chip based multicore platforms through five algorithms. With the presented analysis of the implemented algorithms, the communicating tasks of one core can be scheduled independently...... of tasks on other cores. Assuming a specific time-predictable multicore processor, we evaluate how the read and write primitives of the five algorithms contribute to the worst-case execution time of the communicating tasks. Each of the five algorithms has specific capabilities that make them suitable...

  10. Predicting footbridge vibrations using a probability-based approach

    DEFF Research Database (Denmark)

    Pedersen, Lars; Frier, Christian

    2017-01-01

    Vibrations in footbridges may be problematic as excessive vibrations may occur as a result of actions of pedestrians. Design-stage predictions of levels of footbridge vibration to the action of a pedestrian are useful and have been employed for many years based on a deterministic approach to mode...

  11. Snippet-based relevance predictions for federated web search

    NARCIS (Netherlands)

    Demeester, Thomas; Nguyen, Dong-Phuong; Trieschnigg, Rudolf Berend; Develder, Chris; Hiemstra, Djoerd

    How well can the relevance of a page be predicted, purely based on snippets? This would be highly useful in a Federated Web Search setting where caching large amounts of result snippets is more feasible than caching entire pages. The experiments reported in this paper make use of result snippets and

  12. A burnout prediction model based around char morphology

    Energy Technology Data Exchange (ETDEWEB)

    T. Wu; E. Lester; M. Cloke [University of Nottingham, Nottingham (United Kingdom). Nottingham Energy and Fuel Centre

    2005-07-01

    Poor burnout in a coal-fired power plant has marked penalties in the form of reduced energy efficiency and elevated waste material that can not be utilized. The prediction of coal combustion behaviour in a furnace is of great significance in providing valuable information not only for process optimization but also for coal buyers in the international market. Coal combustion models have been developed that can make predictions about burnout behaviour and burnout potential. Most of these kinetic models require standard parameters such as volatile content, particle size and assumed char porosity in order to make a burnout prediction. This paper presents a new model called the Char Burnout Model (ChB) that also uses detailed information about char morphology in its prediction. The model can use data input from one of two sources. Both sources are derived from image analysis techniques. The first from individual analysis and characterization of real char types using an automated program. The second from predicted char types based on data collected during the automated image analysis of coal particles. Modelling results were compared with a different carbon burnout kinetic model and burnout data from re-firing the chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen across several residence times. An improved agreement between ChB model and DTF experimental data proved that the inclusion of char morphology in combustion models can improve model predictions. 27 refs., 4 figs., 4 tabs.

  13. A burnout prediction model based around char morphology

    Energy Technology Data Exchange (ETDEWEB)

    Tao Wu; Edward Lester; Michael Cloke [University of Nottingham, Nottingham (United Kingdom). School of Chemical, Environmental and Mining Engineering

    2006-05-15

    Several combustion models have been developed that can make predictions about coal burnout and burnout potential. Most of these kinetic models require standard parameters such as volatile content and particle size to make a burnout prediction. This article presents a new model called the char burnout (ChB) model, which also uses detailed information about char morphology in its prediction. The input data to the model is based on information derived from two different image analysis techniques. One technique generates characterization data from real char samples, and the other predicts char types based on characterization data from image analysis of coal particles. The pyrolyzed chars in this study were created in a drop tube furnace operating at 1300{sup o}C, 200 ms, and 1% oxygen. Modeling results were compared with a different carbon burnout kinetic model as well as the actual burnout data from refiring the same chars in a drop tube furnace operating at 1300{sup o}C, 5% oxygen, and residence times of 200, 400, and 600 ms. A good agreement between ChB model and experimental data indicates that the inclusion of char morphology in combustion models could well improve model predictions. 38 refs., 5 figs., 6 tabs.

  14. Blind Test of Physics-Based Prediction of Protein Structures

    Science.gov (United States)

    Shell, M. Scott; Ozkan, S. Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A.

    2009-01-01

    We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences. PMID:19186130

  15. EMD-Based Predictive Deep Belief Network for Time Series Prediction: An Application to Drought Forecasting

    Directory of Open Access Journals (Sweden)

    Norbert A. Agana

    2018-02-01

    Full Text Available Drought is a stochastic natural feature that arises due to intense and persistent shortage of precipitation. Its impact is mostly manifested as agricultural and hydrological droughts following an initial meteorological phenomenon. Drought prediction is essential because it can aid in the preparedness and impact-related management of its effects. This study considers the drought forecasting problem by developing a hybrid predictive model using a denoised empirical mode decomposition (EMD and a deep belief network (DBN. The proposed method first decomposes the data into several intrinsic mode functions (IMFs using EMD, and a reconstruction of the original data is obtained by considering only relevant IMFs. Detrended fluctuation analysis (DFA was applied to each IMF to determine the threshold for robust denoising performance. Based on their scaling exponents, irrelevant intrinsic mode functions are identified and suppressed. The proposed method was applied to predict different time scale drought indices across the Colorado River basin using a standardized streamflow index (SSI as the drought index. The results obtained using the proposed method was compared with standard methods such as multilayer perceptron (MLP and support vector regression (SVR. The proposed hybrid model showed improvement in prediction accuracy, especially for multi-step ahead predictions.

  16. Connecting clinical and actuarial prediction with rule-based methods.

    Science.gov (United States)

    Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

    2015-06-01

    Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).

  17. Large-scale ligand-based predictive modelling using support vector machines.

    Science.gov (United States)

    Alvarsson, Jonathan; Lampa, Samuel; Schaal, Wesley; Andersson, Claes; Wikberg, Jarl E S; Spjuth, Ola

    2016-01-01

    The increasing size of datasets in drug discovery makes it challenging to build robust and accurate predictive models within a reasonable amount of time. In order to investigate the effect of dataset sizes on predictive performance and modelling time, ligand-based regression models were trained on open datasets of varying sizes of up to 1.2 million chemical structures. For modelling, two implementations of support vector machines (SVM) were used. Chemical structures were described by the signatures molecular descriptor. Results showed that for the larger datasets, the LIBLINEAR SVM implementation performed on par with the well-established libsvm with a radial basis function kernel, but with dramatically less time for model building even on modest computer resources. Using a non-linear kernel proved to be infeasible for large data sizes, even with substantial computational resources on a computer cluster. To deploy the resulting models, we extended the Bioclipse decision support framework to support models from LIBLINEAR and made our models of logD and solubility available from within Bioclipse.

  18. Prediction of Banking Systemic Risk Based on Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Shouwei Li

    2013-01-01

    Full Text Available Banking systemic risk is a complex nonlinear phenomenon and has shed light on the importance of safeguarding financial stability by recent financial crisis. According to the complex nonlinear characteristics of banking systemic risk, in this paper we apply support vector machine (SVM to the prediction of banking systemic risk in an attempt to suggest a new model with better explanatory power and stability. We conduct a case study of an SVM-based prediction model for Chinese banking systemic risk and find the experiment results showing that support vector machine is an efficient method in such case.

  19. Prediction-Based Control for Nonlinear Systems with Input Delay

    Directory of Open Access Journals (Sweden)

    I. Estrada-Sánchez

    2017-01-01

    Full Text Available This work has two primary objectives. First, it presents a state prediction strategy for a class of nonlinear Lipschitz systems subject to constant time delay in the input signal. As a result of a suitable change of variable, the state predictor asymptotically provides the value of the state τ units of time ahead. Second, it proposes a solution to the stabilization and trajectory tracking problems for the considered class of systems using predicted states. The predictor-controller convergence is proved by considering a complete Lyapunov functional. The proposed predictor-based controller strategy is evaluated using numerical simulations.

  20. Rate-Based Model Predictive Control of Turbofan Engine Clearance

    Science.gov (United States)

    DeCastro, Jonathan A.

    2006-01-01

    An innovative model predictive control strategy is developed for control of nonlinear aircraft propulsion systems and sub-systems. At the heart of the controller is a rate-based linear parameter-varying model that propagates the state derivatives across the prediction horizon, extending prediction fidelity to transient regimes where conventional models begin to lose validity. The new control law is applied to a demanding active clearance control application, where the objectives are to tightly regulate blade tip clearances and also anticipate and avoid detrimental blade-shroud rub occurrences by optimally maintaining a predefined minimum clearance. Simulation results verify that the rate-based controller is capable of satisfying the objectives during realistic flight scenarios where both a conventional Jacobian-based model predictive control law and an unconstrained linear-quadratic optimal controller are incapable of doing so. The controller is evaluated using a variety of different actuators, illustrating the efficacy and versatility of the control approach. It is concluded that the new strategy has promise for this and other nonlinear aerospace applications that place high importance on the attainment of control objectives during transient regimes.

  1. Meta-Analysis and Systematic Review to Assess the Role of Soluble FMS-Like Tyrosine Kinase-1 and Placenta Growth Factor Ratio in Prediction of Preeclampsia: The SaPPPhirE Study.

    Science.gov (United States)

    Agrawal, Swati; Cerdeira, Ana Sofia; Redman, Christopher; Vatish, Manu

    2018-02-01

    Preeclampsia is a major cause of morbidity and mortality worldwide. Numerous candidate biomarkers have been proposed for diagnosis and prediction of preeclampsia. Measurement of maternal circulating angiogenesis biomarker as the ratio of sFlt-1 (soluble FMS-like tyrosine kinase-1; an antiangiogenic factor)/PlGF (placental growth factor; an angiogenic factor) reflects the antiangiogenic balance that characterizes incipient or overt preeclampsia. The ratio increases before the onset of the disease and thus may help in predicting preeclampsia. We conducted a meta-analysis to explore the predictive accuracy of sFlt-1/PlGF ratio in preeclampsia. We included 15 studies with 534 cases with preeclampsia and 19 587 controls. The ratio has a pooled sensitivity of 80% (95% confidence interval, 0.68-0.88), specificity of 92% (95% confidence interval, 0.87-0.96), positive likelihood ratio of 10.5 (95% confidence interval, 6.2-18.0), and a negative likelihood ratio of 0.22 (95% confidence interval, 0.13-0.35) in predicting preeclampsia in both high- and low-risk patients. Most of the studies have not made a distinction between early- and late-onset disease, and therefore, the analysis for it could not be done. It can prove to be a valuable screening tool for preeclampsia and may also help in decision-making, treatment stratification, and better resource allocation. © 2017 American Heart Association, Inc.

  2. Lipid-Based Formulations Can Enable the Model Poorly Water-Soluble Weakly Basic Drug Cinnarizine to Precipitate in an Amorphous-Salt Form during in Vitro Digestion

    DEFF Research Database (Denmark)

    Khan, Jamal; Rades, Thomas; Boyd, Ben J

    2016-01-01

    The tendency for poorly water-soluble weakly basic drugs to precipitate in a noncrystalline form during the in vitro digestion of lipid-based formulations (LBFs) was linked to an ionic interaction between drug and fatty acid molecules produced upon lipid digestion. Cinnarizine was chosen as a model...... from the starting free base crystalline material to the hydrochloride salt, thus supporting the case that ionic interactions between weak bases and fatty acid molecules during digestion are responsible for producing amorphous-salts upon precipitation. The conclusion has wide implications...... weakly basic drug and was dissolved in a medium-chain (MC) LBF, which was subject to in vitro lipolysis experiments at various pH levels above and below the reported pKa value of cinnarizine (7.47). The solid-state form of the precipitated drug was analyzed using X-ray diffraction (XRD), Fourier...

  3. Implementation of neural network based non-linear predictive control

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1999-01-01

    This paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems, including open-loop unstable and non-minimum phase systems, but has also been proposed to be extended for the control...... of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...... on an efficient quasi-Newton algorithm. The performance is demonstrated on a pneumatic servo system....

  4. Prediction of potential drug targets based on simple sequence properties

    Directory of Open Access Journals (Sweden)

    Lai Luhua

    2007-09-01

    Full Text Available Abstract Background During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical drugs up to now. Identifying potential drug targets is the first step in the process of modern drug discovery for developing novel therapeutic agents. Therefore, the identification and validation of new and effective drug targets are of great value for drug discovery in both academia and pharmaceutical industry. If a protein can be predicted in advance for its potential application as a drug target, the drug discovery process targeting this protein will be greatly speeded up. In the current study, based on the properties of known drug targets, we have developed a sequence-based drug target prediction method for fast identification of novel drug targets. Results Based on simple physicochemical properties extracted from protein sequences of known drug targets, several support vector machine models have been constructed in this study. The best model can distinguish currently known drug targets from non drug targets at an accuracy of 84%. Using this model, potential protein drug targets of human origin from Swiss-Prot were predicted, some of which have already attracted much attention as potential drug targets in pharmaceutical research. Conclusion We have developed a drug target prediction method based solely on protein sequence information without the knowledge of family/domain annotation, or the protein 3D structure. This method can be applied in novel drug target identification and validation, as well as genome scale drug target predictions.

  5. Source apportionment of size-segregated atmospheric particles based on the major water-soluble components in Lecce (Italy)

    International Nuclear Information System (INIS)

    Contini, D.; Cesari, D.; Genga, A.; Siciliano, M.; Ielpo, P.; Guascito, M.R.; Conte, M.

    2014-01-01

    Atmospheric aerosols have potential effects on human health, on the radiation balance, on climate, and on visibility. The understanding of these effects requires detailed knowledge of aerosol composition and size distributions and of how the different sources contribute to particles of different sizes. In this work, aerosol samples were collected using a 10-stage Micro-Orifice Uniform Deposit Impactor (MOUDI). Measurements were taken between February and October 2011 in an urban background site near Lecce (Apulia region, southeast of Italy). Samples were analysed to evaluate the concentrations of water-soluble ions (SO 4 2− , NO 3 − , NH 4 + , Cl − , Na + , K + , Mg 2+ and Ca 2+ ) and of water-soluble organic and inorganic carbon. The aerosols were characterised by two modes, an accumulation mode having a mass median diameter (MMD) of 0.35 ± 0.02 μm, representing 51 ± 4% of the aerosols and a coarse mode (MMD = 4.5 ± 0.4 μm), representing 49 ± 4% of the aerosols. The data were used to estimate the losses in the impactor by comparison with a low-volume sampler. The average loss in the MOUDI-collected aerosol was 19 ± 2%, and the largest loss was observed for NO 3 − (35 ± 10%). Significant losses were observed for Ca 2+ (16 ± 5%), SO 4 2− (19 ± 5%) and K + (10 ± 4%), whereas the losses for Na + and Mg 2+ were negligible. Size-segregated source apportionment was performed using Positive Matrix Factorization (PMF), which was applied separately to the coarse (size interval 1–18 μm) and accumulation (size interval 0.056–1 μm) modes. The PMF model was able to reasonably reconstruct the concentration in each size-range. The uncertainties in the source apportionment due to impactor losses were evaluated. In the accumulation mode, it was not possible to distinguish the traffic contribution from other combustion sources. In the coarse mode, it was not possible to efficiently separate nitrate from the contribution of crustal/resuspension origin

  6. Source apportionment of size-segregated atmospheric particles based on the major water-soluble components in Lecce (Italy)

    Energy Technology Data Exchange (ETDEWEB)

    Contini, D., E-mail: d.contini@isac.cnr.it [Istituto di Scienze dell' Atmosfera e del Clima, ISAC-CNR, Lecce (Italy); Cesari, D. [Istituto di Scienze dell' Atmosfera e del Clima, ISAC-CNR, Lecce (Italy); Genga, A.; Siciliano, M. [Dipartimento di Scienze e Tecnologie Biologiche e Ambientali, Università del Salento, Lecce (Italy); Ielpo, P. [Istituto di Scienze dell' Atmosfera e del Clima, ISAC-CNR, Lecce (Italy); Istituto di Ricerca Sulle Acque, IRSA-CNR, Bari (Italy); Guascito, M.R. [Dipartimento di Scienze e Tecnologie Biologiche e Ambientali, Università del Salento, Lecce (Italy); Conte, M. [Istituto di Scienze dell' Atmosfera e del Clima, ISAC-CNR, Lecce (Italy)

    2014-02-01

    Atmospheric aerosols have potential effects on human health, on the radiation balance, on climate, and on visibility. The understanding of these effects requires detailed knowledge of aerosol composition and size distributions and of how the different sources contribute to particles of different sizes. In this work, aerosol samples were collected using a 10-stage Micro-Orifice Uniform Deposit Impactor (MOUDI). Measurements were taken between February and October 2011 in an urban background site near Lecce (Apulia region, southeast of Italy). Samples were analysed to evaluate the concentrations of water-soluble ions (SO{sub 4}{sup 2−}, NO{sub 3}{sup −}, NH{sub 4}{sup +}, Cl{sup −}, Na{sup +}, K{sup +}, Mg{sup 2+} and Ca{sup 2+}) and of water-soluble organic and inorganic carbon. The aerosols were characterised by two modes, an accumulation mode having a mass median diameter (MMD) of 0.35 ± 0.02 μm, representing 51 ± 4% of the aerosols and a coarse mode (MMD = 4.5 ± 0.4 μm), representing 49 ± 4% of the aerosols. The data were used to estimate the losses in the impactor by comparison with a low-volume sampler. The average loss in the MOUDI-collected aerosol was 19 ± 2%, and the largest loss was observed for NO{sub 3}{sup −} (35 ± 10%). Significant losses were observed for Ca{sup 2+} (16 ± 5%), SO{sub 4}{sup 2−} (19 ± 5%) and K{sup +} (10 ± 4%), whereas the losses for Na{sup +} and Mg{sup 2+} were negligible. Size-segregated source apportionment was performed using Positive Matrix Factorization (PMF), which was applied separately to the coarse (size interval 1–18 μm) and accumulation (size interval 0.056–1 μm) modes. The PMF model was able to reasonably reconstruct the concentration in each size-range. The uncertainties in the source apportionment due to impactor losses were evaluated. In the accumulation mode, it was not possible to distinguish the traffic contribution from other combustion sources. In the coarse mode, it was not possible to

  7. Hydrothermal solubility of uraninite. Final technical report

    International Nuclear Information System (INIS)

    Parks, G.A.; Pohl, D.C.

    1985-01-01

    Experimental measurements of the solubility of UO 2 from 100 to 300 0 C under 500 bars H 2 , in NaCl solutions at pH from 1 to 8 do not agree with solubilities calculated using existing thermodynamic databases. For pH 2 (hyd) has precipitated and is controlling solubility. For pH > 8, solubilities at all temperatures are much lower than predicted, suggesting that the U(OH)/sub delta/ - complex is much weaker than predicted. Extrapolated to 25 0 C, high pH solubility agrees within experimental error with the upper limit suggested by Ryan and Rai (1983). In the pH range 2 to 6, solubilities are up to three orders of magnitude lower than predicted for temperatures exceeding 200 0 C and up to two orders higher than predicted at lower temperatures. pH dependence in this region is negligible suggesting that U(OH) 4 (aq) predominates, thus the stability of this species is higher than presently estimated at low temperatures, but the enthalpy of solution is smaller. A low maximum observed near pH approx. =3 is presently unexplained. 40 refs., 16 figs., 12 tabs

  8. Driver's mental workload prediction model based on physiological indices.

    Science.gov (United States)

    Yan, Shengyuan; Tran, Cong Chi; Wei, Yingying; Habiyaremye, Jean Luc

    2017-09-15

    Developing an early warning model to predict the driver's mental workload (MWL) is critical and helpful, especially for new or less experienced drivers. The present study aims to investigate the correlation between new drivers' MWL and their work performance, regarding the number of errors. Additionally, the group method of data handling is used to establish the driver's MWL predictive model based on subjective rating (NASA task load index [NASA-TLX]) and six physiological indices. The results indicate that the NASA-TLX and the number of errors are positively correlated, and the predictive model shows the validity of the proposed model with an R 2 value of 0.745. The proposed model is expected to provide a reference value for the new drivers of their MWL by providing the physiological indices, and the driving lesson plans can be proposed to sustain an appropriate MWL as well as improve the driver's work performance.

  9. Ontology-based prediction of surgical events in laparoscopic surgery

    Science.gov (United States)

    Katić, Darko; Wekerle, Anna-Laura; Gärtner, Fabian; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie

    2013-03-01

    Context-aware technologies have great potential to help surgeons during laparoscopic interventions. Their underlying idea is to create systems which can adapt their assistance functions automatically to the situation in the OR, thus relieving surgeons from the burden of managing computer assisted surgery devices manually. To this purpose, a certain kind of understanding of the current situation in the OR is essential. Beyond that, anticipatory knowledge of incoming events is beneficial, e.g. for early warnings of imminent risk situations. To achieve the goal of predicting surgical events based on previously observed ones, we developed a language to describe surgeries and surgical events using Description Logics and integrated it with methods from computational linguistics. Using n-Grams to compute probabilities of followup events, we are able to make sensible predictions of upcoming events in real-time. The system was evaluated on professionally recorded and labeled surgeries and showed an average prediction rate of 80%.

  10. Solubility of pllutonium in alkaline salt solutions

    International Nuclear Information System (INIS)

    Hobbs, D.T.; Edwards, T.B.

    1993-01-01

    Plutonium solubility data from several studies have been evaluated. For each data set, a predictive model has been developed where appropriate. In addition, a statistical model and corresponding prediction intervals for plutonium solubility as a quadratic function of the hydroxide concentration have been developed. Because of the wide range of solution compositions, the solubility of plutonium can vary by as much as three orders of magnitude for any given hydroxide concentration and still remain within the prediction interval. Any nuclear safety assessments that depend on the maximum amount of plutonium dissolved in alkaline salt solutions should use concentrations at least as great as the upper prediction limits developed in this study. To increase the confidence in the prediction model, it is recommended that additional solubility tests be conducted at low hydroxide concentrations and with all of the other solution components involved. To validate the model for application to actual waste solutions, it is recommended that the plutonium solubilities in actual waste solutions be determined and compared to the values predicted by the quadratic model

  11. Transcription factor binding sites prediction based on modified nucleosomes.

    Directory of Open Access Journals (Sweden)

    Mohammad Talebzadeh

    Full Text Available In computational methods, position weight matrices (PWMs are commonly applied for transcription factor binding site (TFBS prediction. Although these matrices are more accurate than simple consensus sequences to predict actual binding sites, they usually produce a large number of false positive (FP predictions and so are impoverished sources of information. Several studies have employed additional sources of information such as sequence conservation or the vicinity to transcription start sites to distinguish true binding regions from random ones. Recently, the spatial distribution of modified nucleosomes has been shown to be associated with different promoter architectures. These aligned patterns can facilitate DNA accessibility for transcription factors. We hypothesize that using data from these aligned and periodic patterns can improve the performance of binding region prediction. In this study, we propose two effective features, "modified nucleosomes neighboring" and "modified nucleosomes occupancy", to decrease FP in binding site discovery. Based on these features, we designed a logistic regression classifier which estimates the probability of a region as a TFBS. Our model learned each feature based on Sp1 binding sites on Chromosome 1 and was tested on the other chromosomes in human CD4+T cells. In this work, we investigated 21 histone modifications and found that only 8 out of 21 marks are strongly correlated with transcription factor binding regions. To prove that these features are not specific to Sp1, we combined the logistic regression classifier with the PWM, and created a new model to search TFBSs on the genome. We tested the model using transcription factors MAZ, PU.1 and ELF1 and compared the results to those using only the PWM. The results show that our model can predict Transcription factor binding regions more successfully. The relative simplicity of the model and capability of integrating other features make it a superior method

  12. The Attribute for Hydrocarbon Prediction Based on Attenuation

    International Nuclear Information System (INIS)

    Hermana, Maman; Harith, Z Z T; Sum, C W; Ghosh, D P

    2014-01-01

    Hydrocarbon prediction is a crucial issue in the oil and gas industry. Currently, the prediction of pore fluid and lithology are based on amplitude interpretation which has the potential to produce pitfalls in certain conditions of reservoir. Motivated by this fact, this work is directed to find out other attributes that can be used to reduce the pitfalls in the amplitude interpretation. Some seismic attributes were examined and studies showed that the attenuation attribute is a better attribute for hydrocarbon prediction. Theoretically, the attenuation mechanism of wave propagation is associated with the movement of fluid in the pore; hence the existence of hydrocarbon in the pore will be represented by attenuation attribute directly. In this paper we evaluated the feasibility of the quality factor ratio of P-wave and S-wave (Qp/Qs) as hydrocarbon indicator using well data and also we developed a new attribute based on attenuation for hydrocarbon prediction -- Normalized Energy Reduction Stack (NERS). To achieve these goals, this work was divided into 3 main parts; estimating the Qp/Qs on well log data, testing the new attribute in the synthetic data and applying the new attribute on real data in Malay Basin data. The result show that the Qp/Qs is better than Poisson's ratio and Lamda over Mu as hydrocarbon indicator. The curve, trend analysis and contrast of Qp/Qs is more powerful at distinguishing pore fluid than Poisson ratio and Lamda over Mu. The NERS attribute was successful in distinguishing the hydrocarbon from brine on synthetic data. Applying this attribute on real data on Malay basin, the NERS attribute is qualitatively conformable with the structure and location where the gas is predicted. The quantitative interpretation of this attribute for hydrocarbon prediction needs to be investigated further

  13. Background-Modeling-Based Adaptive Prediction for Surveillance Video Coding.

    Science.gov (United States)

    Zhang, Xianguo; Huang, Tiejun; Tian, Yonghong; Gao, Wen

    2014-02-01

    The exponential growth of surveillance videos presents an unprecedented challenge for high-efficiency surveillance video coding technology. Compared with the existing coding standards that were basically developed for generic videos, surveillance video coding should be designed to make the best use of the special characteristics of surveillance videos (e.g., relative static background). To do so, this paper first conducts two analyses on how to improve the background and foreground prediction efficiencies in surveillance video coding. Following the analysis results, we propose a background-modeling-based adaptive prediction (BMAP) method. In this method, all blocks to be encoded are firstly classified into three categories. Then, according to the category of each block, two novel inter predictions are selectively utilized, namely, the background reference prediction (BRP) that uses the background modeled from the original input frames as the long-term reference and the background difference prediction (BDP) that predicts the current data in the background difference domain. For background blocks, the BRP can effectively improve the prediction efficiency using the higher quality background as the reference; whereas for foreground-background-hybrid blocks, the BDP can provide a better reference after subtracting its background pixels. Experimental results show that the BMAP can achieve at least twice the compression ratio on surveillance videos as AVC (MPEG-4 Advanced Video Coding) high profile, yet with a slightly additional encoding complexity. Moreover, for the foreground coding performance, which is crucial to the subjective quality of moving objects in surveillance videos, BMAP also obtains remarkable gains over several state-of-the-art methods.

  14. Empirical comparison of web-based antimicrobial peptide prediction tools.

    Science.gov (United States)

    Gabere, Musa Nur; Noble, William Stafford

    2017-07-01

    Antimicrobial peptides (AMPs) are innate immune molecules that exhibit activities against a range of microbes, including bacteria, fungi, viruses and protozoa. Recent increases in microbial resistance against current drugs has led to a concomitant increase in the need for novel antimicrobial agents. Over the last decade, a number of AMP prediction tools have been designed and made freely available online. These AMP prediction tools show potential to discriminate AMPs from non-AMPs, but the relative quality of the predictions produced by the various tools is difficult to quantify. We compiled two sets of AMP and non-AMP peptides, separated into three categories-antimicrobial, antibacterial and bacteriocins. Using these benchmark data sets, we carried out a systematic evaluation of ten publicly available AMP prediction methods. Among the six general AMP prediction tools-ADAM, CAMPR3(RF), CAMPR3(SVM), MLAMP, DBAASP and MLAMP-we find that CAMPR3(RF) provides a statistically significant improvement in performance, as measured by the area under the receiver operating characteristic (ROC) curve, relative to the other five methods. Surprisingly, for antibacterial prediction, the original AntiBP method significantly outperforms its successor, AntiBP2 based on one benchmark dataset. The two bacteriocin prediction tools, BAGEL3 and BACTIBASE, both provide very good performance and BAGEL3 outperforms its predecessor, BACTIBASE, on the larger of the two benchmarks. gaberemu@ngha.med.sa or william-noble@uw.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  15. Deep-Learning-Based Drug-Target Interaction Prediction.

    Science.gov (United States)

    Wen, Ming; Zhang, Zhimin; Niu, Shaoyu; Sha, Haozhi; Yang, Ruihan; Yun, Yonghuan; Lu, Hongmei

    2017-04-07

    Identifying interactions between known drugs and targets is a major challenge in drug repositioning. In silico prediction of drug-target interaction (DTI) can speed up the expensive and time-consuming experimental work by providing the most potent DTIs. In silico prediction of DTI can also provide insights about the potential drug-drug interaction and promote the exploration of drug side effects. Traditionally, the performance of DTI prediction depends heavily on the descriptors used to represent the drugs and the target proteins. In this paper, to accurately predict new DTIs between approved drugs and targets without separating the targets into different classes, we developed a deep-learning-based algorithmic framework named DeepDTIs. It first abstracts representations from raw input descriptors using unsupervised pretraining and then applies known label pairs of interaction to build a classification model. Compared with other methods, it is found that DeepDTIs reaches or outperforms other state-of-the-art methods. The DeepDTIs can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.

  16. The Dissolved Oxygen Prediction Method Based on Neural Network

    Directory of Open Access Journals (Sweden)

    Zhong Xiao

    2017-01-01

    Full Text Available The dissolved oxygen (DO is oxygen dissolved in water, which is an important factor for the aquaculture. Using BP neural network method with the combination of purelin, logsig, and tansig activation functions is proposed for the prediction of aquaculture’s dissolved oxygen. The input layer, hidden layer, and output layer are introduced in detail including the weight adjustment process. The breeding data of three ponds in actual 10 consecutive days were used for experiments; these ponds were located in Beihai, Guangxi, a traditional aquaculture base in southern China. The data of the first 7 days are used for training, and the data of the latter 3 days are used for the test. Compared with the common prediction models, curve fitting (CF, autoregression (AR, grey model (GM, and support vector machines (SVM, the experimental results show that the prediction accuracy of the neural network is the highest, and all the predicted values are less than 5% of the error limit, which can meet the needs of practical applications, followed by AR, GM, SVM, and CF. The prediction model can help to improve the water quality monitoring level of aquaculture which will prevent the deterioration of water quality and the outbreak of disease.

  17. On exceeding the solubility limit of Cr+3 dopants in SnO2 nanoparticles based dilute magnetic semiconductors

    Science.gov (United States)

    URS, Kusuma; Bhat, S. V.; Kamble, Vinayak

    2018-04-01

    The paper investigates the magnetic behavior of chromium doped SnO2 Dilute Magnetic Semiconductor (DMS) nanoparticles, through structural, spectroscopic, and magnetic studies. A non-equilibrium solution combustion method is adopted to synthesize 0-5 at. % Cr doped SnO2 nanoparticles. The detailed spectroscopic studies on the system using micro-Raman spectroscopy, x-ray photoelectron spectroscopy, and electron paramagnetic resonance spectroscopy along with the structural analysis confirm the presence of Cr in 3+ oxidation state, which substitutes at Sn4+ site in SnO6 octahedra of the rutile structure. This doping is found to enhance the defects in the system, i.e., oxygen vacancies. All the synthesized SnO2 nanoparticles (with or without dopants) are found to exhibit Room Temperature Ferromagnetism (RTFM). This occurrence of RTFM is attributed to the magnetic exchange interaction through F-centers of oxygen vacancies as well as dopant magnetic impurities and explained through the Bound Magnetic Polaron (BMP) model of DMS systems. Nonetheless, as the doping of Cr is further increased beyond 2%, the solubility limit is achieved. This antiferromagnetic exchange interaction from interstitial Cr dopants dominates over the BMP mechanism and, hence, leads to the decrease in the net magnetic moment drastically.

  18. Development of non-water soluble, ductile mung bean starch based edible film with oxygen barrier and heat sealability.

    Science.gov (United States)

    Rompothi, Onjira; Pradipasena, Pasawadee; Tananuwong, Kanitha; Somwangthanaroj, Anongnat; Janjarasskul, Theeranun

    2017-02-10

    This research determined the effects of starch concentration (3.5-5.0%w/w), and plasticizer [glycerol (0-30%w/w) or sorbitol (0-60%w/w)] on properties of mung bean starch (MBS) films. The result showed that increasing plasticizer concentration tended to decrease tensile strength (TS), elastic modulus (EM) and oxygen permeability (OP); but increase elongation (%E), solubility, water vapor permeability (WVP) and seal strength. The extent of those changes also depended on starch concentration. Glycerol provided better plasticizer efficiency than sorbitol. A bimodal melting endotherm of retrograded structure was evident in non-plasticized film. However, only a low temperature endotherm was observed in polyol-plasticized films, indicating a plasticizer-induced structural modification. The developed ductile MBS films, (TS of 7.14±0.95 to 46.30±3.09MPa, %E of 2.46±0.21 to 56.95±4.34% and EM of 16.29±3.40 to 1428.45±148.72MPa) with an OP of 0.2397±0.0365 to 1.1520±0.1782 ccmm/m 2 daykPa and seal strength up to 422.36±7.93N/m, demonstrated in this study indicate the potential for food packaging applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Solubility and acid-base properties of concentrated phytate in self-medium and in NaCl{sub aq} at T = 298.15 K

    Energy Technology Data Exchange (ETDEWEB)

    Cigala, Rosalia Maria; Crea, Francesco; Lando, Gabriele; Milea, Demetrio [Dipartimento di Chimica Inorganica, Chimica Analitica e Chimica Fisica, Universita di Messina, Via Ferdinando Stagno d' Alcontres, 31, I-98166 Messina (Vill. S. Agata) (Italy); Sammartano, Silvio, E-mail: ssammartano@unime.i [Dipartimento di Chimica Inorganica, Chimica Analitica e Chimica Fisica, Universita di Messina, Via Ferdinando Stagno d' Alcontres, 31, I-98166 Messina (Vill. S. Agata) (Italy)

    2010-11-15

    The acid-base properties of concentrated phytic acid were studied in self-medium and in NaCl{sub aq} (0.5 {<=} I/mol . L{sup -1} {<=} 4.0) by ISE-H{sup +} potentiometry and by direct calorimetry, at T = 298.15 K. At ligand concentrations c{sub (Phy)} > 0.012 mol . L{sup -1}, the formation of several binuclear H{sub i}(Phy){sub 2} (2 {<=} i {<=} 10) species was observed, in addition to the mononuclear H{sub i}Phy (1 {<=} i {<=} 7) ones. The solubility of phytate dodecasodium salt was studied in pure water and in NaCl{sub aq} at different ionic strengths; the total solubility in pure water is S{sub 0}{sup T}=(0.300{+-}0.004)mol.L{sup -1} and it decreases markedly with increasing ionic strength; for example the total solubility of Na{sub 12}Phy at I = 3.0 mol . L{sup -1} is 0.008 mol . L{sup -1}. By the dependence on ionic strength (salt concentration) of the solubility, it was possible to calculate the activity coefficients of phytate as a function of medium concentration. Direct calorimetric titrations were also carried out on Na{sub 12}Phy aqueous solutions at different phytate concentrations (0.025 {<=} c{sub (Phy)}/mol . L{sup -1} {<=} 0.100) and without addition of supporting electrolyte, in order to calculate the enthalpy changes for the protonation equilibria in self-medium of the binuclear H{sub i}(Phy){sub 2} species, at T = 298.15 K. It was observed that the {Delta}H/kJ . mol{sup -1} of the binuclear species are, within the experimental error, independent of the ionic strength; for example for the H{sub 2}(Phy){sub 2} species we obtained: {Delta}H{sub 22} = (-23.6 {+-} 0.6) kJ . mol{sup -1}, and (-23.7 {+-} 0.2) kJ . mol{sup -1} at I = 0.50 and 2.0 mol . L{sup -1}, respectively.

  20. Assessment of cellular estrogenic activity based on estrogen receptor-mediated reduction of soluble-form catechol-O-methyltransferase (COMT expression in an ELISA-based system.

    Directory of Open Access Journals (Sweden)

    Philip Wing-Lok Ho

    Full Text Available Xenoestrogens are either natural or synthetic compounds that mimic the effects of endogenous estrogen. These compounds, such as bisphenol-A (BPA, and phthalates, are commonly found in plastic wares. Exposure to these compounds poses major risk to human health because of the potential to cause endocrine disruption. There is huge demand for a wide range of chemicals to be assessed for such potential for the sake of public health. Classical in vivo assays for endocrine disruption are comprehensive but time-consuming and require sacrifice of experimental animals. Simple preliminary in vitro screening assays can reduce the time and expense involved. We previously demonstrated that catechol-O-methyltransferase (COMT is transcriptionally regulated by estrogen via estrogen receptor (ER. Therefore, detecting corresponding changes of COMT expression in estrogen-responsive cells may be a useful method to estimate estrogenic effects of various compounds. We developed a novel cell-based ELISA to evaluate cellular response to estrogenicity by reduction of soluble-COMT expression in ER-positive MCF-7 cells exposed to estrogenic compounds. In contrast to various existing methods that only detect bioactivity, this method elucidates direct physiological effect in a living cell in response to a compound. We validated our assay using three well-characterized estrogenic plasticizers - BPA, benzyl butyl phthalate (BBP, and di-n-butyl phthalate (DBP. Cells were exposed to either these plasticizers or 17β-estradiol (E2 in estrogen-depleted medium with or without an ER-antagonist, ICI 182,780, and COMT expression assayed. Exposure to each of these plasticizers (10(-9-10(-7M dose-dependently reduced COMT expression (p<0.05, which was blocked by ICI 182,780. Reduction of COMT expression was readily detectable in cells exposed to picomolar level of E2, comparable to other in vitro assays of similar sensitivity. To satisfy the demand for in vitro assays targeting different

  1. Predicting online ratings based on the opinion spreading process

    Science.gov (United States)

    He, Xing-Sheng; Zhou, Ming-Yang; Zhuo, Zhao; Fu, Zhong-Qian; Liu, Jian-Guo

    2015-10-01

    Predicting users' online ratings is always a challenge issue and has drawn lots of attention. In this paper, we present a rating prediction method by combining the user opinion spreading process with the collaborative filtering algorithm, where user similarity is defined by measuring the amount of opinion a user transfers to another based on the primitive user-item rating matrix. The proposed method could produce a more precise rating prediction for each unrated user-item pair. In addition, we introduce a tunable parameter λ to regulate the preferential diffusion relevant to the degree of both opinion sender and receiver. The numerical results for Movielens and Netflix data sets show that this algorithm has a better accuracy than the standard user-based collaborative filtering algorithm using Cosine and Pearson correlation without increasing computational complexity. By tuning λ, our method could further boost the prediction accuracy when using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) as measurements. In the optimal cases, on Movielens and Netflix data sets, the corresponding algorithmic accuracy (MAE and RMSE) are improved 11.26% and 8.84%, 13.49% and 10.52% compared to the item average method, respectively.

  2. PNN-based Rockburst Prediction Model and Its Applications

    Directory of Open Access Journals (Sweden)

    Yu Zhou

    2017-07-01

    Full Text Available Rock burst is one of main engineering geological problems significantly threatening the safety of construction. Prediction of rock burst is always an important issue concerning the safety of workers and equipment in tunnels. In this paper, a novel PNN-based rock burst prediction model is proposed to determine whether rock burst will happen in the underground rock projects and how much the intensity of rock burst is. The probabilistic neural network (PNN is developed based on Bayesian criteria of multivariate pattern classification. Because PNN has the advantages of low training complexity, high stability, quick convergence, and simple construction, it can be well applied in the prediction of rock burst. Some main control factors, such as rocks’ maximum tangential stress, rocks’ uniaxial compressive strength, rocks’ uniaxial tensile strength, and elastic energy index of rock are chosen as the characteristic vector of PNN. PNN model is obtained through training data sets of rock burst samples which come from underground rock project in domestic and abroad. Other samples are tested with the model. The testing results agree with the practical records. At the same time, two real-world applications are used to verify the proposed method. The results of prediction are same as the results of existing methods, just same as what happened in the scene, which verifies the effectiveness and applicability of our proposed work.

  3. Link Prediction in Evolving Networks Based on Popularity of Nodes.

    Science.gov (United States)

    Wang, Tong; He, Xing-Sheng; Zhou, Ming-Yang; Fu, Zhong-Qian

    2017-08-02

    Link prediction aims to uncover the underlying relationship behind networks, which could be utilized to predict missing edges or identify the spurious edges. The key issue of link prediction is to estimate the likelihood of potential links in networks. Most classical static-structure based methods ignore the temporal aspects of networks, limited by the time-varying features, such approaches perform poorly in evolving networks. In this paper, we propose a hypothesis that the ability of each node to attract links depends not only on its structural importance, but also on its current popularity (activeness), since active nodes have much more probability to attract future links. Then a novel approach named popularity based structural perturbation method (PBSPM) and its fast algorithm are proposed to characterize the likelihood of an edge from both existing connectivity structure and current popularity of its two endpoints. Experiments on six evolving networks show that the proposed methods outperform state-of-the-art methods in accuracy and robustness. Besides, visual results and statistical analysis reveal that the proposed methods are inclined to predict future edges between active nodes, rather than edges between inactive nodes.

  4. GIS-BASED PREDICTION OF HURRICANE FLOOD INUNDATION

    Energy Technology Data Exchange (ETDEWEB)

    JUDI, DAVID [Los Alamos National Laboratory; KALYANAPU, ALFRED [Los Alamos National Laboratory; MCPHERSON, TIMOTHY [Los Alamos National Laboratory; BERSCHEID, ALAN [Los Alamos National Laboratory

    2007-01-17

    A simulation environment is being developed for the prediction and analysis of the inundation consequences for infrastructure systems from extreme flood events. This decision support architecture includes a GIS-based environment for model input development, simulation integration tools for meteorological, hydrologic, and infrastructure system models and damage assessment tools for infrastructure systems. The GIS-based environment processes digital elevation models (30-m from the USGS), land use/cover (30-m NLCD), stream networks from the National Hydrography Dataset (NHD) and soils data from the NRCS (STATSGO) to create stream network, subbasins, and cross-section shapefiles for drainage basins selected for analysis. Rainfall predictions are made by a numerical weather model and ingested in gridded format into the simulation environment. Runoff hydrographs are estimated using Green-Ampt infiltration excess runoff prediction and a 1D diffusive wave overland flow routing approach. The hydrographs are fed into the stream network and integrated in a dynamic wave routing module using the EPA's Storm Water Management Model (SWMM) to predict flood depth. The flood depths are then transformed into inundation maps and exported for damage assessment. Hydrologic/hydraulic results are presented for Tropical Storm Allison.

  5. Predicting Social Anxiety Treatment Outcome Based on Therapeutic Email Conversations.

    Science.gov (United States)

    Hoogendoorn, Mark; Berger, Thomas; Schulz, Ava; Stolz, Timo; Szolovits, Peter

    2017-09-01

    Predicting therapeutic outcome in the mental health domain is of utmost importance to enable therapists to provide the most effective treatment to a patient. Using information from the writings of a patient can potentially be a valuable source of information, especially now that more and more treatments involve computer-based exercises or electronic conversations between patient and therapist. In this paper, we study predictive modeling using writings of patients under treatment for a social anxiety disorder. We extract a wealth of information from the text written by patients including their usage of words, the topics they talk about, the sentiment of the messages, and the style of writing. In addition, we study trends over time with respect to those measures. We then apply machine learning algorithms to generate the predictive models. Based on a dataset of 69 patients, we are able to show that we can predict therapy outcome with an area under the curve of 0.83 halfway through the therapy and with a precision of 0.78 when using the full data (i.e., the entire treatment period). Due to the limited number of participants, it is hard to generalize the results, but they do show great potential in this type of information.

  6. Chaos Time Series Prediction Based on Membrane Optimization Algorithms

    Directory of Open Access Journals (Sweden)

    Meng Li

    2015-01-01

    Full Text Available This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ,m and least squares support vector machine (LS-SVM (γ,σ by using membrane computing optimization algorithm. It is an important basis for spectrum management to predict accurately the change trend of parameters in the electromagnetic environment, which can help decision makers to adopt an optimal action. Then, the model presented in this paper is used to forecast band occupancy rate of frequency modulation (FM broadcasting band and interphone band. To show the applicability and superiority of the proposed model, this paper will compare the forecast model presented in it with conventional similar models. The experimental results show that whether single-step prediction or multistep prediction, the proposed model performs best based on three error measures, namely, normalized mean square error (NMSE, root mean square error (RMSE, and mean absolute percentage error (MAPE.

  7. Potential Eye Drop Based on a Calix[4]arene Nanoassembly for Curcumin Delivery: Enhanced Drug Solubility, Stability, and Anti-Inflammatory Effect.

    Science.gov (United States)

    Granata, Giuseppe; Paterniti, Irene; Geraci, Corrada; Cunsolo, Francesca; Esposito, Emanuela; Cordaro, Marika; Blanco, Anna Rita; Cuzzocrea, Salvatore; Consoli, Grazia M L

    2017-05-01

    Curcumin is an Indian spice with a wide spectrum of biological and pharmacological activities but poor aqueous solubility, rapid degradation, and low bioavailability that affect medical benefits. To overcome these limits in ophthalmic application, curcumin was entrapped in a polycationic calix[4]arene-based nanoaggregate by a simple and reproducible method. The calix[4]arene-curcumin supramolecular assembly (Calix-Cur) appeared as a clear colloidal solution consisting in micellar nanoaggregates with size, polydispersity index, surface potential, and drug loading percentage meeting the requirements for an ocular drug delivery system. The encapsulation in the calix[4]arene nanoassembly markedly enhanced the solubility, reduced the degradation, and improved the anti-inflammatory effects of curcumin compared to free curcumin in both in vitro and in vivo experiments. Calix-Cur did not compromise the viability of J774A.1 macrophages and suppressed pro-inflammatory marker expression in J774A.1 macrophages subjected to LPS-induced oxidative stress. Histological and immunohistochemical analyses showed that Calix-Cur reduced signs of inflammation in a rat model of LPS-induced uveitis when topically administrated in the eyes. Overall, the results supported the calix[4]arene nanoassembly as a promising nanocarrier for delivering curcumin to anterior ocular tissues.

  8. PREDICTIVE POTENTIAL FIELD-BASED COLLISION AVOIDANCE FOR MULTICOPTERS

    Directory of Open Access Journals (Sweden)

    M. Nieuwenhuisen

    2013-08-01

    Full Text Available Reliable obstacle avoidance is a key to navigating with UAVs in the close vicinity of static and dynamic obstacles. Wheel-based mobile robots are often equipped with 2D or 3D laser range finders that cover the 2D workspace sufficiently accurate and at a high rate. Micro UAV platforms operate in a 3D environment, but the restricted payload prohibits the use of fast state-of-the-art 3D sensors. Thus, perception of small obstacles is often only possible in the vicinity of the UAV and a fast collision avoidance system is necessary. We propose a reactive collision avoidance system based on artificial potential fields, that takes the special dynamics of UAVs into account by predicting the influence of obstacles on the estimated trajectory in the near future using a learned motion model. Experimental evaluation shows that the prediction leads to smoother trajectories and allows to navigate collision-free through passageways.

  9. Offset Free Tracking Predictive Control Based on Dynamic PLS Framework

    Directory of Open Access Journals (Sweden)

    Jin Xin

    2017-10-01

    Full Text Available This paper develops an offset free tracking model predictive control based on a dynamic partial least square (PLS framework. First, state space model is used as the inner model of PLS to describe the dynamic system, where subspace identification method is used to identify the inner model. Based on the obtained model, multiple independent model predictive control (MPC controllers are designed. Due to the decoupling character of PLS, these controllers are running separately, which is suitable for distributed control framework. In addition, the increment of inner model output is considered in the cost function of MPC, which involves integral action in the controller. Hence, the offset free tracking performance is guaranteed. The results of an industry background simulation demonstrate the effectiveness of proposed method.

  10. Solubility Products of M(II) - Carbonates

    International Nuclear Information System (INIS)

    Grauer, Rolf; Berner, Urs

    1999-01-01

    Many solubility data for M(II) carbonates commonly compiled in tables are contradictory and sometimes obviously wrong. The quality of such data has been evaluated based on the original publications and reliable solubility constants have been selected for the carbonates of Mn, Fe, Co, Ni, Cu, Zn, Cd and Pb with the help of cross-comparisons. (author)

  11. Tetraphenylborate Solubility in High Ionic Strength Salt Solutions

    International Nuclear Information System (INIS)

    Serkiz, S.M.; Ginn, J.D.; Jurgensen, A.R.

    1998-04-01

    Solubility of sodium and potassium salts of the tetraphenylborate ion (TPB) in simulated Savannah River Site High Level Waste was investigated. Data generated from this study allow more accurate predictions of TPB solubility at the In-Tank Precipitation (ITP) facility. Because previous research showed large deviations in the observed solubility of TPB salts when compared with model predictions, additional data were generated to better understand the solubility of TPB in more complex systems of high ionic strength and those containing both potassium and sodium. These data allow evaluation of the ability of current models to accurately predict equilibrium TPB concentrations over the range of experimental conditions investigated in this study

  12. Construction Worker Fatigue Prediction Model Based on System Dynamic

    OpenAIRE

    Wahyu Adi Tri Joko; Ayu Ratnawinanda Lila

    2017-01-01

    Construction accident can be caused by internal and external factors such as worker fatigue and unsafe project environment. Tight schedule of construction project forcing construction worker to work overtime in long period. This situation leads to worker fatigue. This paper proposes a model to predict construction worker fatigue based on system dynamic (SD). System dynamic is used to represent correlation among internal and external factors and to simulate level of worker fatigue. To validate...

  13. Seminal Quality Prediction Using Clustering-Based Decision Forests

    Directory of Open Access Journals (Sweden)

    Hong Wang

    2014-08-01

    Full Text Available Prediction of seminal quality with statistical learning tools is an emerging methodology in decision support systems in biomedical engineering and is very useful in early diagnosis of seminal patients and selection of semen donors candidates. However, as is common in medical diagnosis, seminal quality prediction faces the class imbalance problem. In this paper, we propose a novel supervised ensemble learning approach, namely Clustering-Based Decision Forests, to tackle unbalanced class learning problem in seminal quality prediction. Experiment results on real fertility diagnosis dataset have shown that Clustering-Based Decision Forests outperforms decision tree, Support Vector Machines, random forests, multilayer perceptron neural networks and logistic regression by a noticeable margin. Clustering-Based Decision Forests can also be used to evaluate variables’ importance and the top five important factors that may affect semen concentration obtained in this study are age, serious trauma, sitting time, the season when the semen sample is produced, and high fevers in the last year. The findings could be helpful in explaining seminal concentration problems in infertile males or pre-screening semen donor candidates.

  14. Identification of water-soluble heavy crude oil organic-acids, bases, and neutrals by electrospray ionization and field desorption ionization fourier transform ion cyclotron resonance mass spectrometry.

    Science.gov (United States)

    Stanford, Lateefah A; Kim, Sunghwan; Klein, Geoffrey C; Smith, Donald F; Rodgers, Ryan P; Marshall, Alan G

    2007-04-15

    We identify water-soluble (23 degrees C) crude oil NSO nonvolatile acidic, basic, and neutral crude oil hydrocarbons by negative-ion ESI and continuous flow FD FT-ICR MS at an average mass resolving power, m/deltam50% = 550,000. Of the 7000+ singly charged acidic species identified in South American crude oil, surprisingly, many are water-soluble, and much more so in pure water than in seawater. The truncated m/z distributions for water-soluble components exhibit preferential molecular weight, size, and heteroatom class influences on hydrocarbon solubility. Acidic water-soluble heteroatomic classes detected at >1% relative abundance include O, O2, O3, O4, OS, O2S, O3S, O4S, NO2, NO3, and NO4. Parent oil class abundance does not directly relate to abundance in the water-soluble fraction. Acidic oxygen-containing classes are most prevalent in the water-solubles, whereas acidic nitrogen-containing species are least soluble. In contrast to acidic nitrogen-containing heteroatomic classes, basic nitrogen classes are water-soluble. Water-soluble heteroatomic basic classes detected at >1% relative abundance include N, NO, NO2, NS, NS2, NOS, NO2S, N2, N2O, N2O2, OS, O2S, and O2S2.

  15. Analysis of chemical concepts as the basic of virtual laboratory development and process science skills in solubility and solubility product subject

    Science.gov (United States)

    Syafrina, R.; Rohman, I.; Yuliani, G.

    2018-05-01

    This study aims to analyze the concept characteristics of solubility and solubility products that will serve as the basis for the development of virtual laboratory and students' science process skills. Characteristics of the analyzed concepts include concept definitions, concept attributes, and types of concepts. The concept analysis method uses concept analysis according to Herron. The results of the concept analysis show that there are twelve chemical concepts that become the prerequisite concept before studying the solubility and solubility and five core concepts that students must understand in the solubility and Solubility product. As many as 58.3% of the definitions of the concepts contained in high school textbooks support students' science process skills, the rest of the definition of the concept is memorized. Concept attributes that meet three levels of chemical representation and can be poured into a virtual laboratory have a percentage of 66.6%. Type of concept, 83.3% is a concept based on principle; and 16.6% concepts that state the process. Meanwhile, the science process skills that can be developed based on concept analysis are the ability to observe, calculate, measure, predict, interpret, hypothesize, apply, classify, and inference.

  16. New Temperature-based Models for Predicting Global Solar Radiation

    International Nuclear Information System (INIS)

    Hassan, Gasser E.; Youssef, M. Elsayed; Mohamed, Zahraa E.; Ali, Mohamed A.; Hanafy, Ahmed A.

    2016-01-01

    Highlights: • New temperature-based models for estimating solar radiation are investigated. • The models are validated against 20-years measured data of global solar radiation. • The new temperature-based model shows the best performance for coastal sites. • The new temperature-based model is more accurate than the sunshine-based models. • The new model is highly applicable with weather temperature forecast techniques. - Abstract: This study presents new ambient-temperature-based models for estimating global solar radiation as alternatives to the widely used sunshine-based models owing to the unavailability of sunshine data at all locations around the world. Seventeen new temperature-based models are established, validated and compared with other three models proposed in the literature (the Annandale, Allen and Goodin models) to estimate the monthly average daily global solar radiation on a horizontal surface. These models are developed using a 20-year measured dataset of global solar radiation for the case study location (Lat. 30°51′N and long. 29°34′E), and then, the general formulae of the newly suggested models are examined for ten different locations around Egypt. Moreover, the local formulae for the models are established and validated for two coastal locations where the general formulae give inaccurate predictions. Mostly common statistical errors are utilized to evaluate the performance of these models and identify the most accurate model. The obtained results show that the local formula for the most accurate new model provides good predictions for global solar radiation at different locations, especially at coastal sites. Moreover, the local and general formulas of the most accurate temperature-based model also perform better than the two most accurate sunshine-based models from the literature. The quick and accurate estimations of the global solar radiation using this approach can be employed in the design and evaluation of performance for

  17. Crystal density predictions for nitramines based on quantum chemistry

    International Nuclear Information System (INIS)

    Qiu Ling; Xiao Heming; Gong Xuedong; Ju Xuehai; Zhu Weihua

    2007-01-01

    An efficient and convenient method for predicting the crystalline densities of energetic materials was established based on the quantum chemical computations. Density functional theory (DFT) with four different basis sets (6-31G**, 6-311G**, 6-31+G**, and 6-311++G**) and various semiempirical molecular orbital (MO) methods have been employed to predict the molecular volumes and densities of a series of energetic nitramines including acyclic, monocyclic, and polycyclic/cage molecules. The relationships between the calculated values and experimental data were discussed in detail, and linear correlations were suggested and compared at different levels. The calculation shows that if the selected basis set is larger, it will expend more CPU (central processing unit) time, larger molecular volume and smaller density will be obtained. And the densities predicted by the semiempirical MO methods are all systematically larger than the experimental data. In comparison with other methods, B3LYP/6-31G** is most accurate and economical to predict the solid-state densities of energetic nitramines. This may be instructive to the molecular designing and screening novel HEDMs

  18. Power system dynamic state estimation using prediction based evolutionary technique

    International Nuclear Information System (INIS)

    Basetti, Vedik; Chandel, Ashwani K.; Chandel, Rajeevan

    2016-01-01

    In this paper, a new robust LWS (least winsorized square) estimator is proposed for dynamic state estimation of a power system. One of the main advantages of this estimator is that it has an inbuilt bad data rejection property and is less sensitive to bad data measurements. In the proposed approach, Brown's double exponential smoothing technique has been utilised for its reliable performance at the prediction step. The state estimation problem is solved as an optimisation problem using a new jDE-self adaptive differential evolution with prediction based population re-initialisation technique at the filtering step. This new stochastic search technique has been embedded with different state scenarios using the predicted state. The effectiveness of the proposed LWS technique is validated under different conditions, namely normal operation, bad data, sudden load change, and loss of transmission line conditions on three different IEEE test bus systems. The performance of the proposed approach is compared with the conventional extended Kalman filter. On the basis of various performance indices, the results thus obtained show that the proposed technique increases the accuracy and robustness of power system dynamic state estimation performance. - Highlights: • To estimate the states of the power system under dynamic environment. • The performance of the EKF method is degraded during anomaly conditions. • The proposed method remains robust towards anomalies. • The proposed method provides precise state estimates even in the presence of anomalies. • The results show that prediction accuracy is enhanced by using the proposed model.

  19. Predicting Drug-Target Interactions Based on Small Positive Samples.

    Science.gov (United States)

    Hu, Pengwei; Chan, Keith C C; Hu, Yanxing

    2018-01-01

    A basic task in drug discovery is to find new medication in the form of candidate compounds that act on a target protein. In other words, a drug has to interact with a target and such drug-target interaction (DTI) is not expected to be random. Significant and interesting patterns are expected to be hidden in them. If these patterns can be discovered, new drugs are expected to be more easily discoverable. Currently, a number of computational methods have been proposed to predict DTIs based on their similarity. However, such as approach does not allow biochemical features to be directly considered. As a result, some methods have been proposed to try to discover patterns in physicochemical interactions. Since the number of potential negative DTIs are very high both in absolute terms and in comparison to that of the known ones, these methods are rather computationally expensive and they can only rely on subsets, rather than the full set, of negative DTIs for training and validation. As there is always a relatively high chance for negative DTIs to be falsely identified and as only partial subset of such DTIs is considered, existing approaches can be further improved to better predict DTIs. In this paper, we present a novel approach, called ODT (one class drug target interaction prediction), for such purpose. One main task of ODT is to discover association patterns between interacting drugs and proteins from the chemical structure of the former and the protein sequence network of the latter. ODT does so in two phases. First, the DTI-network is transformed to a representation by structural properties. Second, it applies a oneclass classification algorithm to build a prediction model based only on known positive interactions. We compared the best AUROC scores of the ODT with several state-of-art approaches on Gold standard data. The prediction accuracy of the ODT is superior in comparison with all the other methods at GPCRs dataset and Ion channels dataset. Performance

  20. A probabilistic fragment-based protein structure prediction algorithm.

    Directory of Open Access Journals (Sweden)

    David Simoncini

    Full Text Available Conformational sampling is one of the bottlenecks in fragment-based protein structure prediction approaches. They generally start with a coarse-grained optimization where mainchain atoms and centroids of side chains are considered, followed by a fine-grained optimization with an all-atom representation of proteins. It is during this coarse-grained phase that fragment-based methods sample intensely the conformational space. If the native-like region is sampled more, the accuracy of the final all-atom predictions may be improved accordingly. In this work we present EdaFold, a new method for fragment-based protein structure prediction based on an Estimation of Distribution Algorithm. Fragment-based approaches build protein models by assembling short fragments from known protein structures. Whereas the probability mass functions over the fragment libraries are uniform in the usual case, we propose an algorithm that learns from previously generated decoys and steers the search toward native-like regions. A comparison with Rosetta AbInitio protocol shows that EdaFold is able to generate models with lower energies and to enhance the percentage of near-native coarse-grained decoys on a benchmark of [Formula: see text] proteins. The best coarse-grained models produced by both methods were refined into all-atom models and used in molecular replacement. All atom decoys produced out of EdaFold's decoy set reach high enough accuracy to solve the crystallographic phase problem by molecular replacement for some test proteins. EdaFold showed a higher success rate in molecular replacement when compared to Rosetta. Our study suggests that improving low resolution coarse-grained decoys allows computational methods to avoid subsequent sampling issues during all-atom refinement and to produce better all-atom models. EdaFold can be downloaded from http://www.riken.jp/zhangiru/software.html [corrected].

  1. Estimating Stochastic Volatility Models using Prediction-based Estimating Functions

    DEFF Research Database (Denmark)

    Lunde, Asger; Brix, Anne Floor

    to the performance of the GMM estimator based on conditional moments of integrated volatility from Bollerslev and Zhou (2002). The case where the observed log-price process is contaminated by i.i.d. market microstructure (MMS) noise is also investigated. First, the impact of MMS noise on the parameter estimates from......In this paper prediction-based estimating functions (PBEFs), introduced in Sørensen (2000), are reviewed and PBEFs for the Heston (1993) stochastic volatility model are derived. The finite sample performance of the PBEF based estimator is investigated in a Monte Carlo study, and compared...... to correctly account for the noise are investigated. Our Monte Carlo study shows that the estimator based on PBEFs outperforms the GMM estimator, both in the setting with and without MMS noise. Finally, an empirical application investigates the possible challenges and general performance of applying the PBEF...

  2. Solubility and Permeability Studies of Aceclofenac in Different Oils

    African Journals Online (AJOL)

    The solubility and permeability of aceclofenac were compared with the hydroalcoholic solution of ... the use of lipid based systems such as micro- or .... carriers/vehicles for enhanced solubility and permeability ... modifications: A recent review.

  3. Solubility database for TILA-99

    Energy Technology Data Exchange (ETDEWEB)

    Vuorinen, U.; Carlsson, T. [VTT Chemical Technology, Espoo (Finland); Kulmala, S.; Hakanen, M. [Helsinki Univ. (Finland). Lab. of Radiochemistry; Ahonen, L. [Geological Survey of Finland, Espoo (Finland)

    1998-11-01

    The safety assessment of spent fuel disposal requires solubility values for several elements estimated in Finnish disposal conditions. In Finland four sites (Haestholmen, Kivetty, Olkiluoto and Romuvaara) are investigated for the disposal of spent fuel. Haestholmen and OLkiluoto are onshore sites, while Kivetty and Romuvaara are inland sites. Based on groundwater analysis and classification according to salinity at the planned disposal depth mainly fresh groundwater is encountered at Kivetty and Romuvaara, while brackish and saline water-types are met at Haestholmen and Olkiluoto. Very saline, almost brine-type water ({approx}70 g/l) has been found in the deepest parts of the investigated bedrock at one of the sites (Olkiluoto). The reference waters and conditions were chosen according to the water-types. The considered reference conditions incorporated both the near- and far-field, and both oxidizing and reducing conditions were considered. In the reference conditions, the changes in solubilities were also estimated as caused by possible variations in the pH, carbonate content and redox conditions. Uranium, which is the main component of spent fuel is dealt with in a separate report presenting the solubility of uranium and spent fuel dissolution. In this work the solubilities of all the other elements of concern (Am, Cu, Nb, Np, Pa, Pd, Pu, Ra, Se, Sn, Tc, Zr, Cm, Ni, Sr, Th, C, Cl, Cs, Fe, Ho, I, and Sm) in the safety assessment are considered. Some discussion on the corrosion of the spent fuel canister is also presented. For the estimation of solubilities of the elements in question, literature data was collected that mainly comprised experimentally measured concentrations. The sources used were spent fuel experiments, concentrations measured in solubility measurements, natural concentrations and concentrations from natural analogue sites (especially Palmottu and Hyrkkoelae in Finland) as well as the concentrations measured at the Finnish investigation sites

  4. Solubility database for TILA-99

    International Nuclear Information System (INIS)

    Vuorinen, U.; Carlsson, T.; Kulmala, S.; Hakanen, M.

    1998-11-01

    The safety assessment of spent fuel disposal requires solubility values for several elements estimated in Finnish disposal conditions. In Finland four sites (Haestholmen, Kivetty, Olkiluoto and Romuvaara) are investigated for the disposal of spent fuel. Haestholmen and OLkiluoto are onshore sites, while Kivetty and Romuvaara are inland sites. Based on groundwater analysis and classification according to salinity at the planned disposal depth mainly fresh groundwater is encountered at Kivetty and Romuvaara, while brackish and saline water-types are met at Haestholmen and Olkiluoto. Very saline, almost brine-type water (∼70 g/l) has been found in the deepest parts of the investigated bedrock at one of the sites (Olkiluoto). The reference waters and conditions were chosen according to the water-types. The considered reference conditions incorporated both the near- and far-field, and both oxidizing and reducing conditions were considered. In the reference conditions, the changes in solubilities were also estimated as caused by possible variations in the pH, carbonate content and redox conditions. Uranium, which is the main component of spent fuel is dealt with in a separate report presenting the solubility of uranium and spent fuel dissolution. In this work the solubilities of all the other elements of concern (Am, Cu, Nb, Np, Pa, Pd, Pu, Ra, Se, Sn, Tc, Zr, Cm, Ni, Sr, Th, C, Cl, Cs, Fe, Ho, I, and Sm) in the safety assessment are considered. Some discussion on the corrosion of the spent fuel canister is also presented. For the estimation of solubilities of the elements in question, literature data was collected that mainly comprised experimentally measured concentrations. The sources used were spent fuel experiments, concentrations measured in solubility measurements, natural concentrations and concentrations from natural analogue sites (especially Palmottu and Hyrkkoelae in Finland) as well as the concentrations measured at the Finnish investigation sites. The

  5. Predictability of depression severity based on posterior alpha oscillations.

    Science.gov (United States)

    Jiang, H; Popov, T; Jylänki, P; Bi, K; Yao, Z; Lu, Q; Jensen, O; van Gerven, M A J

    2016-04-01

    We aimed to integrate neural data and an advanced machine learning technique to predict individual major depressive disorder (MDD) patient severity. MEG data was acquired from 22 MDD patients and 22 healthy controls (HC) resting awake with eyes closed. Individual power spectra were calculated by a Fourier transform. Sources were reconstructed via beamforming technique. Bayesian linear regression was applied to predict depression severity based on the spatial distribution of oscillatory power. In MDD patients, decreased theta (4-8 Hz) and alpha (8-14 Hz) power was observed in fronto-central and posterior areas respectively, whereas increased beta (14-30 Hz) power was observed in fronto-central regions. In particular, posterior alpha power was negatively related to depression severity. The Bayesian linear regression model showed significant depression severity prediction performance based on the spatial distribution of both alpha (r=0.68, p=0.0005) and beta power (r=0.56, p=0.007) respectively. Our findings point to a specific alteration of oscillatory brain activity in MDD patients during rest as characterized from MEG data in terms of spectral and spatial distribution. The proposed model yielded a quantitative and objective estimation for the depression severity, which in turn has a potential for diagnosis and monitoring of the recovery process. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  6. A range-based predictive localization algorithm for WSID networks

    Science.gov (United States)

    Liu, Yuan; Chen, Junjie; Li, Gang

    2017-11-01

    Most studies on localization algorithms are conducted on the sensor networks with densely distributed nodes. However, the non-localizable problems are prone to occur in the network with sparsely distributed sensor nodes. To solve this problem, a range-based predictive localization algorithm (RPLA) is proposed in this paper for the wireless sensor networks syncretizing the RFID (WSID) networks. The Gaussian mixture model is established to predict the trajectory of a mobile target. Then, the received signal strength indication is used to reduce the residence area of the target location based on the approximate point-in-triangulation test algorithm. In addition, collaborative localization schemes are introduced to locate the target in the non-localizable situations. Simulation results verify that the RPLA achieves accurate localization for the network with sparsely distributed sensor nodes. The localization accuracy of the RPLA is 48.7% higher than that of the APIT algorithm, 16.8% higher than that of the single Gaussian model-based algorithm and 10.5% higher than that of the Kalman filtering-based algorithm.

  7. Physical properties and solubility parameters of 1-ethyl-3-methylimidazolium based ionic liquids/DMSO mixtures at 298.15 K

    Science.gov (United States)

    Saba, H.; Yumei, Z.; Huaping, W.

    2015-12-01

    Densities, refractive indices, conductivities and viscosities of binary mixtures of 1-ethyl-3-methylimidazolium-based ionic liquids (ILs) with dimethyl sulfoxide at 298.15 K are reported. Excess molar volumes have been calculated from experimental data and were fitted with Redlich-Kister equation. The density and refractive index were found to increase with increasing concentration in all cases except [EMIM]COOH. The free mobility of ions has found to enhance conductivity and decrease viscosity to varying extent in all mixtures being studied. It has been observed that solubility parameters, dielectric constants and nature of anions of ILs being used play a vital role in determining the subsequent characteristics. As DMSO has high dielectric constant therefore, it was able to form interactions with most of ILs except with [EMIM]COOH due to anomalous nature of anion.

  8. Issues concerning the determination of solubility products of sparingly soluble crystalline solids. Solubility of HfO2(cr)

    International Nuclear Information System (INIS)

    Rai, Dhanpat; Kitamura, Akira; Rosso, Kevin M.; Sasaki, Takayuki; Kobayashi, Taishi

    2016-01-01

    Solubility studies were conducted with HfO 2 (cr) solid as a function HCl and ionic strength ranging from 2.0 to 0.004 mol kg -1 . These studies involved (1) using two different amounts of the solid phase, (2) acid washing the bulk solid phase, (3) preheating the solid phase to 1400 C, and (4) heating amorphous HfO 2 (am) suspensions to 90 C to ascertain whether the HfO 2 (am) converts to HfO 2 (cr) and to determine the solubility from the oversaturation direction. Based on the results of these treatments it is concluded that the HfO 2 (cr) contains a small fraction of less crystalline, but not amorphous, material [HfO 2 (lcr)] and this, rather than the HfO 2 (cr), is the solubility-controlling phase in the range of experimental variables investigated in this study. The solubility data are interpreted using both the Pitzer and SIT models and they provide log 10 K 0 values of -(59.75±0.35) and -(59.48±0.41), respectively, for the solubility product of HfO 2 (lcr)[HfO 2 (lcr) + 2H 2 O ↔ Hf 4+ + 4OH - ]. The log 10 of the solubility product of HfO 2 (cr) is estimated to be < -63. The observation of a small fraction of less crystalline higher solubility material is consistent with the general picture that mineral surfaces are often structurally and/or compositionally imperfect leading to a higher solubility than the bulk crystalline solid. This study stresses the urgent need, during interpretation of solubility data, of taking precautions to make certain that the observed solubility behavior for sparingly-soluble solids is assigned to the proper solid phase.

  9. Issues concerning the determination of solubility products of sparingly soluble crystalline solids. Solubility of HfO{sub 2}(cr)

    Energy Technology Data Exchange (ETDEWEB)

    Rai, Dhanpat [Rai Enviro-Chem, LLC, Yachats, OR (United States); Kitamura, Akira [Japan Atomic Energy Agency, Ibaraki (Japan); Rosso, Kevin M. [Pacific Northwest National Laboratory, Richland, WA (United States); Sasaki, Takayuki; Kobayashi, Taishi [Kyoto Univ. (Japan)

    2016-11-01

    Solubility studies were conducted with HfO{sub 2}(cr) solid as a function HCl and ionic strength ranging from 2.0 to 0.004 mol kg{sup -1}. These studies involved (1) using two different amounts of the solid phase, (2) acid washing the bulk solid phase, (3) preheating the solid phase to 1400 C, and (4) heating amorphous HfO{sub 2}(am) suspensions to 90 C to ascertain whether the HfO{sub 2}(am) converts to HfO{sub 2}(cr) and to determine the solubility from the oversaturation direction. Based on the results of these treatments it is concluded that the HfO{sub 2}(cr) contains a small fraction of less crystalline, but not amorphous, material [HfO{sub 2}(lcr)] and this, rather than the HfO{sub 2}(cr), is the solubility-controlling phase in the range of experimental variables investigated in this study. The solubility data are interpreted using both the Pitzer and SIT models and they provide log{sub 10} K{sup 0} values of -(59.75±0.35) and -(59.48±0.41), respectively, for the solubility product of HfO{sub 2}(lcr)[HfO{sub 2}(lcr) + 2H{sub 2}O ↔ Hf{sup 4+} + 4OH{sup -}]. The log{sub 10} of the solubility product of HfO{sub 2}(cr) is estimated to be < -63. The observation of a small fraction of less crystalline higher solubility material is consistent with the general picture that mineral surfaces are often structurally and/or compositionally imperfect leading to a higher solubility than the bulk crystalline solid. This study stresses the urgent need, during interpretation of solubility data, of taking precautions to make certain that the observed solubility behavior for sparingly-soluble solids is assigned to the proper solid phase.

  10. Performance reliability prediction for thermal aging based on kalman filtering

    International Nuclear Information System (INIS)

    Ren Shuhong; Wen Zhenhua; Xue Fei; Zhao Wensheng

    2015-01-01

    The performance reliability of the nuclear power plant main pipeline that failed due to thermal aging was studied by the performance degradation theory. Firstly, through the data obtained from the accelerated thermal aging experiments, the degradation process of the impact strength and fracture toughness of austenitic stainless steel material of the main pipeline was analyzed. The time-varying performance degradation model based on the state space method was built, and the performance trends were predicted by using Kalman filtering. Then, the multi-parameter and real-time performance reliability prediction model for the main pipeline thermal aging was developed by considering the correlation between the impact properties and fracture toughness, and by using the stochastic process theory. Thus, the thermal aging performance reliability and reliability life of the main pipeline with multi-parameter were obtained, which provides the scientific basis for the optimization management of the aging maintenance decision making for nuclear power plant main pipelines. (authors)

  11. Human Posture and Movement Prediction based on Musculoskeletal Modeling

    DEFF Research Database (Denmark)

    Farahani, Saeed Davoudabadi

    2014-01-01

    Abstract This thesis explores an optimization-based formulation, so-called inverse-inverse dynamics, for the prediction of human posture and motion dynamics performing various tasks. It is explained how this technique enables us to predict natural kinematic and kinetic patterns for human posture...... and motion using AnyBody Modeling System (AMS). AMS uses inverse dynamics to analyze musculoskeletal systems and is, therefore, limited by its dependency on input kinematics. We propose to alleviate this dependency by assuming that voluntary postures and movement strategies in humans are guided by a desire...... expenditure, joint forces and other physiological properties derived from the detailed musculoskeletal analysis. Several attempts have been made to uncover the principles underlying motion control strategies in the literature. In case of some movements, like human squat jumping, there is almost no doubt...

  12. Construction Worker Fatigue Prediction Model Based on System Dynamic

    Directory of Open Access Journals (Sweden)

    Wahyu Adi Tri Joko

    2017-01-01

    Full Text Available Construction accident can be caused by internal and external factors such as worker fatigue and unsafe project environment. Tight schedule of construction project forcing construction worker to work overtime in long period. This situation leads to worker fatigue. This paper proposes a model to predict construction worker fatigue based on system dynamic (SD. System dynamic is used to represent correlation among internal and external factors and to simulate level of worker fatigue. To validate the model, 93 construction workers whom worked in a high rise building construction projects, were used as case study. The result shows that excessive workload, working elevation and age, are the main factors lead to construction worker fatigue. Simulation result also shows that these factors can increase worker fatigue level to 21.2% times compared to normal condition. Beside predicting worker fatigue level this model can also be used as early warning system to prevent construction worker accident

  13. Wind power prediction based on genetic neural network

    Science.gov (United States)

    Zhang, Suhan

    2017-04-01

    The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

  14. Machine-Learning-Based No Show Prediction in Outpatient Visits

    Directory of Open Access Journals (Sweden)

    Carlos Elvira

    2018-03-01

    Full Text Available A recurring problem in healthcare is the high percentage of patients who miss their appointment, be it a consultation or a hospital test. The present study seeks patient’s behavioural patterns that allow predicting the probability of no- shows. We explore the convenience of using Big Data Machine Learning models to accomplish this task. To begin with, a predictive model based only on variables associated with the target appointment is built. Then the model is improved by considering the patient’s history of appointments. In both cases, the Gradient Boosting algorithm was the predictor of choice. Our numerical results are considered promising given the small amount of information available. However, there seems to be plenty of room to improve the model if we manage to collect additional data for both patients and appointments.

  15. Prediction and Validation of Mars Pathfinder Hypersonic Aerodynamic Data Base

    Science.gov (United States)

    Gnoffo, Peter A.; Braun, Robert D.; Weilmuenster, K. James; Mitcheltree, Robert A.; Engelund, Walter C.; Powell, Richard W.

    1998-01-01

    Postflight analysis of the Mars Pathfinder hypersonic, continuum aerodynamic data base is presented. Measured data include accelerations along the body axis and axis normal directions. Comparisons of preflight simulation and measurements show good agreement. The prediction of two static instabilities associated with movement of the sonic line from the shoulder to the nose and back was confirmed by measured normal accelerations. Reconstruction of atmospheric density during entry has an uncertainty directly proportional to the uncertainty in the predicted axial coefficient. The sensitivity of the moment coefficient to freestream density, kinetic models and center-of-gravity location are examined to provide additional consistency checks of the simulation with flight data. The atmospheric density as derived from axial coefficient and measured axial accelerations falls within the range required for sonic line shift and static stability transition as independently determined from normal accelerations.

  16. Abalone Muscle Texture Evaluation and Prediction Based on TPA Experiment

    Directory of Open Access Journals (Sweden)

    Jiaxu Dong

    2017-01-01

    Full Text Available The effects of different heat treatments on abalones’ texture properties and sensory characteristics were studied. Thermal processing of abalone muscle was analyzed to determine the optimal heat treatment condition based on fuzzy evaluation. The results showed that heat treatment at 85°C for 1 hour had certain desirable effects on the properties of the abalone meat. Specifically, a back propagation (BP neural network was introduced to predict the equations of statistically significant sensory hardness, springiness, and smell using the texture data gained through TPA (texture profile analysis experiments as input and sensory evaluation data as the desired output. The final outcome was that the predictability was proved to be satisfactory, with an average error of 6.93%.

  17. Rutting Prediction in Asphalt Pavement Based on Viscoelastic Theory

    Directory of Open Access Journals (Sweden)

    Nahi Mohammed Hadi

    2016-01-01

    Full Text Available Rutting is one of the most disturbing failures on the asphalt roads due to the interrupting it is caused to the drivers. Predicting of asphalt pavement rutting is essential tool leads to better asphalt mixture design. This work describes a method of predicting the behaviour of various asphalt pavement mixes and linking these to an accelerated performance testing. The objective of this study is to develop a finite element model based on viscoplastic theory for simulating the laboratory testing of asphalt mixes in Hamburg Wheel Rut Tester (HWRT for rutting. The creep parameters C1, C2 and C3 are developed from the triaxial repeated load creep test at 50°C and at a frequency of 1 Hz and the modulus of elasticity and Poisson’ s ratio determined at the same temperature. Viscoelastic model (creep model is adopted using a FE simulator (ANSYS in order to calculate the rutting for various mixes under a uniform loading pressure of 500 kPa. An eight-node with a three Degrees of Freedom (UX, UY, and UZ Element is used for the simulation. The creep model developed for HWRT tester was verified by comparing the predicted rut depths with the measured one and by comparing the rut depth with ABAQUS result from literature. Reasonable agreement can be obtained between the predicted rut depths and the measured one. Moreover, it is found that creep model parameter C1 and C3 have a strong relationship with rutting. It was clear that the parameter C1 strongly influences rutting than the parameter C3. Finally, it can be concluded that creep model based on finite element method can be used as an effective tool to analyse rutting of asphalt pavements.

  18. Cloud-based Predictive Modeling System and its Application to Asthma Readmission Prediction

    Science.gov (United States)

    Chen, Robert; Su, Hang; Khalilia, Mohammed; Lin, Sizhe; Peng, Yue; Davis, Tod; Hirsh, Daniel A; Searles, Elizabeth; Tejedor-Sojo, Javier; Thompson, Michael; Sun, Jimeng

    2015-01-01

    The predictive modeling process is time consuming and requires clinical researchers to handle complex electronic health record (EHR) data in restricted computational environments. To address this problem, we implemented a cloud-based predictive modeling system via a hybrid setup combining a secure private server with the Amazon Web Services (AWS) Elastic MapReduce platform. EHR data is preprocessed on a private server and the resulting de-identified event sequences are hosted on AWS. Based on user-specified modeling configurations, an on-demand web service launches a cluster of Elastic Compute 2 (EC2) instances on AWS to perform feature selection and classification algorithms in a distributed fashion. Afterwards, the secure private server aggregates results and displays them via interactive visualization. We tested the system on a pediatric asthma readmission task on a de-identified EHR dataset of 2,967 patients. We conduct a larger scale experiment on the CMS Linkable 2008–2010 Medicare Data Entrepreneurs’ Synthetic Public Use File dataset of 2 million patients, which achieves over 25-fold speedup compared to sequential execution. PMID:26958172

  19. Predictive modelling-based design and experiments for synthesis and spinning of bioinspired silk fibres

    Science.gov (United States)

    Gronau, Greta; Jacobsen, Matthew M.; Huang, Wenwen; Rizzo, Daniel J.; Li, David; Staii, Cristian; Pugno, Nicola M.; Wong, Joyce Y.; Kaplan, David L.; Buehler, Markus J.

    2016-01-01

    Scalable computational modelling tools are required to guide the rational design of complex hierarchical materials with predictable functions. Here, we utilize mesoscopic modelling, integrated with genetic block copolymer synthesis and bioinspired spinning process, to demonstrate de novo materials design that incorporates chemistry, processing and material characterization. We find that intermediate hydrophobic/hydrophilic block ratios observed in natural spider silks and longer chain lengths lead to outstanding silk fibre formation. This design by nature is based on the optimal combination of protein solubility, self-assembled aggregate size and polymer network topology. The original homogeneous network structure becomes heterogeneous after spinning, enhancing the anisotropic network connectivity along the shear flow direction. Extending beyond the classical polymer theory, with insights from the percolation network model, we illustrate the direct proportionality between network conductance and fibre Young's modulus. This integrated approach provides a general path towards de novo functional network materials with enhanced mechanical properties and beyond (optical, electrical or thermal) as we have experimentally verified. PMID:26017575

  20. Predictive modelling-based design and experiments for synthesis and spinning of bioinspired silk fibres.

    Science.gov (United States)

    Lin, Shangchao; Ryu, Seunghwa; Tokareva, Olena; Gronau, Greta; Jacobsen, Matthew M; Huang, Wenwen; Rizzo, Daniel J; Li, David; Staii, Cristian; Pugno, Nicola M; Wong, Joyce Y; Kaplan, David L; Buehler, Markus J

    2015-05-28

    Scalable computational modelling tools are required to guide the rational design of complex hierarchical materials with predictable functions. Here, we utilize mesoscopic modelling, integrated with genetic block copolymer synthesis and bioinspired spinning process, to demonstrate de novo materials design that incorporates chemistry, processing and material characterization. We find that intermediate hydrophobic/hydrophilic block ratios observed in natural spider silks and longer chain lengths lead to outstanding silk fibre formation. This design by nature is based on the optimal combination of protein solubility, self-assembled aggregate size and polymer network topology. The original homogeneous network structure becomes heterogeneous after spinning, enhancing the anisotropic network connectivity along the shear flow direction. Extending beyond the classical polymer theory, with insights from the percolation network model, we illustrate the direct proportionality between network conductance and fibre Young's modulus. This integrated approach provides a general path towards de novo functional network materials with enhanced mechanical properties and beyond (optical, electrical or thermal) as we have experimentally verified.

  1. Do Culture-based Segments Predict Selection of Market Strategy?

    Directory of Open Access Journals (Sweden)

    Veronika Jadczaková

    2015-01-01

    Full Text Available Academists and practitioners have already acknowledged the importance of unobservable segmentation bases (such as psychographics yet still focusing on how well these bases are capable of describing relevant segments (the identifiability criterion rather than on how precisely these segments can predict (the predictability criterion. Therefore, this paper intends to add a debate to this topic by exploring whether culture-based segments do account for a selection of market strategy. To do so, a set of market strategy variables over a sample of 251 manufacturing firms was first regressed on a set of 19 cultural variables using canonical correlation analysis. Having found significant relationship in the first canonical function, it was further examined by means of correspondence analysis which cultural segments – if any – are linked to which market strategies. However, as correspondence analysis failed to find a significant relationship, it may be concluded that business culture might relate to the adoption of market strategy but not to the cultural groupings presented in the paper.

  2. Water-soluble vitamins.

    Science.gov (United States)

    Konings, Erik J M

    2006-01-01

    Simultaneous Determination of Vitamins.--Klejdus et al. described a simultaneous determination of 10 water- and 10 fat-soluble vitamins in pharmaceutical preparations by liquid chromatography-diode-array detection (LC-DAD). A combined isocratic and linear gradient allowed separation of vitamins in 3 distinct groups: polar, low-polar, and nonpolar. The method was applied to pharmaceutical preparations, fortified powdered drinks, and food samples, for which results were in good agreement with values claimed. Heudi et al. described a separation of 9 water-soluble vitamins by LC-UV. The method was applied for the quantification of vitamins in polyvitaminated premixes used for the fortification of infant nutrition products. The repeatability of the method was evaluated at different concentration levels and coefficients of variation were based on, for example, LC. Koontz et al. showed results of total folate concentrations measured by microbiological assay in a variety of foods. Samples were submitted in a routine manner to experienced laboratories that regularly perform folate analysis fee-for-service basis in the United States. Each laboratory reported the use of a microbiological method similar to the AOAC Official Method for the determination of folic acid. Striking was, the use of 3 different pH extraction conditions by 4 laboratories. Only one laboratory reported using a tri-enzyme extraction. Results were evaluated. Results for folic acid fortified foods had considerably lower between-laboratory variation, 9-11%, versus >45% for other foods. Mean total folate ranged from 14 to 279 microg/100 g for a mixed vegetable reference material, from 5 to 70 microg/100 g for strawberries, and from 28 to 81 microg/100 g for wholemeal flour. One should realize a large variation in results, which might be caused by slight modifications in the microbiological analysis of total folate in foods or the analysis in various (unfortified) food matrixes. Furthermore, optimal

  3. Iron solubility in highly boron-doped silicon

    International Nuclear Information System (INIS)

    McHugo, S.A.; McDonald, R.J.; Smith, A.R.; Hurley, D.L.; Weber, E.R.

    1998-01-01

    We have directly measured the solubility of iron in high and low boron-doped silicon using instrumental neutron activation analysis. Iron solubilities were measured at 800, 900, 1000, and 1100thinsp degree C in silicon doped with either 1.5x10 19 or 6.5x10 14 thinspboronthinspatoms/cm 3 . We have measured a greater iron solubility in high boron-doped silicon as compared to low boron-doped silicon, however, the degree of enhancement is lower than anticipated at temperatures >800thinsp degree C. The decreased enhancement is explained by a shift in the iron donor energy level towards the valence band at elevated temperatures. Based on this data, we have calculated the position of the iron donor level in the silicon band gap at elevated temperatures. We incorporate the iron energy level shift in calculations of iron solubility in silicon over a wide range of temperatures and boron-doping levels, providing a means to accurately predict iron segregation between high and low boron-doped silicon. copyright 1998 American Institute of Physics

  4. Risk prediction of cardiovascular death based on the QTc interval

    DEFF Research Database (Denmark)

    Nielsen, Jonas B; Graff, Claus; Rasmussen, Peter V

    2014-01-01

    electrocardiograms from 173 529 primary care patients aged 50-90 years were collected during 2001-11. The Framingham formula was used for heart rate-correction of the QT interval. Data on medication, comorbidity, and outcomes were retrieved from administrative registries. During a median follow-up period of 6......AIMS: Using a large, contemporary primary care population we aimed to provide absolute long-term risks of cardiovascular death (CVD) based on the QTc interval and to test whether the QTc interval is of value in risk prediction of CVD on an individual level. METHODS AND RESULTS: Digital...

  5. A New Approach on Estimation of Solubility and n-Octanol/ Water Partition Coefficient for Organohalogen Compounds

    Directory of Open Access Journals (Sweden)

    Chenzhong Cao

    2008-06-01

    Full Text Available The aqueous solubility (logW and n-octanol/water partition coefficient (logPOW are important properties for pharmacology, toxicology and medicinal chemistry. Based on an understanding of the dissolution process, the frontier orbital interaction model was suggested in the present paper to describe the solvent-solute interactions of organohalogen compounds and a general three-parameter model was proposed to predict the aqueous solubility and n-octanol/water partition coefficient for the organohalogen compounds containing nonhydrogen-binding interactions. The model has satisfactory prediction accuracy. Furthermore, every item in the model has a very explicit meaning, which should be helpful to understand the structure-solubility relationship and may be provide a new view on estimation of solubility.

  6. Decline curve based models for predicting natural gas well performance

    Directory of Open Access Journals (Sweden)

    Arash Kamari

    2017-06-01

    Full Text Available The productivity of a gas well declines over its production life as cannot cover economic policies. To overcome such problems, the production performance of gas wells should be predicted by applying reliable methods to analyse the decline trend. Therefore, reliable models are developed in this study on the basis of powerful artificial intelligence techniques viz. the artificial neural network (ANN modelling strategy, least square support vector machine (LSSVM approach, adaptive neuro-fuzzy inference system (ANFIS, and decision tree (DT method for the prediction of cumulative gas production as well as initial decline rate multiplied by time as a function of the Arps' decline curve exponent and ratio of initial gas flow rate over total gas flow rate. It was concluded that the results obtained based on the models developed in current study are in satisfactory agreement with the actual gas well production data. Furthermore, the results of comparative study performed demonstrates that the LSSVM strategy is superior to the other models investigated for the prediction of both cumulative gas production, and initial decline rate multiplied by time.

  7. Mobile Phone-Based Mood Ratings Prospectively Predict Psychotherapy Attendance.

    Science.gov (United States)

    Bruehlman-Senecal, Emma; Aguilera, Adrian; Schueller, Stephen M

    2017-09-01

    Psychotherapy nonattendance is a costly and pervasive problem. While prior research has identified stable patient-level predictors of attendance, far less is known about dynamic (i.e., time-varying) factors. Identifying dynamic predictors can clarify how clinical states relate to psychotherapy attendance and inform effective "just-in-time" interventions to promote attendance. The present study examines whether daily mood, as measured by responses to automated mobile phone-based text messages, prospectively predicts attendance in group cognitive-behavioral therapy (CBT) for depression. Fifty-six Spanish-speaking Latino patients with elevated depressive symptoms (46 women, mean age=50.92years, SD=10.90years), enrolled in a manualized program of group CBT, received daily automated mood-monitoring text messages. Patients' daily mood ratings, message response rate, and delay in responding were recorded. Patients' self-reported mood the day prior to a scheduled psychotherapy session significantly predicted attendance, even after controlling for patients' prior attendance history and age (OR=1.33, 95% CI [1.04, 1.70], p=.02). Positive mood corresponded to a greater likelihood of attendance. Our results demonstrate the clinical utility of automated mood-monitoring text messages in predicting attendance. These results underscore the value of text messaging, and other mobile technologies, as adjuncts to psychotherapy. Future work should explore the use of such monitoring to guide interventions to increase attendance, and ultimately the efficacy of psychotherapy. Copyright © 2017. Published by Elsevier Ltd.

  8. 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.

  9. Analysis Science Process Skills Content in Chemistry Textbooks Grade XI at Solubility and Solubility Product Concept

    Directory of Open Access Journals (Sweden)

    Bayu Antrakusuma

    2017-12-01

    Full Text Available The aim of this research was to determine the analysis of science process skills in textbooks of chemistry grade XI in SMA N 1 Teras, Boyolali. This research used the descriptive method. The instruments were developed based on 10 indicators of science process skills (observing, classifying, finding a conclusion, predicting, raising the question, hypothesizing, planning an experiment, manipulating materials, and equipment, Applying, and communicating. We analyzed 3 different chemistry textbooks that often used by teachers in teaching. The material analyzed in the book was solubility and solubility product concept in terms of concept explanation and student activity. The results of this research showed different science process skill criteria in 3 different chemistry textbooks. Book A appeared 50% of all aspects of science process skills, in Book B appeared 80% of all aspects of science process skills, and in Book C there was 40% of all aspects of the science process skills. The most common indicator in all books was observing (33.3%, followed by prediction (19.05%, classifying (11.90%, Applying (11.90% , planning experiments (9.52%, manipulating materials and equipment (7.14%, finding conclusion (4.76%, communicating (2.38%. Asking the question and hypothesizing did not appear in textbooks.

  10. Model-based prediction of myelosuppression and recovery based on frequent neutrophil monitoring.

    Science.gov (United States)

    Netterberg, Ida; Nielsen, Elisabet I; Friberg, Lena E; Karlsson, Mats O

    2017-08-01

    To investigate whether a more frequent monitoring of the absolute neutrophil counts (ANC) during myelosuppressive chemotherapy, together with model-based predictions, can improve therapy management, compared to the limited clinical monitoring typically applied today. Daily ANC in chemotherapy-treated cancer patients were simulated from a previously published population model describing docetaxel-induced myelosuppression. The simulated values were used to generate predictions of the individual ANC time-courses, given the myelosuppression model. The accuracy of the predicted ANC was evaluated under a range of conditions with reduced amount of ANC measurements. The predictions were most accurate when more data were available for generating the predictions and when making short forecasts. The inaccuracy of ANC predictions was highest around nadir, although a high sensitivity (≥90%) was demonstrated to forecast Grade 4 neutropenia before it occurred. The time for a patient to recover to baseline could be well forecasted 6 days (±1 day) before the typical value occurred on day 17. Daily monitoring of the ANC, together with model-based predictions, could improve anticancer drug treatment by identifying patients at risk for severe neutropenia and predicting when the next cycle could be initiated.

  11. Solubility of Plutonium (IV) Oxalate During Americium/Curium Pretreatment

    International Nuclear Information System (INIS)

    Rudisill, T.S.

    1999-01-01

    Approximately 15,000 L of solution containing isotopes of americium and curium (Am/Cm) will undergo stabilization by vitrification at the Savannah River Site (SRS). Prior to vitrification, an in-tank pretreatment will be used to remove metal impurities from the solution using an oxalate precipitation process. Material balance calculations for this process, based on solubility data in pure nitric acid, predict approximately 80 percent of the plutonium in the solution will be lost to waste. Due to the uncertainty associated with the plutonium losses during processing, solubility experiments were performed to measure the recovery of plutonium during pretreatment and a subsequent precipitation process to prepare a slurry feed for a batch melter. A good estimate of the plutonium content of the glass is required for planning the shipment of the vitrified Am/Cm product to Oak Ridge National Laboratory (ORNL).The plutonium solubility in the oxalate precipitation supernate during pretreatment was 10 mg/mL at 35 degrees C. In two subsequent washes with a 0.25M oxalic acid/0.5M nitric acid solution, the solubility dropped to less than 5 mg/mL. During the precipitation and washing steps, lanthanide fission products in the solution were mostly insoluble. Uranium, and alkali, alkaline earth, and transition metal impurities were soluble as expected. An elemental material balance for plutonium showed that greater than 94 percent of the plutonium was recovered in the dissolved precipitate. The recovery of the lanthanide elements was generally 94 percent or higher except for the more soluble lanthanum. The recovery of soluble metal impurities from the precipitate slurry ranged from 15 to 22 percent. Theoretically, 16 percent of the soluble oxalates should have been present in the dissolved slurry based on the dilution effects and volumes of supernate and wash solutions removed. A trace level material balance showed greater than 97 percent recovery of americium-241 (from the beta dec

  12. Progress in the research of neptunium solubility

    International Nuclear Information System (INIS)

    Jiang Tao; Liu Yongye; Yao Jun

    2012-01-01

    237 Np is considered a possible long-term potential threat for environment, because of its long half-life, high toxicity and its mobile nature under aerobic conditions due to the high chemical stability of its pentavalent state. Therefore 237 Np is considered as one of high-level radioactive waste and need to be disposed in deep geologic disposal repository. The dissolution behavior is an important aspect of migration research. The solubility is considered very important for high level waste geological disposal safety and environmental evaluation. The solubility determines the maximum concentration of the discharge, and then it is initial concentration of the radionuclides migration to the environment. The solubility impact directly on radionuclides migration in host rock, and can be used to predict the concentration and speciation of radionuclides in groundwater around disposal sites many years later. This paper focused on research results of the solubility, some proposals for Np dissolution chemistry research were also been suggested. (authors)

  13. An estimation of influence of humic acid and organic matter originated from bentonite on samarium solubility

    International Nuclear Information System (INIS)

    Kanaji, Mariko; Sato, Haruo; Sasahira, Akira

    1999-10-01

    Organic acids in groundwater are considered to form complexes and increase the solubility of radionuclides released from vitrified waste in a high-level radioactive waste (HLW) repository. To investigate whether the solubility of samarium (Sm) is influenced by organic substances, we measured Sm solubility in the presence of different organic substances and compared those values with results from thermodynamic predictions. Humic acid (Aldrich) is commercially available and soluble organic matter originated from bentonite were used as organic substances in this study. Consequently, the solubility of Sm showed a tendency to apparently increase with increasing the concentration of humic acid, but in the presence of carbonate, thermodynamic predictions suggested that the dominant species are carbonate complexes and that the effect of organic substances are less than that of carbonate. Based on total organic carbon (TOC), the increase of Sm solubility measured with humic acid (Aldrich) was more significant than that in the case with soluble organic matter originated from bentonite. Since bentonite is presumed to include also simple organic matters of which stability constant for forming complexes is low, the effect of soluble organic matter originated from bentonite on the solubility of Sm is considered to be less effective than that of humic acid (Aldrich). Experimental values were compared with model prediction, proposed by Kim, based on data measured in a low pH region. Tentatively we calculated the increase in Sm solubility assuming complexation with humic acid. Trial calculations were carried out on the premise that the complexation reaction of metal ion with humic acid is based on neutralization process by 1-1 complexation. In this process, it was assumed that one metal ion coordinates with one unit of complexation sites which number of proton exchange sites is equal to ionic charge. Consequently, Kim's model indicated that carbonate complexes should be dominant

  14. A prediction method based on grey system theory in equipment condition based maintenance

    International Nuclear Information System (INIS)

    Yan, Shengyuan; Yan, Shengyuan; Zhang, Hongguo; Zhang, Zhijian; Peng, Minjun; Yang, Ming

    2007-01-01

    Grey prediction is a modeling method based on historical or present, known or indefinite information, which can be used for forecasting the development of the eigenvalues of the targeted equipment system and setting up the model by using less information. In this paper, the postulate of grey system theory, which includes the grey generating, the sorts of grey generating and the grey forecasting model, is introduced first. The concrete application process, which includes the grey prediction modeling, grey prediction, error calculation, equal dimension and new information approach, is introduced secondly. Application of a so-called 'Equal Dimension and New Information' (EDNI) technology in grey system theory is adopted in an application case, aiming at improving the accuracy of prediction without increasing the amount of calculation by replacing old data with new ones. The proposed method can provide a new way for solving the problem of eigenvalue data exploding in equal distance effectively, short time interval and real time prediction. The proposed method, which was based on historical or present, known or indefinite information, was verified by the vibration prediction of induced draft fan of a boiler of the Yantai Power Station in China, and the results show that the proposed method based on grey system theory is simple and provides a high accuracy in prediction. So, it is very useful and significant to the controlling and controllable management in safety production. (authors)

  15. Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

    Directory of Open Access Journals (Sweden)

    Michael F Sloma

    2017-11-01

    Full Text Available Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

  16. Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

    Science.gov (United States)

    Sloma, Michael F; Mathews, David H

    2017-11-01

    Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

  17. Phosphate-based glasses: Prediction of acoustical properties

    Science.gov (United States)

    El-Moneim, Amin Abd

    2016-04-01

    In this work, a comprehensive study has been carried out to predict the composition dependence of bulk modulus and ultrasonic attenuation coefficient in the phosphate-based glass systems PbO-P2O5, Li2O-TeO2-B2O3-P2O5, TiO2-Na2O-CaO-P2O5 and Cr2O3-doped Na2O-ZnO-P2O5 at room temperature. The prediction is based on (i) Makishima-Mackenzie theory, which correlates the bulk modulus with packing density and dissociation energy per unit volume, and (ii) Our recently presented semi-empirical formulas, which correlate the ultrasonic attenuation coefficient with the oxygen density, mean atomic ring size, first-order stretching force constant and experimental bulk modulus. Results revealed that our recently presented semi-empirical formulas can be applied successfully to predict changes of ultrasonic attenuation coefficient in binary PbO-P2O5 glasses at 10 MHz frequency and in quaternary Li2O-TeO2-B2O3-P2O5, TiO2-Na2O-CaO-P2O5 and Cr2O3-Na2O-ZnO-P2O5 glasses at 5 MHz frequency. Also, Makishima-Mackenzie theory appears to be valid for the studied glasses if the effect of the basic structural units that present in the glass network is taken into account.

  18. Stand diameter distribution modelling and prediction based on Richards function.

    Directory of Open Access Journals (Sweden)

    Ai-guo Duan

    Full Text Available The objective of this study was to introduce application of the Richards equation on modelling and prediction of stand diameter distribution. The long-term repeated measurement data sets, consisted of 309 diameter frequency distributions from Chinese fir (Cunninghamia lanceolata plantations in the southern China, were used. Also, 150 stands were used as fitting data, the other 159 stands were used for testing. Nonlinear regression method (NRM or maximum likelihood estimates method (MLEM were applied to estimate the parameters of models, and the parameter prediction method (PPM and parameter recovery method (PRM were used to predict the diameter distributions of unknown stands. Four main conclusions were obtained: (1 R distribution presented a more accurate simulation than three-parametric Weibull function; (2 the parameters p, q and r of R distribution proved to be its scale, location and shape parameters, and have a deep relationship with stand characteristics, which means the parameters of R distribution have good theoretical interpretation; (3 the ordinate of inflection point of R distribution has significant relativity with its skewness and kurtosis, and the fitted main distribution range for the cumulative diameter distribution of Chinese fir plantations was 0.4∼0.6; (4 the goodness-of-fit test showed diameter distributions of unknown stands can be well estimated by applying R distribution based on PRM or the combination of PPM and PRM under the condition that only quadratic mean DBH or plus stand age are known, and the non-rejection rates were near 80%, which are higher than the 72.33% non-rejection rate of three-parametric Weibull function based on the combination of PPM and PRM.

  19. Mining key elements for severe convection prediction based on CNN

    Science.gov (United States)

    Liu, Ming; Pan, Ning; Zhang, Changan; Sha, Hongzhou; Zhang, Bolei; Liu, Liang; Zhang, Meng

    2017-04-01

    Severe convective weather is a kind of weather disasters accompanied by heavy rainfall, gust wind, hail, etc. Along with recent developments on remote sensing and numerical modeling, there are high-volume and long-term observational and modeling data accumulated to capture massive severe convective events over particular areas and time periods. With those high-volume and high-variety weather data, most of the existing studies and methods carry out the dynamical laws, cause analysis, potential rule study, and prediction enhancement by utilizing the governing equations from fluid dynamics and thermodynamics. In this study, a key-element mining method is proposed for severe convection prediction based on convolution neural network (CNN). It aims to identify the key areas and key elements from huge amounts of historical weather data including conventional measurements, weather radar, satellite, so as numerical modeling and/or reanalysis data. Under this manner, the machine-learning based method could help the human forecasters on their decision-making on operational weather forecasts on severe convective weathers by extracting key information from the real-time and historical weather big data. In this paper, it first utilizes computer vision technology to complete the data preprocessing work of the meteorological variables. Then, it utilizes the information such as radar map and expert knowledge to annotate all images automatically. And finally, by using CNN model, it cloud analyze and evaluate each weather elements (e.g., particular variables, patterns, features, etc.), and identify key areas of those critical weather elements, then help forecasters quickly screen out the key elements from huge amounts of observation data by current weather conditions. Based on the rich weather measurement and model data (up to 10 years) over Fujian province in China, where the severe convective weathers are very active during the summer months, experimental tests are conducted with

  20. Coal demand prediction based on a support vector machine model

    Energy Technology Data Exchange (ETDEWEB)

    Jia, Cun-liang; Wu, Hai-shan; Gong, Dun-wei [China University of Mining & Technology, Xuzhou (China). School of Information and Electronic Engineering

    2007-01-15

    A forecasting model for coal demand of China using a support vector regression was constructed. With the selected embedding dimension, the output vectors and input vectors were constructed based on the coal demand of China from 1980 to 2002. After compared with lineal kernel and Sigmoid kernel, a radial basis function(RBF) was adopted as the kernel function. By analyzing the relationship between the error margin of prediction and the model parameters, the proper parameters were chosen. The support vector machines (SVM) model with multi-input and single output was proposed. Compared the predictor based on RBF neural networks with test datasets, the results show that the SVM predictor has higher precision and greater generalization ability. In the end, the coal demand from 2003 to 2006 is accurately forecasted. l0 refs., 2 figs., 4 tabs.

  1. Domain Adaptation for Pedestrian Detection Based on Prediction Consistency

    Directory of Open Access Journals (Sweden)

    Yu Li-ping

    2014-01-01

    Full Text Available Pedestrian detection is an active area of research in computer vision. It remains a quite challenging problem in many applications where many factors cause a mismatch between source dataset used to train the pedestrian detector and samples in the target scene. In this paper, we propose a novel domain adaptation model for merging plentiful source domain samples with scared target domain samples to create a scene-specific pedestrian detector that performs as well as rich target domain simples are present. Our approach combines the boosting-based learning algorithm with an entropy-based transferability, which is derived from the prediction consistency with the source classifications, to selectively choose the samples showing positive transferability in source domains to the target domain. Experimental results show that our approach can improve the detection rate, especially with the insufficient labeled data in target scene.

  2. Enhancement of Solubility and Bioavailability of Candesartan ...

    African Journals Online (AJOL)

    Purpose: To enhance the otherwise poor solubility and bioavailability of candesartan cilexetil (CDS). Methods: This ... PEG 6000-based solid dispersions showed 1st order drug release kinetics. ..... the liver due to quercetin's inhibitory effect on.

  3. Diagnostic accuracy of presepsin (soluble CD14 subtype) for prediction of bacteremia in patients with systemic inflammatory response syndrome in the Emergency Department.

    Science.gov (United States)

    Romualdo, Luis García de Guadiana; Torrella, Patricia Esteban; González, Monserrat Viqueira; Sánchez, Roberto Jiménez; Holgado, Ana Hernando; Freire, Alejandro Ortín; Acebes, Sergio Rebollo; Otón, María Dolores Albaladejo

    2014-05-01

    Bacteremia is indicative of severe bacterial infection with significant mortality. Its early diagnosis is extremely important for implementation of antimicrobial therapy but a diagnostic challenge. Although blood culture is the "gold standard" for diagnosis of bacteremia this method has limited usefulness for the early detection of blood-stream infection. In this study we assessed the presepsin as predictor of bacteremia in patients with systemic inflammatory response syndrome (SIRS) on admission to the Emergency Department and compare it with current available infection biomarkers. A total of 226 patients admitted to the Emergency Department with SIRS were included. In 37 patients blood culture had a positive result (bacteremic SIRS group) and 189 had a negative blood culture result (non-bacteremic SIRS group). Simultaneously with blood culture, presepsin, procalcitonin (PCT) and C-reactive protein (CRP) were measured. Receiver operating characteristic (ROC) curve analysis was performed for each biomarker as predictor of bacteremia. Presepsin values were significantly higher in bacteremic SIRS group when compared with non-bacteremic SIRS group. ROC curve analysis and area under curve (AUC) revealed a value of 0.750 for presepsin in differentiating SIRS patients with bacteremia from those without, similar than that for PCT (0.787) and higher than that for CRP (0.602). The best cut-off value for presepsin was 729pg/mL, which was associated with a negative predictive value of 94.4%. Presepsin may contribute to rule out the diagnosis of bacteremia in SIRS patients admitted to the Emergency Department. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  4. Transcriptome dynamics-based operon prediction in prokaryotes.

    Science.gov (United States)

    Fortino, Vittorio; Smolander, Olli-Pekka; Auvinen, Petri; Tagliaferri, Roberto; Greco, Dario

    2014-05-16

    Inferring operon maps is crucial to understanding the regulatory networks of prokaryotic genomes. Recently, RNA-seq based transcriptome studies revealed that in many bacterial species the operon structure vary with the change of environmental conditions. Therefore, new computational solutions that use both static and dynamic data are necessary to create condition specific operon predictions. In this work, we propose a novel classification method that integrates RNA-seq based transcriptome profiles with genomic sequence features to accurately identify the operons that are expressed under a measured condition. The classifiers are trained on a small set of confirmed operons and then used to classify the remaining gene pairs of the organism studied. Finally, by linking consecutive gene pairs classified as operons, our computational approach produces condition-dependent operon maps. We evaluated our approach on various RNA-seq expression profiles of the bacteria Haemophilus somni, Porphyromonas gingivalis, Escherichia coli and Salmonella enterica. Our results demonstrate that, using features depending on both transcriptome dynamics and genome sequence characteristics, we can identify operon pairs with high accuracy. Moreover, the combination of DNA sequence and expression data results in more accurate predictions than each one alone. We present a computational strategy for the comprehensive analysis of condition-dependent operon maps in prokaryotes. Our method can be used to generate condition specific operon maps of many bacterial organisms for which high-resolution transcriptome data is available.

  5. Analyst-to-Analyst Variability in Simulation-Based Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Glickman, Matthew R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Romero, Vicente J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-02-01

    This report describes findings from the culminating experiment of the LDRD project entitled, "Analyst-to-Analyst Variability in Simulation-Based Prediction". For this experiment, volunteer participants solving a given test problem in engineering and statistics were interviewed at different points in their solution process. These interviews are used to trace differing solutions to differing solution processes, and differing processes to differences in reasoning, assumptions, and judgments. The issue that the experiment was designed to illuminate -- our paucity of understanding of the ways in which humans themselves have an impact on predictions derived from complex computational simulations -- is a challenging and open one. Although solution of the test problem by analyst participants in this experiment has taken much more time than originally anticipated, and is continuing past the end of this LDRD, this project has provided a rare opportunity to explore analyst-to-analyst variability in significant depth, from which we derive evidence-based insights to guide further explorations in this important area.

  6. Predicting chick body mass by artificial intelligence-based models

    Directory of Open Access Journals (Sweden)

    Patricia Ferreira Ponciano Ferraz

    2014-07-01

    Full Text Available The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks - with the variables dry-bulb air temperature, duration of thermal stress (days, chick age (days, and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs and neuro-fuzzy networks (NFNs. The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The ANNs enable the simulation of different scenarios, which can assist in managerial decision-making, and they can be embedded in the heating control systems.

  7. Prediction Based Energy Balancing Forwarding in Cellular Networks

    Directory of Open Access Journals (Sweden)

    Yang Jian-Jun

    2017-01-01

    Full Text Available In the recent cellular network technologies, relay stations extend cell coverage and enhance signal strength for mobile users. However, busy traffic makes the relay stations in hot area run out of energy quickly. Energy is a very important factor in the forwarding of cellular network since mobile users(cell phones in hot cells often suffer from low throughput due to energy lack problems. In many situations, the energy lack problems take place because the energy loading is not balanced. In this paper, we present a prediction based forwarding algorithm to let a mobile node dynamically select the next relay station with highest potential energy capacity to resume communication. Key to this strategy is that a relay station only maintains three past status, and then it is able to predict the potential energy capacity. Then, the node selects the next hop with potential maximal energy. Moreover, a location based algorithm is developed to let the mobile node figure out the target region in order to avoid flooding. Simulations demonstrate that our approach significantly increase the aggregate throughput and decrease the delay in cellular network environment.

  8. Module-based outcome prediction using breast cancer compendia.

    Directory of Open Access Journals (Sweden)

    Martin H van Vliet

    Full Text Available BACKGROUND: The availability of large collections of microarray datasets (compendia, or knowledge about grouping of genes into pathways (gene sets, is typically not exploited when training predictors of disease outcome. These can be useful since a compendium increases the number of samples, while gene sets reduce the size of the feature space. This should be favorable from a machine learning perspective and result in more robust predictors. METHODOLOGY: We extracted modules of regulated genes from gene sets, and compendia. Through supervised analysis, we constructed predictors which employ modules predictive of breast cancer outcome. To validate these predictors we applied them to independent data, from the same institution (intra-dataset, and other institutions (inter-dataset. CONCLUSIONS: We show that modules derived from single breast cancer datasets achieve better performance on the validation data compared to gene-based predictors. We also show that there is a trend in compendium specificity and predictive performance: modules derived from a single breast cancer dataset, and a breast cancer specific compendium perform better compared to those derived from a human cancer compendium. Additionally, the module-based predictor provides a much richer insight into the underlying biology. Frequently selected gene sets are associated with processes such as cell cycle, E2F regulation, DNA damage response, proteasome and glycolysis. We analyzed two modules related to cell cycle, and the OCT1 transcription factor, respectively. On an individual basis, these modules provide a significant separation in survival subgroups on the training and independent validation data.

  9. Protein Function Prediction Based on Sequence and Structure Information

    KAUST Repository

    Smaili, Fatima Z.

    2016-05-25

    The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.

  10. Understanding the behaviour of the actinides under disposal conditions: A comparison between calculated and experimental solubilities

    International Nuclear Information System (INIS)

    Pryke, D.C.; Rees, J.H.

    1986-01-01

    The solubilities of plutonium, americium and neptunium measured in simulated near-field waters have compared with those predicted using the simple thermodynamic model NearSol. The dependence of solubility on pH and redox potential is examined in an effort to understand the behaviour of actinides in disposal. The agreement was variable. Differences could be appreciable, in particular for neptunium under oxidizing conditions; conversly, the model successfully predicted the behaviour of neptunium under reducing conditions. Such comparisons pinpointed deficiences in the thermodynamic data base and showed the sensitivity of solubilities to certain experimental parameters such as Eh and the concentration of carbonate ions. A comparison between NearSol and the reaction pathway program PHREEQE gave generally good agreement. NearSol was quicker and easier to use, requiring only limited preselection of participating species; however it did not account for the behaviour of bulk inactive species in solution; like feature will be built into an updated version. (orig.)

  11. Distance matrix-based approach to protein structure prediction.

    Science.gov (United States)

    Kloczkowski, Andrzej; Jernigan, Robert L; Wu, Zhijun; Song, Guang; Yang, Lei; Kolinski, Andrzej; Pokarowski, Piotr

    2009-03-01

    Much structural information is encoded in the internal distances; a distance matrix-based approach can be used to predict protein structure and dynamics, and for structural refinement. Our approach is based on the square distance matrix D = [r(ij)(2)] containing all square distances between residues in proteins. This distance matrix contains more information than the contact matrix C, that has elements of either 0 or 1 depending on whether the distance r (ij) is greater or less than a cutoff value r (cutoff). We have performed spectral decomposition of the distance matrices D = sigma lambda(k)V(k)V(kT), in terms of eigenvalues lambda kappa and the corresponding eigenvectors v kappa and found that it contains at most five nonzero terms. A dominant eigenvector is proportional to r (2)--the square distance of points from the center of mass, with the next three being the principal components of the system of points. By predicting r (2) from the sequence we can approximate a distance matrix of a protein with an expected RMSD value of about 7.3 A, and by combining it with the prediction of the first principal component we can improve this approximation to 4.0 A. We can also explain the role of hydrophobic interactions for the protein structure, because r is highly correlated with the hydrophobic profile of the sequence. Moreover, r is highly correlated with several sequence profiles which are useful in protein structure prediction, such as contact number, the residue-wise contact order (RWCO) or mean square fluctuations (i.e. crystallographic temperature factors). We have also shown that the next three components are related to spatial directionality of the secondary structure elements, and they may be also predicted from the sequence, improving overall structure prediction. We have also shown that the large number of available HIV-1 protease structures provides a remarkable sampling of conformations, which can be viewed as direct structural information about the

  12. The Precipitation Behavior of Poorly Water-Soluble Drugs with an Emphasis on the Digestion of Lipid Based Formulations

    DEFF Research Database (Denmark)

    Khan, Jamal; Rades, Thomas; Boyd, Ben

    2016-01-01

    digestion and drug solubilisation during gastrointestinal transit have been explored in detail, but the implications of drug precipitation beyond the potential adverse effect on bioavailability have received attention only in recent years. Specifically, these implications are that different solid forms...... the events that lead to drug precipitation during the dispersion and digestion of lipid based formulations, common methods used to inhibit precipitation, as well as conventional and newly emerging characterization techniques for studying the solid state form of the precipitated drug. Moreover, selected case...... studies are discussed where drug precipitation has ensued from the digestion of lipid based formulations, as well as the apparent link between drug ionisability and altered solid forms on precipitation, culminating in a discussion about the importance of the solid form on precipitation with relevance...

  13. Fat-soluble vitamin and mineral comparisons between zoo-based and free-ranging koalas (Phascolarctos cinereus).

    Science.gov (United States)

    Schmidt, Debra A; Pye, Geoffrey W; Hamlin-Andrus, Chris C; Ellis, William A; Bercovitch, Fred B; Ellersieck, Mark R; Chen, Tai C; Holick, Michael F

    2013-12-01

    As part of a health investigation on koalas at San Diego Zoo, serum samples were analyzed from 18 free-ranging and 22 zoo-based koalas, Phascolarctos cinereus. Serum concentrations of calcium, chloride, cobalt, copper, iron, magnesium, manganese, molybdenum, phosphorus, potassium, selenium, sodium, zinc, and vitamins A, E, and 25(OH)D3 were quantified. Calcium, chloride, molybdenum, selenium, and vitamin E concentrations were significantly higher in zoo-based koalas than in free-ranging koalas, whereas magnesium, manganese, phosphorus, and zinc concentrations were significantly higher in the free-ranging koalas. No significant differences were found between genders. The results from this study will help to establish a starting point for determining target circulating nutrient concentrations in koalas.

  14. The solubility-permeability interplay and its implications in formulation design and development for poorly soluble drugs.

    Science.gov (United States)

    Dahan, Arik; Miller, Jonathan M

    2012-06-01

    While each of the two key parameters of oral drug absorption, the solubility and the permeability, has been comprehensively studied separately, the relationship and interplay between the two have been largely ignored. For instance, when formulating a low-solubility drug using various solubilization techniques: what are we doing to the apparent permeability when we increase the solubility? Permeability is equal to the drug's diffusion coefficient through the membrane times the membrane/aqueous partition coefficient divided by the membrane thickness. The direct correlation between the intestinal permeability and the membrane/aqueous partitioning, which in turn is dependent on the drug's apparent solubility in the GI milieu, suggests that the solubility and the permeability are closely associated, exhibiting a certain interplay between them, and the current view of treating the one irrespectively of the other may not be sufficient. In this paper, we describe the research that has been done thus far, and present new data, to shed light on this solubility-permeability interplay. It has been shown that decreased apparent permeability accompanies the solubility increase when using different solubilization methods. Overall, the weight of the evidence indicates that the solubility-permeability interplay cannot be ignored when using solubility-enabling formulations; looking solely at the solubility enhancement that the formulation enables may be misleading with regards to predicting the resulting absorption, and hence, the solubility-permeability interplay must be taken into account to strike the optimal solubility-permeability balance, in order to maximize the overall absorption.

  15. Diagnosing solubility limitations – the example of hydrate formation

    Directory of Open Access Journals (Sweden)

    Joerg Berghausen

    2014-07-01

    Full Text Available Solubility is regarded as one of the key challenges in many drug discovery projects. Thus, it’s essential to support the lead finding and optimization efforts by appropriate solubility data. In silico solubility prediction remains challenging and therefore a screening assay is used as a first filter, followed by selected follow-up assays to reveal what causes the low solubility of a specific compound or chemotype. Results from diagnosing the underlying reason for solubility limitation are discussed. As lipophilicity and crystal lattice forces are regarded as main contributors to limiting solubility, changes in solid state are important to be recognized. Solubility limitation by various factors will be presented and the impact of the solid-state is exemplified by compounds that are able to form hydrates.

  16. A new synthetic methodology for the preparation of biocompatible and organo-soluble barbituric- and thiobarbituric acid based chitosan derivatives for biomedical applications

    Energy Technology Data Exchange (ETDEWEB)

    Shahzad, Sohail [Interdisciplinary Research Center in Biomedical Materials, COMSATS Institute of Information Technology, Lahore 54000 (Pakistan); Department of Chemistry, The Islamia University of Bahawalpur, Bahawalpur 63100 (Pakistan); Shahzadi, Lubna [Interdisciplinary Research Center in Biomedical Materials, COMSATS Institute of Information Technology, Lahore 54000 (Pakistan); Mahmood, Nasir [Department of Allied Health Sciences and Chemical Pathology, Department of Human Genetics and Molecular Biology, University of Health Sciences, Lahore (Pakistan); Siddiqi, Saadat Anwar [Interdisciplinary Research Center in Biomedical Materials, COMSATS Institute of Information Technology, Lahore 54000 (Pakistan); Rauf, Abdul [Department of Chemistry, The Islamia University of Bahawalpur, Bahawalpur 63100 (Pakistan); Manzoor, Faisal; Chaudhry, Aqif Anwar [Interdisciplinary Research Center in Biomedical Materials, COMSATS Institute of Information Technology, Lahore 54000 (Pakistan); Rehman, Ihtesham ur [Interdisciplinary Research Center in Biomedical Materials, COMSATS Institute of Information Technology, Lahore 54000 (Pakistan); Department of Materials Science and Engineering, The Kroto Research Institute, The University of Sheffield, North Campus, Broad Lane, Sheffield, S3 7HQ (United Kingdom); Yar, Muhammad, E-mail: drmyar@ciitlahore.edu.pk [Interdisciplinary Research Center in Biomedical Materials, COMSATS Institute of Information Technology, Lahore 54000 (Pakistan)

    2016-09-01

    Chitosan's poor solubility especially in organic solvents limits its use with other organo-soluble polymers; however such combinations are highly required to tailor their properties for specific biomedical applications. This paper describes the development of a new synthetic methodology for the synthesis of organo-soluble chitosan derivatives. These derivatives were synthesized from chitosan (CS), triethyl orthoformate and barbituric or thiobarbituric acid in the presence of 2-butannol. The chemical interactions and new functional motifs in the synthesized CS derivatives were evaluated by FTIR, DSC/TGA, UV/VIS, XRD and {sup 1}H NMR spectroscopy. A cytotoxicity investigation for these materials was performed by cell culture method using VERO cell line and all the synthesized derivatives were found to be non-toxic. The solubility analysis showed that these derivatives were readily soluble in organic solvents including DMSO and DMF. Their potential to use with organo-soluble commercially available polymers was exploited by electrospinning; the synthesized derivatives in combination with polycaprolactone delivered nanofibrous membranes. - Highlights: • Development of a new synthetic methodology • Synthesis of organo-soluble chitosan (CS) derivatives • VERO cells proliferation • Nanofibrous membranes from the synthesized chitosan derivatives and polycaprolactone.

  17. Method of predicting Splice Sites based on signal interactions

    Directory of Open Access Journals (Sweden)

    Deogun Jitender S

    2006-04-01

    Full Text Available Abstract Background Predicting and proper ranking of canonical splice sites (SSs is a challenging problem in bioinformatics and machine learning communities. Any progress in SSs recognition will lead to better understanding of splicing mechanism. We introduce several new approaches of combining a priori knowledge for improved SS detection. First, we design our new Bayesian SS sensor based on oligonucleotide counting. To further enhance prediction quality, we applied our new de novo motif detection tool MHMMotif to intronic ends and exons. We combine elements found with sensor information using Naive Bayesian Network, as implemented in our new tool SpliceScan. Results According to our tests, the Bayesian sensor outperforms the contemporary Maximum Entropy sensor for 5' SS detection. We report a number of putative Exonic (ESE and Intronic (ISE Splicing Enhancers found by MHMMotif tool. T-test statistics on mouse/rat intronic alignments indicates, that detected elements are on average more conserved as compared to other oligos, which supports our assumption of their functional importance. The tool has been shown to outperform the SpliceView, GeneSplicer, NNSplice, Genio and NetUTR tools for the test set of human genes. SpliceScan outperforms all contemporary ab initio gene structural prediction tools on the set of 5' UTR gene fragments. Conclusion Designed methods have many attractive properties, compared to existing approaches. Bayesian sensor, MHMMotif program and SpliceScan tools are freely available on our web site. Reviewers This article was reviewed by Manyuan Long, Arcady Mushegian and Mikhail Gelfand.

  18. Prediction of spectral acceleration response ordinates based on PGA attenuation

    Science.gov (United States)

    Graizer, V.; Kalkan, E.

    2009-01-01

    Developed herein is a new peak ground acceleration (PGA)-based predictive model for 5% damped pseudospectral acceleration (SA) ordinates of free-field horizontal component of ground motion from shallow-crustal earthquakes. The predictive model of ground motion spectral shape (i.e., normalized spectrum) is generated as a continuous function of few parameters. The proposed model eliminates the classical exhausted matrix of estimator coefficients, and provides significant ease in its implementation. It is structured on the Next Generation Attenuation (NGA) database with a number of additions from recent Californian events including 2003 San Simeon and 2004 Parkfield earthquakes. A unique feature of the model is its new functional form explicitly integrating PGA as a scaling factor. The spectral shape model is parameterized within an approximation function using moment magnitude, closest distance to the fault (fault distance) and VS30 (average shear-wave velocity in the upper 30 m) as independent variables. Mean values of its estimator coefficients were computed by fitting an approximation function to spectral shape of each record using robust nonlinear optimization. Proposed spectral shape model is independent of the PGA attenuation, allowing utilization of various PGA attenuation relations to estimate the response spectrum of earthquake recordings.

  19. THE BEHAVIOR OF SOLUBLE METALS ELUTED FROM Ni/Fe-BASED ALLOY REACTORS AFTER HIGH-TEMPERATURE AND HIGH-PRESSURE WATER PROCESS

    Directory of Open Access Journals (Sweden)

    M. Faisal

    2012-05-01

    Full Text Available The behavior of heavy metals eluted from the wall of Ni/Fe-based alloy reactors after high-temperature and high-pressure water reaction were studied at temperatures ranging from 250 to 400oC. For this purpose, water and cysteic acid were heated in two reactor materials which are SUS 316 and Inconel 625. Under the tested conditions, the erratic behaviors of soluble metals eluted from the wall of Ni/Fe-based alloy in high temperature water were observed. Results showed that metals could be eluted even at a short contact time. The presence of air also promotes elution at sub-critical conditions. At sub-critical conditions, a significant amount of Cr was extracted from SUS 316, while only traces of Ni, Fe, Mo and Mn were eluted. In contrast, Ni was removed in significant amounts compared to Cr when Inconel 625 was tested. It was observed that eluted metals tend to increased under acidic conditions and most of those metals were over the limit of WHO guideline for drinking water. The results are significant both on the viewpoint of environmental regulation on disposal of wastes containing heavy metals, toxicity of resulting product and catalytic effect on a particular reaction.

  20. Inclusion of sunflower seed and wheat dried distillers' grains with solubles in a red clover silage-based diet enhances steers performance, meat quality and fatty acid profiles.

    Science.gov (United States)

    Mapiye, C; Aalhus, J L; Turner, T D; Vahmani, P; Baron, V S; McAllister, T A; Block, H C; Uttaro, B; Dugan, M E R

    2014-12-01

    The current study compared beef production, quality and fatty acid (FA) profiles of yearling steers fed a control diet containing 70 : 30 red clover silage (RCS) : barley-based concentrate, a diet containing 11% sunflower seed (SS) substituted for barley, and diets containing SS with 15% or 30% wheat dried distillers' grain with solubles (DDGS). Additions of DDGS were balanced by reductions in RCS and SS to maintain crude fat levels in diets. A total of two pens of eight animals were fed per diet for an average period of 208 days. Relative to the control diet, feeding the SS diet increased (Pproducts (i.e. atypical dienes) with the first double bond at carbon 8 or 9 from the carboxyl end, conjugated linoleic acid isomers with the first double bond from carbon 7 to 10 from the carboxyl end, t-18:1 isomers, and reduced (Pmeat tenderness. However, in general feeding DGGS-15 or DDGS-30 diets did not change FA proportions relative to feeding the SS diet. Overall, adding SS to a RCS-based diet enhanced muscle proportions of 18:2n-6 biohydrogenation products, and further substitutions of DDGS in the diet improved beef production, and quality while maintaining proportions of potentially functional bioactive FA including vaccenic and rumenic acids.

  1. Comparison of a novel spray congealing procedure with emulsion-based methods for the micro-encapsulation of water-soluble drugs in low melting point triglycerides.

    Science.gov (United States)

    McCarron, Paul A; Donnelly, Ryan F; Al-Kassas, Rasil

    2008-09-01

    The particle size characteristics and encapsulation efficiency of microparticles prepared using triglyceride materials and loaded with two model water-soluble drugs were evaluated. Two emulsification procedures based on o/w and w/o/w methodologies were compared to a novel spray congealing procedure. After extensive modification of both emulsification methods, encapsulation efficiencies of 13.04% tetracycline HCl and 11.27% lidocaine HCl were achievable in a Witepsol-based microparticle. This compares to much improved encapsulation efficiencies close to 100% for the spray congealing method, which was shown to produce spherical particles of approximately 58 microm. Drug release studies from a Witepsol formulation loaded with lidocaine HCl showed a temperature-dependent release mechanism, which displayed diffusion-controlled kinetics at temperatures approximately 25 degrees C, but exhibited almost immediate release when triggered using temperatures close to that of skin. Therefore, such a system may find application in topical semi-solid formulations, where a temperature-induced burst release is preferred.

  2. The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model

    Science.gov (United States)

    Baehr, J.; Fröhlich, K.; Botzet, M.; Domeisen, D. I. V.; Kornblueh, L.; Notz, D.; Piontek, R.; Pohlmann, H.; Tietsche, S.; Müller, W. A.

    2015-05-01

    A seasonal forecast system is presented, based on the global coupled climate model MPI-ESM as used for CMIP5 simulations. We describe the initialisation of the system and analyse its predictive skill for surface temperature. The presented system is initialised in the atmospheric, oceanic, and sea ice component of the model from reanalysis/observations with full field nudging in all three components. For the initialisation of the ensemble, bred vectors with a vertically varying norm are implemented in the ocean component to generate initial perturbations. In a set of ensemble hindcast simulations, starting each May and November between 1982 and 2010, we analyse the predictive skill. Bias-corrected ensemble forecasts for each start date reproduce the observed surface temperature anomalies at 2-4 months lead time, particularly in the tropics. Niño3.4 sea surface temperature anomalies show a small root-mean-square error and predictive skill up to 6 months. Away from the tropics, predictive skill is mostly limited to the ocean, and to regions which are strongly influenced by ENSO teleconnections. In summary, the presented seasonal prediction system based on a coupled climate model shows predictive skill for surface temperature at seasonal time scales comparable to other seasonal prediction systems using different underlying models and initialisation strategies. As the same model underlying our seasonal prediction system—with a different initialisation—is presently also used for decadal predictions, this is an important step towards seamless seasonal-to-decadal climate predictions.

  3. Feature-Based and String-Based Models for Predicting RNA-Protein Interaction

    Directory of Open Access Journals (Sweden)

    Donald Adjeroh

    2018-03-01

    Full Text Available In this work, we study two approaches for the problem of RNA-Protein Interaction (RPI. In the first approach, we use a feature-based technique by combining extracted features from both sequences and secondary structures. The feature-based approach enhanced the prediction accuracy as it included much more available information about the RNA-protein pairs. In the second approach, we apply search algorithms and data structures to extract effective string patterns for prediction of RPI, using both sequence information (protein and RNA sequences, and structure information (protein and RNA secondary structures. This led to different string-based models for predicting interacting RNA-protein pairs. We show results that demonstrate the effectiveness of the proposed approaches, including comparative results against leading state-of-the-art methods.

  4. Research on cardiovascular disease prediction based on distance metric learning

    Science.gov (United States)

    Ni, Zhuang; Liu, Kui; Kang, Guixia

    2018-04-01

    Distance metric learning algorithm has been widely applied to medical diagnosis and exhibited its strengths in classification problems. The k-nearest neighbour (KNN) is an efficient method which treats each feature equally. The large margin nearest neighbour classification (LMNN) improves the accuracy of KNN by learning a global distance metric, which did not consider the locality of data distributions. In this paper, we propose a new distance metric algorithm adopting cosine metric and LMNN named COS-SUBLMNN which takes more care about local feature of data to overcome the shortage of LMNN and improve the classification accuracy. The proposed methodology is verified on CVDs patient vector derived from real-world medical data. The Experimental results show that our method provides higher accuracy than KNN and LMNN did, which demonstrates the effectiveness of the Risk predictive model of CVDs based on COS-SUBLMNN.

  5. Adaptive DIT-Based Fringe Tracking and Prediction at IOTA

    Science.gov (United States)

    Wilson, Edward; Pedretti, Ettore; Bregman, Jesse; Mah, Robert W.; Traub, Wesley A.

    2004-01-01

    An automatic fringe tracking system has been developed and implemented at the Infrared Optical Telescope Array (IOTA). In testing during May 2002, the system successfully minimized the optical path differences (OPDs) for all three baselines at IOTA. Based on sliding window discrete Fourier transform (DFT) calculations that were optimized for computational efficiency and robustness to atmospheric disturbances, the algorithm has also been tested extensively on off-line data. Implemented in ANSI C on the 266 MHZ PowerPC processor running the VxWorks real-time operating system, the algorithm runs in approximately 2.0 milliseconds per scan (including all three interferograms), using the science camera and piezo scanners to measure and correct the OPDs. Preliminary analysis on an extension of this algorithm indicates a potential for predictive tracking, although at present, real-time implementation of this extension would require significantly more computational capacity.

  6. Adaptive learning compressive tracking based on Markov location prediction

    Science.gov (United States)

    Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan

    2017-03-01

    Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.

  7. Optimization of arterial age prediction models based in pulse wave

    Energy Technology Data Exchange (ETDEWEB)

    Scandurra, A G [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina); Meschino, G J [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina); Passoni, L I [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina); Dai Pra, A L [Engineering Aplied Artificial Intelligence Group, Mathematics Department, Mar del Plata University (Argentina); Introzzi, A R [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina); Clara, F M [Bioengineering Laboratory, Electronic Department, Mar del Plata University (Argentina)

    2007-11-15

    We propose the detection of early arterial ageing through a prediction model of arterial age based in the coherence assumption between the pulse wave morphology and the patient's chronological age. Whereas we evaluate several methods, a Sugeno fuzzy inference system is selected. Models optimization is approached using hybrid methods: parameter adaptation with Artificial Neural Networks and Genetic Algorithms. Features selection was performed according with their projection on main factors of the Principal Components Analysis. The model performance was tested using the bootstrap error type .632E. The model presented an error smaller than 8.5%. This result encourages including this process as a diagnosis module into the device for pulse analysis that has been developed by the Bioengineering Laboratory staff.

  8. Mining Behavior Based Safety Data to Predict Safety Performance

    Energy Technology Data Exchange (ETDEWEB)

    Jeffrey C. Joe

    2010-06-01

    The Idaho National Laboratory (INL) operates a behavior based safety program called Safety Observations Achieve Results (SOAR). This peer-to-peer observation program encourages employees to perform in-field observations of each other's work practices and habits (i.e., behaviors). The underlying premise of conducting these observations is that more serious accidents are prevented from occurring because lower level “at risk” behaviors are identified and corrected before they can propagate into culturally accepted “unsafe” behaviors that result in injuries or fatalities. Although the approach increases employee involvement in safety, the premise of the program has not been subject to sufficient empirical evaluation. The INL now has a significant amount of SOAR data on these lower level “at risk” behaviors. This paper describes the use of data mining techniques to analyze these data to determine whether they can predict if and when a more serious accident will occur.

  9. Stress corrosion cracking of nickel base alloys characterization and prediction

    International Nuclear Information System (INIS)

    Santarini, G.; Pinard-Legry, G.

    1988-01-01

    For many years, studies have been carried out in several laboratories to characterize the IGSCC (Intergranular Stress Corrosion Cracking) behaviour of nickel base alloys in aqueous environments. For their relative shortness, CERTs (Constant Extension Rate Tests) have been extensively used, especially at the Corrosion Department of the CEA. However, up to recently, the results obtained with this method remained qualitative. This paper presents a first approach to a quantitative interpretation of CERT results. The basic datum used is the crack trace depth distribution determined on a specimen section at the end of a CERT. It is shown that this information can be used for the calculation of initiation and growth parameters which quantitatively characterize IGSCC phenomenon. Moreover, the rationale proposed should lead to the determination of intrinsic cracking parameters, and so, to in-service behaviour prediction

  10. A Prediction-based Smart Meter Data Generator

    DEFF Research Database (Denmark)

    Iftikhar, Nadeem; Liu, Xiufeng; Nordbjerg, Finn Ebertsen

    2016-01-01

    With the prevalence of cloud computing and In-ternet of Things (IoT), smart meters have become one of the main components of smart city strategy. Smart meters generate large amounts of fine-grained data that is used to provide useful information to consumers and utility companies for decision......, mainly due to privacy issues. This paper proposes a smart meter data generator that can generate realistic energy consumption data by making use of a small real-world dataset as seed. The generator generates data using a prediction-based method that depends on historical energy consumption patterns along......-making. Now-a-days, smart meter analytics systems consist of analytical algorithms that process massive amounts of data. These analytics algorithms require ample amounts of realistic data for testing and verification purposes. However, it is usually difficult to obtain adequate amounts of realistic data...

  11. Demand Management Based on Model Predictive Control Techniques

    Directory of Open Access Journals (Sweden)

    Yasser A. Davizón

    2014-01-01

    Full Text Available Demand management (DM is the process that helps companies to sell the right product to the right customer, at the right time, and for the right price. Therefore the challenge for any company is to determine how much to sell, at what price, and to which market segment while maximizing its profits. DM also helps managers efficiently allocate undifferentiated units of capacity to the available demand with the goal of maximizing revenue. This paper introduces control system approach to demand management with dynamic pricing (DP using the model predictive control (MPC technique. In addition, we present a proper dynamical system analogy based on active suspension and a stability analysis is provided via the Lyapunov direct method.

  12. Optimization of arterial age prediction models based in pulse wave

    International Nuclear Information System (INIS)

    Scandurra, A G; Meschino, G J; Passoni, L I; Dai Pra, A L; Introzzi, A R; Clara, F M

    2007-01-01

    We propose the detection of early arterial ageing through a prediction model of arterial age based in the coherence assumption between the pulse wave morphology and the patient's chronological age. Whereas we evaluate several methods, a Sugeno fuzzy inference system is selected. Models optimization is approached using hybrid methods: parameter adaptation with Artificial Neural Networks and Genetic Algorithms. Features selection was performed according with their projection on main factors of the Principal Components Analysis. The model performance was tested using the bootstrap error type .632E. The model presented an error smaller than 8.5%. This result encourages including this process as a diagnosis module into the device for pulse analysis that has been developed by the Bioengineering Laboratory staff

  13. Operational Numerical Weather Prediction systems based on Linux cluster architectures

    International Nuclear Information System (INIS)

    Pasqui, M.; Baldi, M.; Gozzini, B.; Maracchi, G.; Giuliani, G.; Montagnani, S.

    2005-01-01

    The progress in weather forecast and atmospheric science has been always closely linked to the improvement of computing technology. In order to have more accurate weather forecasts and climate predictions, more powerful computing resources are needed, in addition to more complex and better-performing numerical models. To overcome such a large computing request, powerful workstations or massive parallel systems have been used. In the last few years, parallel architectures, based on the Linux operating system, have been introduced and became popular, representing real high performance-low cost systems. In this work the Linux cluster experience achieved at the Laboratory far Meteorology and Environmental Analysis (LaMMA-CNR-IBIMET) is described and tips and performances analysed

  14. Prediction-based association control scheme in dense femtocell networks

    Science.gov (United States)

    Pham, Ngoc-Thai; Huynh, Thong; Hwang, Won-Joo; You, Ilsun; Choo, Kim-Kwang Raymond

    2017-01-01

    The deployment of large number of femtocell base stations allows us to extend the coverage and efficiently utilize resources in a low cost manner. However, the small cell size of femtocell networks can result in frequent handovers to the mobile user, and consequently throughput degradation. Thus, in this paper, we propose predictive association control schemes to improve the system’s effective throughput. Our design focuses on reducing handover frequency without impacting on throughput. The proposed schemes determine handover decisions that contribute most to the network throughput and are proper for distributed implementations. The simulation results show significant gains compared with existing methods in terms of handover frequency and network throughput perspective. PMID:28328992

  15. A solid phospholipid-bile salts-mixed micelles based on the fast dissolving oral films to improve the oral bioavailability of poorly water-soluble drugs

    Science.gov (United States)

    Lv, Qing-yuan; Li, Xian-yi; Shen, Bao-de; Dai, Ling; Xu, He; Shen, Cheng-ying; Yuan, Hai-long; Han, Jin

    2014-06-01

    The phospholipid-bile salts-mixed micelles (PL-BS-MMs) are potent carriers used for oral absorption of drugs that are poorly soluble in water; however, there are many limitations associated with liquid formulations. In the current study, the feasibility of preparing the fast dissolving oral films (FDOFs) containing PL-BS-MMs was examined. FDOFs incorporated with Cucurbitacin B (Cu B)-loaded PL-sodium deoxycholate (SDC)-MMs have been developed and characterized. To prepare the MMs and to serve as the micellar carrier, a weight ratio of 1:0.8 and total concentration of 54 mg/mL was selected for the PL/SDC based on the size, size distribution, zeta potential, encapsulation efficiency, and morphology. The concentration of Cu B was determined to be 5 mg/mL. Results showed that a narrow size distributed nanomicelles with a mean particle size of 86.21 ± 6.11 nm and a zeta potential of -31.21 ± 1.17 mV was obtained in our optimized Cu B-PL/SDC-MMs formulation. FDOFs were produced by solvent casting method and the formulation with 50 mg/mL of pullulan and 40 mg/mL of PEG 400 were deemed based on the physico-mechanical properties. The FDOFs containing Cu B-PL/SDC-MMs were easily reconstituted in a transparent and clear solution giving back a colloidal system with spherical micelles in the submicron range. In the in vitro dissolution test, the FDOFs containing Cu B-PL/SDC-MMs showed an increased dissolution velocity markedly. The pharmacokinetics study showed that the FDOFs containing PL-SDC-MMs not only kept the absorption properties as same as the PL-SDC-MMs, but also significantly increased the oral bioavailability of Cu B compared to the Cu B suspension ( p < 0.05). This study showed that the FDOFs containing Cu B-PL/SDC-MMs could represent a novel platform for the delivery of poorly water-soluble drugs via oral administration. Furthermore, the integration with the FDOFs could also provide a simple and cost-effective manner for the solidification of PL-SDC-MMs.

  16. Molecular Thermodynamic Modeling of Mixed Solvent Solubility

    DEFF Research Database (Denmark)

    Ellegaard, Martin Dela; Abildskov, Jens; O’Connell, John P.

    2010-01-01

    A method based on statistical mechanical fluctuation solution theory for composition derivatives of activity coefficients is employed for estimating dilute solubilities of 11 solid pharmaceutical solutes in nearly 70 mixed aqueous and nonaqueous solvent systems. The solvent mixtures range from...... nearly ideal to strongly nonideal. The database covers a temperature range from 293 to 323 K. Comparisons with available data and other existing solubility methods show that the method successfully describes a variety of observed mixed solvent solubility behaviors using solute−solvent parameters from...

  17. Fault trend prediction of device based on support vector regression

    International Nuclear Information System (INIS)

    Song Meicun; Cai Qi

    2011-01-01

    The research condition of fault trend prediction and the basic theory of support vector regression (SVR) were introduced. SVR was applied to the fault trend prediction of roller bearing, and compared with other methods (BP neural network, gray model, and gray-AR model). The results show that BP network tends to overlearn and gets into local minimum so that the predictive result is unstable. It also shows that the predictive result of SVR is stabilization, and SVR is superior to BP neural network, gray model and gray-AR model in predictive precision. SVR is a kind of effective method of fault trend prediction. (authors)

  18. The necessity of recovering soluble phosphorus from sewage sludge ashes before use in concrete based on concrete setting and workability

    DEFF Research Database (Denmark)

    Sigvardsen, Nina Marie; Ottosen, Lisbeth M.

    2016-01-01

    By replacing cement with alternative ashes, such as sewage sludge ashes (SSA) from mono-incineration plants, it is possible to reduce the CO2-emmision from the production of cement. SSA contains a large amount of phosphate which can be extracted before addition in concrete. The Danish Standard DS...... the increased addition of SP and the initial setting time is seen. By comparison with the limit for initial setting time established in DS/EN 450-1 it is possible to establish a limit for SP of 0.54 wt% cement. When studying the workability an objective limit for SP of 0.16 wt% cement can be established. SSA...... from the Danish mono-incineration plant at Spildevandscenter Avedøre is examined. At a pH-value of 13 it is possible to replace 55% and 16% of the cement, based on the set limits, with SSA from Spildevandscenter Avedøre, before it is necessary to extract SP from SSA before adding to the concrete...

  19. Water-soluble upper GI based on clinical findings is reliable to detect anastomotic leaks after laparoscopic gastric bypass.

    Science.gov (United States)

    Katasani, V G; Leeth, R R; Tishler, D S; Leath, T D; Roy, B P; Canon, C L; Vickers, S M; Clements, R H

    2005-11-01

    Anastomotic leak after laparoscopic Roux-en-Y gastric bypass (LGB) is a major complication that must be recognized and treated early for best results. There is controversy in the literature regarding the reliability of upper GI series (UGI) in diagnosing leaks. LGB was performed in patients meeting NIH criteria for the surgical treatment of morbid obesity. All leaks identified at the time of surgery were repaired with suture and retested. Drains were placed at the surgeon's discretion. Postoperatively, UGI was performed by an experienced radiologist if there was a clinical suspicion of leak. From September 2001 until October 2004, a total of 553 patients (age 40.4 +/- 9.2 years, BMI 48.6 +/- 7.2) underwent LGB at UAB. Seventy-eight per cent (431 of 553) of patients had no clinical evidence suggesting anastomotic leak and were managed expectantly. Twenty-two per cent (122 of 553) of patients met at least one inclusion criteria for leak and underwent UGI. Four of 122 patients (3.2%) had a leak, two from anastomosis and two from the perforation of the stapled end of the Roux limb. No patient returned to the operating room without a positive UGI. High clinical suspicion and selectively performed UGI based on clinical evidence is reliable in detecting leaks.

  20. Nanobody Based Immunoassay for Human Soluble Epoxide Hydrolase Detection Using Polymeric Horseradish Peroxidase (PolyHRP) for Signal Enhancement: The Rediscovery of PolyHRP?

    Science.gov (United States)

    Li, Dongyang; Cui, Yongliang; Morisseau, Christophe; Gee, Shirley J; Bever, Candace S; Liu, Xiangjiang; Wu, Jian; Hammock, Bruce D; Ying, Yibin

    2017-06-06

    Soluble epoxide hydrolase (sEH) is a potential pharmacological target for treating hypertension, vascular inflammation, cancer, pain, and multiple cardiovascular related diseases. A variable domain of the heavy chain antibody (termed single domain antibody (sdAb), nanobody, or VHH) possesses the advantages of small size, high stability, ease of genetic manipulation, and ability for continuous manufacture, making such nanobody a superior choice as an immunoreagent. In this work, we developed an ultrasensitive nanobody based immunoassay for human sEH detection using polymeric horseradish peroxidase (PolyHRP) for signal enhancement. Llama nanobodies against human sEH were used as the detection antibody in sandwich enzyme linked immunosorbent assays (ELISA) with polyclonal anti-sEH as the capture antibody. A conventional sandwich ELISA using a horseradish peroxidase (HRP) labeled anti-hemeagglutinin (HA) tag as the tracer showed a marginal sensitivity (0.0015 optical density (OD)·mL/ng) and limit of detection (LOD) of 3.02 ng/mL. However, the introduction of the PolyHRP as the tracer demonstrated a 141-fold increase in the sensitivity (0.21 OD·mL/ng) and 57-fold decrease in LOD (0.05 ng/mL). Systematic comparison of three different tracers in four ELISA formats demonstrated the overwhelming advantage of PolyHRP as a label for nanobody based immunoassay. This enhanced sEH immunoassay was further evaluated in terms of selectivity against other epoxide hydrolases and detection of the target protein in human tissue homogenate samples. Comparison with an enzyme activity based assay and a Western blot for sEH detection reveals good correlation with the immunoassay. This work demonstrates increased competiveness of nanobodies for practical sEH protein detection utilizing PolyHRP. It is worthwhile to rediscover the promising potential of PolyHRP in nanobody and other affinity based methods after its low-profile existence for decades.

  1. Revisiting Hansen Solubility Parameters by Including Thermodynamics

    NARCIS (Netherlands)

    Louwerse, Manuel J; Fernández-Maldonado, Ana María; Rousseau, Simon; Moreau-Masselon, Chloe; Roux, Bernard; Rothenberg, Gadi

    2017-01-01

    The Hansen solubility parameter approach is revisited by implementing the thermodynamics of dissolution and mixing. Hansen's pragmatic approach has earned its spurs in predicting solvents for polymer solutions, but for molecular solutes improvements are needed. By going into the details of entropy

  2. Power load prediction based on GM (1,1)

    Science.gov (United States)

    Wu, Di

    2017-05-01

    Currently, Chinese power load prediction is highly focused; the paper deeply studies grey prediction and applies it to Chinese electricity consumption during the recent 14 years; through after-test test, it obtains grey prediction which has good adaptability to medium and long-term power load.

  3. Serum Soluble Corin is Decreased in Stroke.

    Science.gov (United States)

    Peng, Hao; Zhu, Fangfang; Shi, Jijun; Han, Xiujie; Zhou, Dan; Liu, Yan; Zhi, Zhongwen; Zhang, Fuding; Shen, Yun; Ma, Juanjuan; Song, Yulin; Hu, Weidong

    2015-07-01

    Soluble corin was decreased in coronary heart disease. Given the connections between cardiac dysfunction and stroke, circulating corin might be a candidate marker of stroke risk. However, the association between circulating corin and stroke has not yet been studied in humans. Here, we aimed to examine the association in patients wtith stroke and community-based healthy controls. Four hundred eighty-one patients with ischemic stroke, 116 patients with hemorrhagic stroke, and 2498 healthy controls were studied. Serum soluble corin and some conventional risk factors of stroke were examined. Because circulating corin was reported to be varied between men and women, the association between serum soluble corin and stroke was evaluated in men and women, respectively. Patients with ischemic and hemorrhagic stroke had a significantly lower level of serum soluble corin than healthy controls in men and women (all P values, stroke than men in the highest quartile. Women in the lowest quartile of serum soluble corin were also more likely to have ischemic (OR, 3.10; 95% confidence interval, 1.76-5.44) and hemorrhagic (OR, 8.54; 95% confidence interval, 2.35-31.02) stroke than women in the highest quartile. ORs of ischemic and hemorrhagic stroke were significantly increased with the decreasing levels of serum soluble corin in men and women (all P values for trend, stroke compared with healthy controls. Our findings raise the possibility that serum soluble corin may have a pathogenic role in stroke. © 2015 American Heart Association, Inc.

  4. A Realistic Seizure Prediction Study Based on Multiclass SVM.

    Science.gov (United States)

    Direito, Bruno; Teixeira, César A; Sales, Francisco; Castelo-Branco, Miguel; Dourado, António

    2017-05-01

    A patient-specific algorithm, for epileptic seizure prediction, based on multiclass support-vector machines (SVM) and using multi-channel high-dimensional feature sets, is presented. The feature sets, combined with multiclass classification and post-processing schemes aim at the generation of alarms and reduced influence of false positives. This study considers 216 patients from the European Epilepsy Database, and includes 185 patients with scalp EEG recordings and 31 with intracranial data. The strategy was tested over a total of 16,729.80[Formula: see text]h of inter-ictal data, including 1206 seizures. We found an overall sensitivity of 38.47% and a false positive rate per hour of 0.20. The performance of the method achieved statistical significance in 24 patients (11% of the patients). Despite the encouraging results previously reported in specific datasets, the prospective demonstration on long-term EEG recording has been limited. Our study presents a prospective analysis of a large heterogeneous, multicentric dataset. The statistical framework based on conservative assumptions, reflects a realistic approach compared to constrained datasets, and/or in-sample evaluations. The improvement of these results, with the definition of an appropriate set of features able to improve the distinction between the pre-ictal and nonpre-ictal states, hence minimizing the effect of confounding variables, remains a key aspect.

  5. Solubility Products of M(II) - Carbonates

    Energy Technology Data Exchange (ETDEWEB)

    Grauer, Rolf; Berner, Urs [ed.

    1999-01-01

    Many solubility data for M(II) carbonates commonly compiled in tables are contradictory and sometimes obviously wrong. The quality of such data has been evaluated based on the original publications and reliable solubility constants have been selected for the carbonates of Mn, Fe, Co, Ni, Cu, Zn, Cd and Pb with the help of cross-comparisons. (author) translated from a PSI internal report written in German in 1994 (TM-44-94-05). 5 figs., 1 tab., 68 refs.

  6. Alkyl polyglucoside vs. ethoxylated surfactant-based microemulsions as vehicles for two poorly water-soluble drugs: physicochemical characterization and in vivo skin performance

    Directory of Open Access Journals (Sweden)

    Pajić Nataša Z. Bubić

    2017-12-01

    Full Text Available Two types of biocompatible surfactants were evaluated for their capability to formulate skin-friendly/non-irritant microemulsions as vehicles for two poorly water-soluble model drugs differing in properties and concentrations: alkyl polyglucosides (decyl glucoside and caprylyl/capryl glucoside and ethoxylated surfactants (glycereth-7-caprylate/ caprate and polysorbate 80. Phase behavior, structural inversion and microemulsion solubilization potential for sertaconazole nitrate and adapalene were found to be highly dependent on the surfactants structure and HLB value. Performed characterization (polarized light microscopy, pH, electrical conductivity, rheological, FTIR and DSC measurements indicated a formulation containing glycereth- 7-caprylate/caprate as suitable for incorporation of both drugs, whereas alkyl polyglucoside-based systems did not exhibit satisfying solubilization capacity for sertaconazole nitrate. Further, monitored parameters were strongly affected by sertaconazole nitrate incorporation, while they remained almost unchanged in adapalene-loaded vehicles. In addition, results of the in vivo skin performance study supported acceptable tolerability for all investigated formulations, suggesting selected microemulsions as promising carriers worth exploring further for effective skin delivery of model drugs.

  7. A Collaborative Evaluation of LC-MS/MS Based Methods for BMAA Analysis: Soluble Bound BMAA Found to Be an Important Fraction

    Directory of Open Access Journals (Sweden)

    Elisabeth J. Faassen

    2016-02-01

    Full Text Available Exposure to β-N-methylamino-l-alanine (BMAA might be linked to the incidence of amyotrophic lateral sclerosis, Alzheimer’s disease and Parkinson’s disease. Analytical chemistry plays a crucial role in determining human BMAA exposure and the associated health risk, but the performance of various analytical methods currently employed is rarely compared. A CYANOCOST initiated workshop was organized aimed at training scientists in BMAA analysis, creating mutual understanding and paving the way towards interlaboratory comparison exercises. During this workshop, we tested different methods (extraction followed by derivatization and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS analysis, or directly followed by LC-MS/MS analysis for trueness and intermediate precision. We adapted three workup methods for the underivatized analysis of animal, brain and cyanobacterial samples. Based on recovery of the internal standard D3BMAA, the underivatized methods were accurate (mean recovery 80% and precise (mean relative standard deviation 10%, except for the cyanobacterium Leptolyngbya. However, total BMAA concentrations in the positive controls (cycad seeds showed higher variation (relative standard deviation 21%–32%, implying that D3BMAA was not a good indicator for the release of BMAA from bound forms. Significant losses occurred during workup for the derivatized method, resulting in low recovery (<10%. Most BMAA was found in a trichloroacetic acid soluble, bound form and we recommend including this fraction during analysis.

  8. Student certainty answering misconception question: study of Three-Tier Multiple-Choice Diagnostic Test in Acid-Base and Solubility Equilibrium

    Science.gov (United States)

    Ardiansah; Masykuri, M.; Rahardjo, S. B.

    2018-04-01

    Students’ concept comprehension in three-tier multiple-choice diagnostic test related to student confidence level. The confidence level related to certainty and student’s self-efficacy. The purpose of this research was to find out students’ certainty in misconception test. This research was quantitative-qualitative research method counting students’ confidence level. The research participants were 484 students that were studying acid-base and equilibrium solubility subject. Data was collected using three-tier multiple-choice (3TMC) with thirty questions and students’ questionnaire. The findings showed that #6 item gives the highest misconception percentage and high student confidence about the counting of ultra-dilute solution’s pH. Other findings were that 1) the student tendency chosen the misconception answer is to increase over item number, 2) student certainty decreased in terms of answering the 3TMC, and 3) student self-efficacy and achievement were related each other in the research. The findings suggest some implications and limitations for further research.

  9. Determination of catecholamine in human serum by a fluorescent quenching method based on a water-soluble fluorescent conjugated polymer-enzyme hybrid system.

    Science.gov (United States)

    Huang, Hui; Gao, Yuan; Shi, Fanping; Wang, Guannan; Shah, Syed Mazhar; Su, Xingguang

    2012-03-21

    In this paper, a sensitive water-soluble fluorescent conjugated polymer biosensor for catecholamine (dopamine DA, adrenaline AD and norepinephrine NE) was developed. In the presence of horse radish peroxidase (HRP) and H(2)O(2), catecholamine could be oxidized and the oxidation product of catecholamine could quench the photoluminescence (PL) intensity of poly(2,5-bis(3-sulfonatopropoxy)-1,4-phenylethynylenealt-1,4-poly(phenylene ethynylene)) (PPESO(3)). The quenching PL intensity of PPESO(3) (I(0)/I) was proportional to the concentration of DA, AD and NE in the concentration ranges of 5.0 × 10(-7) to 1.4 × 10(-4), 5.0 × 10(-6) to 5.0 × 10(-4), and 5.0 × 10(-6) to 5.0 × 10(-4) mol L(-1), respectively. The detection limit for DA, AD and NE was 1.4 × 10(-7) mol L(-1), 1.0 × 10(-6) and 1.0 × 10(-6) mol L(-1), respectively. The PPESO(3)-enzyme hybrid system based on the fluorescence quenching method was successfully applied for the determination of catecholamine in human serum samples with good accuracy and satisfactory recovery. The results were in good agreement with those provided by the HPLC-MS method.

  10. A simple bubbling system for measuring radon (222Rn) gas concentrations in water samples based on the high solubility of radon in olive oil.

    Science.gov (United States)

    Al-Azmi, D; Snopek, B; Sayed, A M; Domanski, T

    2004-01-01

    Based on the different levels of solubility of radon gas in organic solvents and water, a bubbling system has been developed to transfer radon gas, dissolving naturally in water samples, to an organic solvent, i.e. olive oil, which is known to be a good solvent of radon gas. The system features the application of a fixed volume of bubbling air by introducing a fixed volume of water into a flask mounted above the system, to displace an identical volume of air from an air cylinder. Thus a gravitational flow of water is provided without the need for pumping. Then, the flushing air (radon-enriched air) is directed through a vial containing olive oil, to achieve deposition of the radon gas by another bubbling process. Following this, the vial (containing olive oil) is measured by direct use of gamma ray spectrometry, without the need of any chemical or physical processing of the samples. Using a standard solution of 226Ra/222Rn, a lowest measurable concentration (LMC) of radon in water samples of 9.4 Bq L(-1) has been achieved (below the maximum contaminant level of 11 Bq L(-1)).

  11. Alkyl polyglucoside vs. ethoxylated surfactant-based microemulsions as vehicles for two poorly water-soluble drugs: physicochemical characterization and in vivo skin performance.

    Science.gov (United States)

    Pajić, Nataša Z Bubić; Todosijević, Marija N; Vuleta, Gordana M; Cekić, Nebojša D; Dobričić, Vladimir D; Vučen, Sonja R; Čalija, Bojan R; Lukić, Milica Ž; Ilić, Tanja M; Savić, Snežana D

    2017-12-20

    Two types of biocompatible surfactants were evaluated for their capability to formulate skin-friendly/non-irritant microemulsions as vehicles for two poorly water-soluble model drugs differing in properties and concentrations: alkyl polyglucosides (decyl glucoside and caprylyl/capryl glucoside) and ethoxylated surfactants (glycereth-7-caprylate/ caprate and polysorbate 80). Phase behavior, structural inversion and microemulsion solubilization potential for sertaconazole nitrate and adapalene were found to be highly dependent on the surfactants structure and HLB value. Performed characterization (polarized light microscopy, pH, electrical conductivity, rheological, FTIR and DSC measurements) indicated a formulation containing glycereth- 7-caprylate/caprate as suitable for incorporation of both drugs, whereas alkyl polyglucoside-based systems did not exhibit satisfying solubilization capacity for sertaconazole nitrate. Further, monitored parameters were strongly affected by sertaconazole nitrate incorporation, while they remained almost unchanged in adapalene-loaded vehicles. In addition, results of the in vivo skin performance study supported acceptable tolerability for all investigated formulations, suggesting selected microemulsions as promising carriers worth exploring further for effective skin delivery of model drugs.

  12. Foundation Settlement Prediction Based on a Novel NGM Model

    Directory of Open Access Journals (Sweden)

    Peng-Yu Chen

    2014-01-01

    Full Text Available Prediction of foundation or subgrade settlement is very important during engineering construction. According to the fact that there are lots of settlement-time sequences with a nonhomogeneous index trend, a novel grey forecasting model called NGM (1,1,k,c model is proposed in this paper. With an optimized whitenization differential equation, the proposed NGM (1,1,k,c model has the property of white exponential law coincidence and can predict a pure nonhomogeneous index sequence precisely. We used two case studies to verify the predictive effect of NGM (1,1,k,c model for settlement prediction. The results show that this model can achieve excellent prediction accuracy; thus, the model is quite suitable for simulation and prediction of approximate nonhomogeneous index sequence and has excellent application value in settlement prediction.

  13. Soluble CD163

    DEFF Research Database (Denmark)

    Møller, Holger J

    2012-01-01

    CD163 is an endocytic receptor for haptoglobin-hemoglobin complexes and is expressed solely on macrophages and monocytes. As a result of ectodomain shedding, the extracellular portion of CD163 circulates in blood as a soluble protein (sCD163) at 0.7-3.9 mg/l in healthy individuals. The function o...

  14. Solubility Part 1

    NARCIS (Netherlands)

    Tantra, Ratna; Bolea, Eduardo; Bouwmeester, H.; Rey-Castro, Carlos; David, C.A.A.; Dogné, Jean Michel; Laborda, Francisco; Laloy, Julie; Robinson, Kenneth N.; Undas, A.K.; Zande, van der M.

    2016-01-01

    This chapter gives an overview of different methods that can potentially be used to determine the solubility of nanomaterials. In general, the methods presented can be broadly divided into four categories: separation methods, methods to quantify free ions, methods to quantify total dissolved

  15. Solubility and physical properties of sugars in pressurized water

    International Nuclear Information System (INIS)

    Saldaña, Marleny D.A.; Alvarez, Víctor H.; Haldar, Anupam

    2012-01-01

    Highlights: ► Sugar solubility in pressurized water and density at high pressures were measured. ► Glucose solubility was higher than that of lactose as predicted by their σ-profiles. ► Sugar aqueous solubility decreased with an increase in pressure from 15 to 120 bar. ► Aqueous glucose molecular packing shows high sensitivity to pressure. ► The COSMO-SAC model qualitatively predicted the sugar solubility data. - Abstract: In this study, the solubility, density, and refractive index of glucose and lactose in water as a function of temperature were measured. For solubility of sugars in pressurized water, experimental data were obtained at pressures of (15 to 120) bar and temperatures of (373 to 433) K using a dynamic flow high pressure system. Density data for aqueous sugar solutions were obtained at pressures of (1 to 300) bar and temperatures of (298 to 343) K. The refractive index of aqueous sugar solutions was obtained at 293 K and atmospheric pressure. Activity coefficient models, Van Laar and the Conductor-like Screening Model-Segment Activity Coefficient (COSMO-SAC), were used to fit and predict the experimental solubility data, respectively. The results obtained showed that the solubility of both sugars in pressurized water increase with an increase in temperature. However, with the increase of pressure from 15 bar to 120 bar, the solubility of both sugars in pressurized water decreased. The Van Laar model fit the experimental aqueous solubility data with deviations lower than 13 and 53% for glucose and lactose, respectively. The COSMO-SAC model predicted qualitatively the aqueous solubility of these sugars.

  16. Modeling of Salt Solubilities in Mixed Solvents

    DEFF Research Database (Denmark)

    Chiavone-Filho, O.; Rasmussen, Peter

    2000-01-01

    A method to correlate and predict salt solubilities in mixed solvents using a UNIQUAC+Debye-Huckel model is developed. The UNIQUAC equation is applied in a form with temperature-dependent parameters. The Debye-Huckel model is extended to mixed solvents by properly evaluating the dielectric...... constants and the liquid densities of the solvent media. To normalize the activity coefficients, the symmetric convention is adopted. Thermochemical properties of the salt are used to estimate the solubility product. It is shown that the proposed procedure can describe with good accuracy a series of salt...

  17. Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments.

    Science.gov (United States)

    Zheng, Ce; Kurgan, Lukasz

    2008-10-10

    beta-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of beta-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based beta-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM) values serve as an input to the support vector machine (SVM) predictor. We show that (1) all four predicted secondary structures are useful; (2) the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3) the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential beta-turns, while the remaining four amino acids are useful to predict non-beta-turns. Empirical evaluation using three nonredundant datasets shows favorable Q total, Q predicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Q total barrier and achieves Q total = 80.9%, MCC = 0.47, and Q predicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC) competing methods, respectively. Experiments show that the proposed method constitutes an improvement over the competing prediction

  18. Star-sensor-based predictive Kalman filter for satelliteattitude estimation

    Institute of Scientific and Technical Information of China (English)

    林玉荣; 邓正隆

    2002-01-01

    A real-time attitude estimation algorithm, namely the predictive Kalman filter, is presented. This algorithm can accurately estimate the three-axis attitude of a satellite using only star sensor measurements. The implementation of the filter includes two steps: first, predicting the torque modeling error, and then estimating the attitude. Simulation results indicate that the predictive Kalman filter provides robust performance in the presence of both significant errors in the assumed model and in the initial conditions.

  19. Properties of uncharged water-soluble tetra({omega}-methoxypolyethyleneoxy)phthalocyanine free base: Viable switching of the optical response by means of H{sub 3}O{sup +} ions

    Energy Technology Data Exchange (ETDEWEB)

    Mineo, Placido [Department of Chemistry, University of Catania and INSTM UdR of Catania, Viale Andrea Doria 6, 95125 Catania (Italy); Istituto per i Processi Chimico Fisici - CNR, Viale Ferdinando Stagno D' Alcontres, 37, 98158 Messina (Italy); Lupo, Fabio; Fragala, Ignazio; Scamporrino, Emilio [Department of Chemistry, University of Catania and INSTM UdR of Catania, Viale Andrea Doria 6, 95125 Catania (Italy); Gulino, Antonino, E-mail: agulino@unict.it [Department of Chemistry, University of Catania and INSTM UdR of Catania, Viale Andrea Doria 6, 95125 Catania (Italy)

    2012-02-15

    An uncharged water-soluble tetra ({omega}-methoxypolyethyleneoxy)phthalocyanine was characterized by MALDI-TOF mass spectrometry, UV-vis and luminescence measurements. The polyether substituents render water soluble this uncharged phthalocyanine. Relevant changes are observed in emission measurements upon protonation. The phthalocyanine free base and its protonated forms can be switched alternating H{sub 3}O{sup +} and OH{sup -} ions as inputs, being the intensity of the luminescence spectra the output. Binary codes 1 or 0 can be assigned to the high luminescent phthalocyanine free base state or to the low luminescent protonated state, respectively. The read-out procedure is fast and the system is reversible. In addition, the exploiting of the luminescent properties of the present water soluble phthalocyanine could be of relevance also for biological applications (photosensitizers for the photodynamic therapy). Highlights: Black-Right-Pointing-Pointer An uncharged water soluble tetra ({omega}-methoxypolyethyleneoxy)phthalocyanine was characterized. Black-Right-Pointing-Pointer Phthalocyanine protonation changes the luminescence output. Black-Right-Pointing-Pointer The system can be switched alternating H{sub 3}O{sup +} and OH{sup -} as inputs. Black-Right-Pointing-Pointer The read-out procedure is fast and reversible. Black-Right-Pointing-Pointer Binary codes are assigned to the high and low luminescent states, respectively.

  20. Solubility of perfumery and fragrance raw materials based on cyclohexane in 1-octanol under ambient and high pressures up to 900 MPa

    International Nuclear Information System (INIS)

    Domanska, Urszula; Morawski, Piotr; Piekarska, Maria

    2008-01-01

    The (solid + liquid) phase equilibria (SLE) of binary mixtures containing 1-octanol and fragrance raw materials based on cyclohexane were investigated. The systems {1-octanol (1) + cyclohexyl carboxylic acid (CCA), or cyclohexyl acetic acid (CAA), or cyclohexyl acetate (CA), or 2-cyclohexyl ethyl acetate (2CEA), or 2-cyclohexyl ethanol (2CE)(2)} have been measured by a dynamic method in wide range of temperatures from (220 to 320) K and ambient pressure. For all systems SLE diagrams were detected as eutectic mixtures with complete miscibility in the liquid phase. The experimental data were correlated by means of the Wilson and NRTL equations, utilizing parameters derived from the (solid + liquid) equilibrium. The root-mean-square deviations of the solubility temperatures for all calculated data are dependent upon the particular system and the particular equation used. Additionally, the SLE in binary mixture that contain {1-octanol (1) + CCA (2)} has been measured under very high pressures up to about 900 MPa at the temperature range from T = (303.15 to 353.15) K. The thermostatted apparatus for the measurements of transition pressures from the (liquid + solid) state was used. The freezing and melting temperatures at a constant composition increase monotonously with pressure. The high pressure experimental results obtained at isothermal conditions (p-x) were interpolated to more convenient T-x diagram. Data of the (pressure + temperature) composition relation at the high pressure (solid + liquid) phase equilibria was correlated by the polynomial based on the Yang model. The basic thermodynamic properties of pure substances viz. the melting point, enthalpy of fusion, enthalpy of solid-solid phase transition, and glass transition, have been determined by the differential scanning calorimetry (DSC)