WorldWideScience

Sample records for model yielded good

  1. Food for thought: pretty good multispecies yield

    DEFF Research Database (Denmark)

    Rindorf, Anna; Dichmont, C. M.; Levin, P.S.

    2017-01-01

    that broader ecosystem, economic, and social objectives are addressed. We investigate how the principles of a “pretty good yield” range of fishing mortalities assumed to provide >95% of the average yield for a single stock can be expanded to a pretty good multispecies yield (PGMY) space and further to pretty...... good multidimensional yield to accommodate situations where the yield from a stock affects the ecosystem, economic and social benefits, or sustainability. We demonstrate in a European example that PGMY is a practical concept. As PGMY provides a safe operating space for management that adheres...

  2. How good is good in hydrological modeling?

    Science.gov (United States)

    Seibert, J.; Vis, M.; van Meerveld, I. H. J.

    2016-12-01

    Models are never perfect and hydrological models are no exception. Even with the most sophisticated hydrological models, runoff simulations never fully agree. This is at least partly because of uncertainties in the observed input and output data. On the other hand, even a poor model can often provide fair simulations simply because the forcing data (precipitation, temperature, …) do not allow the model to go completely wrong. Commonly used measures to assess model performance, such as the Nash-Sutcliffe model efficiency, do not allow direct judgment of model performance in terms of what can be achieved with a certain dataset, and different guidelines are given in the literature on what values indicate a good model performance. This is not satisfactory, especially when it comes to assessing the performances of uncalibrated models. We, therefore, suggest the use of an upper and a lower benchmark to better assess model performance. The upper benchmark is a measure of what can be achieved and can be quantified by the performance of a calibrated simple model. The lower benchmark is a measure of what can be expected and can be quantified by an ensemble mean of an uncalibrated simple model where random parameter sets or parameter sets from other catchments are used. In this contribution, we focus on this lower benchmark. Preliminary results using the HBV model, a simple, bucket-type model, indicated surprisingly good model performance of the ensemble means, even when individual parameterisations resulted in very poor fits. To test this further, we applied the HBV model using data from 600 catchments in the USA. The model was calibrated for each catchment and different ensembles where used to compute ensemble mean time series based on: 1) random parameter values, 2) parameter sets from all 600 catchments (minus the one in question), 3) parameter sets from all catchments in the respective hydrological region as defined by the USGS, and 4) parameter sets from the x nearest

  3. How good is good enough? Data requirements for reliable crop yield simulations and yield-gap analysis

    NARCIS (Netherlands)

    Grassini, P.; Bussel, van L.G.J.; Wart, van J.; Wolf, J.; Claessens, L.; Yang, H.; Boogaard, H.L.; Groot, de H.L.E.; Ittersum, van M.K.; Cassman, K.G.

    2015-01-01

    Numerous studies have been published during the past two decades that use simulation models to assesscrop yield gaps (quantified as the difference between potential and actual farm yields), impact of climatechange on future crop yields, and land-use change. However, there is a wide range in quality

  4. Goods Transport Modelling, Vol 1

    DEFF Research Database (Denmark)

    Petersen, Morten Steen (red.); Kristiansen, Jørgen

    The report is a study of data requirements and methodologies for goods transport. The study is intended to provide the basis for general discussion about the application of goods transport models in Denmark. The report provides an overview of different types of models and data availability....

  5. Sticky Price Models and Durable Goods

    OpenAIRE

    Robert Barsky; Christopher L. House; Miles Kimball

    2005-01-01

    This paper shows that there are striking implications that stem from including durable goods in otherwise conventional sticky price models. The behavior of these models depends heavily on whether durable goods are present and whether these goods have sticky prices. If long-lived durables have sticky prices, then even small durables sectors can cause the model to behave as though most prices were sticky. Conversely, if durable goods prices are flexible then the model exhibits unwelcome behavio...

  6. Incorporating phenology into yield models

    Science.gov (United States)

    Gray, J. M.; Friedl, M. A.

    2015-12-01

    Because the yields of many crops are sensitive to meteorological forcing during specific growth stages, phenological information has potential utility in yield mapping and forecasting exercises. However, most attempts to explain the spatiotemporal variability in crop yields with weather data have relied on growth stage definitions that do not change from year-to-year, even though planting, maturity, and harvesting dates show significant interannual variability. We tested the hypothesis that quantifying temperature exposures over dynamically determined growth stages would better explain observed spatiotemporal variability in crop yields than statically defined time periods. Specifically, we used National Agricultural and Statistics Service (NASS) crop progress data to identify the timing of the start of the maize reproductive growth stage ("silking"), and examined the correlation between county-scale yield anomalies and temperature exposures during either the annual or long-term average silking period. Consistent with our hypothesis and physical understanding, yield anomalies were more correlated with temperature exposures during the actual, rather than the long-term average, silking period. Nevertheless, temperature exposures alone explained a relatively low proportion of the yield variability, indicating that other factors and/or time periods are also important. We next investigated the potential of using remotely sensed land surface phenology instead of NASS progress data to retrieve crop growth stages, but encountered challenges related to crop type mapping and subpixel crop heterogeneity. Here, we discuss the potential of overcoming these challenges and the general utility of remotely sensed land surface phenology in crop yield mapping.

  7. Conceptual Models Core to Good Design

    CERN Document Server

    Johnson, Jeff

    2011-01-01

    People make use of software applications in their activities, applying them as tools in carrying out tasks. That this use should be good for people--easy, effective, efficient, and enjoyable--is a principal goal of design. In this book, we present the notion of Conceptual Models, and argue that Conceptual Models are core to achieving good design. From years of helping companies create software applications, we have come to believe that building applications without Conceptual Models is just asking for designs that will be confusing and difficult to learn, remember, and use. We show how Concept

  8. Evaluation of trends in wheat yield models

    Science.gov (United States)

    Ferguson, M. C.

    1982-01-01

    Trend terms in models for wheat yield in the U.S. Great Plains for the years 1932 to 1976 are evaluated. The subset of meteorological variables yielding the largest adjusted R(2) is selected using the method of leaps and bounds. Latent root regression is used to eliminate multicollinearities, and generalized ridge regression is used to introduce bias to provide stability in the data matrix. The regression model used provides for two trends in each of two models: a dependent model in which the trend line is piece-wise continuous, and an independent model in which the trend line is discontinuous at the year of the slope change. It was found that the trend lines best describing the wheat yields consisted of combinations of increasing, decreasing, and constant trend: four combinations for the dependent model and seven for the independent model.

  9. Regression Models For Saffron Yields in Iran

    Science.gov (United States)

    S. H, Sanaeinejad; S. N, Hosseini

    Saffron is an important crop in social and economical aspects in Khorassan Province (Northeast of Iran). In this research wetried to evaluate trends of saffron yield in recent years and to study the relationship between saffron yield and the climate change. A regression analysis was used to predict saffron yield based on 20 years of yield data in Birjand, Ghaen and Ferdows cities.Climatologically data for the same periods was provided by database of Khorassan Climatology Center. Climatologically data includedtemperature, rainfall, relative humidity and sunshine hours for ModelI, and temperature and rainfall for Model II. The results showed the coefficients of determination for Birjand, Ferdows and Ghaen for Model I were 0.69, 0.50 and 0.81 respectively. Also coefficients of determination for the same cities for model II were 0.53, 0.50 and 0.72 respectively. Multiple regression analysisindicated that among weather variables, temperature was the key parameter for variation ofsaffron yield. It was concluded that increasing temperature at spring was the main cause of declined saffron yield during recent years across the province. Finally, yield trend was predicted for the last 5 years using time series analysis.

  10. Amplitude Models for Discrimination and Yield Estimation

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, William Scott [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-09-01

    This seminar presentation describes amplitude models and yield estimations that look at the data in order to inform legislation. The following points were brought forth in the summary: global models that will predict three-component amplitudes (R-T-Z) were produced; Q models match regional geology; corrected source spectra can be used for discrimination and yield estimation; three-component data increase coverage and reduce scatter in source spectral estimates; three-component efforts must include distance-dependent effects; a community effort on instrument calibration is needed.

  11. Functional dynamic factor models with application to yield curve forecasting

    KAUST Repository

    Hays, Spencer

    2012-09-01

    Accurate forecasting of zero coupon bond yields for a continuum of maturities is paramount to bond portfolio management and derivative security pricing. Yet a universal model for yield curve forecasting has been elusive, and prior attempts often resulted in a trade-off between goodness of fit and consistency with economic theory. To address this, herein we propose a novel formulation which connects the dynamic factor model (DFM) framework with concepts from functional data analysis: a DFM with functional factor loading curves. This results in a model capable of forecasting functional time series. Further, in the yield curve context we show that the model retains economic interpretation. Model estimation is achieved through an expectation- maximization algorithm, where the time series parameters and factor loading curves are simultaneously estimated in a single step. Efficient computing is implemented and a data-driven smoothing parameter is nicely incorporated. We show that our model performs very well on forecasting actual yield data compared with existing approaches, especially in regard to profit-based assessment for an innovative trading exercise. We further illustrate the viability of our model to applications outside of yield forecasting.

  12. The good, the bad and the ugly of marine reserves for fishery yields.

    Science.gov (United States)

    De Leo, Giulio A; Micheli, Fiorenza

    2015-11-05

    Marine reserves (MRs) are used worldwide as a means of conserving biodiversity and protecting depleted populations. Despite major investments in MRs, their environmental and social benefits have proven difficult to demonstrate and are still debated. Clear expectations of the possible outcomes of MR establishment are needed to guide and strengthen empirical assessments. Previous models show that reserve establishment in overcapitalized, quota-based fisheries can reduce both catch and population abundance, thereby negating fisheries and even conservation benefits. By using a stage-structured, spatially explicit stochastic model, we show that catches under quota-based fisheries that include a network of MRs can exceed maximum sustainable yield (MSY) under conventional quota management if reserves provide protection to old, large spawners that disproportionally contribute to recruitment outside the reserves. Modelling results predict that the net fishery benefit of MRs is lost when gains in fecundity of old, large individuals are small, is highest in the case of sedentary adults with high larval dispersal, and decreases with adult mobility. We also show that environmental variability may mask fishery benefits of reserve implementation and that MRs may buffer against collapse when sustainable catch quotas are exceeded owing to stock overestimation or systematic overfishing.

  13. Sediment Yield Modeling in a Large Scale Drainage Basin

    Science.gov (United States)

    Ali, K.; de Boer, D. H.

    2009-05-01

    This paper presents the findings of spatially distributed sediment yield modeling in the upper Indus River basin. Spatial erosion rates calculated by using the Thornes model at 1-kilometre spatial resolution and monthly time scale indicate that 87 % of the annual gross erosion takes place in the three summer months. The model predicts a total annual erosion rate of 868 million tons, which is approximately 4.5 times the long- term observed annual sediment yield of the basin. Sediment delivery ratios (SDR) are hypothesized to be a function of the travel time of surface runoff from catchment cells to the nearest downstream channel. Model results indicate that higher delivery ratios (SDR > 0.6) are found in 18 % of the basin area, mostly located in the high-relief sub-basins and in the areas around the Nanga Parbat Massif. The sediment delivery ratio is lower than 0.2 in 70 % of the basin area, predominantly in the low-relief sub-basins like the Shyok on the Tibetan Plateau. The predicted annual basin sediment yield is 244 million tons which compares reasonably to the measured value of 192.5 million tons. The average annual specific sediment yield in the basin is predicted as 1110 tons per square kilometre. Model evaluation based on accuracy statistics shows very good to satisfactory performance ratings for predicted monthly basin sediment yields and for mean annual sediment yields of 17 sub-basins. This modeling framework mainly requires global datasets, and hence can be used to predict erosion and sediment yield in other ungauged drainage basins.

  14. Preparation of new 2,3-diphenylpropenoic acid esters - good yields even for the more hindered Z isomers.

    Science.gov (United States)

    Boros, László; Felföldi, Károly; Pálinkó, István

    2004-03-31

    The potassium salt of E- and Z-2,3-diphenylpropenoic acids prepared in situ could be esterified efficiently in DMSO with the appropriate alkyl halides at room temperature. In this way 10 previously undescribed esters of these acids were synthesised and characterised. Excellent yields were observed for most of the E isomers and the more hindered Z esters were also obtained in good yields, far better than those obtained applying the classical acid-catalysed esterification reaction.

  15. Geoelectrical parameter-based multivariate regression borehole yield model for predicting aquifer yield in managing groundwater resource sustainability

    Directory of Open Access Journals (Sweden)

    Kehinde Anthony Mogaji

    2016-07-01

    Full Text Available This study developed a GIS-based multivariate regression (MVR yield rate prediction model of groundwater resource sustainability in the hard-rock geology terrain of southwestern Nigeria. This model can economically manage the aquifer yield rate potential predictions that are often overlooked in groundwater resources development. The proposed model relates the borehole yield rate inventory of the area to geoelectrically derived parameters. Three sets of borehole yield rate conditioning geoelectrically derived parameters—aquifer unit resistivity (ρ, aquifer unit thickness (D and coefficient of anisotropy (λ—were determined from the acquired and interpreted geophysical data. The extracted borehole yield rate values and the geoelectrically derived parameter values were regressed to develop the MVR relationship model by applying linear regression and GIS techniques. The sensitivity analysis results of the MVR model evaluated at P ⩽ 0.05 for the predictors ρ, D and λ provided values of 2.68 × 10−05, 2 × 10−02 and 2.09 × 10−06, respectively. The accuracy and predictive power tests conducted on the MVR model using the Theil inequality coefficient measurement approach, coupled with the sensitivity analysis results, confirmed the model yield rate estimation and prediction capability. The MVR borehole yield prediction model estimates were processed in a GIS environment to model an aquifer yield potential prediction map of the area. The information on the prediction map can serve as a scientific basis for predicting aquifer yield potential rates relevant in groundwater resources sustainability management. The developed MVR borehole yield rate prediction mode provides a good alternative to other methods used for this purpose.

  16. Statistical modelling and deconvolution of yield meter data

    DEFF Research Database (Denmark)

    Tøgersen, Frede Aakmann; Waagepetersen, Rasmus Plenge

    2004-01-01

    This paper considers the problem of mapping spatial variation of yield in a field using data from a yield monitoring system on a combine harvester. The unobserved yield is assumed to be a Gaussian random field and the yield monitoring system data is modelled as a convolution of the yield and an i...

  17. Years of research yield nothing, and that's good news for physicists

    CERN Multimedia

    Johnson, G

    2002-01-01

    Analysis of data from the Tevatron has so far not revealed the existence of supersymmetric particles. The results are good though because they establish a new lower limit for the mass of one of the hypothetical particles, a gluino (2 pages).

  18. Demand and routing models for urban goods movement simulation

    OpenAIRE

    Polimeni, Antonio; Russo, Francesco; Vitetta, Antonino

    2010-01-01

    This paper presents a macro-architecture for simulating goods movements in an urban area. Urban goods supply is analysed when the retailer is the decision-maker and chooses to supply his/her shop. Two components are considered: demand in terms of goods supply and vehicle routing with constraints to simulate goods movements. To analyse demand we consider a multi-step model, while to analyse goods movements a Vehicle Routing Problem with Time Windows (VRPTW) is formalized. We exa...

  19. A Good Image Model Eases Restoration

    Science.gov (United States)

    2002-02-06

    algorithms, and various classical as well as unexpected new applications of the BV ( bounded variation ) image model, first introduced into image processing by Rudin, Osher, and Fatemi in 1992 Physica D, 60:259-268.

  20. Growth and yield models for Dahurian larch plantations

    Institute of Scientific and Technical Information of China (English)

    Yuan Jinlan

    1999-01-01

    Several equations were seiected using nonlinear regression analysis for setting up growth and yield models of Dahurian larch (Larix gmelinii Rupr.) plantations. Data of 405 stem analysis trees were collected from 336 temporary plots throughout the Daxing'an Mountains. Results showed that the Richards equation was the best model for estimating tree height, stand mean height and stand dominant height by age; the Power equation was the fittest model for predicting tree volume by DBH and tree height, and the Logarithmic stand volume equation was good for predicting stand volume from age, mean height, basal area and other stand variables. These models can be used to construct volume tables, site index table and other forestry tables for Dahurian plantations.

  1. Statistical modelling and deconvolution of yield meter data

    DEFF Research Database (Denmark)

    Tøgersen, Frede Aakmann; Waagepetersen, Rasmus Plenge

    previously harvested along the swath. The unobserved yield is assumed to be a Gaussian random field and the yield monitoring system data is modelled as a convolution of the yield and an impulse response function. This results in an unusual spatial covariance structure (depending on the driving pattern......Data for yield maps can be obtained from modern combine harvesters equipped with a differential global positioning system and a yield monitoring system. Due to delay and smoothing effects in the combine harvester the recorded yield data for a location represents a shifted weighted average of yield...... of the combine harvester) for the yield monitoring system data. Parameters of the impulse response function and the spatial covariance function of the yield are estimated using maximum likelihood. The fitted model is assessed using certain empirical directional covariograms and the yield is finally predicted...

  2. Crop Yield Forecasted Model Based on Time Series Techniques

    Institute of Scientific and Technical Information of China (English)

    Li Hong-ying; Hou Yan-lin; Zhou Yong-juan; Zhao Hui-ming

    2012-01-01

    Traditional studies on potential yield mainly referred to attainable yield: the maximum yield which could be reached by a crop in a given environment. The new concept of crop yield under average climate conditions was defined in this paper, which was affected by advancement of science and technology. Based on the new concept of crop yield, the time series techniques relying on past yield data was employed to set up a forecasting model. The model was tested by using average grain yields of Liaoning Province in China from 1949 to 2005. The testing combined dynamic n-choosing and micro tendency rectification, and an average forecasting error was 1.24%. In the trend line of yield change, and then a yield turning point might occur, in which case the inflexion model was used to solve the problem of yield turn point.

  3. A general model of the public goods dilemma.

    Science.gov (United States)

    Frank, Steven A

    2010-06-01

    An individually costly act that benefits all group members is a public good. Natural selection favours individual contribution to public good [corrected] only when some benefit to the individual offsets the cost of contribution. Problems of sex ratio, parasite virulence, microbial metabolism, punishment of noncooperators, and nearly all aspects of sociality have been analysed as public goods shaped by kin and group selection. Here, I develop two general aspects of the public goods problem that have received relatively little attention. First, variation in individual resources favours selfish individuals to vary their allocation to public goods. Those individuals better endowed contribute their excess resources to public benefit, whereas those individuals with fewer resources contribute less to the public good. Thus, purely selfish behaviour causes individuals to stratify into upper classes that contribute greatly to public benefit and social cohesion and to lower classes that contribute little to the public good. Second, if group success absolutely requires production of the public good, then the pressure favouring production is relatively high. By contrast, if group success depends weakly on the public good, then the pressure favouring production is relatively weak. Stated in this way, it is obvious that the role of baseline success is important. However, discussions of public goods problems sometimes fail to emphasize this point sufficiently. The models here suggest simple tests for the roles of resource variation and baseline success. Given the widespread importance of public goods, better models and tests would greatly deepen our understanding of many processes in biology and sociality.

  4. Yield model for unthinned Sitka spruce plantations in Ireland

    Energy Technology Data Exchange (ETDEWEB)

    Omiyale, O.; Joyce, P.M.

    1982-01-01

    Over the past few decades the construction of yield models, has progressed from the graphical through mathematical and biomathematic approach. The development of a biomathematical growth model for Sitka spruce plantations is described. It is suggested that this technique can serve as a basis for general yield model construction of plantation species in Ireland. (Refs. 15).

  5. BioSTAR, a New Biomass and Yield Modeling Software

    Science.gov (United States)

    Kappas, M.; Degener, J.; Bauboeck, R.

    2013-12-01

    , sorghum, sunflower and, sugar beet. Calibrations for rye grass, cup plant, poplar and willow still need to be performed. A Comparison of simulated and observed biomass yields for sites in Lower Saxony has rendered good results with errors (RMSE) ranging from below 10% (winter wheat, n= 102) and 18.6 % (sunflower, n=8) (Bauböck, unpublished). Because simulations can be made with limited soil data (soil type or texture class) and a limited climate data set (smallest set can be either monthly means of precipitation, temperature and, radiation or precipitation, temperature and, humidity) and the software is capable of processing large datasets, the model appears to be a promising tool for mid or large scale biomass and yield predictions. Up to now the model has only been used for yield predictions with current state climate and climate change scenarios in Lower Saxony, but comparisons with output data of the model AquaCrop (Steduto, et al., 2009) have shown good performance in arid and semi-arid climates (Bauböck, 2013).

  6. Time series models of environmental exposures: Good predictions or good understanding.

    Science.gov (United States)

    Barnett, Adrian G; Stephen, Dimity; Huang, Cunrui; Wolkewitz, Martin

    2017-04-01

    Time series data are popular in environmental epidemiology as they make use of the natural experiment of how changes in exposure over time might impact on disease. Many published time series papers have used parameter-heavy models that fully explained the second order patterns in disease to give residuals that have no short-term autocorrelation or seasonality. This is often achieved by including predictors of past disease counts (autoregression) or seasonal splines with many degrees of freedom. These approaches give great residuals, but add little to our understanding of cause and effect. We argue that modelling approaches should rely more on good epidemiology and less on statistical tests. This includes thinking about causal pathways, making potential confounders explicit, fitting a limited number of models, and not over-fitting at the cost of under-estimating the true association between exposure and disease. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Model of wealth and goods dynamics in a closed market

    Science.gov (United States)

    Ausloos, Marcel; Peķalski, Andrzej

    2007-01-01

    A simple computer simulation model of a closed market on a fixed network with free flow of goods and money is introduced. The model contains only two variables: the amount of goods and money beside the size of the system. An initially flat distribution of both variables is presupposed. We show that under completely random rules, i.e. through the choice of interacting agent pairs on the network and of the exchange rules that the market stabilizes in time and shows diversification of money and goods. We also indicate that the difference between poor and rich agents increases for small markets, as well as for systems in which money is steadily deduced from the market through taxation. It is also found that the price of goods decreases when taxes are introduced, likely due to the less availability of money.

  8. Genetic analysis to identify good combiners for ToLCV resistance and yield components in tomato using interspecific hybridization

    Indian Academy of Sciences (India)

    Ramesh K. Singh; N. Rai; Major Singh; S. N. Singh; K. Srivastava

    2014-12-01

    The interspecific hybridization for tomato leaf curl virus (ToLCV) resistance was carried out among 10 genetically diverse tomato genotypes (diversified by 50 SSR markers). Among the 10 parents, four susceptible cultivars of Solanum lycopersicum were crossed with six resistant wilds, such as S. pimpinellifolium, S. habrochaites, S. chemielewskii, S. ceraseforme, S. peruvianum and S. chilense in a line × tester mating design. All the 24 hybrids and their parents were grown in the field and glasshouse conditions to determine the general-combining abilities (GCA) and specific-combining abilities (SCA). The variances due to SCA and GCA showed both additive and nonadditive gene effects. Based on GCA estimates, EC-520061 and WIR-5032 were good general combiners while based on SCA estimates, PBC × EC-520061 and PBC × EC-521080 were best specific combiners for coefficient of infection and fruit yield per plant in both the environments. These lines could be selected and utilized in ToLCV resistance and high yield breeding programme for improving the traits.

  9. ZNJPrice/Earnings Ratio Model through Dividend Yield and Required Yield Above Expected Inflation

    Directory of Open Access Journals (Sweden)

    Emil Mihalina

    2010-07-01

    Full Text Available Price/earnings ratio is the most popular and most widespread evaluation model used to assess relative capital asset value on financial markets. In functional terms, company earnings in the very long term can be described with high significance. Empirically, it is visible from long-term statistics that the demanded (required yield on capital markets has certain regularity. Thus, investors first require a yield above the stable inflation rate and then a dividend yield and a capital increase caused by the growth of earnings that influence the price, with the assumption that the P/E ratio is stable. By combining the Gordon model for current dividend value, the model of market capitalization of earnings (price/earnings ratio and bearing in mind the influence of the general price levels on company earnings, it is possible to adjust the price/earnings ratio by deriving a function of the required yield on capital markets measured by a market index through dividend yield and inflation rate above the stable inflation rate increased by profit growth. The S&P 500 index for example, has in the last 100 years grown by exactly the inflation rate above the stable inflation rate increased by profit growth. The comparison of two series of price/earnings ratios, a modelled one and an average 7-year ratio, shows a notable correlation in the movement of two series of variables, with a three year deviation. Therefore, it could be hypothesized that three years of the expected inflation level, dividend yield and profit growth rate of the market index are discounted in the current market prices. The conclusion is that, at the present time, the relationship between the adjusted average price/earnings ratio and its effect on the market index on one hand and the modelled price/earnings ratio on the other can clearly show the expected dynamics and course in the following period.

  10. Rice yield forecasting models using satellite imagery in Egypt

    Directory of Open Access Journals (Sweden)

    N.A. Noureldin

    2013-06-01

    Full Text Available Ability to make yield prediction before harvest using satellite remote sensing is important in many aspects of agricultural decision-making. In this study, canopy reflectance band and different band ratios in form of vegetation indices (VI with leaf area index (LAI were used to generate remotely sensed pre-harvest empirical rice yield prediction models. LAI measurements, spectral data derived from two SPOT data acquired on August 24, 2008 and August 23, 2009 and observed rice yield were used as main inputs for rice yield modeling. Each remotely sensed factor was used separately and in combination with LAI to generate the models. The results showed that green spectral band, middle infra-red spectral band and green vegetation index (GVI did not show sufficient capability as rice yield estimators while other inputs such as red spectral band, near infrared spectral band and vegetation indices that are algebraic ratios from these two spectral bands when used separately or in combined with leaf area index (LAI produced high accurate rice yield estimation models. The validation process was carried out using two statistical tests; standard error of estimate and the correlation coefficient between modeled and predicted yield. The validation results indicated that using normalized difference vegetation index (NDVI combined with leaf area index (LAI produced the model with highest accuracy and stability during the two rice seasons. The generated models are applicable 90 days after planting in any similar environmental conditions and agricultural practices.

  11. Do Flexible Durable Goods Prices Undermine Sticky Price Models?

    OpenAIRE

    Robert Barsky; Christopher L. House; Miles Kimball

    2003-01-01

    Multi-sector sticky price models have surprising implications when durable goods have flexible prices. While in actual data the production of virtually all durables exhibits strong negative responses to monetary contractions, in dynamic general equilibrium models a monetary contraction causes the output of flexibly priced durables to expand. Indeed, in the polar case in which only nondurables have sticky prices, the negative comovement of durable and nondurable production exactly offsets and ...

  12. Predicting the Yield Stress of SCC using Materials Modelling

    DEFF Research Database (Denmark)

    Thrane, Lars Nyholm; Hasholt, Marianne Tange; Pade, Claus

    2005-01-01

    A conceptual model for predicting the Bingham rheological parameter yield stress of SCC has been established. The model used here is inspired by previous work of Oh et al. (1), predicting that the yield stress of concrete relative to the yield stress of paste is a function of the relative thickness...... of excess paste around the aggregate. The thickness of excess paste is itself a function of particle shape, particle size distribution, and particle packing. Seven types of SCC were tested at four different excess paste contents in order to verify the conceptual model. Paste composition and aggregate shape...... and distribution were varied between SCC types. The results indicate that yield stress of SCC may be predicted using the model....

  13. MODELING OF SEDIMENT AND NONPOINT SOURCE POLLUTANT YIELD

    Institute of Scientific and Technical Information of China (English)

    Huai'en LI; Xiaokang Hong; Bing SHEN

    2001-01-01

    For water and soil conservation and water pollution control, it is very important to simulate and predict the load of sediment and pollutant during storm-runoff. On the basis of analyzing the simultaneous measurements of flow, sediment and pollutants observed at watershed outlet, a practical sediment yield model is developed by standardizing the load rate. The results show that the standardized pollutant yield equals effective rainfall and the process of effective load yield is the same as effective rainfall hyetograph. Comparison with measured data show that this model is applicable to various pollutants.

  14. Comparing Sediment Yield Predictions from Different Hydrologic Modeling Schemes

    Science.gov (United States)

    Dahl, T. A.; Kendall, A. D.; Hyndman, D. W.

    2015-12-01

    Sediment yield, or the delivery of sediment from the landscape to a river, is a difficult process to accurately model. It is primarily a function of hydrology and climate, but influenced by landcover and the underlying soils. These additional factors make it much more difficult to accurately model than water flow alone. It is not intuitive what impact different hydrologic modeling schemes may have on the prediction of sediment yield. Here, two implementations of the Modified Universal Soil Loss Equation (MUSLE) are compared to examine the effects of hydrologic model choice. Both the Soil and Water Assessment Tool (SWAT) and the Landscape Hydrology Model (LHM) utilize the MUSLE for calculating sediment yield. SWAT is a lumped parameter hydrologic model developed by the USDA, which is commonly used for predicting sediment yield. LHM is a fully distributed hydrologic model developed primarily for integrated surface and groundwater studies at the watershed to regional scale. SWAT and LHM models were developed and tested for two large, adjacent watersheds in the Great Lakes region; the Maumee River and the St. Joseph River. The models were run using a variety of single model and ensemble downscaled climate change scenarios from the Coupled Model Intercomparison Project 5 (CMIP5). The initial results of this comparison are discussed here.

  15. Top ten models constrained by b {yields} s{gamma}

    Energy Technology Data Exchange (ETDEWEB)

    Hewett, J.L.

    1994-05-01

    The radiative decay b {yields} s{gamma} is examined in the Standard Model and in nine classes of models which contain physics beyond the Standard Model. The constraints which may be placed on these models from the recent results of the CLEO Collaboration on both inclusive and exclusive radiative B decays is summarized. Reasonable bounds are found the parameters in some of the models.

  16. Water Yield and Sediment Yield Simulations for Teba Catchment in Spain Using SWRRB Model: Ⅰ. Model Input and Simulation Experiment

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Water yield and sediment yield in the Teba catchment, Spain, were simulated using SWRRB (Simulator for Water Resources in Rural Basins) model. The model is composed of 198 mathematical equations. About 120 items (variables) were input for the simulation, including meteorological and climatic factors, hydrologic factors, topographic factors, parent materials, soils, vegetation, human activities, etc. The simulated results involved surface runoff, subsurface runoff, sediment, peak flow, evapotranspiration, soil water, total biomass,etc. Careful and thorough input data preparation and repeated simulation experiments are the key to get the accurate results. In this work the simulation accuracy for annual water yield prediction reached to 83.68%.``

  17. An Inventory Model for Special Display Goods with Seasonal Demand

    Science.gov (United States)

    Kawakatsu, Hidefumi

    2010-10-01

    The present study discusses the retailer's optimal replenishment policy for seasonal products. The demand rate of seasonal merchandise such as clothes, sporting goods, children's toys and electrical home appearances tends to decrease with time after reaching its maximum value. In this study, we focus on "Special Display Goods", which are heaped up in end displays or special areas at retail stores. They are sold at a fast velocity when their quantity displayed is large, but are sold at a low velocity if the quantity becomes small. We develop the model with a finite time horizon (selling period) to determine the optimal replenishment policy, which maximizes the retailer's total profit. Numerical examples are presented to illustrate the theoretical underpinnings of the proposed model.

  18. Vulnerable Derivatives and Good Deal Bounds: A Structural Model

    DEFF Research Database (Denmark)

    Murgoci, Agatha

    2013-01-01

    can be obtained. We provide a link between the objective probability measure and the range of potential risk-neutral measures, which has an intuitive economic meaning. We also provide tight pricing bounds for European calls and show how to extend the call formula to pricing other financial products......We price vulnerable derivatives -- i.e. derivatives where the counterparty may default. These are basically the derivatives traded on the over-the-counter (OTC) markets. Default is modeled in a structural framework. The technique employed for pricing is good deal bounds (GDBs). The method imposes...... a new restriction in the arbitrage free model by setting upper bounds on the Sharpe ratios (SRs) of the assets. The potential prices that are eliminated represent unreasonably good deals. The constraint on the SR translates into a constraint on the stochastic discount factor. Thus, tight pricing bounds...

  19. Evaluation of the Williams-type model for barley yields in North Dakota and Minnesota

    Science.gov (United States)

    Barnett, T. L. (Principal Investigator)

    1981-01-01

    The Williams-type yield model is based on multiple regression analysis of historial time series data at CRD level pooled to regional level (groups of similar CRDs). Basic variables considered in the analysis include USDA yield, monthly mean temperature, monthly precipitation, soil texture and topographic information, and variables derived from these. Technologic trend is represented by piecewise linear and/or quadratic functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test (1970-1979) demonstrate that biases are small and performance based on root mean square appears to be acceptable for the intended AgRISTARS large area applications. The model is objective, adequate, timely, simple, and not costly. It consideres scientific knowledge on a broad scale but not in detail, and does not provide a good current measure of modeled yield reliability.

  20. A Distance Function Model with Good and Bad Outputs

    OpenAIRE

    2014-01-01

    We present an approach that pursues an adequate representation of product transformation possibilities for a technology generating, in addition to marketed (good) products, some environmentally detrimental non-marketed byproducts (bad outputs). As the shadow price of a non-marketed output depends on its marginal transformation rates with marketed outputs, representation of technological relationships between different groups of outputs deserves a particular attention. We model the technology ...

  1. How Good Are Statistical Models at Approximating Complex Fitness Landscapes?

    Science.gov (United States)

    du Plessis, Louis; Leventhal, Gabriel E.; Bonhoeffer, Sebastian

    2016-01-01

    Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations. PMID:27189564

  2. How Good Are Statistical Models at Approximating Complex Fitness Landscapes?

    Science.gov (United States)

    du Plessis, Louis; Leventhal, Gabriel E; Bonhoeffer, Sebastian

    2016-09-01

    Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations.

  3. The Impact of Statistical Leakage Models on Design Yield Estimation

    Directory of Open Access Journals (Sweden)

    Rouwaida Kanj

    2011-01-01

    Full Text Available Device mismatch and process variation models play a key role in determining the functionality and yield of sub-100 nm design. Average characteristics are often of interest, such as the average leakage current or the average read delay. However, detecting rare functional fails is critical for memory design and designers often seek techniques that enable accurately modeling such events. Extremely leaky devices can inflict functionality fails. The plurality of leaky devices on a bitline increase the dimensionality of the yield estimation problem. Simplified models are possible by adopting approximations to the underlying sum of lognormals. The implications of such approximations on tail probabilities may in turn bias the yield estimate. We review different closed form approximations and compare against the CDF matching method, which is shown to be most effective method for accurate statistical leakage modeling.

  4. Modelling crop yield in Iberia under drought conditions

    Science.gov (United States)

    Ribeiro, Andreia; Páscoa, Patrícia; Russo, Ana; Gouveia, Célia

    2017-04-01

    The improved assessment of the cereal yield and crop loss under drought conditions are essential to meet the increasing economy demands. The growing frequency and severity of the extreme drought conditions in the Iberian Peninsula (IP) has been likely responsible for negative impacts on agriculture, namely on crop yield losses. Therefore, a continuous monitoring of vegetation activity and a reliable estimation of drought impacts is crucial to contribute for the agricultural drought management and development of suitable information tools. This works aims to assess the influence of drought conditions in agricultural yields over the IP, considering cereal yields from mainly rainfed agriculture for the provinces with higher productivity. The main target is to develop a strategy to model drought risk on agriculture for wheat yield at a province level. In order to achieve this goal a combined assessment was made using a drought indicator (Standardized Precipitation Evapotranspiration Index, SPEI) to evaluate drought conditions together with a widely used vegetation index (Normalized Difference Vegetation Index, NDVI) to monitor vegetation activity. A correlation analysis between detrended wheat yield and SPEI was performed in order to assess the vegetation response to each time scale of drought occurrence and also identify the moment of the vegetative cycle when the crop yields are more vulnerable to drought conditions. The time scales and months of SPEI, together with the months of NDVI, better related with wheat yield were chosen to perform a multivariate regression analysis to simulate crop yield. Model results are satisfactory and highlighted the usefulness of such analysis in the framework of developing a drought risk model for crop yields. In terms of an operational point of view, the results aim to contribute to an improved understanding of crop yield management under dry conditions, particularly adding substantial information on the advantages of combining

  5. A dynamic tomato growth and yield model (TOMGRO).

    NARCIS (Netherlands)

    Jones, J.W.; Dayan, E.; Allen, L.H.; Keulen, van H.; Challa, H.

    1991-01-01

    Models of the greenhouse environment and of crops are needed to determine optimal strategies for environment control in regions where new greenhouse industries are developing. In this research, a physiological model of tomato crop development and yield was developed. A series of differential

  6. Modelling biomass production and yield of horticultural crops: a review.

    NARCIS (Netherlands)

    Marcelis, L.F.M.; Heuvelink, E.; Goudriaan, J.

    1998-01-01

    Descriptive and explanatory modelling of biomass production and yield of horticultural crops is reviewed with special reference to the simulation of leaf area, light interception, dry matter (DM) production, DM partitioning and DM content. Most models for prediction of harvest date (timing of produc

  7. Water Yield and Sediment Yield Simulations for Teba Catchment in Spain Using SWRRB Model: Ⅱ.Simulation Results

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Simulated results of water yield, sediment yield, surface runoff, subsurface runoff, peak flow, evapotranspiration, etc., in the Teba catchment, Spain, using SWRRB (Simulator for Water Resources in Rural Basins) model are presented and the related problems are discussed. The results showed that water yield and sediment yield could be satisfactorily simulated using SWRRB model The accuracy of the annual water yield simulation in the Teba catchment was up to 83.68%, which implied that this method could be effectively used to predict the annual or inter-annual water yield and to realize the quantification of geographic elements and processes of a river basin.``

  8. Modeling temporal and spatial variability of crop yield

    Science.gov (United States)

    Bonetti, S.; Manoli, G.; Scudiero, E.; Morari, F.; Putti, M.; Teatini, P.

    2014-12-01

    In a world of increasing food insecurity the development of modeling tools capable of supporting on-farm decision making processes is highly needed to formulate sustainable irrigation practices in order to preserve water resources while maintaining adequate crop yield. The design of these practices starts from the accurate modeling of soil-plant-atmosphere interaction. We present an innovative 3D Soil-Plant model that couples 3D hydrological soil dynamics with a mechanistic description of plant transpiration and photosynthesis, including a crop growth module. Because of its intrinsically three dimensional nature, the model is able to capture spatial and temporal patterns of crop yield over large scales and under various climate and environmental factors. The model is applied to a 25 ha corn field in the Venice coastland, Italy, that has been continuously monitored over the years 2010 and 2012 in terms of both hydrological dynamics and yield mapping. The model results satisfactorily reproduce the large variability observed in maize yield (from 2 to 15 ton/ha). This variability is shown to be connected to the spatial heterogeneities of the farmland, which is characterized by several sandy paleo-channels crossing organic-rich silty soils. Salt contamination of soils and groundwater in a large portion of the area strongly affects the crop yield, especially outside the paleo-channels, where measured salt concentrations are lower than the surroundings. The developed model includes a simplified description of the effects of salt concentration in soil water on transpiration. The results seem to capture accurately the effects of salt concentration and the variability of the climatic conditions occurred during the three years of measurements. This innovative modeling framework paves the way to future large scale simulations of farmland dynamics.

  9. Vulnerable Derivatives and Good Deal Bounds: A Structural Model

    DEFF Research Database (Denmark)

    Murgoci, Agatha

    2013-01-01

    a new restriction in the arbitrage free model by setting upper bounds on the Sharpe ratios (SRs) of the assets. The potential prices that are eliminated represent unreasonably good deals. The constraint on the SR translates into a constraint on the stochastic discount factor. Thus, tight pricing bounds...... can be obtained. We provide a link between the objective probability measure and the range of potential risk-neutral measures, which has an intuitive economic meaning. We also provide tight pricing bounds for European calls and show how to extend the call formula to pricing other financial products...

  10. A crop model-based approach for sunflower yields

    Directory of Open Access Journals (Sweden)

    João Guilherme Dal Belo Leite

    2014-10-01

    Full Text Available Pushed by the Brazilian biodiesel policy, sunflower (Helianthus annuus L. production is becoming increasingly regarded as an option to boost farmers' income, particularly under semi-arid conditions. Biodiesel related opportunities increase the demand for decision-making information at different levels, which could be met by simulation models. This study aimed to evaluate the performance of the crop model OILCROP-SUN to simulate sunflower development and growth under Brazilian conditions and to explore sunflower water- and nitrogen-limited, water-limited and potential yield and yield variability over an array of sowing dates in the northern region of the state of Minas Gerais, Brazil. For model calibration, an experiment was conducted in which two sunflower genotypes (H358 and E122 were cultivated in a clayey soil. Growth components (leaf area index, above ground biomass, grain yield and development stages (crop phenology were measured. A database composed of 27 sunflower experiments from five Brazilian regions was used for model evaluation. The spatial yield distribution of sunflower was mapped using ordinary kriging in ArcGIS. The model simulated sunflower grain productivity satisfactorily (Root Mean Square Error ≈ 13 %. Simulated yields were relatively high (1,750 to 4,250 kg ha-1 and the sowing window was fairly wide (Oct to Feb for northwestern locations, where sunflower could be cultivated as a second crop (double cropping at the end of the rainy season. The hybrid H358 had higher yields for all simulated sowing dates, growth conditions and selected locations.

  11. The Meaning of Goodness-of-Fit Tests: Commentary on "Goodness-of-Fit Assessment of Item Response Theory Models"

    Science.gov (United States)

    Thissen, David

    2013-01-01

    In this commentary, David Thissen states that "Goodness-of-fit assessment for IRT models is maturing; it has come a long way from zero." Thissen then references prior works on "goodness of fit" in the index of Lord and Novick's (1968) classic text; Yen (1984); Drasgow, Levine, Tsien, Williams, and Mead (1995); Chen and…

  12. Study on Model for High Yield and Good Quality of N, P Application Quantity and Density of Peppermint (Mentha piperita L.)%椒样薄荷氮、磷用量及密度高产优质回归模型研究

    Institute of Scientific and Technical Information of China (English)

    窦宏涛; 张连杰; 邢文艳; 王安

    2009-01-01

    为了探明在超高产条件下椒样薄荷高产优质的农艺模型以及对其精油品质的影响,采用三因子二次饱和D最优设计方案,选取对椒样薄荷精油产量影响较大的密度蜀、氮肥用量X2、磷肥用量X3为调控因子,以每公顷精油产量Y为目标函数,研究椒样薄荷栽培数学模型.结果表明,影响椒样薄荷精油产量的各因素权重依次为氮肥用量X2密度X1磷肥用量X3,依据建立的模型,目标精油产量≥100.5 kg/hm2时优质高产最佳农艺方案为:密度X117.55万~22.05万苗/hm2,氮肥用量X2纯氮172.5~217.5 kg/hm2,磷肥用量X3纯磷118.5~150 kg/hm2;品质分析结果表明,密度对精油品质有显著影响,氮肥用量对精油品质的影响与密度密切相关,在密度较低时影响不明显,而在密度较高时有一定的影响,适量控氮可以提高精油品质,过量施氮会降低精油品质,磷肥用量对精油品质影响不明显.%The study was carried out by using the principle of agricultural ecology and the qualified design of three square saturated D, in which the factors of density(X1), application quantity of nitrogen(X2) and phosphorus (X3) were taken as the adjusting factors, and the yield (Y) of each hectare as target function, Through the study we got a mathematic model for cultivation of peppermint. The result indicated that, under the condition of this experiment design, factors affecting yield of the essential oil of peppermint in experiment region were in order as application quantity of nitrogen(X2)> density(X1)> application quantity of phosphorus(X3) when the target yield was greater than 100.5 kg/hm2, the optimum formula of peppermint this region was as follows: density X1 was 175500~220500 plant/bm2, application amount of N fertilizerX2 was 172.5-217.5 kg/hm2, application amount of P2O5 fertilizer X3 was 118.5-150 kg/hm2; Quality analyses show: quality of the essential oil were influenced significantly by density, while the

  13. MODELLING CHALLENGES TO FORECAST URBAN GOODS DEMAND FOR RAIL

    Directory of Open Access Journals (Sweden)

    Antonio COMI

    2015-12-01

    Full Text Available This paper explores the new research challenges for forecasting urban goods demand by rail. In fact, the growing interest to find urban logistics solutions for improving city sustainability and liveability, mainly due to the reduction of urban road accessibility and environmental constraints, has pushed to explore solutions alternative to the road. Multimodal urban logistics, based on the use of railway, seem an interesting alternative solution, but it remained mainly at conceptual level. Few studies have explored the factors, that push actors to find competitive such a system with respect to the road, and modelling framework for forecasting the relative demand. Therefore, paper reviews the current literature, investigates the factors involved in choosing such a mode, and finally, recalls a recent modelling framework and hence proposes some advancements that allow to point out the rail transport alternative.

  14. MEDIA AND DEVELOPMENT MODEL: FROM MODERNIZATION TO GOOD GOVERMENT

    Directory of Open Access Journals (Sweden)

    Ana Fernández Viso

    2013-04-01

    Full Text Available This paper describes and analyzes, from a historical perspective, the role that one of the central institutions of modernity, the media, has played in the development models and policies promoted by the actors of the international aid system since the 1950s. In addition, it presents and discusses the critiques to these models and policies made by intellectuals, governments, and civil society organizations from Southern countries, which have led to questioning the role of media in development processes and to redefining their inclusion in the development policies from the 1970s. Finally, the paper contributes some elements to reflect on the relationship between media, good government and development under the framework of the current governance reform strategies.

  15. Yield models for commercial willow biomass plantations in Sweden

    Energy Technology Data Exchange (ETDEWEB)

    Mola-Yudego, Blas [Faculty of Forestry, University of Joensuu, P.O. Box 111, FI-801 01 Joensuu (Finland); Aronsson, Paer [Department of Crop Production Ecology, Swedish University of Agricultural Sciences (SLU), P.O. Box 7016, S-750 07 Uppsala (Sweden)

    2008-09-15

    A yield model for willow plantations for bioenergy production in Sweden was developed based on recorded production of 2082 commercial plantations during the period 1989-2005. The model predicts yield for the first, second and third harvest using oats (avena) production as agro-climatic index. The mean annual yields were 2.6, 4.2 and 4.5 oven dry tonnes (odt) per hectare during the first, second and third cutting cycles, respectively. The yield correlated inversely with the length of the cutting cycle. The results of the study show significant differences between growers, which suggest the importance of proper management in the establishment and tending of the plantations. Model estimates for 25% of the best growers vary from 4.0 to 6.3 odt ha{sup -1} yr{sup -1} in 5-year-rotation plantations during the first cutting cycle, and from 5.4 to 7.1 odt ha{sup -1} yr{sup -1} in 4-year-rotations for the second cutting cycle. The proposed model can be applied in policy making and for management planning. (author)

  16. Dynamic modelling of pectin extraction describing yield and functional characteristics

    DEFF Research Database (Denmark)

    Andersen, Nina Marianne; Cognet, T.; Santacoloma, P. A.

    2017-01-01

    A dynamic model of pectin extraction is proposed that describes pectin yield, degree of esterification and intrinsic viscosity. The dynamic model is one dimensional in the peel geometry and includes mass transport of pectin by diffusion and reaction kinetics of hydrolysis, degradation and de-esterification....... The model takes into account the effects of the process conditions such as temperature and acid concentration on extraction kinetics. It is shown that the model describes pectin bulk solution concentration, degree of esterification and intrinsic viscosity in pilot scale extractions from lime peel...

  17. ASSESSMENT OF THE ARTIFICIAL NEURAL NETWORKS TO GEOMORPHIC MODELLING OF SEDIMENT YIELD FOR UNGAUGED CATCHMENTS, ALGERIA

    Directory of Open Access Journals (Sweden)

    Khanchoul Kamel

    2014-01-01

    Full Text Available Knowledge of sediment yield and the factors controlling it provides useful information for estimating erosion intensities within river basins. The objective of this study was to build a model from which suspended sediment yield could be estimated from ungauged rivers using computed sediment yield and physical factors. Researchers working on suspended sediment transported by wadis in the Maghreb are usually facing the lack of available data for such river types. Further study of the prediction of sediment transport in these regions and its variability is clearly required. In this work, ANNs were built between sediment yield established from longterm measurement series at gauging stations in Algerian catchments and corresponding basic physiographic parameters such as rainfall, runoff, lithology index, coefficient of torrentiality, and basin area. The proposed Levenberg-Marquardt and Multilayer Perceptron algorithms to train the neural networks of the current research study was based on the feed-forward backpropagation method with combinations of number of neurons in each hidden layer, transfer function, error goal. Additionally, three statistical measurements, namely the root mean square error (RMSE, the coefficient of determination (R², and the efficiency factor (EF have been reported for examining the forecasting accuracy of the developed model. Single plot displays of network outputs with respect to targets for training have provided good performance results and good fitting . Thus, ANNs were a promising method for predicting suspended sediment yield in ungauged Algerian catchments.

  18. Buffalos milk yield analysis using random regression models

    Directory of Open Access Journals (Sweden)

    A.S. Schierholt

    2010-02-01

    Full Text Available Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed, daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genético de Bubalinos (PROMEBUL and from records of EMBRAPA Amazônia Oriental - EAO herd, located in Belém, Pará, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre’s polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre’s polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.

  19. Neural Network in Modeling Malaysian Oil Palm Yield

    Directory of Open Access Journals (Sweden)

    Zuhaimy Ismail

    2011-01-01

    Full Text Available Problem statement: Forecasting of palm oil yield has become an important element in the management of oil palm industry for proper planning and decision making. The importance of yield forecasting has led us to explore modeling of palm oil yield for Malaysia using the most recent development of Artificial Neural Network (ANN. The main issue in yield forecasting is to predict the future value with the minimum error. Approach: Artificial neural networks are computing systems containing many interconnected nonlinear neurons, capable of extracting linear and nonlinear regularity in a given data set. It is an artificial intelligence model originally designed to replicate the human brains learning process, a network with many elements or neurons that are connected by communications channels or connectors. The ANN can perform a particular function when certain values are assigned to the connections or weights between elements. In this study, a secondary data set from the Malaysian Palm Oil Board (MPOB on the foliar nutrient composition, fertilizer trials and Fresh Fruit Bunch (FFB yield were taken and analyzed. The foliar nutrient composition variables are the nitrogen N, phosphorus P, potassium K, calcium Ca and magnesium Mg concentration, while the fertilizer trials data are the N, P, K and Mg fertilizers and are measured in kg per palm per year. The foliar composition data was presented in the form of measured values whiles the fertilizer data in ordinal levels, from zero to three. Results: Two experiments were conducted to demonstrate the implementation ANN and for both experiment, the result demonstrated that the number of hidden nodes produces an effect to the overall forecast performance of the ANN architecture. From the first experiment, it shows that the number of runs does not affect the ANN performance, but changing the momentum to learning rates, due to shows a significant improvement in the forecast result. The experimental result will be

  20. Stellar yields from metal-rich asymptotic giant branch models

    CERN Document Server

    Karakas, Amanda I

    2016-01-01

    We present new theoretical stellar yields and surface abundances for three grids of metal-rich asymptotic giant branch (AGB) models. Post-processing nucleosynthesis results are presented for stellar models with initial masses between 1$M_{\\odot}$ and 7.5$M_{\\odot}$ for $Z=0.007$, and 1$M_{\\odot}$ and 8$M_{\\odot}$ for $Z=0.014$ (solar) and $Z=0.03$. We include stellar surface abundances as a function of thermal pulse on the AGB for elements from C to Bi and for a selection of isotopic ratios for elements up to Fe and Ni (e.g., $^{12}$C/$^{13}$C), which can be obtained from observations of molecules in stars and from the laboratory analysis of meteoritic stardust grains. Ratios of elemental abundances of He/H, C/O, and N/O are also included, which are useful for direct comparison to observations of AGB stars and their progeny including planetary nebulae. The integrated elemental stellar yields are presented for each model in the grid for hydrogen, helium and all stable elements from C to Bi. Yields of Li are al...

  1. Evaluation of weather-based rice yield models in India

    Science.gov (United States)

    Sudharsan, D.; Adinarayana, J.; Reddy, D. Raji; Sreenivas, G.; Ninomiya, S.; Hirafuji, M.; Kiura, T.; Tanaka, K.; Desai, U. B.; Merchant, S. N.

    2013-01-01

    The objective of this study was to compare two different rice simulation models—standalone (Decision Support System for Agrotechnology Transfer [DSSAT]) and web based (SImulation Model for RIce-Weather relations [SIMRIW])—with agrometeorological data and agronomic parameters for estimation of rice crop production in southern semi-arid tropics of India. Studies were carried out on the BPT5204 rice variety to evaluate two crop simulation models. Long-term experiments were conducted in a research farm of Acharya N G Ranga Agricultural University (ANGRAU), Hyderabad, India. Initially, the results were obtained using 4 years (1994-1997) of data with weather parameters from a local weather station to evaluate DSSAT simulated results with observed values. Linear regression models used for the purpose showed a close relationship between DSSAT and observed yield. Subsequently, yield comparisons were also carried out with SIMRIW and DSSAT, and validated with actual observed values. Realizing the correlation coefficient values of SIMRIW simulation values in acceptable limits, further rice experiments in monsoon (Kharif) and post-monsoon (Rabi) agricultural seasons (2009, 2010 and 2011) were carried out with a location-specific distributed sensor network system. These proximal systems help to simulate dry weight, leaf area index and potential yield by the Java based SIMRIW on a daily/weekly/monthly/seasonal basis. These dynamic parameters are useful to the farming community for necessary decision making in a ubiquitous manner. However, SIMRIW requires fine tuning for better results/decision making.

  2. Climate Change Modelling and Its Roles to Chinese Crops Yield

    Institute of Scientific and Technical Information of China (English)

    JU Hui; LIN Er-da; Tim Wheeler; Andrew Challinor; JIANG Shuai

    2013-01-01

    Climate has been changing in the last fifty years in China and will continue to change regardless any efforts for mitigation. Agriculture is a climate-dependent activity and highly sensitive to climate changes and climate variability. Understanding the interactions between climate change and agricultural production is essential for society stable development of China. The first mission is to fully understand how to predict future climate and link it with agriculture production system. In this paper, recent studies both domestic and international are reviewed in order to provide an overall image of the progress in climate change researches. The methods for climate change scenarios construction are introduced. The pivotal techniques linking crop model and climate models are systematically assessed and climate change impacts on Chinese crops yield among model results are summarized. The study found that simulated productions of grain crop inherit uncertainty from using different climate models, emission scenarios and the crops simulation models. Moreover, studies have different spatial resolutions, and methods for general circulation model (GCM) downscaling which increase the uncertainty for regional impacts assessment. However, the magnitude of change in crop production due to climate change (at 700 ppm CO2 eq correct) appears within ±10%for China in these assessments. In most literatures, the three cereal crop yields showed decline under climate change scenarios and only wheat in some region showed increase. Finally, the paper points out several gaps in current researches which need more studies to shorten the distance for objective recognizing the impacts of climate change on crops. The uncertainty for crop yield projection is associated with climate change scenarios, CO2 fertilization effects and adaptation options. Therefore, more studies on the fields such as free air CO2 enrichment experiment and practical adaptations implemented need to be carried out.

  3. NEST: A Comprehensive Model for Scintillation Yield in Liquid Xenon

    CERN Document Server

    Szydagis, M; Kazkaz, K; Mock, J; Stolp, D; Sweany, M; Tripathi, M; Uvarov, S; Walsh, N; Woods, M

    2011-01-01

    A comprehensive model for explaining scintillation yield in liquid xenon is introduced. We unify various definitions of work function which abound in the literature and incorporate all available data on electron recoil scintillation yield. This results in a better understanding of electron recoil, and facilitates an improved description of nuclear recoil. An incident gamma energy range of O(1 keV) to O(1 MeV) and electric fields between 0 and O(10 kV/cm) are incorporated into this heuristic model. We show results from a Geant4 implementation, but because the model has a few free parameters, implementation in any simulation package should be simple. We use a quasi-empirical approach, with an objective of improving detector calibrations and performance verification. The model will aid in the design and optimization of future detectors. This model is also easy to extend to other noble elements. In this paper we lay the foundation for an exhaustive simulation code which we call NEST (Noble Element Simulation Tech...

  4. Model for Predicting Climatic Yield of Sugarcane in Nanning City

    Institute of Scientific and Technical Information of China (English)

    Zhanggui; LAN; Guanghai; LI; Yulian; LIANG; Yuhong; YANG; Xiaoping; LI

    2014-01-01

    According to spatial distribution of climate disasters in Nanning City and physiological and ecological indicator demands of sugarcane,with the aid of HJ- 1 CCD satellite remote sensing images,basic meteorological data and geographic information data,this paper established the model for predicting climatic yield of sugarcane in Nanning City,to predict total yield of sugarcane in Nanning City. Results indicated that the distribution of sugarcane in Nanning City is greatly influenced by drought. In 2010,regions suffered from drought had sugarcane planting area of 346. 20 km2,accounting for 18.88% of the total sugarcane planting area. The influence of frost disaster on distribution of sugarcane in Nanning City is limited. Regions suffered from frost had sugarcane planting area of only 67. 1 km2,taking up 3.75% of the total sugarcane planting area. In 2010,the climatic yield of sugarcane in Nanning City was 8. 8446 million tons. It proved that the prediction accuracy of the model is up to 90%.

  5. WFIRST-AFTA Coronagraph Science Yield Modeling with EXOSIMS

    CERN Document Server

    Savransky, Dmitry

    2015-01-01

    We present and discuss the design details of an extensible, modular, open source software framework called EXOSIMS, which creates end-to-end simulations of space-based exoplanet imaging missions. We motivate the development and baseline implementation of the component parts of this software with models of the WFIRST-AFTA coronagraph, and present initial results of mission simulations for various iterations of the WFIRST-AFTA coronagraph design. We present and discuss two sets of simulations: The first compares the science yield of completely different instruments in the form of early competing coronagraph designs for WFIRST-AFTA. The second set of simulations evaluates the effects of different operating assumptions, specifically the assumed post-processing capabilities and telescope vibration levels. We discuss how these results can guide further instrument development and the expected evolution of science yields.

  6. Good God?!? Lamentations as a model for mourning the loss of the good God.

    Science.gov (United States)

    Houck-Loomis, Tiffany

    2012-09-01

    This article will address the devastating psychological and social effects due to the loss of one's primary love-object, namely God in the case of faith communities and religious individuals. By using Melanie Klein's Object Relations Theory (Klein in Envy and gratitude and other works 1946/1963. The Free Press, New York, 1975a) as a way to enter the text of Lamentations, I will articulate an alternative reading that can serve as a model for Pastors and Educators to use when walking with individuals and communities through unspeakable losses. I will argue that Lamentations may be used as a tool for naming confounding depression and anxiety that stems from a damaged introjected object (one's personal God). This tool may provide individuals and communities a framework for placing anger and contempt upon God in order to re-assimilate this loved yet hated object, eventually leading toward healing and restoration of the self.

  7. Soybean yield modeling using bootstrap methods for small samples

    Energy Technology Data Exchange (ETDEWEB)

    Dalposso, G.A.; Uribe-Opazo, M.A.; Johann, J.A.

    2016-11-01

    One of the problems that occur when working with regression models is regarding the sample size; once the statistical methods used in inferential analyzes are asymptotic if the sample is small the analysis may be compromised because the estimates will be biased. An alternative is to use the bootstrap methodology, which in its non-parametric version does not need to guess or know the probability distribution that generated the original sample. In this work we used a set of soybean yield data and physical and chemical soil properties formed with fewer samples to determine a multiple linear regression model. Bootstrap methods were used for variable selection, identification of influential points and for determination of confidence intervals of the model parameters. The results showed that the bootstrap methods enabled us to select the physical and chemical soil properties, which were significant in the construction of the soybean yield regression model, construct the confidence intervals of the parameters and identify the points that had great influence on the estimated parameters. (Author)

  8. Stellar Models and Yields of Asymptotic Giant Branch Stars

    CERN Document Server

    Karakas, Amanda I

    2007-01-01

    We present stellar yields calculated from detailed models of low and intermediate-mass asymptotic giant branch (AGB) stars. We evolve models with a range of mass from 1 to 6Msun, and initial metallicities from solar to 1/200th of the solar metallicity. Each model was evolved from the zero age main sequence to near the end of the thermally-pulsing AGB phase, and through all intermediate phases including the core He-flash for stars initially less massive than 2.5Msun. For each mass and metallicity, we provide tables containing structural details of the stellar models during the TP-AGB phase, and tables of the stellar yields for 74 species from hydrogen through to sulphur, and for a small number of iron-group nuclei. All tables are available for download. Our results have many applications including use in population synthesis studies and the chemical evolution of galaxies and stellar systems, and for comparison to the composition of AGB and post-AGB stars and planetary nebulae.

  9. Mechanical model for yield strength of nanocrystalline materials under high strain rate loading

    Institute of Scientific and Technical Information of China (English)

    朱荣涛; 周剑秋; 马璐; 张振忠

    2008-01-01

    To understand the high strain rate deformation mechanism and determine the grain size,strain rate and porosity dependent yield strength of nanocrystalline materials,a new mechanical model based on the deformation mechanism of nanocrystalline materials under high strain rate loading was developed.As a first step of the research,the yield behavior of the nanocrystalline materials under high strain rate loading was mainly concerned in the model and uniform deformation was assumed for simplification.Nanocrystalline materials were treated as composites consisting of grain interior phase and grain boundary phase,and grain interior and grain boundary deformation mechanisms under high strain rate loading were analyzed,then Voigt model was applied to coupling grain boundary constitutive relation with mechanical model for grain interior phase to describe the overall yield mechanical behavior of nanocrystalline materials.The predictions by the developed model on the yield strength of nanocrysatlline materials at high strain rates show good agreements with various experimental data.Further discussion was presented for calculation results and relative experimental observations.

  10. Runoff and sediment yield modeling in a medium-size mediterranean watershed

    Directory of Open Access Journals (Sweden)

    Ossama M.M. Abdelwahab

    2013-09-01

    Full Text Available The AnnAGNPS model was used to estimate runoff, peak discharge and sediment yield at the event scale in the Carapelle watershed, a Mediterranean medium-size watershed (506 km2 located in Apulia, Southern Italy. The model was calibrated and validated using five years of runoff and sediment yield data measured at a monitoring station located at Ordona – Ponte dei Sauri Bridge. A total of 36 events was used to estimate the output of the model during the period 2007-2011, in comparison to the corresponding observations at the watershed outlet. The model performed well in predicting runoff, as was testified by the high values of the coefficients of efficiency and determination during the validation process. The peak flows predictions were satisfactory especially for the high flow events; the prediction capability of sediment yield was good, even if a slight over-estimation was observed. Finally, the model was used to evaluate the effectiveness of different Management practices (MPs on the watershed (converting wheat to forest, using vegetated streams, crop rotation corn/soybean, no tillage. While the maximum reduction in sediment yield was achieved converting wheat to forest, the best compromises between soil conservation and agriculture resulted to be crop rotations.

  11. Comparison of Three Modelling Approaches to Simulate Regional Crop Yield: A Case Study of Winter Wheat Yield in Western Germany

    NARCIS (Netherlands)

    Soltani Largani, Afsaneh; Bakker, M.M.; Veldkamp, A.; Stoorvogel, J.J.

    2016-01-01

    The need for more comparisons among models is widely recognized. This study aimed to compare three different modelling approaches for their capability to simulate and predict trends and patterns of winter wheat yield in Western Germany. The three modelling approaches included an empirical model, a p

  12. Paddy crop yield estimation in Kashmir Himalayan rice bowl using remote sensing and simulation model.

    Science.gov (United States)

    Muslim, Mohammad; Romshoo, Shakil Ahmad; Rather, A Q

    2015-06-01

    The Kashmir Himalayan region of India is expected to be highly prone to the change in agricultural land use because of its geo-ecological fragility, strategic location vis-à-vis the Himalayan landscape, its trans-boundary river basins, and inherent socio-economic instabilities. Food security and sustainability of the region are thus greatly challenged by these impacts. The effect of future climate change, increased competition for land and water, labor from non-agricultural sectors, and increasing population adds to this complex problem. In current study, paddy rice yield at regional level was estimated using GIS-based environment policy integrated climate (GEPIC) model. The general approach of current study involved combining regional level crop database, regional soil data base, farm management data, and climatic data outputs with GEPIC model. The simulated yield showed that estimated production to be 4305.55 kg/ha (43.05 q h(-1)). The crop varieties like Jhelum, K-39, Chenab, China 1039, China-1007, and Shalimar rice-1 grown in plains recorded average yield of 4783.3 kg/ha (47.83 q ha(-1)). Meanwhile, high altitude areas with varieties like Kohsaar, K-78 (Barkat), and K-332 recorded yield of 4102.2 kg/ha (41.02 q ha(-1)). The observed and simulated yield showed a good match with R (2) = 0.95, RMSE = 132.24 kg/ha, respectively.

  13. Yield-Ensuring DAC-Embedded Opamp Design Based on Accurate Behavioral Model Development

    Science.gov (United States)

    Jang, Yeong-Shin; Nguyen, Hoai-Nam; Ryu, Seung-Tak; Lee, Sang-Gug

    An accurate behavioral model of a DAC-embedded opamp (DAC-opamp) is developed for a yield-ensuring LCD column driver design. A lookup table for the V-I curve of the unit differential pair in the DAC-opamp is extracted from a circuit simulation and is later manipulated through a random error insertion. Virtual ground assumption simplifies the output voltage estimation algorithm. The developed behavioral model of a 5-bit DAC-opamp shows good agreement with the circuit level simulation with less than 5% INL difference.

  14. Global proteomic characterization of uterine histotroph recovered from beef heifers yielding good quality and degenerate day 7 embryos.

    Science.gov (United States)

    Beltman, M E; Mullen, M P; Elia, G; Hilliard, M; Diskin, M G; Evans, A C; Crowe, M A

    2014-01-01

    The objective was to analyze the proteomic composition of uterine flushes collected from beef heifers on day 7 after insemination. Estrus was synchronized in crossbred beef heifers by using a protocol with a controlled intravaginal drug releasing device. Heifers detected in standing estrus (within 24-48 h after removal of controlled intravaginal drug releasing device) were inseminated (estrus = day 0) with frozen-thawed semen from a single ejaculate of a bull with proven fertility. Heifers from which an embryo was recovered (after slaughter on day 7) were classified as either having a viable embryo (morula/blastocyst stage) or a degenerate embryo (arrested at the 2- to 16-cell stage). The overall recovery rate (viable and degenerate combined) was 64%. Global liquid chromatography coupled to tandem mass spectrometry proteomic analysis of the histotroph collected identified 40 high-confidence proteins present on day 7; 26 proteins in the viable group, 10 in the degenerate group, and 4 shared between both groups. Five proteins (platelet-activating factor acetylhydrolase IB subunit γ [PAFAH1B3], tubulin α-1D chain, tubulin β-4A chain, cytochrome C, and dihydropyrimidinase-related protein-2) were unique or more abundant in the histotroph collected from animals with a viable embryo, and 1 protein (S100-A4) was more abundant in the histotroph collected from animals with a degenerate embryo. Of interest, PAFAH1B3, detected only in histotroph from the group yielding viable embryos, belongs to the group of platelet-activating factors that are known to be important for the development of the pre-implantation embryo in other species. To our knowledge this is the first report of PAFAH1B3 in relation to bovine early embryonic development.

  15. Dynamic Processes in Network Goods: Modeling, Analysis and Applications

    Science.gov (United States)

    Paothong, Arnut

    2013-01-01

    The network externality function plays a very important role in the study of economic network industries. Moreover, the consumer group dynamic interactions coupled with network externality concept is going to play a dominant role in the network goods in the 21st century. The existing literature is stemmed on a choice of externality function with…

  16. Statistical modelling and deconvolution of yield meter data

    DEFF Research Database (Denmark)

    Tøgersen, Frede Aakmann; Waagepetersen, Rasmus Plenge

    Data for yield maps can be obtained from modern combine harvesters equipped with a differential global positioning system and a yield monitoring system. Due to delay and smoothing effects in the combine harvester the recorded yield data for a location represents a shifted weighted average of yiel...

  17. Traumatic Coagulopathy: Where are the Good Experimental Models?

    Science.gov (United States)

    2008-10-01

    factor model,24 a mathematical model of dilutional coagulopathy,17 gene therapy enhanced clotting in a murine von Willebrand model20 and a sheep model...1997;77:905–910. 35. Lei TC, Scott DW. Induction of tolerance to factor VIII inhibitors by gene therapy with immunodominant A2 and C2 domains presented by B...included two rabbit model studies,15,24 focused on the role of factor VII in an endotoxin model15 and antibody-induced hemophilia in a von Wille- brand

  18. How good are one-dimensional Josephson junction models?

    DEFF Research Database (Denmark)

    Lomdahl, P. S.; Olsen, O.H.; Eilbeck, J. C.

    1985-01-01

    A two-dimensional model of Josephson junctions of overlap type is presented and shown to reduce to the usual one-dimensional (1D) model in the limit of a very narrow junction. Comparisons between the stability limits for fluxon reflection obtained from the two models suggest that the many results...

  19. An introduction to good practices in cognitive modeling

    NARCIS (Netherlands)

    A. Heathcote; S.D. Brown; E.-J. Wagenmakers

    2015-01-01

    Cognitive modeling can provide important insights into the underlying causes of behavior, but the validity of those insights rests on careful model development and checking. We provide guidelines on five important aspects of the practice of cognitive modeling: parameter recovery, testing selective i

  20. Crop Yield and Area can be Reliably Estimated Using Farmer Supplied Yield Data, Remote Sensing and Crop Models in Australia.

    Science.gov (United States)

    Lawes, R.

    2016-12-01

    The Australian grain growing region is vast and occupies where some 25 million tonnes of wheat is produced from latitudes -27 to -42, where soils, crops and climates vary considerably. Predicting the area of individual crops is time consuming and currently conducted by survey, while yield estimates are derived from these areas and from information about grain receivables with little pre-harvest information available to industry. The existing approach fails to provide reliable, timely, small scale information about production. Similarly, previous attempts to predict yield using satellite derived information rely on information collected using the existing systems to calibrate models. We have developed a crop productivity and yield model - called C-Store Crop - that uses remotely sensed vegetation indices, along with site based rainfall, radiation and temperature information. Model calibration using 3000 points derived from farmer supplied yield maps for wheat, barley, canola and chickpea showed strong relationships (>70%) between modelled plant mass and observed crop yield at the paddock scale. C-Store Crop is being applied at 250m and 25m grid resolution. Farmer supplied yield data was also used to train a combination of Radar and Landsat images collected whilst the crop is growing to discriminate between crop types. Landsat information alone was unable to discriminate legume and cereal crops. Problems such as cloud prevented accessing appropriate scenes. Inclusion of Radar information reduced errors of commission and omission. By combining the C-Store Crop model with remote estimates of crop type, we anticipate predicting crop type and crop yield with uncertainty estimates across the Australian continent.

  1. The Web economy: goods, users, models and policies

    CERN Document Server

    Vafopoulos, Michalis

    2011-01-01

    Web emerged as an antidote to the rapidly increasing quantity of accumulated knowledge and become successful because it facilitates massive participation and communication with minimum costs. Today, its enormous impact, scale and dynamism in time and space make very difficult (and sometimes impossible) to measure and anticipate the effects in human society. In addition to that, we demand from the Web to be fast, secure, reliable, all-inclusive and trustworthy in any transaction. The scope of the present article is to review a part of the Web economy literature that will help us to identify its major participants and their functions. The goal is to understand how the Web economy differs from the traditional setting and what implications have these differences. Secondarily, we attempt to establish a minimal common understanding about the incentives and properties of the Web economy. In this direction the concept of Web Goods and a new classification of Web Users are introduced and analyzed This article, is not,...

  2. De praeceptis ferendis: good practice in multi-model ensembles

    Directory of Open Access Journals (Sweden)

    I. Kioutsioukis

    2014-06-01

    Full Text Available Ensembles of air quality models have been formally and empirically shown to outperform single models in many cases. Evidence suggests that ensemble error is reduced when the members form a diverse and accurate ensemble. Diversity and accuracy are hence two factors that should be taken care of while designing ensembles in order for them to provide better predictions. There exists a trade-off between diversity and accuracy for which one cannot be gained without expenses of the other. Theoretical aspects like the bias-variance-covariance decomposition and the accuracy-diversity decomposition are linked together and support the importance of creating ensemble that incorporates both the elements. Hence, the common practice of unconditional averaging of models without prior manipulation limits the advantages of ensemble averaging. We demonstrate the importance of ensemble accuracy and diversity through an inter-comparison of ensemble products for which a sound mathematical framework exists, and provide specific recommendations for model selection and weighting for multi model ensembles. To this end we have devised statistical tools that can be used for diagnostic evaluation of ensemble modelling products, complementing existing operational methods.

  3. Climate-based statistical regression models for crop yield forecasting of coffee in humid tropical Kerala, India

    Science.gov (United States)

    Jayakumar, M.; Rajavel, M.; Surendran, U.

    2016-07-01

    A study on the variability of coffee yield of both Coffea arabica and Coffea canephora as influenced by climate parameters (rainfall (RF), maximum temperature (Tmax), minimum temperature (Tmin), and mean relative humidity (RH)) was undertaken at Regional Coffee Research Station, Chundale, Wayanad, Kerala State, India. The result on the coffee yield data of 30 years (1980 to 2009) revealed that the yield of coffee is fluctuating with the variations in climatic parameters. Among the species, productivity was higher for C. canephora coffee than C. arabica in most of the years. Maximum yield of C. canephora (2040 kg ha-1) was recorded in 2003-2004 and there was declining trend of yield noticed in the recent years. Similarly, the maximum yield of C. arabica (1745 kg ha-1) was recorded in 1988-1989 and decreased yield was noticed in the subsequent years till 1997-1998 due to year to year variability in climate. The highest correlation coefficient was found between the yield of C. arabica coffee and maximum temperature during January (0.7) and between C. arabica coffee yield and RH during July (0.4). Yield of C. canephora coffee had highest correlation with maximum temperature, RH and rainfall during February. Statistical regression model between selected climatic parameters and yield of C. arabica and C. canephora coffee was developed to forecast the yield of coffee in Wayanad district in Kerala. The model was validated for years 2010, 2011, and 2012 with the coffee yield data obtained during the years and the prediction was found to be good.

  4. Climate-based statistical regression models for crop yield forecasting of coffee in humid tropical Kerala, India

    Science.gov (United States)

    Jayakumar, M.; Rajavel, M.; Surendran, U.

    2016-12-01

    A study on the variability of coffee yield of both Coffea arabica and Coffea canephora as influenced by climate parameters (rainfall (RF), maximum temperature (Tmax), minimum temperature (Tmin), and mean relative humidity (RH)) was undertaken at Regional Coffee Research Station, Chundale, Wayanad, Kerala State, India. The result on the coffee yield data of 30 years (1980 to 2009) revealed that the yield of coffee is fluctuating with the variations in climatic parameters. Among the species, productivity was higher for C. canephora coffee than C. arabica in most of the years. Maximum yield of C. canephora (2040 kg ha-1) was recorded in 2003-2004 and there was declining trend of yield noticed in the recent years. Similarly, the maximum yield of C. arabica (1745 kg ha-1) was recorded in 1988-1989 and decreased yield was noticed in the subsequent years till 1997-1998 due to year to year variability in climate. The highest correlation coefficient was found between the yield of C. arabica coffee and maximum temperature during January (0.7) and between C. arabica coffee yield and RH during July (0.4). Yield of C. canephora coffee had highest correlation with maximum temperature, RH and rainfall during February. Statistical regression model between selected climatic parameters and yield of C. arabica and C. canephora coffee was developed to forecast the yield of coffee in Wayanad district in Kerala. The model was validated for years 2010, 2011, and 2012 with the coffee yield data obtained during the years and the prediction was found to be good.

  5. Nutrient Balance in Relation to High Yield and Good Quality of Potato on an Acid Purple Soil in Chongqing,China

    Institute of Scientific and Technical Information of China (English)

    HETIANXIU; HEFUJIAN; 等

    2001-01-01

    A field experiment was carried out to study nutrient balance among N,P,K and Mg in potato cultivation on an acid purple soil in Chongqing,China,The experiment included 8 treatments with equal P rate of 120 kg P2O5 hm-2 :N0K2,N1K2,NK2K2,N3K2,N2K0,N2K1,N2K1Mg and N2K3,where N0,N1,N2 and N3 stand for the N rates of 0,75,150 and 225 kg N hm-2 ,and K0,K1,K2 and K3 for the K rates of 0,165,330 and 495kg K2O hm-2,respectively,Among the treatments designed ,Treatment N2K2 with a nutrient suply ration of N:P2O5:K2O:MgO=1.25:1.275:0.28 gave the highest tuber yield nd dry matter ,highest starch and Zn and lowest NO3- contents in tuber,and high N,P and K use effciency with and uptake ratio of N:P:K:Mg=11.38:1:13.32:0.33 by tuber,Yield and starch and protein contents of tuber were the lowest in Treatment N0K2.Dry matter was the highest N,P and K utilization rates .Statistical analysis showed that yields of tuber and starch were in a positive linear correlation with the uptake amount of various nutrients and protein of the potato tuber was in a significantly positive linear correlation with tuber N content and in a singificantly negative linear correlation with tuber K and Mg contents .Balaced application of N,P,K and Mg fertilizers(Treatment N2K2)was recommended for realiztion of high yield and good quality in potato cultivation.

  6. Neural network forecasting model based on phase space re-construction in water yield of mine

    Institute of Scientific and Technical Information of China (English)

    LIU Wei-lin; DONG Zeng-chuan; CHEN Nan-xiang; CAO Lian-hai

    2007-01-01

    The neutral network forecasting model based on the phase space reconstruction was proposed. First, through reconstructing the phase space, the time series of single variable was done excursion and expanded into multi- dimension series which included the ergodic information and more rich information could be excavated. Then, on the basis of the embedding dimension of the time series, the structure form of neutral network was constructed, of which the node number in input layer was the embedding dimension of the time series minus 1, and the node number in output layers was 1. Finally, as an example,the model was applied for water yield of mine forecasting. The result shows that the model has good fitting accuracy and forecasting precision.

  7. Goodness-of-fit tests in mixed models

    KAUST Repository

    Claeskens, Gerda

    2009-05-12

    Mixed models, with both random and fixed effects, are most often estimated on the assumption that the random effects are normally distributed. In this paper we propose several formal tests of the hypothesis that the random effects and/or errors are normally distributed. Most of the proposed methods can be extended to generalized linear models where tests for non-normal distributions are of interest. Our tests are nonparametric in the sense that they are designed to detect virtually any alternative to normality. In case of rejection of the null hypothesis, the nonparametric estimation method that is used to construct a test provides an estimator of the alternative distribution. © 2009 Sociedad de Estadística e Investigación Operativa.

  8. DEVELOPMENT OF A NOVEL EMPIRICAL MODEL TO ESTIMATE THE KRAFT PULP YIELD OF FAST-GROWING EUCALYPTUS

    Directory of Open Access Journals (Sweden)

    Jing Liu,

    2012-01-01

    Full Text Available In this study, several kraft pulps were produced by kraft pulping of fast-growing Eucalyptus with a wide range of cooking conditions. The dependences between pulp yields and some pulp properties, namely, kappa number, HexA contents, and cellulose viscosities, were well investigated. It was found that kraft pulp yields linearly decreased with the reduction of HexA-free kappa number in two different stages, respectively, in which a transition point of measured pulp yield of 48.7% was observed. A similar relationship between pulp yield and HexA was also found, in which the resulting transition point of HexA content was 67 μmol/g. Moreover, the logarithm of pulp viscosity was linearly proportional to the reduction of lignin-free pulp yields. Then, a novel empirical model was successfully developed based on these findings. The parameters in this empirical model were calculated by least-squares estimation using the experimental data from active alkali values of 13.2, 14.7 and 17.8. Another data set was used to verify the effectiveness of this model in predicting the pulp yields. Finally, a good agreement (a linear regression coefficient of 90.59% between experimental and fitting data was obtained, which indicated that the kraft pulp yield of fast-growing Eucalyptus could be accurately predicted by this novel empirical model.

  9. Dynamics in a nonlinear Keynesian good market model

    Energy Technology Data Exchange (ETDEWEB)

    Naimzada, Ahmad, E-mail: ahmad.naimzada@unimib.it [Department of Economics, Quantitative Methods and Management, University of Milano-Bicocca, U7 Building, Via Bicocca degli Arcimboldi 8, 20126 Milano (Italy); Pireddu, Marina, E-mail: marina.pireddu@unimib.it [Department of Mathematics and Applications, University of Milano-Bicocca, U5 Building, Via Cozzi 55, 20125 Milano (Italy)

    2014-03-15

    In this paper, we show how a rich variety of dynamical behaviors can emerge in the standard Keynesian income-expenditure model when a nonlinearity is introduced, both in the cases with and without endogenous government spending. A specific sigmoidal functional form is used for the adjustment mechanism of income with respect to the excess demand, in order to bound the income variation. With the aid of analytical and numerical tools, we investigate the stability conditions, bifurcations, as well as periodic and chaotic dynamics. Globally, we study multistability phenomena, i.e., the coexistence of different kinds of attractors.

  10. Forecasting Moroccan Wheat Yields using Two Statistical Models

    Science.gov (United States)

    Wechsung, F.; Childers, K.; Frieler, K.; Hoffmann, P.

    2015-12-01

    The economy of Morocco is highly dependent on fluctuations in wheat yield. Since very little of the Moroccan wheat harvest is irrigated, this leaves the annual wheat yield dependent on precipitation fluctuations and large scale weather patterns over the north Atlantic. Here we suggest two predictors of the annual change in Moroccan wheat yield based on these relationships. The first, pre-planting indicator relies on the sea surface temperature (SST) anomalies of the north Atlantic in September through November and are reinforced by a mid-season predictor based on the weighted precipitation from October through February. Partial least squares regression is used to determine the three most relevant patterns of Atlantic SST which offer an early indication of the upcoming wheat yield. The prediction is greatly enhanced by the inclusion of the cumulative monthly precipitation weighted by the wheat cultivation areas, from October through the wheat harvest. It is not surprising that the total precipitation in Morocco influences the annual wheat yield, however it is remarkable the degree to which early season precipitation sums are able to forecast the national wheat yield. Higher resolution precipitation reanalysis products from AgMERRA and NOAA have coefficients of determination greater than 0.5 by February (r2=0.78 and 0.57, respectively). The more frequently updated NOAA 0.5° resolution precipitation product has a slightly lower but still significant correlation (r2=0.48).

  11. Modelling the impact of forest loss on shallow landslide sediment yield, Ijuez river catchment, Spanish Pyrenees

    Directory of Open Access Journals (Sweden)

    2007-01-01

    Full Text Available The SHETRAN model for simulating the sediment yield arising from shallow landslides at the scale of a river catchment was applied to the 45-km2 Ijuez catchment in the central Spanish Pyrenees, to investigate the effect of loss of forest cover on landslide and debris flow incidence and on catchment sediment yield. The application demonstrated how such a model, with a large number of parameters to be evaluated, can be used even when directly measured data are not available: rainfall and discharge time series were generated by reference to other local records and data providing the basis for a soil map were obtained by a short field campaign. Uncertainty bounds for the outputs were determined as a function of the uncertainty in the values of key model parameters. For a four-year period and for the existing forested state of the catchment, a good ability to simulate the observed long term spatial distribution of debris flows (represented by a 45-year inventory and to determine catchment sediment yield within the range of regional observations was demonstrated. The lower uncertainty bound on simulated landslide occurrence approximated the observed annual rate of landsliding and suggests that landslides provide a relatively minor proportion of the total sediment yield, at least in drier years. A scenario simulation in which the forest cover was replaced by grassland indicated an increase in landsliding but a decrease in the number of landslides which evolve into debris flows and, at least for drier years, a reduction in sediment delivery to the channel network.

  12. The importance of information goods abstraction levels for information commerce process models

    NARCIS (Netherlands)

    Wijnhoven, Fons

    2002-01-01

    A process model, in the context of e-commerce, is an organized set of activities for the creation, (re-)production, trade and delivery of goods. Electronic commerce studies have created important process models for the trade of physical goods via Internet. These models are not easily suitable for th

  13. Goodness of fit to a mathematical model for Drosophila sleep behavior is reduced in hyposomnolent mutants

    Directory of Open Access Journals (Sweden)

    Joshua M. Diamond

    2016-01-01

    Full Text Available The conserved nature of sleep in Drosophila has allowed the fruit fly to emerge in the last decade as a powerful model organism in which to study sleep. Recent sleep studies in Drosophila have focused on the discovery and characterization of hyposomnolent mutants. One common feature of these animals is a change in sleep architecture: sleep bout count tends to be greater, and sleep bout length lower, in hyposomnolent mutants. I propose a mathematical model, produced by least-squares nonlinear regression to fit the form Y = aX∧b, which can explain sleep behavior in the healthy animal as well as previously-reported changes in total sleep and sleep architecture in hyposomnolent mutants. This model, fit to sleep data, yields coefficient of determination R squared, which describes goodness of fit. R squared is lower, as compared to control, in hyposomnolent mutants insomniac and fumin. My findings raise the possibility that low R squared is a feature of all hyposomnolent mutants, not just insomniac and fumin. If this were the case, R squared could emerge as a novel means by which sleep researchers might assess sleep dysfunction.

  14. Good modelling practice in applying computational fluid dynamics for WWTP modelling.

    Science.gov (United States)

    Wicklein, Edward; Batstone, Damien J; Ducoste, Joel; Laurent, Julien; Griborio, Alonso; Wicks, Jim; Saunders, Stephen; Samstag, Randal; Potier, Olivier; Nopens, Ingmar

    2016-01-01

    Computational fluid dynamics (CFD) modelling in the wastewater treatment (WWT) field is continuing to grow and be used to solve increasingly complex problems. However, the future of CFD models and their value to the wastewater field are a function of their proper application and knowledge of their limits. As has been established for other types of wastewater modelling (i.e. biokinetic models), it is timely to define a good modelling practice (GMP) for wastewater CFD applications. An International Water Association (IWA) working group has been formed to investigate a variety of issues and challenges related to CFD modelling in water and WWT. This paper summarizes the recommendations for GMP of the IWA working group on CFD. The paper provides an overview of GMP and, though it is written for the wastewater application, is based on general CFD procedures. A forthcoming companion paper to provide specific details on modelling of individual wastewater components forms the next step of the working group.

  15. In situ cryopreservation of human embryonic stem cells in gas-permeable membrane culture cassettes for high post-thaw yield and good manufacturing practice.

    Science.gov (United States)

    Amps, K J; Jones, M; Baker, D; Moore, H D

    2010-06-01

    The development of efficient and robust methods for the cryopreservation of human embryonic stem cells (hESCs) is important for the production of master and working cell banks for future clinical applications. Such methods must meet requirements of good manufacturing practice (GMP) and maintain genetic stability of the cell line. We investigated the culture of four Shef hESC lines in gas permeable 'culture cassettes' which met GMP compliance. hESCs adhered rapidly to the membrane and colonies displayed good proliferation and expansion. After 5-7 days of culture, hESCs were cryopreserved in situ using 10% dimethyl sulphoxide in foetal calf serum at approximately 1 degrees C/min. This method was compared with a control of standard flask culture and cryopreservation in vials. Post-thaw cassette culture displayed relative proliferation ratios (fold increase above flask/cryovial culture) of 114 (Shef 4), 8.2 (Shef 5), 195 (shef 6) and 17.5 (Shef 7). The proportion of cells expressing pluripotency markers after cryopreservation was consistently greater in cassette culture than for the control with the markers SSEA3 and SSEA4 exhibiting a significant increase (P> or =0.05). The efficiency of cell line culture in cassette was associated with the overall passage number of the cell line. The procedure enables cryopreservation of relatively large quantities of hESCs in situ, whilst returning high yields of viable, undifferentiated stem cells, thereby increasing capacity to scale up with greater efficacy.

  16. Regional crop modelling in Europe: The impact of climate conditions and farm characteristics on maize yields

    NARCIS (Netherlands)

    Reidsma, P.; Ewert, F.; Boogaard, H.; Diepen, van K.

    2009-01-01

    Impacts of climate variability and climate change on regional crop yields are commonly assessed using process-based crop models. These models, however, simulate potential and water limited yields, which do not always relate to observed yields. The latter are largely influenced by crop management, wh

  17. Parameters of AMMI Model for Yield Stability Analysis in Durum Wheat

    Directory of Open Access Journals (Sweden)

    Naser Sabaghnia

    2013-06-01

    Full Text Available The improvement of new genotypes with acceptable yield stability in different environments is an important issue in breeding programs. In order to study genotype × environment (GE interaction and to determine the most stable durum wheat genotypes, field experiments were conducted with 20 genotypes for three years (2007-2009. Results showed highly significant GE interaction indicating the possibility of selection for the most stable genotypes. The AMMI (additive main effect and multiplicative interaction analysis indicated that the first five axes were significant based on F-test of Gollob while the other tests (FGH1 and FGH2 identified first three axes as significant AMMI model components. Furthermore, according to FRatio test and cross validation results, only first two axes were significant. According to these distinct numbers of significant axes, sixteen AMMI stability parameters plus ASV(AMMI stability value were computed. Our results showed that EV- and D-based parameters, displayed G7 and G8, SIPC-based parameters indicated G3 and G4 and AMGE-based parameters identified G15 as the most stable genotypes. Genotypes G15 and G7 were the highest mean yielding genotypes and so they could be regarded as the most favorable durum wheat genotypes. The results of this investigation proved that the most of AMMI stability parameters are suitable indices for discriminating stable genotypes and AMGE-based parameters can detect highly seed yield genotypes with good stability.

  18. Parameters of AMMI Model for Yield Stability Analysis in Durum Wheat

    Directory of Open Access Journals (Sweden)

    Naser Sabaghnia

    2013-07-01

    Full Text Available The improvement of new genotypes with acceptable yield stability in different environments is an important issue in breeding programs. In order to study genotype × environment (GE interaction and to determine the most stable durum wheat genotypes, field experiments were conducted with 20 genotypes for three years (2007-2009. Results showed highly significant GE interaction indicating the possibility of selection for the most stable genotypes. The AMMI (additive main effect and multiplicative interaction analysis indicated that the first five axes were significant based on F-test of Gollob while the other tests (FGH1 and FGH2 identified first three axes as significant AMMI model components. Furthermore, according to FRatio test and cross validation results, only first two axes were significant. According to these distinct numbers of significant axes, sixteen AMMI stability parameters plus ASV (AMMI stability value were computed. Our results showed that EV- and D-based parameters, displayed G7 and G8, SIPC-based parameters indicated G3 and G4 and AMGE-based parameters identified G15 as the most stable genotypes. Genotypes G15 and G7 were the highest mean yielding genotypes and so they could be regarded as the most favorable durum wheat genotypes. The results of this investigation proved that the most of AMMI stability parameters are suitable indices for discriminating stable genotypes and AMGE-based parameters can detect highly seed yield genotypes with good stability.

  19. Development of a remote sensing-based rice yield forecasting model

    Energy Technology Data Exchange (ETDEWEB)

    Mosleh, M.K.; Hassan, Q.K.; Chowdhury, E.H.

    2016-11-01

    This study aimed to develop a remote sensing-based method for forecasting rice yield by considering vegetation greenness conditions during initial and peak greenness stages of the crop; and implemented for “boro” rice in Bangladeshi context. In this research, we used Moderate Resolution Imaging Spectroradiometer (MODIS)-derived two 16-day composite of normalized difference vegetation index (NDVI) images at 250 m spatial resolution acquired during the initial (January 1 to January 16) and peak greenness (March 23/24 to April 6/7 depending on leap year) stages in conjunction with secondary datasets (i.e., boro suitability map, and ground-based information) during 2007-2012 period. The method consisted of two components: (i) developing a model for delineating area under rice cultivation before harvesting; and (ii) forecasting rice yield as a function of NDVI. Our results demonstrated strong agreements between the model (i.e., MODIS-based) and ground-based area estimates during 2010-2012 period, i.e., coefficient of determination (R2); root mean square error (RMSE); and relative error (RE) in between 0.93 to 0.95; 30,519 to 37,451 ha; and ±10% respectively at the 23 district-levels. We also found good agreements between forecasted (i.e., MODIS-based) and ground-based yields during 2010-2012 period (R2 between 0.76 and 0.86; RMSE between 0.21 and 0.29 Mton/ha, and RE between -5.45% and 6.65%) at the 23 district-levels. We believe that our developments of forecasting the boro rice yield would be useful for the decision makers in addressing food security in Bangladesh. (Author)

  20. Gastric yield pressure and gastric yield volume to assess anti-reflux barrier in a porcine model.

    Science.gov (United States)

    Duarte, Marcos E S; Freitag, Carmen P F; Fornari, Fernando; Kruel, Cleber R P; Sanches, Paulo R S; Thomé, Paulo R O; Callegari-Jacques, Sidia M; Möllerke, Roseli O; Vicente, Yvone A M V A; Goldani, Helena A S; Barros, Sérgio G S

    2013-04-01

    Anti-reflux barrier (ARB) resistance may be useful to test new treatments for gastroesophageal reflux (GER). The ARB has been estimated by increasing gastric yield pressure (GYP) and gastric yield volume (GYV) in animal models but has not been validated. This study aimed to develop an experimental model suitable for assessing the ARB resistance to increasing intragastric pressure and volume and its reproducibility in a seven-day interval. Ten two-month-old female Large-White swine were studied. Intragastric pressure and volume were recorded using a digital system connected to a Foley catheter inserted through gastrostomy into the stomach. GYP and GYV were defined as the gastric pressure and volume able to yield gastric contents into the esophagus detected by esophageal pH. A sudden pH drop below 3 sustained during 5 min was considered diagnostic for gastric yield. Animals were studied again after seven days. On days 0 and 7, there were no significant differences for GYP (mean ± SD = 7.66 ± 3.02 mmHg vs. 7.07 ± 3.54 mmHg, p = .686) and GYV (636.70 ± 216.74 ml vs. 608.30 ± 276.66 ml; p = .299), respectively. Concordance correlation coefficient (ρc) was significant for GYP (ρc = 0.634, 95% CI = 0.141-0.829, p = .006), but not for GYV (ρc = 0.291, 95% CI = -0.118 to 0.774, p = .196). This study demonstrated an experimental model, assessing the ARB resistance. GYP seems to be a more reliable parameter than GYV for assessment of ARB resistance.

  1. Complex oscillatory yielding of model hard-sphere glasses.

    Science.gov (United States)

    Koumakis, N; Brady, J F; Petekidis, G

    2013-04-26

    The yielding behavior of hard sphere glasses under large-amplitude oscillatory shear has been studied by probing the interplay of Brownian motion and shear-induced diffusion at varying oscillation frequencies. Stress, structure and dynamics are followed by experimental rheology and Browian dynamics simulations. Brownian-motion-assisted cage escape dominates at low frequencies while escape through shear-induced collisions at high ones, both related with a yielding peak in G''. At intermediate frequencies a novel, for hard sphere glasses, double peak in G'' is revealed reflecting both mechanisms. At high frequencies and strain amplitudes a persistent structural anisotropy causes a stress drop within the cycle after strain reversal, while higher stress harmonics are minimized at certain strain amplitudes indicating an apparent harmonic response.

  2. A Unified Model for the Prediction of Yield Strength in Particulate-Reinforced Metal Matrix Nanocomposites

    Directory of Open Access Journals (Sweden)

    F. A. Mirza

    2015-08-01

    Full Text Available Lightweighting in the transportation industry is today recognized as one of the most important strategies to improve fuel efficiency and reduce anthropogenic climate-changing, environment-damaging, and human death-causing emissions. However, the structural applications of lightweight alloys are often limited by some inherent deficiencies such as low stiffness, high wear rate and inferior strength. These properties could be effectively enhanced by the addition of stronger and stiffer reinforcements, especially nano-sized particles, into metal matrix to form composites. In most cases three common strengthening mechanisms (load-bearing effect, mismatch of coefficients of thermal expansion, and Orowan strengthening have been considered to predict the yield strength of metal matrix nanocomposites (MMNCs. This study was aimed at developing a unified model by taking into account the matrix grain size and porosity (which is unavoidable in the materials processing such as casting and powder metallurgy in the prediction of the yield strength of MMNCs. The Zener pinning effect of grain boundaries by the nano-sized particles has also been integrated. The model was validated using the experimental data of magnesium- and titanium-based nanocomposites containing different types of nano-sized particles (namely, Al2O3, Y2O3, and carbon nanotubes. The predicted results were observed to be in good agreement with the experimental data reported in the literature.

  3. Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions

    NARCIS (Netherlands)

    Li, T.; Hasegawa, T.; Yin, X.; Zhu, Y.; Boote, K.; Adam, M.; Bregaglio, S.; Buis, S.; Confalonieri, R.; Fumoto, T.; Gaydon, D.; Marcaida III, M.; Nakagawa, H.; Oriol, P.; Ruane, A.C.; Ruget, F.; Singh, B.; Singh, U.; Tang, L.; Yoshida, H.; Zhang, Z.; Bouman, B.

    2015-01-01

    Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluat

  4. Model suitability to assess regional potato yield patterns in northern Ecuador

    NARCIS (Netherlands)

    Soltani Largani, A.; Stoorvogel, J.J.; Veldkamp, A.

    2013-01-01

    A wide range of scenario studies aiming at rural development require regional patterns of crop yield. This study aims to evaluate three different modeling approaches for their suitability to assess regional potato yield patterns. The three model approaches include (1) an empirical model; (2) a proce

  5. Event-Based Modeling of Driver Yielding Behavior to Pedestrians at Two-Lane Roundabout Approaches.

    Science.gov (United States)

    Salamati, Katayoun; Schroeder, Bastian J; Geruschat, Duane R; Rouphail, Nagui M

    2014-01-01

    Unlike other types of controlled intersections, drivers do not always comply with the "yield to pedestrian" sign at the roundabouts. This paper aims to identify the contributing factors affecting the likelihood of driver yielding to pedestrians at two-lane roundabouts. It further models the likelihood of driver yielding based on these factors using logistic regression. The models have been applied to 1150 controlled pedestrian crossings at entry and exit legs of two-lane approaches of six roundabouts across the country. The logistic regression models developed support prior research that the likelihood of driver yielding at the entry leg of roundabouts is higher than at the exit. Drivers tend to yield to pedestrians carrying a white cane more often than to sighted pedestrians. Drivers traveling in the far lane, relative to pedestrian location, have a lower probability of yielding to a pedestrian. As the speed increases the probability of driver yielding decreases. At the exit leg of the roundabout, drivers turning right from the adjacent lane have a lower propensity of yielding than drivers coming from other directions. The findings of this paper further suggest that although there has been much debate on pedestrian right-of-way laws and distinction between pedestrian waiting positions (in the street versus at the curb), this factor does not have a significant impact on driver yielding rate. The logistic regression models also quantify the effect of each of these factors on propensity of driver yielding. The models include variables which are specific to each study location and explain the impact size of each study location on probability of yielding. The models generated in this research will be useful to transportation professionals and researchers interested in understanding the factors that impact driver yielding at modern roundabouts. The results of the research can be used to isolate factors that may increase yielding (such as lower roundabout approach speeds

  6. Modelling of the parametric yield in decananometer SRAM-Arrays

    Directory of Open Access Journals (Sweden)

    Th. Fischer

    2006-01-01

    Full Text Available In today's decananometer (90 nm, 65 nm, ..., CMOS technologies variations of device parameters play an ever more important role. Due to the demand for low leakage systems, supply voltage is decreased on one hand and the transistor threshold voltage is increased on the other hand. This reduces the overdrive voltage of the transistors and leads to decreasing read and write security margins in static memories (SRAM. In addition, smaller dimensions of the devices lead to increasing variations of the device parameters, thus mismatch effects increase. It can be shown that local variations of the transistor parameters limit the functionality of circuits stronger than variations on a global scale or hard defects. We show a method to predict the yield for a large number of SRAM devices without time consuming Monte Carlo simulations in dependence of various parameters (Vdd, temperature, technology options, transistor dimensions, .... This helps the designer to predict the yield for various system options and transistor dimensions, to choose the optimal solution for a specific product.

  7. Yield gap analysis of cumin in nine regions of Khorasan provinces using modelling approach

    Directory of Open Access Journals (Sweden)

    behnam kamkar

    2009-06-01

    Full Text Available There are three hierarchical steps to fill the yield gaps in agricultural systems. These steps are determination of potential yield, yield gaps and system optimization to fill yield gaps. In this study a simple mechanistic model was developed and tested to determine potential yield and yield gaps of Cumin (Cuminum cyminum in nine regions of Khorasan provinces (including Bojnourd, Qaeen, Mashhad, Neishabour, Sabzewar, Gonabad, Ferdous, Kashmar and Birjand. Collected data of related year from 228 fields were used to calculate yield gaps. Results indicated variable potential yields in different climatic conditions (the areas with cooler climate and higher radiation had higher potential yields. Also, yield gaps varied considerably between regions (from 2.42 ton.ha-1 in Bojnourd to 0.68 ton.ha-1 in Sabzewar. The highest value for potential yield belonged to Bojnourd (3.7 ton.ha-1. The collected data from studied fields and sensitivity analysis on sowing date (based on common sowing dates range showed that inappropriate sowing dates was one of the most important yield reducing factors in all regions. Results revealed that if the yield gaps can be filled based on appropriate management option, yield can be increased by two to three folds in some regions.

  8. Simulation of nitrous oxide effluxes, crop yields and soil physical properties using the LandscapeDNDC model in managed ecosystem

    Science.gov (United States)

    Nyckowiak, Jedrzej; Lesny, Jacek; Haas, Edwin; Juszczak, Radoslaw; Kiese, Ralf; Butterbach-Bahl, Klaus; Olejnik, Janusz

    2014-05-01

    Modeling of nitrous oxide emissions from soil is very complex. Many different biological and chemical processes take place in soils which determine the amount of emitted nitrous oxide. Additionaly, biogeochemical models contain many detailed factors which may determine fluxes and other simulated variables. We used the LandscapeDNDC model in order to simulate N2O emissions, crop yields and soil physical properties from mineral cultivated soils in Poland. Nitrous oxide emissions from soils were modeled for fields with winter wheat, winter rye, spring barley, triticale, potatoes and alfalfa crops. Simulations were carried out for the plots of the Brody arable experimental station of Poznan University of Life Science in western Poland and covered the period 2003 - 2012. The model accuracy and its efficiency was determined by comparing simulations result with measurements of nitrous oxide emissions (measured with static chambers) from about 40 field campaigns. N2O emissions are strongly dependent on temperature and soil water content, hence we compared also simulated soil temperature at 10cm depth and soil water content at the same depth with the daily measured values of these driving variables. We compared also simulated yield quantities for each individual experimental plots with yield quantities which were measured in the period 2003-2012. We conclude that the LandscapeDNDC model is capable to simulate soil N2O emissions, crop yields and physical properties of soil with satisfactorily good accuracy and efficiency.

  9. Uncertainties in Predicting Rice Yield by Current Crop Models Under a Wide Range of Climatic Conditions

    Science.gov (United States)

    Li, Tao; Hasegawa, Toshihiro; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Adam, Myriam; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fumoto, Tamon; Gaydon, Donald; Marcaida, Manuel, III; Nakagawa, Hiroshi; Oriol, Philippe; Ruane, Alex C.; Ruget, Francoise; Singh, Balwinder; Singh, Upendra; Tang, Liang; Tao, Fulu; Wilkens, Paul; Yoshida, Hiroe; Zhang, Zhao; Bouman, Bas

    2014-01-01

    Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10 percent of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperature.

  10. Comparison of statistical models to estimate daily milk yield in single milking testing schemes

    Directory of Open Access Journals (Sweden)

    Marija Klopcˇic

    2010-01-01

    Full Text Available Different statistical models were compared to estimate daily milk yield from morning or evening milking test results. The experiment was conducted on 14 family farms with 325 recorded cows. The amount of explained variance was higher for models including the effects of partial milk yield, the interval between successive milking, the interaction between partial milk yield and the milking interval and the farm (R2 = 0.976 for AM, R2 = 0.956 for PM than for models including partial milk yield effect only (R2 = 0.957 for AM, R2 = 0.937 for PM. Estimates of daily milk yield from linear models were more accurate than those obtained by doubling single milking weights. The results show that more complex model gives the best fit to the data. Differences between models according to determination and correlation coefficient were minor. Further investigations on larger sets of data are needed to draw more general conclusion.

  11. The empirical likelihood goodness-of-fit test for regression model

    Institute of Scientific and Technical Information of China (English)

    Li-xing ZHU; Yong-song QIN; Wang-li XU

    2007-01-01

    Goodness-of-fit test for regression modes has received much attention in literature. In this paper, empirical likelihood (EL) goodness-of-fit tests for regression models including classical parametric and autoregressive (AR) time series models are proposed. Unlike the existing locally smoothing and globally smoothing methodologies, the new method has the advantage that the tests are self-scale invariant and that the asymptotic null distribution is chi-squared. Simulations are carried out to illustrate the methodology.

  12. Can the agricultural AquaCrop model simulate water use and yield of a poplar short-rotation coppice?

    Science.gov (United States)

    Horemans, Joanna A; Van Gaelen, Hanne; Raes, Dirk; Zenone, Terenzio; Ceulemans, Reinhart

    2017-06-01

    We calibrated and evaluated the agricultural model AquaCrop for the simulation of water use and yield of a short-rotation coppice (SRC) plantation with poplar (Populus) in East Flanders (Belgium) during the second and the third rotation (first 2 years only). Differences in crop development and growth during the course of the rotations were taken into account during the model calibration. Overall, the AquaCrop model showed good performance for the daily simulation of soil water content (R(2) of 0.57-0.85), of green canopy cover (R(2) > 0.87), of evapotranspiration (ET; R(2) > 0.76), and of potential yield. The simulated, total yearly water use of the SRC ranged between 55% and 85% of the water use of a reference grass ecosystem calculated under the same environmental conditions. Crop transpiration was between 67% and 93% of total ET, with lower percentages in the first than in the second year of each rotation. The observed (dry mass) yield ranged from 6.61 to 14.76 Mg ha(-1) yr(-1). A yield gap of around 30% was observed between the second and the third rotation, as well as between simulated and observed yield during the third rotation. This could possibly be explained by the expansion of the understory (weed) layer; the relative cover of understory weeds was 22% in the third year of the third rotation. The agricultural AquaCrop model simulated total water use and potential yield of the operational SRC in a reliable way. As the plantation was extensively managed, potential effects of irrigation and/or fertilization on ET and on yield were not considered in this study.

  13. Modeling of secondary organic aerosol yields from laboratory chamber data

    Directory of Open Access Journals (Sweden)

    M. N. Chan

    2009-04-01

    Full Text Available A product-specific model for secondary organic aerosol (SOA formation and composition based on equilibrium gas-particle partitioning is evaluated. The model is applied to represent laboratory data on the ozonolysis of α-pinene under dry, dark, and low-NOx conditions in the presence of ammonium sulfate seed aerosol. Using five major identified products, the model is fit to the chamber data. From the optimal fitting, SOA oxygen-to-carbon (O/C and hydrogen-to-carbon (H/C ratios are modeled. The discrepancy between measured H/C ratios and those based on the oxidation products used in the model fitting suggests the potential importance of particle-phase reactions. Data fitting is also carried out using the volatility basis set, wherein oxidation products are parsed into volatility bins. The product-specific model is best used for an SOA precursor for which a substantial fraction of the aerosol-phase oxidation products has been identified.

  14. Yield stress, volume change, and shear strength behaviour of unsaturated soils: validation of the SFG model

    National Research Council Canada - National Science Library

    Zhou, Annan; Sheng, Daichao

    2009-01-01

    The model recently presented by Sheng, Fredlund, and Gens, known as the SFG model, provides a consistent explanation of yield stress, shear strength, and volume change behaviour of unsaturated soils...

  15. Event-Based Modeling of Driver Yielding Behavior at Unsignalized Crosswalks.

    Science.gov (United States)

    Schroeder, Bastian J; Rouphail, Nagui M

    2011-07-01

    This research explores factors associated with driver yielding behavior at unsignalized pedestrian crossings and develops predictive models for yielding using logistic regression. It considers the effect of variables describing driver attributes, pedestrian characteristics and concurrent conditions at the crosswalk on the yield response. Special consideration is given to 'vehicle dynamics constraints' that form a threshold for the potential to yield. Similarities are identified to driver reaction in response to the 'amber' indication at a signalized intersection. The logit models were developed from data collected at two unsignalized mid-block crosswalks in North Carolina. The data include 'before' and 'after' observations of two pedestrian safety treatments, an in-street pedestrian crossing sign and pedestrian-actuated in-roadway warning lights.The analysis suggests that drivers are more likely to yield to assertive pedestrians who walk briskly in their approach to the crosswalk. In turn, the yield probability is reduced with higher speeds, deceleration rates and if vehicles are traveling in platoons. The treatment effects proved to be significant and increased the propensity of drivers to yield, but their effectiveness may be dependent on whether the pedestrian activates the treatment.The results of this research provide new insights on the complex interaction of pedestrians and vehicles at unsignalized intersections and have implications for future work towards predictive models for driver yielding behavior. The developed logit models can provide the basis for representing driver yielding behavior in a microsimulation modeling environment.

  16. RRM: An incentive reputation model for promoting good behaviors in distributed systems

    Institute of Scientific and Technical Information of China (English)

    ZHANG Hong; DUAN HaiXin; LIU Wu

    2008-01-01

    Reputation systems represent soft security mechanisms that complement tradi tional information security mechanisms. They are now widely used in online e-commerce markets and communities in order to stimulate good behaviors as well as to restrainadverse behaviors. This paper analyzes the limitations of the conversational reputation models and proposes an incentive reputation model called the resilient reputation model (RRM) for the distributed reputation systems. The objective of this reputation model is not only to encourage the users to provide good services and, therefore, to maximize the probability of good transaction outcomes, but also to punish those adverse users who are trying to manipulate the application systems. The simulation results indicate that the proposed reputation model (RRM) could effectively resist against the common adverse behaviors, while protecting the profits of sincere users from being blemished by those adversaries.

  17. A GUIDED SWAT MODEL APPLICATION ON SEDIMENT YIELD MODELING IN PANGANI RIVER BASIN: LESSONS LEARNT

    Directory of Open Access Journals (Sweden)

    Preksedis Marco Ndomba

    2008-12-01

    Full Text Available The overall objective of this paper is to report on the lessons learnt from applying Soil and Water Assessment Tool (SWAT in a well guided sediment yield modelling study. The study area is the upstream of Pangani River Basin (PRB, the Nyumba Ya Mungu (NYM reservoir catchment, located in the North Eastern part of Tanzania. It should be noted that, previous modeling exercises in the region applied SWAT with preassumption that inter-rill or sheet erosion was the dominant erosion type. In contrast, in this study SWAT model application was guided by results of analysis of high temporal resolution of sediment flow data and hydro-meteorological data. The runoff component of the SWAT model was calibrated from six-years (i.e. 1977–1982 of historical daily streamflow data. The sediment component of the model was calibrated using one-year (1977–1988 daily sediment loads estimated from one hydrological year sampling programme (between March and November, 2005 rating curve. A long-term period over 37 years (i.e. 1969–2005 simulation results of the SWAT model was validated to downstream NYM reservoir sediment accumulation information. The SWAT model captured 56 percent of the variance (CE and underestimated the observed daily sediment loads by 0.9 percent according to Total Mass Control (TMC performance indices during a normal wet hydrological year, i.e., between November 1, 1977 and October 31, 1978, as the calibration period. SWAT model predicted satisfactorily the long-term sediment catchment yield with a relative error of 2.6 percent. Also, the model has identified erosion sources spatially and has replicated some erosion processes as determined in other studies and field observations in the PRB. This result suggests that for catchments where sheet erosion is dominant SWAT model may substitute the sediment-rating curve. However, the SWAT model could not capture the dynamics of sediment load delivery in some seasons to the catchment outlet.

  18. A GUIDED SWAT MODEL APPLICATION ON SEDIMENT YIELD MODELING IN PANGANI RIVER BASIN: LESSONS LEARNT

    Directory of Open Access Journals (Sweden)

    Preksedis M. Ndomba

    2008-01-01

    Full Text Available The overall objective of this paper is to report on the lessons learnt from applying Soil and Water Assessment Tool (SWAT in a well guided sediment yield modelling study. The study area is the upstream of Pangani River Basin (PRB, the Nyumba Ya Mungu (NYM reservoir catchment, located in the North Eastern part of Tanzania. It should be noted that, previous modeling exercises in the region applied SWAT with preassumption that inter-rill or sheet erosion was the dominant erosion type. In contrast, in this study SWAT model application was guided by results of analysis of high temporal resolution of sediment flow data and hydro-meteorological data. The runoff component of the SWAT model was calibrated from six-years (i.e. 1977¿1982 of historical daily streamflow data. The sediment component of the model was calibrated using one-year (1977-1988 daily sediment loads estimated from one hydrological year sampling programme (between March and November, 2005 rating curve. A long-term period over 37 years (i.e. 1969-2005 simulation results of the SWAT model was validated to downstream NYM reservoir sediment accumulation information. The SWAT model captured 56 percent of the variance (CE and underestimated the observed daily sediment loads by 0.9 percent according to Total Mass Control (TMC performance indices during a normal wet hydrological year, i.e., between November 1, 1977 and October 31, 1978, as the calibration period. SWAT model predicted satisfactorily the long-term sediment catchment yield with a relative error of 2.6 percent. Also, the model has identified erosion sources spatially and has replicated some erosion processes as determined in other studies and field observations in the PRB. This result suggests that for catchments where sheet erosion is dominant SWAT model may substitute the sediment-rating curve. However, the SWAT model could not capture the dynamics of sediment load delivery in some seasons to the catchment outlet.

  19. Fission yield calculation using toy model based on Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Jubaidah, E-mail: jubaidah@student.itb.ac.id [Nuclear Physics and Biophysics Division, Department of Physics, Bandung Institute of Technology. Jl. Ganesa No. 10 Bandung – West Java, Indonesia 40132 (Indonesia); Physics Department, Faculty of Mathematics and Natural Science – State University of Medan. Jl. Willem Iskandar Pasar V Medan Estate – North Sumatera, Indonesia 20221 (Indonesia); Kurniadi, Rizal, E-mail: rijalk@fi.itb.ac.id [Nuclear Physics and Biophysics Division, Department of Physics, Bandung Institute of Technology. Jl. Ganesa No. 10 Bandung – West Java, Indonesia 40132 (Indonesia)

    2015-09-30

    Toy model is a new approximation in predicting fission yield distribution. Toy model assumes nucleus as an elastic toy consist of marbles. The number of marbles represents the number of nucleons, A. This toy nucleus is able to imitate the real nucleus properties. In this research, the toy nucleons are only influenced by central force. A heavy toy nucleus induced by a toy nucleon will be split into two fragments. These two fission fragments are called fission yield. In this research, energy entanglement is neglected. Fission process in toy model is illustrated by two Gaussian curves intersecting each other. There are five Gaussian parameters used in this research. They are scission point of the two curves (R{sub c}), mean of left curve (μ{sub L}) and mean of right curve (μ{sub R}), deviation of left curve (σ{sub L}) and deviation of right curve (σ{sub R}). The fission yields distribution is analyses based on Monte Carlo simulation. The result shows that variation in σ or µ can significanly move the average frequency of asymmetry fission yields. This also varies the range of fission yields distribution probability. In addition, variation in iteration coefficient only change the frequency of fission yields. Monte Carlo simulation for fission yield calculation using toy model successfully indicates the same tendency with experiment results, where average of light fission yield is in the range of 90yield is in about 135

  20. Correlation Models for Light Olefin Yields from Catalytic Pyrolysis of Petroleum Residue

    Institute of Scientific and Technical Information of China (English)

    DongXiaoli; MengXianghai; GaoJinsen; XuChunming

    2005-01-01

    Correlation models for light olefin yields from residue catalytic pyrolysis are studied. Experiments are carried out in a confined fluidized bed reactor for Daqing (China) atmospheric residue catalytic pyrolysis over LCM-5 pyrolyzing catalyst. The influences of reaction temperature, residence time and the weight ratios of catalyst-to-oil and steam-to-oil on light olefin yields are researched. Correlation models for light olefin yields are established, and the model parameters obtained, with the least square method. Results for error analysis and the F-statistical test show that the correlation models have high calculation precision.

  1. Unifying distance-based goodness-of-fit indicators for hydrologic model assessment

    Science.gov (United States)

    Cheng, Qinbo; Reinhardt-Imjela, Christian; Chen, Xi; Schulte, Achim

    2014-05-01

    The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on

  2. Model for improving safety in transporting dangerous goods for the Serbian Army

    Directory of Open Access Journals (Sweden)

    Dragan S. Kostadinović

    2012-07-01

    Full Text Available Design and improvement of the safety of transport of dangerous goods is a multidimensional and dynamic process which can be implemented using several different methods and techniques. In defining the model of improving the safety of transport of dangerous goods for the purposes of the Serbian Army, the Deming's approach to quality management system has been used. The analysis of the existing organization of transport of dangerous goods in the Army of Serbia has established the basic causes that affect the reduction in security as well as specific measures to be taken to improve the safety of transport of dangerous goods in the Serbian Army. The benchmark concept, widely used in the world, especially among organizations dealing with the same kind of logistic services, has been applied to indentify measures to improve the safety of transport of dangerous goods in the Serbian Army.

  3. Optimizing hurricane disaster relief goods distribution: model development and application with respect to planning strategies.

    Science.gov (United States)

    Horner, Mark W; Downs, Joni A

    2010-07-01

    Over the last few years, hurricane emergencies have been among the most pervasive major disruptions in the United States, particularly in the south-east region of the country. A key aspect of managing hurricane disasters involves logistical planning to facilitate the distribution and transportation of relief goods to populations in need. This study shows how a variant of the capacitated warehouse location model can be used to manage the flow of goods shipments to people in need. In this application, the model is used with protocols set forth in Florida's Comprehensive Emergency Plan and tested in a smaller city in north Florida. Scenarios explore the effects of alternate goods distribution strategies on the provision of disaster relief. Results show that measures describing people's accessibility to relief goods are affected by the distribution infrastructure used to provide relief, as well as assumptions made regarding the population(s) assumed to be in need of aid.

  4. Generalized elastic model yields a fractional Langevin equation description.

    Science.gov (United States)

    Taloni, Alessandro; Chechkin, Aleksei; Klafter, Joseph

    2010-04-23

    Starting from a generalized elastic model which accounts for the stochastic motion of several physical systems such as membranes, (semi)flexible polymers, and fluctuating interfaces among others, we derive the fractional Langevin equation (FLE) for a probe particle in such systems, in the case of thermal initial conditions. We show that this FLE is the only one fulfilling the fluctuation-dissipation relation within a new family of fractional Brownian motion equations. The FLE for the time-dependent fluctuations of the donor-acceptor distance in a protein is shown to be recovered. When the system starts from nonthermal conditions, the corresponding FLE, which does not fulfill the fluctuation-dissipation relation, is derived.

  5. Modelling the Relationship Between Summer Maize NPK Uptake and Yield on the Basis of Soil Fertility Indices

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Quantitative estimation of fertilizer requirements can help to increase maize (Zea mays L.) yields and improve the fertilizer use efficiency. The model for the Quantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) was calibrated for maize by use of soil fertility data and fertilizer trials at different sites of the Huang Huai Hal river plain in China. The QUEFTS model accounts for interactions between nitrogen (N), phosphorus (P) and potassium (K). It describes the effects of soil characteristics on maize yields in four steps: (1) assessment of the potential supply of N, P and K based on soil chemical data; (2) calculation of the actual uptake of N, P and K, in function of the potential supply as determined in step 1; (3) draft the yield ranges as a function of the actual uptake of N, P and K as determined in step 2; (4) calculation of the maize yield based on the three yield ranges established in step 3. Data of field experiments with different fertilization treatments of various regions in China during the years of 1985 to 1995 were used to calibrate the QUEFTS model for summer maize. In step 1 the N, P and K recovered from their amount applied were described by new equa tions. The minimum and maximum accumulated N, P and K (kg grain kg-1) in summer maize were determined as (21-64), (126-384) and (20-90), respectively. The simulated yields were in good agreement with the observed ones. It was concluded that the calibrated and adjusted QUEFTS model could be useful to improve fertilizer recommendations for maize in the Huang Huai Hai plain of China.

  6. Sensing Story Elements and Structure in Good Literature, the Models for Children's Writing.

    Science.gov (United States)

    Vilscek, Elaine

    1990-01-01

    Discusses how teachers can build upon childrens' natural sense of story, identify good books to serve as models of story elements and structure, and highlight the worth of an author's or illustrator's techniques of story craft as models for improved student writing. (SR)

  7. Computing arbitrage-free yields in multi-factor Gaussian shadow-rate term structure models

    OpenAIRE

    Marcel A. Priebsch

    2013-01-01

    This paper develops a method to approximate arbitrage-free bond yields within a term structure model in which the short rate follows a Gaussian process censored at zero (a "shadow-rate model" as proposed by Black, 1995). The censoring ensures that model-implied yields are constrained to be positive, but it also introduces non-linearity that renders standard bond pricing formulas inapplicable. In particular, yields are not linear functions of the underlying state vector as they are in affine t...

  8. Dependence of simulated positron emitter yields in ion beam cancer therapy on modeling nuclear fragmentation

    DEFF Research Database (Denmark)

    Lühr, Armin; Priegnitz, Marlen; Fiedler, Fine;

    2014-01-01

    In ion beam cancer therapy, range verification in patients using positron emission tomography (PET) requires the comparison of measured with simulated positron emitter yields. We found that (1) changes in modeling nuclear interactions strongly affected the positron emitter yields and that (2) Monte...

  9. Local and omnibus goodness-of-fit tests in classical measurement error models

    KAUST Repository

    Ma, Yanyuan

    2010-09-14

    We consider functional measurement error models, i.e. models where covariates are measured with error and yet no distributional assumptions are made about the mismeasured variable. We propose and study a score-type local test and an orthogonal series-based, omnibus goodness-of-fit test in this context, where no likelihood function is available or calculated-i.e. all the tests are proposed in the semiparametric model framework. We demonstrate that our tests have optimality properties and computational advantages that are similar to those of the classical score tests in the parametric model framework. The test procedures are applicable to several semiparametric extensions of measurement error models, including when the measurement error distribution is estimated non-parametrically as well as for generalized partially linear models. The performance of the local score-type and omnibus goodness-of-fit tests is demonstrated through simulation studies and analysis of a nutrition data set.

  10. Simulation Models of Leaf Area Index and Yield for Cotton Grown with Different Soil Conditioners.

    Directory of Open Access Journals (Sweden)

    Lijun Su

    Full Text Available Simulation models of leaf area index (LAI and yield for cotton can provide a theoretical foundation for predicting future variations in yield. This paper analyses the increase in LAI and the relationships between LAI, dry matter, and yield for cotton under three soil conditioners near Korla, Xinjiang, China. Dynamic changes in cotton LAI were evaluated using modified logistic, Gaussian, modified Gaussian, log normal, and cubic polynomial models. Universal models for simulating the relative leaf area index (RLAI were established in which the application rate of soil conditioner was used to estimate the maximum LAI (LAIm. In addition, the relationships between LAIm and dry matter mass, yield, and the harvest index were investigated, and a simulation model for yield is proposed. A feasibility analysis of the models indicated that the cubic polynomial and Gaussian models were less accurate than the other three models for simulating increases in RLAI. Despite significant differences in LAIs under the type and amount of soil conditioner applied, LAIm could be described by aboveground dry matter using Michaelis-Menten kinetics. Moreover, the simulation model for cotton yield based on LAIm and the harvest index presented in this work provided important theoretical insights for improving water use efficiency in cotton cultivation and for identifying optimal application rates of soil conditioners.

  11. Estimation of Winter Wheat Biomass and Yield by Combining the AquaCrop Model and Field Hyperspectral Data

    Directory of Open Access Journals (Sweden)

    Xiuliang Jin

    2016-11-01

    Full Text Available Knowledge of spatial and temporal variations in crop growth is important for crop management and stable crop production for the food security of a country. A combination of crop growth models and remote sensing data is a useful method for monitoring crop growth status and estimating crop yield. The objective of this study was to use spectral-based biomass values generated from spectral indices to calibrate the AquaCrop model using the particle swarm optimization (PSO algorithm to improve biomass and yield estimations. Spectral reflectance and concurrent biomass and yield were measured at the Xiaotangshan experimental site in Beijing, China, during four winter wheat-growing seasons. The results showed that all of the measured spectral indices were correlated with biomass to varying degrees. The normalized difference matter index (NDMI was the best spectral index for estimating biomass, with the coefficient of determination (R2, root mean square error (RMSE, and relative RMSE (RRMSE values of 0.77, 1.80 ton/ha, and 25.75%, respectively. The data assimilation method (R2 = 0.83, RMSE = 1.65 ton/ha, and RRMSE = 23.60% achieved the most accurate biomass estimations compared with the spectral index method. The estimated yield was in good agreement with the measured yield (R2 = 0.82, RMSE = 0.55 ton/ha, and RRMSE = 8.77%. This study offers a new method for agricultural resource management through consistent assessments of winter wheat biomass and yield based on the AquaCrop model and remote sensing data.

  12. Performance evaluation of selected crop yield-water use models for wheat crop

    Directory of Open Access Journals (Sweden)

    H. E. Igbadun

    2001-10-01

    Full Text Available Crop yield-water use models that provide useful information about the exact form of crop response to different amounts of water used by the crop throughout its growth stages and those that provide adequate information for decisions on optimal use of water in the farm were evaluated. Three crop yield models: Jensen (1968, Minhas et al., (1974 and Bras and Cordova (1981 additive type models were studied. Wheat (Triticum aestivum was planted at the Institute for Agricultural Research Farm during the 1995/96 and 1996/97 irrigation seasons of November to March. The data collected from the field experiments during the 1995/96 planting season were used to calibrate the models and their stress sensitivity factors estimated for four selected growth stages of the wheat crop. The ability of the model to predict grain yield of wheat with the estimated stress sensitivity factors was evaluated by comparing predicted grain yields by each model with those obtained in the field during the 1996/97 season. The three models performed fairly well in predicting grain yields, as the predicted results were not significantly different from the field measured grain yield at 5% level of significance.

  13. A spectral-spatial-dynamic hierarchical Bayesian (SSD-HB) model for estimating soybean yield

    Science.gov (United States)

    Kazama, Yoriko; Kujirai, Toshihiro

    2014-10-01

    A method called a "spectral-spatial-dynamic hierarchical-Bayesian (SSD-HB) model," which can deal with many parameters (such as spectral and weather information all together) by reducing the occurrence of multicollinearity, is proposed. Experiments conducted on soybean yields in Brazil fields with a RapidEye satellite image indicate that the proposed SSD-HB model can predict soybean yield with a higher degree of accuracy than other estimation methods commonly used in remote-sensing applications. In the case of the SSD-HB model, the mean absolute error between estimated yield of the target area and actual yield is 0.28 t/ha, compared to 0.34 t/ha when conventional PLS regression was applied, showing the potential effectiveness of the proposed model.

  14. RICE YIELD ESTIMATION THROUGH ASSIMILATING SATELLITE DATA INTO A CROP SIMUMLATION MODEL

    Directory of Open Access Journals (Sweden)

    N. T. Son

    2016-06-01

    Full Text Available Rice is globally the most important food crop, feeding approximately half of the world’s population, especially in Asia where around half of the world’s poorest people live. Thus, advanced spatiotemporal information of rice crop yield during crop growing season is critically important for crop management and national food policy making. The main objective of this study was to develop an approach to integrate remotely sensed data into a crop simulation model (DSSAT for rice yield estimation in Taiwan. The data assimilation was processed to integrate biophysical parameters into DSSAT model for rice yield estimation using the particle swarm optimization (PSO algorithm. The cost function was constructed based on the differences between the simulated leaf area index (LAI and MODIS LAI, and the optimization process starts from an initial parameterization and accordingly adjusts parameters (e.g., planting date, planting population, and fertilizer amount in the crop simulation model. The fitness value obtained from the cost function determined whether the optimization algorithm had reached the optimum input parameters using a user-defined tolerance. The results of yield estimation compared with the government’s yield statistics indicated the root mean square error (RMSE of 11.7% and mean absolute error of 9.7%, respectively. This study demonstrated the applicability of satellite data assimilation into a crop simulation model for rice yield estimation, and the approach was thus proposed for crop yield monitoring purposes in the study region.

  15. Rice Yield Estimation Through Assimilating Satellite Data Into a Crop Simumlation Model

    Science.gov (United States)

    Son, N. T.; Chen, C. F.; Chen, C. R.; Chang, L. Y.; Chiang, S. H.

    2016-06-01

    Rice is globally the most important food crop, feeding approximately half of the world's population, especially in Asia where around half of the world's poorest people live. Thus, advanced spatiotemporal information of rice crop yield during crop growing season is critically important for crop management and national food policy making. The main objective of this study was to develop an approach to integrate remotely sensed data into a crop simulation model (DSSAT) for rice yield estimation in Taiwan. The data assimilation was processed to integrate biophysical parameters into DSSAT model for rice yield estimation using the particle swarm optimization (PSO) algorithm. The cost function was constructed based on the differences between the simulated leaf area index (LAI) and MODIS LAI, and the optimization process starts from an initial parameterization and accordingly adjusts parameters (e.g., planting date, planting population, and fertilizer amount) in the crop simulation model. The fitness value obtained from the cost function determined whether the optimization algorithm had reached the optimum input parameters using a user-defined tolerance. The results of yield estimation compared with the government's yield statistics indicated the root mean square error (RMSE) of 11.7% and mean absolute error of 9.7%, respectively. This study demonstrated the applicability of satellite data assimilation into a crop simulation model for rice yield estimation, and the approach was thus proposed for crop yield monitoring purposes in the study region.

  16. Multiaxial yield surface of transversely isotropic foams: Part I-Modeling

    Science.gov (United States)

    Ayyagari, Ravi Sastri; Vural, Murat

    2015-01-01

    A new yield criterion is proposed for transversely isotropic solid foams. Its derivation is based on the hypothesis that the yielding in foams is driven by the total strain energy density, rather than a completely phenomenological approach. This allows defining the yield surface with minimal number of parameters and does not require complex experiments. The general framework used leads to the introduction of new scalar measures of stress and strain (characteristic stress and strain) for transversely isotropic foams. Furthermore, the central hypothesis that the total strain energy density drives yielding in foams ascribes to the characteristic stress an analogous role of von Mises stress in metal plasticity. Unlike the overwhelming majority of yield models in literature the proposed model recognizes the tension-compression difference in yield behavior of foams through a linear mean stress term. Predictions of the proposed yield model are in excellent agreement with the results of uniaxial, biaxial and triaxial FE analyses implemented on both isotropic and transversely isotropic Kelvin foam models.

  17. Creep-fatigue modelling in structural steels using empirical and constitutive creep methods implemented in a strip-yield model

    Science.gov (United States)

    Andrews, Benjamin J.

    The phenomena of creep and fatigue have each been thoroughly studied. More recently, attempts have been made to predict the damage evolution in engineering materials due to combined creep and fatigue loading, but these formulations have been strictly empirical and have not been used successfully outside of a narrow set of conditions. This work proposes a new creep-fatigue crack growth model based on constitutive creep equations (adjusted to experimental data) and Paris law fatigue crack growth. Predictions from this model are compared to experimental data in two steels: modified 9Cr-1Mo steel and AISI 316L stainless steel. Modified 9Cr-1Mo steel is a high-strength steel used in the construction of pressure vessels and piping for nuclear and conventional power plants, especially for high temperature applications. Creep-fatigue and pure creep experimental data from the literature are compared to model predictions, and they show good agreement. Material constants for the constitutive creep model are obtained for AISI 316L stainless steel, an alloy steel widely used for temperature and corrosion resistance for such components as exhaust manifolds, furnace parts, heat exchangers and jet engine parts. Model predictions are compared to pure creep experimental data, with satisfactory results. Assumptions and constraints inherent in the implementation of the present model are examined. They include: spatial discretization, similitude, plane stress constraint and linear elasticity. It is shown that the implementation of the present model had a non-trivial impact on the model solutions in 316L stainless steel, especially the spatial discretization. Based on these studies, the following conclusions are drawn: 1. The constitutive creep model consistently performs better than the Nikbin, Smith and Webster (NSW) model for predicting creep and creep-fatigue crack extension. 2. Given a database of uniaxial creep test data, a constitutive material model such as the one developed for

  18. A new prediction model for grain yield in Northeast China based on spring North Atlantic Oscillation and late-winter Bering Sea ice cover

    Science.gov (United States)

    Zhou, Mengzi; Wang, Huijun; Huo, Zhiguo

    2017-04-01

    Accurate estimations of grain output in the agriculturally important region of Northeast China are of great strategic significance for guaranteeing food security. New prediction models for maize and rice yields are built in this paper based on the spring North Atlantic Oscillation index and the Bering Sea ice cover index. The year-to-year increment is first forecasted and then the original yield value is obtained by adding the historical yield of the previous year. The multivariate linear prediction model of maize shows good predictive ability, with a low normalized root-mean-square error (NRMSE) of 13.9%, and the simulated yield accounts for 81% of the total variance of the observation. To improve the performance of the multivariate linear model, a combined forecasting model of rice is built by considering the weight of the predictors. The NRMSE of the model is 12.9% and the predicted rice yield explains 71% of the total variance. The corresponding cross-validation test and independent samples test further demonstrate the efficiency of the models. It is inferred that the statistical models established here by applying year-to-year increment approach could make rational prediction for the maize and rice yield in Northeast China before harvest. The present study may shed new light on yield prediction in advance by use of antecedent large-scale climate signals adequately.

  19. Yield loss prediction models based on early estimation of weed pressure

    DEFF Research Database (Denmark)

    Asif, Ali; Streibig, Jens Carl; Andreasen, Christian

    2013-01-01

    Weed control thresholds have been used to reduce costs and avoid unacceptable yield loss. Estimation of weed infestation has often been based on counts of weed plants per unit area or measurement of their relative leaf area index. Various linear, hyperbolic, and sigmoidal regression models have...... been proposed to predict yield loss, relative to yield in weed free environment from early measurements of weed infestation. The models are integrated in some weed management advisory systems. Generally, the recommendations from the advisory systems are applied to the whole field, but weed control...... time of weeds relative to crop. The aim of the review is to analyze various approaches to estimate infestation of weeds and the literature about yield loss prediction for multispecies. We discuss limitations of regression models and possible modifications to include the influential factors related...

  20. Model Identification and FE Simulations: Effect of Different Yield Loci and Hardening Laws in Sheet Forming

    Science.gov (United States)

    Flores, P.; Duchêne, L.; Lelotte, T.; Bouffioux, C.; El Houdaigui, F.; Van Bael, A.; He, S.; Duflou, J.; Habraken, A. M.

    2005-08-01

    The bi-axial experimental equipment developed by Flores enables to perform Baushinger shear tests and successive or simultaneous simple shear tests and plane-strain tests. Such experiments and classical tensile tests investigate the material behavior in order to identify the yield locus and the hardening models. With tests performed on two steel grades, the methods applied to identify classical yield surfaces such as Hill or Hosford ones as well as isotropic Swift type hardening or kinematic Armstrong-Frederick hardening models are explained. Comparison with the Taylor-Bishop-Hill yield locus is also provided. The effect of both yield locus and hardening model choice will be presented for two applications: Single Point Incremental Forming (SPIF) and a cup deep drawing.

  1. Is Technology Good for Us? A Eudaimonic Meta-Model for Evaluating the Contributive Capability of Technologies for a Good Life.

    Science.gov (United States)

    Spence, Edward H

    2011-12-01

    The title refers to the question addressed in this paper, namely, to what degree if any technology, including nanotechnologies, in the form of products and processes, is capable of contributing to a good life. To answer that question, the paper will develop a meta-normative model whose primary purpose is to determine the essential conditions that any normative theory of the Good Life and Technology (T-GLAT) must adequately address in order to be able to account for, explain and evaluate the Contributive Capability of Technology for a Good Life (CCT-GL). By CCT-GL understand the capability of any technological product or process in its design and/or its use to contribute in some way, if any, to the good life of individuals and society at large. In this paper, the all-embracing term "technology" will be used to refer to both the products and processes of different technologies.

  2. Comparison of empirical models to estimate soil erosion and sediment yield in micro catchments

    Directory of Open Access Journals (Sweden)

    Lida Eisazadeh

    2015-05-01

    Full Text Available Assessment of sediment yield in soil conservation and watershed Project and implementation plan for water and soil resources management is so important. Regarding to somewhere that doesn’t have enough information and statistical data such as upper river branches, Empirical models should be used to estimate erosion and sediment yield. However the efficiency and usage of these models before calibration isn’t clear. In this research, the measurement of erosion and sediment yield of 10 basins upstream of reservoirshas been estimated by RUSLE and MPSIAC empirical models.In order to compare means between measured and estimated datat-test method was applied.Theresults indicated no significant differences between means of measured and estimated sediment yield in MPSAIC model in 5% level. In contrast, T-test showed contrary results in RUSLE model. Then the applicability and priority of two models were examined by statistical methodssuch as MAE and MBE methods. By regarding to accuracy and precision, MPSIAC model placed in first priorityto estimate soil erosion and sediment yield and has minimum value of MAE=0.79 and MBE = -0.59.

  3. Effects of stage of pregnancy on variance components, daily milk yields and 305-day milk yield in Holstein cows, as estimated by using a test-day model.

    Science.gov (United States)

    Yamazaki, T; Hagiya, K; Takeda, H; Osawa, T; Yamaguchi, S; Nagamine, Y

    2016-08-01

    Pregnancy and calving are elements indispensable for dairy production, but the daily milk yield of cows decline as pregnancy progresses, especially during the late stages. Therefore, the effect of stage of pregnancy on daily milk yield must be clarified to accurately estimate the breeding values and lifetime productivity of cows. To improve the genetic evaluation model for daily milk yield and determine the effect of the timing of pregnancy on productivity, we used a test-day model to assess the effects of stage of pregnancy on variance component estimates, daily milk yields and 305-day milk yield during the first three lactations of Holstein cows. Data were 10 646 333 test-day records for the first lactation; 8 222 661 records for the second; and 5 513 039 records for the third. The data were analyzed within each lactation by using three single-trait random regression animal models: one model that did not account for the stage of pregnancy effect and two models that did. The effect of stage of pregnancy on test-day milk yield was included in the model by applying a regression on days pregnant or fitting a separate lactation curve for each days open (days from calving to pregnancy) class (eight levels). Stage of pregnancy did not affect the heritability estimates of daily milk yield, although the additive genetic and permanent environmental variances in late lactation were decreased by accounting for the stage of pregnancy effect. The effects of days pregnant on daily milk yield during late lactation were larger in the second and third lactations than in the first lactation. The rates of reduction of the 305-day milk yield of cows that conceived fewer than 90 days after the second or third calving were significantly (Ppregnancy in the first, compared with later, lactations should be included when determining the optimal number of days open to maximize lifetime productivity in dairy cows.

  4. Modelling Bambara Groundnut Yield in Southern Africa: Towards a Climate-Resilient Future

    Science.gov (United States)

    Karunaratne, A. S.; Walker, S.; Ruane, A. C.

    2015-01-01

    Current agriculture depends on a few major species grown as monocultures that are supported by global research underpinning current productivity. However, many hundreds of alternative crops have the potential to meet real world challenges by sustaining humanity, diversifying agricultural systems for food and nutritional security, and especially responding to climate change through their resilience to certain climate conditions. Bambara groundnut (Vigna subterranea (L.) Verdc.), an underutilised African legume, is an exemplar crop for climate resilience. Predicted yield performances of Bambara groundnut by AquaCrop (a crop-water productivity model) were evaluated for baseline (1980-2009) and mid-century climates (2040-2069) under 20 downscaled Global Climate Models (CMIP5-RCP8.5), as well as for climate sensitivities (AgMIPC3MP) across 3 locations in Southern Africa (Botswana, South Africa, Namibia). Different land - races of Bambara groundnut originating from various semi-arid African locations showed diverse yield performances with diverse sensitivities to climate. S19 originating from hot-dry conditions in Namibia has greater future yield potential compared to the Swaziland landrace Uniswa Red-UN across study sites. South Africa has the lowest yield under the current climate, indicating positive future yield trends. Namibia reported the highest baseline yield at optimum current temperatures, indicating less yield potential in future climates. Bambara groundnut shows positive yield potential at temperatures of up to 31degC, with further warming pushing yields down. Thus, many regions in Southern Africa can utilize Bambara groundnut successfully in the coming decades. This modelling exercise supports decisions on genotypic suitability for present and future climates at specific locations.

  5. Modelling Bambara Groundnut Yield in Southern Africa: Towards a Climate-Resilient Future

    Science.gov (United States)

    Karunaratne, A. S.; Walker, S.; Ruane, A. C.

    2015-01-01

    Current agriculture depends on a few major species grown as monocultures that are supported by global research underpinning current productivity. However, many hundreds of alternative crops have the potential to meet real world challenges by sustaining humanity, diversifying agricultural systems for food and nutritional security, and especially responding to climate change through their resilience to certain climate conditions. Bambara groundnut (Vigna subterranea (L.) Verdc.), an underutilised African legume, is an exemplar crop for climate resilience. Predicted yield performances of Bambara groundnut by AquaCrop (a crop-water productivity model) were evaluated for baseline (1980-2009) and mid-century climates (2040-2069) under 20 downscaled Global Climate Models (CMIP5-RCP8.5), as well as for climate sensitivities (AgMIPC3MP) across 3 locations in Southern Africa (Botswana, South Africa, Namibia). Different land - races of Bambara groundnut originating from various semi-arid African locations showed diverse yield performances with diverse sensitivities to climate. S19 originating from hot-dry conditions in Namibia has greater future yield potential compared to the Swaziland landrace Uniswa Red-UN across study sites. South Africa has the lowest yield under the current climate, indicating positive future yield trends. Namibia reported the highest baseline yield at optimum current temperatures, indicating less yield potential in future climates. Bambara groundnut shows positive yield potential at temperatures of up to 31degC, with further warming pushing yields down. Thus, many regions in Southern Africa can utilize Bambara groundnut successfully in the coming decades. This modelling exercise supports decisions on genotypic suitability for present and future climates at specific locations.

  6. TOWARDS A CONCEPTUAL FRAMEWORK OF ISLAMIC LEADERSHIP SUCCESSOR'S ATTRIBUTES MODEL AND GOOD GOVERNANCE

    Directory of Open Access Journals (Sweden)

    Naji Zuhair Alsarhi

    2015-12-01

    Full Text Available The purpose of this paper is to propose a conceptual model that explains the relationship between Islamic leadership successionpersonalityattributes and good governance. The paper sources information from an extensive search of literature to design a conceptual model of Islamic leadership succession (personal attributes & governmental characteristics of Succession and good governance. The model will provide an integration of relationships that will add valuable insights into improved leadership succession theory in the related literature. The paper may assist particularly policy makers and strategists to focus on new possibilities of leadership successors attributes that will lead to improved governance as well as government performance in the world in general, and the Palestine community, in particular.

  7. Cereal Yield Modeling in Finland Using Optical and Radar Remote Sensing

    Directory of Open Access Journals (Sweden)

    Jouko Kleemola

    2010-09-01

    Full Text Available During 1996–2006, the Ministry of Agriculture and Forestry in Finland (MAFF, MTT Agrifood Research and the Finnish Geodetic Institute performed a joint remote sensing satellite research project. It evaluated the applicability of optical satellite (Landsat, SPOT data for cereal yield estimations in the annual crop inventory program. Four Optical Vegetation Indices models (I: Infrared polynomial, II: NDVI, III: GEMI, IV: PARND/FAPAR were validated to estimate cereal baseline yield levels (yb using solely optical harmonized satellite data (Optical Minimum Dataset. The optimized Model II (NDVI yb level was 4,240 kg/ha (R2 0.73, RMSE 297 kg/ha for wheat and 4390 kg/ha (R2 0.61, RMSE 449 kg/ha for barley and Model I yb was 3,480 kg/ha for oats (R2 0.76, RMSE 258 kg/ha. Optical VGI yield estimates were validated with CropWatN crop model yield estimates using SPOT and NOAA data (mean R2 0.71, RMSE 436 kg/ha and with composite SAR/ASAR and NDVI models (mean R2 0.61, RMSE 402 kg/ha using both reflectance and backscattering data. CropWatN and Composite SAR/ASAR & NDVI model mean yields were 4,754/4,170 kg/ha for wheat, 4,192/3,848 kg/ha for barley and 4,992/2,935 kg/ha for oats.

  8. Determinants of the Government Bond Yield in Spain: A Loanable Funds Model

    Directory of Open Access Journals (Sweden)

    Yu Hsing

    2015-07-01

    Full Text Available This paper applies demand and supply analysis to examine the government bond yield in Spain. The sample ranges from 1999.Q1 to 2014.Q2. The EGARCH model is employed in empirical work. The Spanish government bond yield is positively associated with the government debt/GDP ratio, the short-term Treasury bill rate, the expected inflation rate, the U.S. 10 year government bond yield and a dummy variable representing the debt crisis and negatively affected by the GDP growth rate and the expected nominal effective exchange rate.

  9. Wastewater Treatment Model in Washing Stations for Vehicles Transporting Dangerous Goods

    Directory of Open Access Journals (Sweden)

    Robert Muha

    2004-09-01

    Full Text Available Car washing is a task performed by every passenger carowner more or less frequently, mainly to achieve a finer appearanceof the vehicle rather than for the need for cleanness.In the transport business, the owner's concern is to presentclean and orderly vehicles on the road as a relevant external elementof order, implying good corporate image to customers. Onthe other hand, in dangerous goods transportation there areother reasons requiring special technology of washing, applicableto the transport means used, depending on the change oftype of goods in carriage, the preliminary preparation of a vehicleto load the cargo, or to undergo maintenance.Water applied in the technology of washing collects the residueof goods carried in the vehicle and is polluted to such an extentthat it cannot be discharged into sewers - nor directly into awatercourse - without previous treatment.The paper presents a solution model and a sequence oftechnological procedures involved in an efficient treatment ofthe polluted wastewater in tank wash stations, in which mostlyvehicles carrying ADR goods are washed.

  10. Modelling daily sediment yield from a meso-scale catchment, a case study in SW Poland

    Energy Technology Data Exchange (ETDEWEB)

    Keesstra, S. D.; Schoorl, J.; Temme, A. J. A. M.

    2009-07-01

    For management purposes it is important to be able to assess the sediment yield of a catchment. however, at this moment models designed for estimating sediment yield are only capable to give either very detailed storm-based information or year averages. The storm-based models require input data that are not available for most catchment. However, models that estimate yearly averages, ignore a lot of other detailed information, like daily discharge and precipitation data. There are currently no models available that model sediment yield on the temporal scale of one day and the spatial scale of a meso-scale catchment, without making use of very detailed input data. To fill this scientific and management gap, landscape evolution model LAPSUS has been adapted to model sediment yield on a daily basis. This model has the water balance as a base. To allow calibration with the discharge at the outlet, a subsurface flow module has been added to the model. (Author) 12 refs.

  11. EVALUATION OF MARKETABLE LEAF YIELD OF FLUTED PUMPKIN IN DIFFERENT ENVIRONMENTS USING ADDITIVE MAIN EFFECTS AND MULTIPLICATIVE INTERACTION (AMMI MODEL

    Directory of Open Access Journals (Sweden)

    Fayeun L. Stephen

    2016-01-01

    Full Text Available This study was conducted to determine the yield stability and to analyse the Genotype by Environment Interaction (GEI of twenty five genotypes of fluted pumpkin genotypes. The experiment was laid out in a randomized complete block design (RCBD with three replications under four environments using Additive Main effects and Multiplicative Interaction (AMMI analysis. The mean squares of the analysis of variance revealed significant genotype, environment and GEI on marketable leaf yield per plant. AMMI analysis revealed that the major contributions to treatment sum of squares were environments (3.24%, GEI (46.90% and genotypes (49.70%, respectively, suggesting that the marketable leaf yield of the genotypes were under the major genotypic effects of GEI. The first two principal component axes (PCA 1 and 2 cumulatively contributed 93.50% of the total GEI and were significant (p ≤ 0.01. The biplot accounted for 85.82% of the total variation. The AMMI model identified genotypes Ftn44, Ftk20, and Fts34 as most stable, while Fta39 with highest yield (398.80g/plant had the largest negative interaction. The best genotype with respect to Abeokuta location was Ftw21 while Fta39 was the best for Akure area. Therefore, these genotypes can be recommended according to their specific adaptation areas. Abeokuta in the 2012 and 2013 had positive interaction values of 14.38 and 9.46 respectively whereas Akure in 2012 and 2013 recorded negative interaction values of -5.03 and -18.81 respectively. Akure 2013 was the most discriminating environment and had the highest mean yield thus it is considered as a very good environment for cultivation of fluted pumpkin for marketable leaf yield.

  12. Good Corporate Governance and Predicting Financial Distress Using Logistic and Probit Regression Model

    Directory of Open Access Journals (Sweden)

    Juniarti Juniarti

    2013-01-01

    Full Text Available The study aims to prove whether good corporate governance (GCG is able to predict the probability of companies experiencing financial difficulties. Financial ratios that traditionally used for predicting bankruptcy remains used in this study. Besides, this study also compares logit and probit regression models, which are widely used in research related accounting bankruptcy prediction. Both models will be compared to determine which model is more superior. The sample in this study is the infrastructure, transportation, utilities & trade, services and hotels companies experiencing financial distress in the period 2008-2011. The results show that GCG and other three variables control i.e DTA, CR and company category do not prove significantly to predict the probability of companies experiencing financial difficulties. NPM, the only variable that proved significantly distinguishing healthy firms and distress. In general, logit and probit models do not result in different conclusions. Both of the models confirm the goodness of fit of models and the results of hypothesis testing. In terms of classification accuracy, logit model proves more accurate predictions than the probit models.

  13. Statistical rice yield modeling using blended MODIS-Landsat based crop phenology metrics in Taiwan

    Science.gov (United States)

    Chen, C. R.; Chen, C. F.; Nguyen, S. T.; Lau, K. V.

    2015-12-01

    Taiwan is a populated island with a majority of residents settled in the western plains where soils are suitable for rice cultivation. Rice is not only the most important commodity, but also plays a critical role for agricultural and food marketing. Information of rice production is thus important for policymakers to devise timely plans for ensuring sustainably socioeconomic development. Because rice fields in Taiwan are generally small and yet crop monitoring requires information of crop phenology associating with the spatiotemporal resolution of satellite data, this study used Landsat-MODIS fusion data for rice yield modeling in Taiwan. We processed the data for the first crop (Feb-Mar to Jun-Jul) and the second (Aug-Sep to Nov-Dec) in 2014 through five main steps: (1) data pre-processing to account for geometric and radiometric errors of Landsat data, (2) Landsat-MODIS data fusion using using the spatial-temporal adaptive reflectance fusion model, (3) construction of the smooth time-series enhanced vegetation index 2 (EVI2), (4) rice yield modeling using EVI2-based crop phenology metrics, and (5) error verification. The fusion results by a comparison bewteen EVI2 derived from the fusion image and that from the reference Landsat image indicated close agreement between the two datasets (R2 > 0.8). We analysed smooth EVI2 curves to extract phenology metrics or phenological variables for establishment of rice yield models. The results indicated that the established yield models significantly explained more than 70% variability in the data (p-value 0.8), in both cases. The root mean square error (RMSE) and mean absolute error (MAE) used to measure the model accuracy revealed the consistency between the estimated yields and the government's yield statistics. This study demonstrates advantages of using EVI2-based phenology metrics (derived from Landsat-MODIS fusion data) for rice yield estimation in Taiwan prior to the harvest period.

  14. Yield response of winter wheat cultivars to environments modeled by different variance-covariance structures in linear mixed models

    Energy Technology Data Exchange (ETDEWEB)

    Studnicki, M.; Mądry, W.; Noras, K.; Wójcik-Gront, E.; Gacek, E.

    2016-11-01

    The main objectives of multi-environmental trials (METs) are to assess cultivar adaptation patterns under different environmental conditions and to investigate genotype by environment (G×E) interactions. Linear mixed models (LMMs) with more complex variance-covariance structures have become recognized and widely used for analyzing METs data. Best practice in METs analysis is to carry out a comparison of competing models with different variance-covariance structures. Improperly chosen variance-covariance structures may lead to biased estimation of means resulting in incorrect conclusions. In this work we focused on adaptive response of cultivars on the environments modeled by the LMMs with different variance-covariance structures. We identified possible limitations of inference when using an inadequate variance-covariance structure. In the presented study we used the dataset on grain yield for 63 winter wheat cultivars, evaluated across 18 locations, during three growing seasons (2008/2009-2010/2011) from the Polish Post-registration Variety Testing System. For the evaluation of variance-covariance structures and the description of cultivars adaptation to environments, we calculated adjusted means for the combination of cultivar and location in models with different variance-covariance structures. We concluded that in order to fully describe cultivars adaptive patterns modelers should use the unrestricted variance-covariance structure. The restricted compound symmetry structure may interfere with proper interpretation of cultivars adaptive patterns. We found, that the factor-analytic structure is also a good tool to describe cultivars reaction on environments, and it can be successfully used in METs data after determining the optimal component number for each dataset. (Author)

  15. Yield response of winter wheat cultivars to environments modeled by different variance-covariance structures in linear mixed models

    Directory of Open Access Journals (Sweden)

    Marcin Studnicki

    2016-06-01

    Full Text Available The main objectives of multi-environmental trials (METs are to assess cultivar adaptation patterns under different environmental conditions and to investigate genotype by environment (G×E interactions. Linear mixed models (LMMs with more complex variance-covariance structures have become recognized and widely used for analyzing METs data. Best practice in METs analysis is to carry out a comparison of competing models with different variance-covariance structures. Improperly chosen variance-covariance structures may lead to biased estimation of means resulting in incorrect conclusions. In this work we focused on adaptive response of cultivars on the environments modeled by the LMMs with different variance-covariance structures. We identified possible limitations of inference when using an inadequate variance-covariance structure. In the presented study we used the dataset on grain yield for 63 winter wheat cultivars, evaluated across 18 locations, during three growing seasons (2008/2009-2010/2011 from the Polish Post-registration Variety Testing System. For the evaluation of variance-covariance structures and the description of cultivars adaptation to environments, we calculated adjusted means for the combination of cultivar and location in models with different variance-covariance structures. We concluded that in order to fully describe cultivars adaptive patterns modelers should use the unrestricted variance-covariance structure. The restricted compound symmetry structure may interfere with proper interpretation of cultivars adaptive patterns. We found, that the factor-analytic structure is also a good tool to describe cultivars reaction on environments, and it can be successfully used in METs data after determining the optimal component number for each dataset.

  16. Analysis of hadron yield data within hadron resonance gas model with multi-component eigenvolume corrections

    CERN Document Server

    Vovchenko, Volodymyr

    2016-01-01

    We analyze the sensitivity of thermal fits to heavy-ion hadron yield data of ALICE and NA49 collaborations to the systematic uncertainties in the hadron resonance gas (HRG) model related to the modeling of the eigenvolume interactions. We find a surprisingly large sensitivity in extraction of chemical freeze-out parameters to the assumptions regarding eigenvolumes of different hadrons. We additionally study the effect of including yields of light nuclei into the thermal fits to LHC data and find even larger sensitivity to the modeling of their eigenvolumes. The inclusion of light nuclei yields, thus, may lead to further destabilization of thermal fits. Our results show that modeling of eigenvolume interactions plays a crucial role in thermodynamics of HRG and that conclusions based on a non-interacting HRG are not unique.

  17. Multivariate Statistical Models for Predicting Sediment Yields from Southern California Watersheds

    Science.gov (United States)

    Gartner, Joseph E.; Cannon, Susan H.; Helsel, Dennis R.; Bandurraga, Mark

    2009-01-01

    Debris-retention basins in Southern California are frequently used to protect communities and infrastructure from the hazards of flooding and debris flow. Empirical models that predict sediment yields are used to determine the size of the basins. Such models have been developed using analyses of records of the amount of material removed from debris retention basins, associated rainfall amounts, measures of watershed characteristics, and wildfire extent and history. In this study we used multiple linear regression methods to develop two updated empirical models to predict sediment yields for watersheds located in Southern California. The models are based on both new and existing measures of volume of sediment removed from debris retention basins, measures of watershed morphology, and characterization of burn severity distributions for watersheds located in Ventura, Los Angeles, and San Bernardino Counties. The first model presented reflects conditions in watersheds located throughout the Transverse Ranges of Southern California and is based on volumes of sediment measured following single storm events with known rainfall conditions. The second model presented is specific to conditions in Ventura County watersheds and was developed using volumes of sediment measured following multiple storm events. To relate sediment volumes to triggering storm rainfall, a rainfall threshold was developed to identify storms likely to have caused sediment deposition. A measured volume of sediment deposited by numerous storms was parsed among the threshold-exceeding storms based on relative storm rainfall totals. The predictive strength of the two models developed here, and of previously-published models, was evaluated using a test dataset consisting of 65 volumes of sediment yields measured in Southern California. The evaluation indicated that the model developed using information from single storm events in the Transverse Ranges best predicted sediment yields for watersheds in San

  18. Yield Model Development (YMD) implementation plan for fiscal years 1981 and 1982

    Science.gov (United States)

    Ambroziak, R. A. (Principal Investigator)

    1981-01-01

    A plan is described for supporting USDA crop production forecasting and estimation by (1) testing, evaluating, and selecting crop yield models for application testing; (2) identifying areas of feasible research for improvement of models; and (3) conducting research to modify existing models and to develop new crop yield assessment methods. Tasks to be performed for each of these efforts are described as well as for project management and support. The responsibilities of USDA, USDC, USDI, and NASA are delineated as well as problem areas to be addressed.

  19. Can Agrometeorological Indices of Adverse Weather Conditions Help to Improve Yield Prediction by Crop Models?

    Directory of Open Access Journals (Sweden)

    Branislava Lalić

    2014-12-01

    Full Text Available The impact of adverse weather conditions (AWCs on crop production is random in both time and space and depends on factors such as severity, previous agrometeorological conditions, and plant vulnerability at a specific crop development stage. Any exclusion or improper treatment of any of these factors can cause crop models to produce significant under- or overestimates of yield. The analysis presented in this paper focuses on a range of agrometeorological indices (AMI related to AWCs that might affect real yield as well as simulated yield. For this purpose, the analysis addressed four indicators of extreme temperatures and three indicators of dry conditions during the growth period of maize and winter wheat in Austria, Croatia, Serbia, Slovakia, and Sweden. It is shown that increases in the number and intensity of AWCs cannot be unambiguously associated with increased deviations in simulated yields. The identified correlations indicate an increase in modeling uncertainty. This finding represents important information for the crop modeling community. Additionally, it opens a window of opportunity for a statistical (“event scenario” approach based on correlations between agrometeorological indices of AWCs and crop yield data series. This approach can provide scenarios for certain locations, crop types, and AWC patterns and, therefore, improve yield forecasting in the presence of AWCs.

  20. Simulation of winter wheat yield and its uncertainty band; A comparison of two crop growth models

    Science.gov (United States)

    Javad Khordadi Varamini, Mohammad; Nassiri Mahallati, Mehdi; Alizadeh, Amin

    2016-04-01

    In this study, we used the WOFOST and AquaCrop crop growth simulation models to examine crop yield responses to a set of plausible scenarios of climate change in Mashhad region, located in Ghareghom basin, northeast of Iran up to 2040. We selected winter wheat as an indicator crop. Also six AOGCMs including GFCM21, HADCM3, INCM3, IPCM4, MPEH5 and NCCCSM under A2 and B1 emission scenarios are used. LARS-WG statistical method for downscaling is utilized. In the present research, using 7-year observed crop data, the crop models were calibrated and then validated. Evaluation of WOFOST and AquaCrop models confirmed the models are able for simulating the yield of wheat grown in the study area. The results showed that average potential yield of wheat ranged from 3.43 to 8.42 and 2.76 to 6.49 ton.ha-1, in AquaCrop and WOFOST models, respectively. Finally, the uncertainty band due to the six AOGCMs for estimating crop yield is drawn and investigated. These bands show possible changes for the yield in the future period to the past one. It can be concluded the positive effects of climate warming and elevated CO2 concentrations on the production in the studied region.

  1. Simulating yield response to water of Teff (Eragrostis tef) with FAO's AquaCrop model

    NARCIS (Netherlands)

    Araya, A.; Keesstra, S.D.; Stroosnijder, L.

    2010-01-01

    In a semi-arid environment, the main challenge for crop production is water deficit. FAO's AquaCrop model, which simulates yield response to water, has been calibrated to explore alternative water management strategies in teff crop. To calibrate and evaluate this model, we used independent data sets

  2. A model for the [gamma]p[yields][pi][sup +][pi][sup -]p reactions

    Energy Technology Data Exchange (ETDEWEB)

    Gomez Tejedor, J.A. (Dept. de Fisica Teorica, Centro Mixto Universidad de Valencia-CSIC, Burjassot (Spain) IFIC, Centro Mixto Universidad de Valencia-CSIC, Burjassot (Spain)); Oset, E. (Dept. de Fisica Teorica, Centro Mixto Universidad de Valencia-CSIC, Burjassot (Spain) IFIC, Centro Mixto Universidad de Valencia-CSIC, Burjassot (Spain))

    1994-05-09

    We have studied the [gamma]p[yields][pi][sup +][pi][sup -]p reaction using a model which includes N, [Delta](1232), N[sup *](1440) and N[sup *](1520) intermediate baryonic states and the [rho]-meson as intermediate 2[pi]-resonance. The model reproduces fairly well experimental cross sections below E[sub [gamma

  3. Simulating yield response to water of Teff (Eragrostis tef) with FAO's AquaCrop model

    NARCIS (Netherlands)

    Araya, A.; Keesstra, S.D.; Stroosnijder, L.

    2010-01-01

    In a semi-arid environment, the main challenge for crop production is water deficit. FAO's AquaCrop model, which simulates yield response to water, has been calibrated to explore alternative water management strategies in teff crop. To calibrate and evaluate this model, we used independent data sets

  4. Nutrient Balance in Relation to High Yield andGood{1mm Quality of Potatoon an Acid Purple Soil in Chongqing,1mm China

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A field experiment was carried out to study nutrient balance among N,P, K and Mg in potato cultivation on an acid purple soil in Chongqing,China. The experiment included 8 treatments with equal P rate of 120 kgP{2O5 hm-2: N0K2, N1K2,N2K2, N3K2, N2K0, N2K1,N2K1Mg and N2K3, where N0, N1, N2 andN3 stand for the N rates of 0, 75, 150 and 225 kg N hm-2, andK0, K1, K2 and K3 for the K rates of 0,165, 330 and 495 kg K2O hm-2, respectively. Among thetreatments designed, Treatment N2K2 with a nutrientsupply ratio of N:P2O5:K2O:MgO = 1.25:1:2.75:0.28 gavethe highest tuber yield and dry matter, highest starch and Znand lowest NO-3 contents in tuber, and high N, P and Kuse efficiency with an uptake ratio of N:P:K:Mg = 11.38:1:13.32:0.33 bytuber. Yield and starch and protein contents of tuber were thelowest in Treatment N0K2. Dry matter was the lowest butprotein and NO-3 contents were the highest in TreatmentN2K0. Treatment N2K1Mg had the highest N, Pand K utilization rates. Statistical analysis showed that yields oftuber and starch were in a positive linear correlation with the uptakeamount of various nutrients and protein of the potato tuber was in asignificantly positive linear correlation with tuber N content and in asignificantly negative linear correlation with tuber K and Mg contents.Balanced application of N, P, K and Mg fertilizers (TreatmentN2K2) was recommended for realization of high yield andgood quality in potato cultivation.

  5. New methods to measure and model logistics and goods effects by the use of the CLG-DSS Model

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Jensen, Anders Vestergaard

    2004-01-01

    This paper concerns the assessment and modelling of so-called logistics and goods effects (LG-effects) as part of a wider economic analysis by use of the developed CLG-DSS model. The results presented are based an on-going study, Task 9 about evaluation modelling and decision support systems (DSS...... The aim of this paper is to present these four LG-effects with a special emphasis on a possible way of modelling these and interpreting their importance. The calculations are carried out by using the CLG-DSS model and case studies concerning the fixed links across the Great Belt and Øresund....... It is proposed to model the effects in two ways. First the paper presents a combined method modelling the four effects into one aggregate effect characterized by the goods-related time benefits. Second the paper describes a more refined, disaggregate method approach that, however, at this stage only concerns...

  6. Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model

    Science.gov (United States)

    Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.

    2012-12-01

    uptake of water (root profile), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients). We find that the optimal carboxylation rate and optimal photosynthesis temperature parameters contribute most to the uncertainty in NPP and GPP simulations whereas stomatal conductance is the most sensitive parameter controlling SH, followed by optimal photosynthesis temperature and optimal carboxylation rate. The spatial variation of the ranked correlation between input parameters and output variables is well explained by rain and temperature drivers, suggesting that climate mediated regionally different sensitivities of modeled sugarcane yield to the model parameters, for Australia and Brazil.

  7. How Good Can We Get? Using mathematical models to predict the future of athletics

    CERN Document Server

    Mureika, J R

    1998-01-01

    Track and field world records have risen and fallen throughout the history of the sport. A recent rash of record-breaking performances has prompted the question: "How good can we get?". This article offers a review of several attempts to answer this question, based on mathematical modeling of key physiological processes. The predictions are compared with present-day world records, and a discussion of the future of athletics ensues...

  8. Rice Yield Estimation by Integrating Remote Sensing with Rice Growth Simulation Model

    Institute of Scientific and Technical Information of China (English)

    O. ABOU-ISMAIL; HUANG Jing-Feng; WANG Ren-Chao

    2004-01-01

    Since remote sensing can provide information on the actual status of an agricultural crop, the integration between remote sensing data and crop growth simulation models has become an important trend for yield estimation and prediction.The main objective of this research was to combine a rice growth simulation model with remote sensing data to estimate rice grain yield for different growing seasons leading to an assessment of rice yield at regional levels. Integration between NOAA (National Oceanic and Atmospheric Administration) AVHRR (Advanced Very High Resolution Radiometer) data and the rice growth simulation model ORYZA1 to develop a new software, which was named as Rice-SRS Model, resulted in accurate estimates for rice yield in Shaoxing, China, with an estimation error reduced to 1.03% and 0.79% over-estimation and 0.79% under-estimation for early, single and late season rice, respectively. Selecting suitable dates for remote sensing images was an important factor which could influence estimation accuracy. Thus, given the different growing periods for each rice season, four images were needed for early and late rice, while five images were preferable for single season rice.Estimating rice yield using two or three images was possible, however, if images were obtained during the panicle initiation and heading stages.

  9. Comparing the performance of 11 crop simulation models in predicting yield response to nitrogen fertilization

    DEFF Research Database (Denmark)

    Salo, T J; Palosuo, T; Kersebaum, K C

    2016-01-01

    , Finland. This is the largest standardized crop model inter-comparison under different levels of N supply to date. The models were calibrated using data from 2002 and 2008, of which 2008 included six N rates ranging from 0 to 150 kg N/ha. Calibration data consisted of weather, soil, phenology, leaf area...... index (LAI) and yield observations. The models were then tested against new data for 2009 and their performance was assessed and compared with both the two calibration years and the test year. For the calibration period, root mean square error between measurements and simulated grain dry matter yields...... mineralization as a function of soil temperature and moisture. Furthermore, specific weather event impacts such as low temperatures after emergence in 2009, tending to enhance tillering, and a high precipitation event just before harvest in 2008, causing possible yield penalties, were not captured by any...

  10. Estimating crop yield using a satellite-based light use efficiency model

    DEFF Research Database (Denmark)

    Yuan, Wenping; Chen, Yang; Xia, Jiangzhou

    2016-01-01

    for simulating crops’ GPP. At both irrigated and rainfed sites, the EC-LUE model exhibits a similar level of performance. However, large errors are found when simulating yield based on crop harvest index. This analysis highlights the need to improve the representation of the harvest index and carbon allocation...... primary production (GPP) and yield of crops. The EC-LUE model can explain on average approximately 90% of the variability in GPP for 36 FLUXNET sites globally. The results indicate that a universal set of parameters, independent of crop species (except for C4 crops), can be adopted in the EC-LUE model...... for improving crop yield estimations from satellite-based methods....

  11. Relationship between soybean yield/quality and soil quality in a major soybean-producing area based on a 2D-QSAR model

    Science.gov (United States)

    Gao, Ming; Li, Shiwei

    2017-05-01

    Based on experimental data of the soybean yield and quality from 30 sampling points, a quantitative structure-activity relationship model (2D-QSAR) was established using the soil quality (elements, pH, organic matter content and cation exchange capacity) as independent variables and soybean yield or quality as the dependent variable, with SPSS software. During the modeling, the full data set (30 and 14 compounds) was divided into a training set (24 and 11 compounds) for model generation and a test set (6 and 3 compounds) for model validation. The R2 values of the resulting models and data were 0.826 and 0.808 for soybean yield and quality, respectively, and all regression coefficients were significant (P < 0.05). The correlation coefficient R2pred of observed values and predicted values of the soybean yield and soybean quality in the test set were 0.961 and 0.956, respectively, indicating that the models had a good predictive ability. Moreover, the Mo, Se, K, N and organic matter contents and the cation exchange capacity of soil had a positive effect on soybean production, and the B, Mo, Se, K and N contents and cation exchange coefficient had a positive effect on soybean quality. The results are instructive for enhancing soils to improve the yield and quality of soybean, and this method can also be used to study other crops or regions, providing a theoretical basis to improving the yield and quality of crops.

  12. New methods to measure and model logistics and goods effects by the use of the CLG-DSS Model

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Jensen, Anders Vestergaard

    2004-01-01

    This paper concerns the assessment and modelling of so-called logistics and goods effects (LG-effects) as part of a wider economic analysis by use of the developed CLG-DSS model. The results presented are based an on-going study, Task 9 about evaluation modelling and decision support systems (DSS......) in the Centre for Logistics and Goods Transport (CLG) 2001-2005 funded by the Danish Council for Technical-Scientific Research (STVF). Within the area of research on logistics the interaction between logistics and transportation is of great relevance. Task 9 and other recent studies have found that several...... companies are taking account of logistics and transport by setting up, among other things, specific departments to improve their handling. Some aspects in the transport sector concerning goods movement and consequences have not so far got the attention they deserve. In CLG Task 9 four LG-effects have been...

  13. Development of a Coupled Hydrological/Sediment Yield Model for a Watershed at Regional Level

    Science.gov (United States)

    Rajbhandaril, Narayan; Crosson, William; Tsegaye, Teferi; Coleman, Tommy; Liu, Yaping; Soman, Vishwas

    1998-01-01

    Development of a hydrologic model for the study of environmental conservation requires a comprehensive understanding of individual-storm affecting hydrologic and sedimentologic processes. The hydrologic models that we are currently coupling are the Simulator for Hydrology and Energy Exchange at the Land Surface (SHEELS) and the Distributed Runoff Model (DRUM). SHEELS runs continuously to estimate surface energy fluxes and sub-surface soil water fluxes, while DRUM operates during and following precipitation events to predict surface runoff and peak flow through channel routing. The lateral re-distribution of surface water determined by DRUM is passed to SHEELS, which then adjusts soil water contents throughout the profile. The model SHEELS is well documented in Smith et al. (1993) and Laymen and Crosson (1995). The model DRUM is well documented in Vieux et al. (1990) and Vieux and Gauer (1994). The coupled hydrologic model, SHEELS/DRUM, does not simulate sedimentologic processes. The simulation of the sedimentologic process is important for environmental conservation planning and management. Therefore, we attempted to develop a conceptual frame work for coupling a sediment yield model with SHEELS/DRUM to estimate individual-storm sediment yield from a watershed at a regional level. The sediment yield model that will be used for this study is the Universal Soil Loss Equation (USLE) with some modifications to enable the model to predict individual-storm sediment yield. The predicted sediment yield does not include wind erosion and erosion caused by irrigation and snow melt. Units used for this study are those given by Foster et al. (1981) for SI units.

  14. A new, integrated, continuous purification process template for monoclonal antibodies: Process modeling and cost of goods studies.

    Science.gov (United States)

    Xenopoulos, Alex

    2015-11-10

    An evolving biopharmaceutical industry requires advancements in biomanufacturing that offer increased productivity and improved economics without sacrificing process robustness. Accordingly, we have developed a new monoclonal antibody purification template comprised of flocculation-based clarification, capture by continuous multi-column protein A chromatography and flow-through polishing. The new process offers a robust, single-use manufacturing solution while significantly reducing overall cost of goods. Modeling studies verify that the individual clarification, capture and polishing solutions offer significant advantages as stand-alone unit operations. These technologies were also designed to be integrated into a continuous purification template. Process modeling studies have been used to highlight both cost and operational advantages of the new process template. Depending on scale, savings of more than 20% and 60% were seen for commercial and clinical operation, respectively. Integrating the technologies into a continuous process consistently offered additional cost advantages. During template development, process modeling was instrumental in highlighting the importance of identifying technologies that provided high product yield and purification factors. Additionally, high product concentration and eliminating the need for intermediate product dilution emerged as important considerations for newly developed unit operations. Combining experimental work with insights from modeling can significantly improve the outcome of product and process development.

  15. The Forecasting Power of the Yield Curve, a Supervised Factor Model Approach

    DEFF Research Database (Denmark)

    Boldrini, Lorenzo; Hillebrand, Eric Tobias

    We study the forecast power of the yield curve for macroeconomic time series, such as consumer price index, personal consumption expenditures, producer price index, real disposable income, unemployment rate, and industrial production. We employ a state-space model in which the forecasting objective......¨urkaynak, Sack, and Wright (2006) and Diebold and Li (2006) and macroeconomic data from FRED. We compare the models by means of the conditional predictive ability test of Giacomini and White (2006). We find that the yield curve has more forecast power for real variables compared to inflation measures...

  16. Dependence of simulated positron emitter yields in ion beam cancer therapy on modeling nuclear fragmentation.

    Science.gov (United States)

    Lühr, Armin; Priegnitz, Marlen; Fiedler, Fine; Sobolevsky, Nikolai; Bassler, Niels

    2014-01-01

    In ion beam cancer therapy, range verification in patients using positron emission tomography (PET) requires the comparison of measured with simulated positron emitter yields. We found that (1) changes in modeling nuclear interactions strongly affected the positron emitter yields and that (2) Monte Carlo simulations with SHIELD-HIT10Areasonably matched the most abundant PET isotopes (11)C and (15)O. We observed an ion-energy (i.e., depth) dependence of the agreement between SHIELD-HIT10Aand measurement. Improved modeling requires more accurate measurements of cross-section values.

  17. Implications of b{yields}s{gamma} in the Weinberg three-Higgs-doublet models

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Darwin; Chen, Chuan-Hung; Geng, Chao-Qiang [National Tsing Hua Univ., Hsinchu, TW (China). Dept. of Physics

    1996-06-01

    Using recent experimental measurements on Br(b{yields}s{gamma}) from CLEO, we study the constraints on the charged Higgs sector in various three-Higgs-doublet models. Some phenomenological implications in these models with emphasis on CP violation are presented. In particular, in some of these models, the CP violating muon polarization in K{sub {mu}3} can be detected using the current KEK experiment E246. (author)

  18. Estimating Rice Yield under Changing Weather Conditions in Kenya Using CERES Rice Model

    OpenAIRE

    W. O. Nyang’au; Mati, B. M.; Kalamwa, K.; Wanjogu, R. K.; L. K. Kiplagat

    2014-01-01

    Effects of change in weather conditions on the yields of Basmati 370 and IR 2793-80-1 cultivated under System of Rice Intensification (SRI) in Mwea and Western Kenya irrigation schemes were assessed through sensitivity analysis using the Ceres rice model v 4.5 of the DSSAT modeling system. Genetic coefficients were determined using 2010 experimental data. The model was validated using rice growth and development data during the 2011 cropping season. Two SRI farmers were selected randomly from...

  19. Model of Yield Response of Corn to Plant Population and Absorption of Solar Energy

    Science.gov (United States)

    Overman, Allen R.; Scholtz, Richard V.

    2011-01-01

    Biomass yield of agronomic crops is influenced by a number of factors, including crop species, soil type, applied nutrients, water availability, and plant population. This article is focused on dependence of biomass yield (Mg ha−1 and g plant−1) on plant population (plants m−2). Analysis includes data from the literature for three independent studies with the warm-season annual corn (Zea mays L.) grown in the United States. Data are analyzed with a simple exponential mathematical model which contains two parameters, viz. Ym (Mg ha−1) for maximum yield at high plant population and c (m2 plant−1) for the population response coefficient. This analysis leads to a new parameter called characteristic plant population, xc = 1/c (plants m−2). The model is shown to describe the data rather well for the three field studies. In one study measurements were made of solar radiation at different positions in the plant canopy. The coefficient of absorption of solar energy was assumed to be the same as c and provided a physical basis for the exponential model. The three studies showed no definitive peak in yield with plant population, but generally exhibited asymptotic approach to maximum yield with increased plant population. Values of xc were very similar for the three field studies with the same crop species. PMID:21297960

  20. Model of yield response of corn to plant population and absorption of solar energy.

    Directory of Open Access Journals (Sweden)

    Allen R Overman

    Full Text Available Biomass yield of agronomic crops is influenced by a number of factors, including crop species, soil type, applied nutrients, water availability, and plant population. This article is focused on dependence of biomass yield (Mg ha(-1 and g plant(-1 on plant population (plants m(-2. Analysis includes data from the literature for three independent studies with the warm-season annual corn (Zea mays L. grown in the United States. Data are analyzed with a simple exponential mathematical model which contains two parameters, viz. Y(m (Mg ha(-1 for maximum yield at high plant population and c (m(2 plant(-1 for the population response coefficient. This analysis leads to a new parameter called characteristic plant population, x(c = 1/c (plants m(-2. The model is shown to describe the data rather well for the three field studies. In one study measurements were made of solar radiation at different positions in the plant canopy. The coefficient of absorption of solar energy was assumed to be the same as c and provided a physical basis for the exponential model. The three studies showed no definitive peak in yield with plant population, but generally exhibited asymptotic approach to maximum yield with increased plant population. Values of x(c were very similar for the three field studies with the same crop species.

  1. Estimating Rice Yield under Changing Weather Conditions in Kenya Using CERES Rice Model

    Directory of Open Access Journals (Sweden)

    W. O. Nyang’au

    2014-01-01

    Full Text Available Effects of change in weather conditions on the yields of Basmati 370 and IR 2793-80-1 cultivated under System of Rice Intensification (SRI in Mwea and Western Kenya irrigation schemes were assessed through sensitivity analysis using the Ceres rice model v 4.5 of the DSSAT modeling system. Genetic coefficients were determined using 2010 experimental data. The model was validated using rice growth and development data during the 2011 cropping season. Two SRI farmers were selected randomly from each irrigation scheme and their farms were used as research fields. Daily maximum and minimum temperatures and precipitation were collected from the weather station in each of the irrigation schemes while daily solar radiation was generated using weatherman in the DSSAT shell. The study revealed that increase in both maximum and minimum temperatures affects Basmati 370 and IR 2793-80-1 grain yield under SRI. Increase in atmospheric CO2 concentration led to an increase in grain yield for both Basmati and IR 2793-80-1 under SRI and increase in solar radiation also had an increasing impact on both Basmati 370 and IR 2793-80-1 grain yield. The results of the study therefore show that weather conditions in Kenya affect rice yield under SRI and should be taken into consideration to improve food security.

  2. Spatial modeling of contemporary crop yields in China under sustainable and unsustainable water use scenarios

    Science.gov (United States)

    Grogan, D. S.; Zhang, F.; Li, C.; Frolking, S.

    2011-12-01

    Irrigated agriculture is an important part of China's population and economic growth. Currently, water needed to irrigate crops can be drawn from surface runoff, streams, reservoirs, renewable groundwater, or fossil groundwater. Fossil groundwater is not sustainable over long time periods, and therefore regions that rely on this source for irrigation water could face water shortages in the future, and may already be experiencing water stress today. This study uses two models, one to calculate water balance and the other to simulate crop yields, to address the question: how much unsustainable water is currently used for irrigation in China, and by how much would the use of only sustainable water reduce crop yields? The amount of sustainable water available for irrigation is determined using the WBMplus model. This model uses precipitation and temperature drivers, along with gridded data of soils, cropping, and irrigation, to simulate soil moisture, potential evapotranspiration, surface runoff, stream flow, and reservoir storage, in 30 min grid cells. The model also computes demand for irrigation water, and the capacity of various sources to supply that demand in each grid cell. The DNDC model, which has been evaluated against crop yield in a number of studies in China, is used to predict crop yield for ~50 crop types involved in ~100 cropping systems across China, under zero and full irrigation for each grid cell. Yields using only the sustainable irrigation water capacity will be calculated by weighing the zero and full irrigation yields based on the water availability results of WBMplus for each grid cell. With this methodology, we estimate how national-scale food production would be changed by limiting agricultural water use.

  3. A review on statistical models for identifying climate contributions to crop yields

    Institute of Scientific and Technical Information of China (English)

    SHI Wenjiao; TAO Fulu; ZHANG Zhao

    2013-01-01

    Statistical models using historical data on crop yields and weather to calibrate relatively simple regression equations have been widely and extensively applied in previous studies,and have provided a common alternative to process-based models,which require extensive input data on cultivar,management,and soil conditions.However,very few studies had been conducted to review systematically the previous statistical models for indentifying climate contributions to crop yields.This paper introduces three main statistical methods,i.e.,time-series model,cross-section model and panel model,which have been used to identify such issues in the field of agrometeorology.Generally,research spatial scale could be categorized into two types using statistical models,including site scale and regional scale (e.g.global scale,national scale,provincial scale and county scale).Four issues exist in identifying response sensitivity of crop yields to climate change by statistical models.The issues include the extent of spatial and temporal scale,non-climatic trend removal,colinearity existing in climate variables and non-consideration of adaptations.Respective resolutions for the above four issues have been put forward in the section of perspective on the future of statistical models finally.

  4. Retail Location Choice with Complementary Goods: An Agent-Based Model

    Science.gov (United States)

    Huang, Arthur; Levinson, David

    This paper models the emergence of retail clusters on a supply chain network comprised of suppliers, retailers, and consumers. Firstly, an agent-based model is proposed to investigate retail location distribution in a market of two complementary goods. The methodology controls for supplier locales and unit sales prices of retailers and suppliers, and a consumer’s willingness to patronize a retailer depends on the total travel distance of buying both goods. On a circle comprised of discrete locations, retailers play a non-cooperative game of location choice to maximize individual profits. Our findings suggest that the probability distribution of the number of clusters in equilibrium follows power law and that hierarchical distribution patterns are much more likely to occur than the spread-out ones. In addition, retailers of complementary goods tend to co-locate at supplier locales. Sensitivity tests on the number of retailers are also performed. Secondly, based on the County Business Patterns (CBP) data of Minneapolis-St. Paul from US Census 2000 database, we find that the number of clothing stores and the distribution of food stores at the zip code level follows power-law distribution.

  5. Comparison of the Smith-Purcell Radiation Yield for Different Models

    CERN Document Server

    Malovytsia, M S

    2016-01-01

    Smith-Purcell radiation is used in several applications including the measurement of the longitudinal profile of electron bunches. A correct reconstruction of such profile requires a good understanding of the underlying model. We have compared the leading models of Smith-Purcell radiation and shown that they are in agreement within the experimental errors.

  6. Empirical validation of the InVEST water yield ecosystem service model at a national scale.

    Science.gov (United States)

    Redhead, J W; Stratford, C; Sharps, K; Jones, L; Ziv, G; Clarke, D; Oliver, T H; Bullock, J M

    2016-11-01

    A variety of tools have emerged with the goal of mapping the current delivery of ecosystem services and quantifying the impact of environmental changes. An important and often overlooked question is how accurate the outputs of these models are in relation to empirical observations. In this paper we validate a hydrological ecosystem service model (InVEST Water Yield Model) using widely available data. We modelled annual water yield in 22 UK catchments with widely varying land cover, population and geology, and compared model outputs with gauged river flow data from the UK National River Flow Archive. Values for input parameters were selected from existing literature to reflect conditions in the UK and were subjected to sensitivity analyses. We also compared model performance between precipitation and potential evapotranspiration data sourced from global- and UK-scale datasets. We then tested the transferability of the results within the UK by additional validation in a further 20 catchments. Whilst the model performed only moderately with global-scale data (linear regression of modelled total water yield against empirical data; slope=0.763, intercept=54.45, R(2)=0.963) with wide variation in performance between catchments, the model performed much better when using UK-scale input data, with closer fit to the observed data (slope=1.07, intercept=3.07, R(2)=0.990). With UK data the majority of catchments showed modelled water yield but there was a minor but consistent overestimate per hectare (86m(3)/ha/year). Additional validation on a further 20 UK catchments was similarly robust, indicating that these results are transferable within the UK. These results suggest that relatively simple models can give accurate measures of ecosystem services. However, the choice of input data is critical and there is a need for further validation in other parts of the world. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Good initialization model with constrained body structure for scene text recognition

    Science.gov (United States)

    Zhu, Anna; Wang, Guoyou; Dong, Yangbo

    2016-09-01

    Scene text recognition has gained significant attention in the computer vision community. Character detection and recognition are the promise of text recognition and affect the overall performance to a large extent. We proposed a good initialization model for scene character recognition from cropped text regions. We use constrained character's body structures with deformable part-based models to detect and recognize characters in various backgrounds. The character's body structures are achieved by an unsupervised discriminative clustering approach followed by a statistical model and a self-build minimum spanning tree model. Our method utilizes part appearance and location information, and combines character detection and recognition in cropped text region together. The evaluation results on the benchmark datasets demonstrate that our proposed scheme outperforms the state-of-the-art methods both on scene character recognition and word recognition aspects.

  8. Simulation of potato yield in temperate condition by the AquaCrop model

    DEFF Research Database (Denmark)

    Razzaghi, Fatemeh; Zhenjiang, Zhou; Andersen, Mathias Neumann

    2017-01-01

    to calculate the soil water balance on a daily basis has become widespread in the last decades. Therefore, this study was performed to simulate potato yield, dry matter and soil water content under different water stress condition using the AquaCrop model. Three levels of irrigation comprising full irrigated...... was simulated using the AquaCrop model. Data from full irrigated treatment of 2014 was used for model calibration and data from 2013 (If, Id, and I0 treatments), 2014 (Id, and I0 treatments) and 2015 (If, Id, and I0 treatments) were used for model validation. The sensitivity analysis of different parameters...... showed that KcTr, HI0, CCX, calendar day from sowing to start of senescence and WP* had the most pronounced influence on tuber yield. The result showed that the AquaCrop model simulated soil water content, canopy cover and above-ground dry matter during the crop growth seasons with acceptable accuracy...

  9. Simple model relating recombination rates and non-proportional light yield in scintillators

    Energy Technology Data Exchange (ETDEWEB)

    Moses, William W.; Bizarri, Gregory; Singh, Jai; Vasil' ev, Andrey N.; Williams, Richard T.

    2008-09-24

    We present a phenomenological approach to derive an approximate expression for the local light yield along a track as a function of the rate constants of different kinetic orders of radiative and quenching processes for excitons and electron-hole pairs excited by an incident {gamma}-ray in a scintillating crystal. For excitons, the radiative and quenching processes considered are linear and binary, and for electron-hole pairs a ternary (Auger type) quenching process is also taken into account. The local light yield (Y{sub L}) in photons per MeV is plotted as a function of the deposited energy, -dE/dx (keV/cm) at any point x along the track length. This model formulation achieves a certain simplicity by using two coupled rate equations. We discuss the approximations that are involved. There are a sufficient number of parameters in this model to fit local light yield profiles needed for qualitative comparison with experiment.

  10. A model for the {gamma}N{yields}{pi}{pi}N reaction

    Energy Technology Data Exchange (ETDEWEB)

    Gomez Tejedor, J.A.; Oset, E. [Departamento de Fisica Teorica Centro Mixto Universidad de Valencia-CSIC, Burjassot, Valencia (Spain)]|[IFIC Centro Mixto Universidad de Valencia-CSIC, Burjassot, Valencia (Spain)

    1996-11-01

    We have studied the {gamma}N {yields} {pi}{pi}N reaction using a model which includes N, {Delta}(1232), N{sup *}(1440) and N{sup *}(1520) intermediate baryonic states and the {rho}-meson as intermediate {pi}{pi} resonance. The model reproduces fairly well experimental cross sections below E{sub {gamma}} = 800 MeV and invariant-mass distributions even at higher energies. One of the interesting findings of the study is that the {gamma}N{yields}N{sup *}(1520) {yields} {Delta}{pi} process is very important and interferes strongly with the dominant {Delta}-Kroll-Ruderman term to produce the experimental peak of the cross section. (author) 10 refs, 1 fig

  11. A plasticity model with yield surface distortion for non proportional loading

    CERN Document Server

    François, Marc Louis Maurice

    2010-01-01

    In order to enhance the modeling of metallic materials behavior in non proportional loadings, a modification of the classical elastic-plastic models including distortion of the yield surface is proposed. The new yield criterion uses the same norm as in the classical von Mises based criteria, and a "distorted stress" Sd replacing the usual stress deviator S. The obtained yield surface is then ?egg-shaped? similar to those experimentally observed and depends on only one new material parameter. The theory is built in such a way as to recover the classical one for proportional loading. An identification procedure is proposed to obtain the material parameters. Simulations and experiments are compared for a 2024 T4 aluminum alloy for both proportional and nonproportional tension-torsion loading paths.

  12. Genotype by environment interaction for seed yield per plant in rapeseed using AMMI model

    Directory of Open Access Journals (Sweden)

    Ana Marjanović-Jeromela

    2011-02-01

    Full Text Available The objective of this study was to assess genotype by environment interaction for seed yield per plant in rapeseed cultivars grown in Northern Serbia by the AMMI (additive main effects and multiplicative interaction model. The study comprised 19 rapeseed genotypes, analyzed in seven years through field trials arranged in a randomized complete block design, with three replicates. Seed yield per plant of the tested cultivars varied from 1.82 to 19.47 g throughout the seven seasons, with an average of 7.41 g. In the variance analysis, 72.49% of the total yield variation was explained by environment, 7.71% by differences between genotypes, and 19.09% by genotype by environment interaction. On the biplot, cultivars with high yield genetic potential had positive correlation with the seasons with optimal growing conditions, while the cultivars with lower yield potential were correlated to the years with unfavorable conditions. Seed yield per plant is highly influenced by environmental factors, which indicates the adaptability of specific genotypes to specific seasons.

  13. An integrated, probabilistic model for improved seasonal forecasting of agricultural crop yield under environmental uncertainty

    Directory of Open Access Journals (Sweden)

    Nathaniel K. Newlands

    2014-06-01

    Full Text Available We present a novel forecasting method for generating agricultural crop yield forecasts at the seasonal and regional-scale, integrating agroclimate variables and remotely-sensed indices. The method devises a multivariate statistical model to compute bias and uncertainty in forecasted yield at the Census of Agricultural Region (CAR scale across the Canadian Prairies. The method uses robust variable-selection to select the best predictors within spatial subregions. Markov-Chain Monte Carlo (MCMC simulation and random forest-tree machine learning techniques are then integrated to generate sequential forecasts through the growing season. Cross-validation of the model was performed by hindcasting/backcasting it and comparing its forecasts against available historical data (1987-2011 for spring wheat (Triticum aestivum L.. The model was also validated for the 2012 growing season by comparing its forecast skill at the CAR, provincial and Canadian Prairie region scales against available statistical survey data. Mean percent departures between wheat yield forecasted were under-estimated by 1-4 % in mid-season and over-estimated by 1 % at the end of the growing season. This integrated methodology offers a consistent, generalizable approach for sequentially forecasting crop yield at the regional-scale. It provides a statistically robust, yet flexible way to concurrently adjust to data-rich and data-sparse situations, adaptively select different predictors of yield to changing levels of environmental uncertainty, and to update forecasts sequentially so as to incorporate new data as it becomes available. This integrated method also provides additional statistical support for assessing the accuracy and reliability of model-based crop yield forecasts in time and space.

  14. Estimation efficiency of usage satellite derived and modelled biophysical products for yield forecasting

    Science.gov (United States)

    Kolotii, Andrii; Kussul, Nataliia; Skakun, Sergii; Shelestov, Andrii; Ostapenko, Vadim; Oliinyk, Tamara

    2015-04-01

    Efficient and timely crop monitoring and yield forecasting are important tasks for ensuring of stability and sustainable economic development [1]. As winter crops pay prominent role in agriculture of Ukraine - the main focus of this study is concentrated on winter wheat. In our previous research [2, 3] it was shown that usage of biophysical parameters of crops such as FAPAR (derived from Geoland-2 portal as for SPOT Vegetation data) is far more efficient for crop yield forecasting to NDVI derived from MODIS data - for available data. In our current work efficiency of usage such biophysical parameters as LAI, FAPAR, FCOVER (derived from SPOT Vegetation and PROBA-V data at resolution of 1 km and simulated within WOFOST model) and NDVI product (derived from MODIS) for winter wheat monitoring and yield forecasting is estimated. As the part of crop monitoring workflow (vegetation anomaly detection, vegetation indexes and products analysis) and yield forecasting SPIRITS tool developed by JRC is used. Statistics extraction is done for landcover maps created in SRI within FP-7 SIGMA project. Efficiency of usage satellite based and modelled with WOFOST model biophysical products is estimated. [1] N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "Sensor Web approach to Flood Monitoring and Risk Assessment", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 815-818. [2] F. Kogan, N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk, "Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models," International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 192-203, 2013. [3] Kussul O., Kussul N., Skakun S., Kravchenko O., Shelestov A., Kolotii A, "Assessment of relative efficiency of using MODIS data to winter wheat yield forecasting in Ukraine", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 3235 - 3238.

  15. Good manufacturing practice for modelling air pollution: Quality criteria for computer models to calculate air pollution

    Science.gov (United States)

    Dekker, C. M.; Sliggers, C. J.

    To spur on quality assurance for models that calculate air pollution, quality criteria for such models have been formulated. By satisfying these criteria the developers of these models and producers of the software packages in this field can assure and account for the quality of their products. In this way critics and users of such (computer) models can gain a clear understanding of the quality of the model. Quality criteria have been formulated for the development of mathematical models, for their programming—including user-friendliness, and for the after-sales service, which is part of the distribution of such software packages. The criteria have been introduced into national and international frameworks to obtain standardization.

  16. AMMI Model for Interpreting Clone-Environment Interaction in Starch Yield of Cassava

    Directory of Open Access Journals (Sweden)

    SHOLIHIN

    2011-03-01

    Full Text Available The aim of the study was to analyze the interaction between clone and environment for starch yield in six month-old plants of cassava clones based on additive main effects and multiplicative interaction (AMMI model. The experiments were conducted on mineral soil in four different locations: Lumajang (inceptisol, Kediri (entisol, Pati (alfisol, and Tulangbawang (ultisol. The experiments were carried out during 2004-2005, using a split plot design withthree replications. The main plots were the simple and the improved technology. The clones used were fifteen clones. Parameter recorded was starch yield (kg/ha of the 6 month old plants. The data were analyzed using the AMMI model. Based on the AMMI analysis, environmental factors being important in determining the stability of the starch yield were soil density for subsoil, pH of topsoil, and the maximum air humidity four months after planting. The clones of CMM97001-87, CMM97002-183, CMM97011-191, CMM97006-44, and Adhira 4 were identified as stable clones in starch yield within 6 month-old plants. CMM97007-235 was adapted to maximum relative humidity 4 months after planting and to lower pH of topsoil, whereas, MLG 10311 was adapted to lower bulk density. The mean starch yield of MLG 10311 was the highest six months after planting.

  17. Bibliography of forest water yields, flooding issues, and the hydrologic modeling of extreme flood events

    Science.gov (United States)

    Mark H. Eisenbies; M.B. Adams; W. Michael Aust; James A. Burger

    2007-01-01

    Floods continue to cause significant damage in the United States and elsewhere, and questions about the causes of flooding continue to be debated. A significant amount of research has been conducted on the relationship between forest management activities and water yield, peak flows, and flooding; somewhat less research has been conducted on the modeling of these...

  18. Climate Impacts on Chinese Corn Yields: A Fractional Polynomial Regression Model

    NARCIS (Netherlands)

    Kooten, van G.C.; Sun, Baojing

    2012-01-01

    In this study, we examine the effect of climate on corn yields in northern China using data from ten districts in Inner Mongolia and two in Shaanxi province. A regression model with a flexible functional form is specified, with explanatory variables that include seasonal growing degree days,

  19. COMPARISON OF THREE MODELS TO PREDICT ANNUAL SEDIMENT YIELD IN CARONI RIVER BASIN, VENEZUELA

    Directory of Open Access Journals (Sweden)

    Edilberto Guevara-Pérez

    2007-06-01

    Full Text Available Caroní River Basin is located in the south-eastern part of Venezuela; with an area of 92.000 km², 40% of which belongs to the main affluent, the Paragua River. Caroní basin is the source of 66% of energy of the country. About 85% of the hydro electrical energy is generated in Guri reservoir located in the lower part of the watershed. To take provisions to avoid the reservoir silting it is very important the study of sediment yield of the basin. In this paper result of three empirical sediment yield models: LangbeinSchumm, Universal Soil Loss Equation-USLE and Poesen, are compared with observed data from five sub basins with records of twenty to thirty years. Men values of sediment yield for low, middle and upper Caroní are of 27, 76, 17 t/km²-year, respectively; and 46 and 78 t/km²-year for low and upper Paragua sub basins are. Standard errors of estimates vary between 13 and 29 for Langbein-Schumm model; between 8 and 32 for USLE procedure; and between 9 and 79, for Poesen model. Sediment yield predictions by Langbein-Schumm model seem to the best in Caroní basin.

  20. COMPARISON OF THREE MODELS TO PREDICT ANNUAL SEDIMENT YIELD IN CARONI RIVER BASIN, VENEZUELA

    Directory of Open Access Journals (Sweden)

    Edilberto Guevara-Pérez

    2007-01-01

    Full Text Available Caroní River Basin is located in the south-eastern part of Venezuela; with an area of 92.000 km2, 40% of which belongs to the main affluent, the Paragua River. Caroní basin is the source of 66% of energy of the country. About 85% of the hydro electrical energy is generated in Guri reservoir located in the lower part of the watershed. To take provisions to avoid the reservoir silting it is very important the study of sediment yield of the basin. In this paper result of three empirical sediment yield models: Langbein- Schumm, Universal Soil Loss Equation-USLE and Poesen, are compared with observed data from five sub basins with records of twenty to thirty years. Men values of sediment yield for low, middle and upper Caroní are of 27, 76, 17 t/km2-year, respectively; and 46 and 78 t/km2-year for low and upper Paragua sub basins are. Standard errors of estimates vary between 13 and 29 for Langbein-Schumm model; between 8 and 32 for USLE procedure; and between 9 and 79, for Poesen model. Sediment yield predictions by Langbein-Schumm model seem to the best in Caroní basin.

  1. Validation of Crop Weather Models for'Crop Assessment arid Yield ...

    African Journals Online (AJOL)

    over predict grain yields of maize, sorghum and wheat, a fact that could be attributed to the inadequacy of the model .... Of particular interest in this category is the cesses (Hanks and Hill, 1980). ... ter and basic infiltration rate for soii data. The.

  2. Crop model data assimilation with the Ensemble Kalman filter for improving regional crop yield forecasts

    NARCIS (Netherlands)

    Wit, de A.J.W.; Diepen, van C.A.

    2007-01-01

    Uncertainty in spatial and temporal distribution of rainfall in regional crop yield simulations comprises a major fraction of the error on crop model simulation results. In this paper we used an Ensemble Kalman filter (EnKF) to assimilate coarse resolution satellite microwave sensor derived soil

  3. Supporting Crop Loss Insurance Policy of Indonesia through Rice Yield Modelling and Forecasting

    Science.gov (United States)

    van Verseveld, Willem; Weerts, Albrecht; Trambauer, Patricia; de Vries, Sander; Conijn, Sjaak; van Valkengoed, Eric; Hoekman, Dirk; Grondard, Nicolas; Hengsdijk, Huib; Schrevel, Aart; Vlasbloem, Pieter; Klauser, Dominik

    2017-04-01

    The Government of Indonesia has decided on a crop insurance policy to assist Indonesia's farmers and to boost food security. To support the Indonesian government, the G4INDO project (www.g4indo.org) is developing/constructing an integrated platform implemented in the Delft-FEWS forecasting system (Werner et al., 2013). The integrated platform brings together remote sensed data (both visible and radar) and hydrologic, crop and reservoir modelling and forecasting to improve the modelling and forecasting of rice yield. The hydrological model (wflow_sbm), crop model (wflow_lintul) and reservoir models (RTC-Tools) are coupled on time stepping basis in the OpenStreams framework (see https://github.com/openstreams/wflow) and deployed in the integrated platform to support seasonal forecasting of water availability and crop yield. First we will show the general idea about the G4INDO project, the integrated platform (including Sentinel 1 & 2 data) followed by first (reforecast) results of the coupled models for predicting water availability and crop yield in the Brantas catchment in Java, Indonesia. Werner, M., Schellekens, J., Gijsbers, P., Van Dijk, M., Van den Akker, O. and Heynert K, 2013. The Delft-FEWS flow forecasting system, Environmental Modelling & Software; 40:65-77. DOI: 10.1016/j.envsoft.2012.07.010.

  4. Good teacher, good tutor

    Directory of Open Access Journals (Sweden)

    Couto LB

    2016-07-01

    Full Text Available Lucélio B Couto, Gustavo S Romão, Reinaldo B Bestetti  Department of Medicine, University of Ribeirão Preto, Ribeirão Preto, Brazil We have read with great interest the paper by Kassab et al, who have essentially shown that good teachers will be good tutors in a problem-based learning (PBL environment. We have been facing great difficulties to select tutors because there has been no tradition in PBL in our region in the preuniversity teaching. Furthermore, the majority of our teachers have been formed in a discipline-based medical curriculum. Therefore, it is reassuring to learn from the work by Kassab et al that subject-matter mastery is the powerful independent predictor of tutoring skills.  View the original paper by Kassab and colleagues.

  5. SPATIO-TEMPORAL MODELING OF AGRICULTURAL YIELD DATA WITH AN APPLICATION TO PRICING CROP INSURANCE CONTRACTS

    Science.gov (United States)

    Ozaki, Vitor A.; Ghosh, Sujit K.; Goodwin, Barry K.; Shirota, Ricardo

    2009-01-01

    This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Paraná (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited. PMID:19890450

  6. SPATIO-TEMPORAL MODELING OF AGRICULTURAL YIELD DATA WITH AN APPLICATION TO PRICING CROP INSURANCE CONTRACTS.

    Science.gov (United States)

    Ozaki, Vitor A; Ghosh, Sujit K; Goodwin, Barry K; Shirota, Ricardo

    2008-11-01

    This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Paraná (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

  7. Refinement and evaluation of the Massachusetts firm-yield estimator model version 2.0

    Science.gov (United States)

    Levin, Sara B.; Archfield, Stacey A.; Massey, Andrew J.

    2011-01-01

    The firm yield is the maximum average daily withdrawal that can be extracted from a reservoir without risk of failure during an extended drought period. Previously developed procedures for determining the firm yield of a reservoir were refined and applied to 38 reservoir systems in Massachusetts, including 25 single- and multiple-reservoir systems that were examined during previous studies and 13 additional reservoir systems. Changes to the firm-yield model include refinements to the simulation methods and input data, as well as the addition of several scenario-testing capabilities. The simulation procedure was adapted to run at a daily time step over a 44-year simulation period, and daily streamflow and meteorological data were compiled for all the reservoirs for input to the model. Another change to the model-simulation methods is the adjustment of the scaling factor used in estimating groundwater contributions to the reservoir. The scaling factor is used to convert the daily groundwater-flow rate into a volume by multiplying the rate by the length of reservoir shoreline that is hydrologically connected to the aquifer. Previous firm-yield analyses used a constant scaling factor that was estimated from the reservoir surface area at full pool. The use of a constant scaling factor caused groundwater flows during periods when the reservoir stage was very low to be overestimated. The constant groundwater scaling factor used in previous analyses was replaced with a variable scaling factor that is based on daily reservoir stage. This change reduced instability in the groundwater-flow algorithms and produced more realistic groundwater-flow contributions during periods of low storage. Uncertainty in the firm-yield model arises from many sources, including errors in input data. The sensitivity of the model to uncertainty in streamflow input data and uncertainty in the stage-storage relation was examined. A series of Monte Carlo simulations were performed on 22 reservoirs

  8. Analysis of shape isomer yields of 237Pu in the framework of dynamical–statistical model

    Indian Academy of Sciences (India)

    Hadi Eslamizadeh

    2012-02-01

    Data on shape isomer yield for + 235U reaction at $E^{\\text{lab}}$ = 20–29 MeV are analysed in the framework of a combined dynamical–statistical model. From this analysis, information on the double humped fission barrier parameters for some Pu isotopes has been obtained and it is shown that the depth of the second potential well should be less than the results of statistical model calculations.

  9. Determining Rheological Parameters of Generalized Yield-Power-Law Fluid Model

    Directory of Open Access Journals (Sweden)

    Stryczek Stanislaw

    2004-09-01

    Full Text Available The principles of determining rheological parameters of drilling muds described by a generalized yield-power-law are presented in the paper. Functions between tangent stresses and shear rate are given. The conditions of laboratory measurements of rheological parameters of generalized yield-power-law fluids are described and necessary mathematical relations for rheological model parameters given. With the block diagrams, the methodics of numerical solution of these relations has been presented. Rheological parameters of an exemplary drilling mud have been calculated with the use of this numerical program.

  10. Sustainable fisheries in shallow lakes: an independent empirical test of the Chinese mitten crab yield model

    Science.gov (United States)

    Wang, Haijun; Liang, Xiaomin; Wang, Hongzhu

    2017-07-01

    Next to excessive nutrient loading, intensive aquaculture is one of the major anthropogenic impacts threatening lake ecosystems. In China, particularly in the shallow lakes of mid-lower Changjiang (Yangtze) River, continuous overstocking of the Chinese mitten crab ( Eriocheir sinensis) could deteriorate water quality and exhaust natural resources. A series of crab yield models and a general optimum-stocking rate model have been established, which seek to benefit both crab culture and the environment. In this research, independent investigations were carried out to evaluate the crab yield models and modify the optimum-stocking model. Low percentage errors (average 47%, median 36%) between observed and calculated crab yields were obtained. Specific values were defined for adult crab body mass (135 g/ind.) and recapture rate (18% and 30% in lakes with submerged macrophyte biomass above and below 1 000 g/m2) to modify the optimum-stocking model. Analysis based on the modified optimum-stocking model indicated that the actual stocking rates in most lakes were much higher than the calculated optimum-stocking rates. This implies that, for most lakes, the current stocking rates should be greatly reduced to maintain healthy lake ecosystems.

  11. Sustainable fisheries in shallow lakes: an independent empirical test of the Chinese mitten crab yield model

    Science.gov (United States)

    Wang, Haijun; Liang, Xiaomin; Wang, Hongzhu

    2016-08-01

    Next to excessive nutrient loading, intensive aquaculture is one of the major anthropogenic impacts threatening lake ecosystems. In China, particularly in the shallow lakes of mid-lower Changjiang (Yangtze) River, continuous overstocking of the Chinese mitten crab (Eriocheir sinensis) could deteriorate water quality and exhaust natural resources. A series of crab yield models and a general optimum-stocking rate model have been established, which seek to benefit both crab culture and the environment. In this research, independent investigations were carried out to evaluate the crab yield models and modify the optimum-stocking model. Low percentage errors (average 47%, median 36%) between observed and calculated crab yields were obtained. Specific values were defined for adult crab body mass (135 g/ind.) and recapture rate (18% and 30% in lakes with submerged macrophyte biomass above and below 1 000 g/m2) to modify the optimum-stocking model. Analysis based on the modified optimum-stocking model indicated that the actual stocking rates in most lakes were much higher than the calculated optimum-stocking rates. This implies that, for most lakes, the current stocking rates should be greatly reduced to maintain healthy lake ecosystems.

  12. Surrogate models for identifying robust, high yield regions of parameter space for ICF implosion simulations

    Science.gov (United States)

    Humbird, Kelli; Peterson, J. Luc; Brandon, Scott; Field, John; Nora, Ryan; Spears, Brian

    2016-10-01

    Next-generation supercomputer architecture and in-transit data analysis have been used to create a large collection of 2-D ICF capsule implosion simulations. The database includes metrics for approximately 60,000 implosions, with x-ray images and detailed physics parameters available for over 20,000 simulations. To map and explore this large database, surrogate models for numerous quantities of interest are built using supervised machine learning algorithms. Response surfaces constructed using the predictive capabilities of the surrogates allow for continuous exploration of parameter space without requiring additional simulations. High performing regions of the input space are identified to guide the design of future experiments. In particular, a model for the yield built using a random forest regression algorithm has a cross validation score of 94.3% and is consistently conservative for high yield predictions. The model is used to search for robust volumes of parameter space where high yields are expected, even given variations in other input parameters. Surrogates for additional quantities of interest relevant to ignition are used to further characterize the high yield regions. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344, Lawrence Livermore National Security, LLC. LLNL-ABS-697277.

  13. A goodness-of-fit test for occupancy models with correlated within-season revisits

    Science.gov (United States)

    Wright, Wilson; Irvine, Kathryn M.; Rodhouse, Thomas J.

    2016-01-01

    Occupancy modeling is important for exploring species distribution patterns and for conservation monitoring. Within this framework, explicit attention is given to species detection probabilities estimated from replicate surveys to sample units. A central assumption is that replicate surveys are independent Bernoulli trials, but this assumption becomes untenable when ecologists serially deploy remote cameras and acoustic recording devices over days and weeks to survey rare and elusive animals. Proposed solutions involve modifying the detection-level component of the model (e.g., first-order Markov covariate). Evaluating whether a model sufficiently accounts for correlation is imperative, but clear guidance for practitioners is lacking. Currently, an omnibus goodnessof- fit test using a chi-square discrepancy measure on unique detection histories is available for occupancy models (MacKenzie and Bailey, Journal of Agricultural, Biological, and Environmental Statistics, 9, 2004, 300; hereafter, MacKenzie– Bailey test). We propose a join count summary measure adapted from spatial statistics to directly assess correlation after fitting a model. We motivate our work with a dataset of multinight bat call recordings from a pilot study for the North American Bat Monitoring Program. We found in simulations that our join count test was more reliable than the MacKenzie–Bailey test for detecting inadequacy of a model that assumed independence, particularly when serial correlation was low to moderate. A model that included a Markov-structured detection-level covariate produced unbiased occupancy estimates except in the presence of strong serial correlation and a revisit design consisting only of temporal replicates. When applied to two common bat species, our approach illustrates that sophisticated models do not guarantee adequate fit to real data, underscoring the importance of model assessment. Our join count test provides a widely applicable goodness-of-fit test and

  14. Genetic parameters for milk yield and persistency in Carora dairy cattle breed using random regression model

    Directory of Open Access Journals (Sweden)

    Emanuela Tullo

    2014-12-01

    Full Text Available In tropical environments, lactation curves with lower peaks and higher persistency (PS might be desirable from both an economical and a physiological point of view. The objective of this study was to obtain genetic parameters for test day (TD yields, and PS for the tropical breed Carora and to compare these with results from a standard 305-d-milk yield animal model. Four random regression models (RRM were used on a dataset composed of 95,606 TD records collected in Venezuela and tested to find the best fitting the data. Estimated daily heritabilities for milk yields ranged from 0.21 to 0.30, with the lowest values around the peak of lactation. Lactation repeatabilities ranged from 0.50 to 0.56. Correlations between the breeding values obtained with the RRM and the lactation model currently used in Venezuela [single trait Animal Model (stAM] are quite high and positive (Pearson correlation=0.71 and Spearman correlation=0.72. Correlations between PS and 305-d-milk yield estimated breeding values (EBV ranged from -0.18 (PS as the deviation of daily productions in the interval 50-279 days in milk from a point at the end of lactation to 0.52 (PS as EBV difference between the second and the first stage of lactation. The use of PS indexes accounting for milk yield may allow the selection of individuals able to express their potential genetic values in tropical environment, without incurring in excessive heat stress losses.

  15. The decay b{yields}sg at NLL in the standard model

    Energy Technology Data Exchange (ETDEWEB)

    Liniger, Patrick [Institut fuer theoretische Physik, Universitaet Bern, Bern (Switzerland). E-mail: liniger@itp.unibe.ch

    2001-06-01

    I present a standard model calculation of the decay rate {gamma}(b{yields}sg) (g denotes a gluon) at next-to-leading logarithms (NLL). In order to obtain a meaningful physical result, the decay b{yields}sgg and certain contributions of b{yields}sf-barf (where f are the light quark flavours u, d and s) have to be included as well. Numerically we obtain B{sup NLL}(b{yields}sg) (5.0{+-}1.0)x10{sup -3} which is more than a factor of two larger than the leading logarithmic result B{sup LL}(b{yields}sg) = (2.2{+-}0.8)x10{sup -3}. Furthermore, I consider the impact of this contribution on the charmless hadronic branching ratio B{sub c/}, which could be used to extract the CKM ratio vertical bar V{sub ub}/V{sub cb} vertical bar with more accuracy. Finally, I have a brief look at B{sub c/} in scenarios where the Wilson coefficient C{sub 8} is enhanced by new physics. (author)

  16. A new elliptic-parabolic yield surface model revised by an adaptive criterion for granular soils

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    An adaptive criterion for shear yielding as well as shear failure of soils is proposed in this paper to address the fact that most criteria,including the Mohr-Coulomb criterion,the Lade criterion and the Matsuoka-Nakai criterion,cannot agree well with the experimental results when the value of the intermediate principal stress parameter is too big.The new criterion can adjust an adaptive parameter based on the experimental results in order to make the theoretical calculations fit the test results more accurately.The original elliptic-parabolic yield surface model can capture both soil contraction and dilation behaviors.However,it normally over-predicts the soil strength due to its application of the Extended Mises criterion.A new elliptic-parabolic yield surface mode is presented in this paper,which introduces the adaptive criterion in three-dimensional principal stress space.The new model can well model the stress-strain behavior of soils under general stress conditions.Compared to the original model which can only simulate soil behavior under triaxial compression conditions,the new model can simulate soil behaviors under both triaxial compression conditions and general stress conditions.

  17. [On-site measurement of landfill gas yield and verification of IPCC model].

    Science.gov (United States)

    Luo, Yu-Xiang; Wang, Wei; Gao, Xing-Bao

    2009-11-01

    In order to obtain the accurate yield of landfill gas in Yulongkeng Landfill, Shenzhen, improved pumping test was conducted. The methane production rates of the influence region were figured out as 14.67 x 10(-5), 9.46 x 10(-5), 9.55 x 10(-5), and 4.28 x 10(-5) m3/(t x h), respectively. According to the methane production rate, the whole methane yield of Yulongkeng Landfill in 2005 was 322 m3/h, which indicated that Yulongkeng Landfill had went into stationary phase and the recycle of landfill gas was not valuable. IPCC model was verified by the measured data. Degradation half life of the waste was the key parameter concerned to the prediction accuracy of IPCC model. In China, the degradable waste in municipal solid waste was mainly kitchen waste leading to a short degradation period, which caused the degradation half life was shorter than the proposed value in IPCC model. For the improvement in prediction accuracy of landfill gas yield, the model parameters should be adopted reasonably based on a full survey of waste characterization in China, which will boost the applicability of IPCC model.

  18. An Evolutionary Model of Cooperation, Fairness and Altruistic Punishment in Public Good Games

    Science.gov (United States)

    Hetzer, Moritz; Sornette, Didier

    2013-01-01

    We identify and explain the mechanisms that account for the emergence of fairness preferences and altruistic punishment in voluntary contribution mechanisms by combining an evolutionary perspective together with an expected utility model. We aim at filling a gap between the literature on the theory of evolution applied to cooperation and punishment, and the empirical findings from experimental economics. The approach is motivated by previous findings on other-regarding behavior, the co-evolution of culture, genes and social norms, as well as bounded rationality. Our first result reveals the emergence of two distinct evolutionary regimes that force agents to converge either to a defection state or to a state of coordination, depending on the predominant set of self- or other-regarding preferences. Our second result indicates that subjects in laboratory experiments of public goods games with punishment coordinate and punish defectors as a result of an aversion against disadvantageous inequitable outcomes. Our third finding identifies disadvantageous inequity aversion as evolutionary dominant and stable in a heterogeneous population of agents endowed initially only with purely self-regarding preferences. We validate our model using previously obtained results from three independently conducted experiments of public goods games with punishment. PMID:24260101

  19. Canine cell line, IPC-366, as a good model for the study of inflammatory breast cancer.

    Science.gov (United States)

    Caceres, S; Peña, L; Lacerda, L; Illera, M J; de Andres, P J; Larson, R A; Gao, H; Debeb, B G; Woodward, W A; Reuben, J M; Illera, J C

    2017-09-01

    Inflammatory breast cancer (IBC) is an aggressive type of cancer with poor survival in women. Inflammatory mammary cancer (IMC) in dogs is very similar to human IBC and it has been proposed as a good surrogate model for study the human disease. The aim was to determine if IPC-366 shared characteristics with the IBC cell line SUM149. The comparison was conducted in terms of ability to grow (adherent and nonadherent conditions), stem cell markers expression using flow cytometry, protein production using western blot and tumorigenic capacity. Our results revealed that both are capable of forming long-term mammospheres with a grape-like morphology. Adherent and nonadherent cultures exhibited fast growth in vivo. Stem cell markers expressions showed that IPC-366 and SUM149 in adherent and nonadherent conditions has mesenchymal-like characteristics, E-cadherin and N-cadherin, was higher in adherent than in nonadherent cultures. Therefore, this study determines that both cell lines are similar and IPC-366 is a good model for the human and canine disease. © 2016 John Wiley & Sons Ltd.

  20. An evolutionary model of cooperation, fairness and altruistic punishment in public good games.

    Directory of Open Access Journals (Sweden)

    Moritz Hetzer

    Full Text Available We identify and explain the mechanisms that account for the emergence of fairness preferences and altruistic punishment in voluntary contribution mechanisms by combining an evolutionary perspective together with an expected utility model. We aim at filling a gap between the literature on the theory of evolution applied to cooperation and punishment, and the empirical findings from experimental economics. The approach is motivated by previous findings on other-regarding behavior, the co-evolution of culture, genes and social norms, as well as bounded rationality. Our first result reveals the emergence of two distinct evolutionary regimes that force agents to converge either to a defection state or to a state of coordination, depending on the predominant set of self- or other-regarding preferences. Our second result indicates that subjects in laboratory experiments of public goods games with punishment coordinate and punish defectors as a result of an aversion against disadvantageous inequitable outcomes. Our third finding identifies disadvantageous inequity aversion as evolutionary dominant and stable in a heterogeneous population of agents endowed initially only with purely self-regarding preferences. We validate our model using previously obtained results from three independently conducted experiments of public goods games with punishment.

  1. Assessing a brand equity model for fast moving consumer goods in cosmetic and hygiene industry

    Directory of Open Access Journals (Sweden)

    Alireza Karbasivar

    2014-11-01

    Full Text Available This paper presents an empirical investigation to study the effects of ten factors on brand equity. The study provides an assessment using a brand equity model for fast moving consumer goods in cosmetic and hygiene industry. The study has accomplished among people who purchase goods in six major cities of Iran based on an adapted questionnaire originally developed by Aaker (1992a [Aaker, D. A. (1992a. The value of brand equity. Journal of Business Strategy, 13(4, 27-32.]. Cronbach alpha has been calculated as 0.88, which is well above the minimum acceptable level of 0.7. In addition, Kaiser-Meyer-Olkin Measure of Sampling adequacy and Bartlett's test of Sphericity approximation Chi-Square are 0.878, 276628 with Sig. = 0.000, respectively. The proposed study of this paper uses structural equation modeling to test different hypotheses of the survey. The Root Mean Square Error of Approximation (RMSEA, Comparative Fit Index (CFI and Chi-Square/df are 0.067, 0.840 and 4.244 and they are within desirable levels. While the effects of seven factors on brand equity have been confirmed. However, the survey does not confirm the effects of perceived value, advertisement effectiveness and advertisement to brand on brand equity. In our survey, brand loyalty maintains the highest positive impact followed by having updated brand, trust to brand, perceived quality to brand, brand awareness, intensity of supply and perception to brand.

  2. Power and Contention Control Scheme: As a Good Candidate for Interference Modeling in Cognitive Radio Network

    Directory of Open Access Journals (Sweden)

    Ireyuwa E. Igbinosa

    2015-10-01

    Full Text Available Due to the ever growing need for spectrum, the cognitive radio (CR has been proposed to improve the radio spectrum utilization. In this scenario, the secondary users (SU are permitted to share spectrum with the licensed primary users (SU with a strict condition that they do not cause harmful interference to the cognitive network. In this work, we have proposed an interference model for cognitive radio network that utilizes power or contention control interference management schemes. We derived the probability density function (PDF with the power control scheme, where the power of transmission of the CR transmitter is guided by the power control law and also with contention control scheme that has a fixed transmission power for all CR transmitter controlled by a contention control protocol. This protocol makes a decision on which CR transmitter can transmit at any point in time. In this work, we have shown that power and contention control schemes are good candidates for interference modeling in cognitive radio system. The impact of the unknown location of the primary receiver on the resulting interference generated by the CR transmitters was investigated and the results shows that the challenges of the hidden primary receivers lead to higher CR-primary interference in respect to higher mean and variance. Finally, the presented results show power control and the contention control scheme are good candidates in reducing the interference generated by the cognitive radio network.

  3. Coupled Oscillator Model of the Business Cycle withFluctuating Goods Markets

    Science.gov (United States)

    Ikeda, Y.; Aoyama, H.; Fujiwara, Y.; Iyetomi, H.; Ogimoto, K.; Souma, W.; Yoshikawa, H.

    The sectoral synchronization observed for the Japanese business cycle in the Indices of Industrial Production data is an example of synchronization. The stability of this synchronization under a shock, e.g., fluctuation of supply or demand, is a matter of interest in physics and economics. We consider an economic system made up of industry sectors and goods markets in order to analyze the sectoral synchronization observed for the Japanese business cycle. A coupled oscillator model that exhibits synchronization is developed based on the Kuramoto model with inertia by adding goods markets, and analytic solutions of the stationary state and the coupling strength are obtained. We simulate the effects on synchronization of a sectoral shock for systems with different price elasticities and the coupling strengths. Synchronization is reproduced as an equilibrium solution in a nearest neighbor graph. Analysis of the order parameters shows that the synchronization is stable for a finite elasticity, whereas the synchronization is broken and the oscillators behave like a giant oscillator with a certain frequency additional to the common frequency for zero elasticity.

  4. Scientific Opinion on good modelling practice in the context of mechanistic effect models for risk assessment of plant protection products

    Directory of Open Access Journals (Sweden)

    EFSA Panel on Plant Protection Products and their Residues (PPR

    2014-03-01

    Full Text Available The Panel has interpreted the Terms of Reference as a stepwise analysis of issues relevant to both the development and the evaluation of models to assess ecological effects of pesticides. The regulatory model should be selected or developed to address the relevant specific protection goal. The basis of good modelling practice must be the knowledge of relevant processes and the availability of data of sufficient quality. The opinion identifies several critical steps in order to set models within risk assessment, namely: problem formulation, considering the specific protection goals for the taxa or functional groups of concern; model domain of applicability, which drives the species and scenarios to model; species (and life stage selection, considering relevant life history traits and toxicological/toxicokinetics characteristics of the pesticide; selection of the environmental scenario, which is defined by a combination of abiotic, biotic and agronomic parameters to provide a realistic worst-case situation. Model development should follow the modelling cycle, in which every step has to be fully documented: (i problem definition; (ii model formulation, i.e. design of a conceptual model; (iii model formalisation, in which variables and parameters are linked together into mathematical equations or algorithms; (iv model implementation, in which a computer code is produced and verified; (v model setup, including sensitivity analysis, uncertainty analysis and comparison with observed data, that delivers the regulatory model; (vi prior to actual use in risk assessment, the regulatory model should be evaluated for relevance to the specific protection goals; (vii feedback from risk assessor with possible recommendations for model improvement. Model evaluation by regulatory authorities should consider each step of the modelling cycle: the opinion identifies points of particular attention for the use of mechanistic effect models in pesticide risk assessment

  5. Inflow, Outflow, Yields, and Stellar Population Mixing in Chemical Evolution Models

    Science.gov (United States)

    Andrews, Brett H.; Weinberg, David H.; Schönrich, Ralph; Johnson, Jennifer A.

    2017-02-01

    Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the stellar initial mass function, the SN Ia delay time distribution, stellar yields, and stellar population mixing. Using flexCE, a flexible one-zone chemical evolution code, we investigate the effects of and trade-offs between parameters. Two critical parameters are SFE and the outflow mass-loading parameter, which shift the knee in [O/Fe]–[Fe/H] and the equilibrium abundances that the simulations asymptotically approach, respectively. One-zone models with simple star formation histories follow narrow tracks in [O/Fe]–[Fe/H] unlike the observed bimodality (separate high-α and low-α sequences) in this plane. A mix of one-zone models with inflow timescale and outflow mass-loading parameter variations, motivated by the inside-out galaxy formation scenario with radial mixing, reproduces the two sequences better than a one-zone model with two infall epochs. We present [X/Fe]–[Fe/H] tracks for 20 elements assuming three different supernova yield models and find some significant discrepancies with solar neighborhood observations, especially for elements with strongly metallicity-dependent yields. We apply principal component abundance analysis to the simulations and existing data to reveal the main correlations among abundances and quantify their contributions to variation in abundance space. For the stellar population mixing scenario, the abundances of α-elements and elements with metallicity-dependent yields dominate the first and second principal components, respectively, and collectively explain 99% of the variance in the model. flexCE is a python package available at https://github.com/bretthandrews/flexCE.

  6. Analysis of S Wave Propagation Through a Nonlinear Joint with the Continuously Yielding Model

    Science.gov (United States)

    Cui, Zhen; Sheng, Qian; Leng, Xianlun

    2017-01-01

    Seismic wave propagation through joints that are embedded in a rock mass is a critical issue for aseismic issues of underground rock engineering. Few studies have investigated nonlinear joints with a continuously yielding model. In this paper, a time-domain recursive method (TDRM) for an S wave across a nonlinear Mohr-Coulomb (MC) slip model is extended to a continuously yielding (CY) model. Verification of the TDRM-based results is conducted by comparison with the simulated results via a built-in model of 3DEC code. Using parametric studies, the effect of normal stress level, amplitude of incident wave, initial joint shear stiffness, and joint spacing is discussed and interpreted for engineering applications because a proper in situ stress level (overburden depth) and acceptable quality of surrounding rock mass are beneficial for seismic stability issues of underground rock excavation. Comparison between the results from the MC model and the CY model is presented both for an idealized impulse excitation and a real ground motion record. Compared with the MC model, complex joint behaviors, such as tangential stiffness degradation, normal stress dependence, and the hysteresis effect, that occurred in the wave propagation can be described with the CY model. The MC model seems to underestimate the joint shear displacement in a high normal stress state and in a real ground motion excitation case.

  7. Sediment Yields Revealed and Fluid Modelling by Twice LiDAR Surveys in Active Tectonics Area

    Science.gov (United States)

    Hsieh, Y.; Chan, Y.; Hu, J.; Lin, C.

    2010-12-01

    LiDAR technique allows rapid acquisition of high resolution and high precision topographic data. The technique has found considerable use in the earth sciences, for example for fluvial morphology and flood modelling. These developments have offered new opportunities for investigating spatial and temporal patterns of morphological change in gravel-bed river and have contributed to develop in two points: (1)morphometric estimates of sediment transport and sediment yields ;(2)boundary conditions for numerical models, including computational fluid dynamics and modelling. This topographic research funded by the Taiwan Central Geological Survey, surveyed the terrain of the Lanyang River before and after the typhoon season using Airborne LiDAR technique, and computed the terrain variations. The Lanyang River is one of main rivers in Taiwan and often suffers the influence of typhoon during summer. Most of sediments generated from slump and soil erosion into river were transported from the upstream watershed and resulted in the riverbed changes during the typhoon season. In 2008, there are four significant typhoon events influencing this area, including the Kalmaegi, Fung-wong, Sinlaku, and Jangmi typhoons. At present, sediment yield calculation often used empirical or theoretical formula as well as data collected at hydrological stations, and rarely had the actual measured value through high-resolution topography. The variations of the terrain on the riverbed may be regarded as the sediment yield of the bed load transported during the typhoon season. This research used high-resolution terrain models to compute sediment yield of the bed load, and further discussed volumes of sediment yield in watershed during the typhoon season. In the Lanyang River we discovered that the upstream and midstream channel still had the characteristics of erosion and transportation during the typhoon season. The results imply significant sediment yield and transportation from the upstream

  8. The power of a good idea: quantitative modeling of the spread of ideas from epidemiological models

    CERN Document Server

    Bettencourt, L M A; Kaiser, D I; Castillo-Chavez, C; Bettencourt, Lu\\'{i}s M.A.; Cintr\\'{o}n-Arias, Ariel; Kaiser, David I.; Castillo-Ch\\'{a}vez, Carlos

    2005-01-01

    The population dynamics underlying the diffusion of ideas hold many qualitative similarities to those involved in the spread of infections. In spite of much suggestive evidence this analogy is hardly ever quantified in useful ways. The standard benefit of modeling epidemics is the ability to estimate quantitatively population average parameters, such as interpersonal contact rates, incubation times, duration of infectious periods, etc. In most cases such quantities generalize naturally to the spread of ideas and provide a simple means of quantifying sociological and behavioral patterns. Here we apply several paradigmatic models of epidemics to empirical data on the advent and spread of Feynman diagrams through the theoretical physics communities of the USA, Japan, and the USSR in the period immediately after World War II. This test case has the advantage of having been studied historically in great detail, which allows validation of our results. We estimate the effectiveness of adoption of the idea in the thr...

  9. How Bad/Good Are the External Forward Shock Models of Gamma-Ray Bursts?

    CERN Document Server

    Wang, Xiang-Gao; Liang, En-Wei; Gao, He; Li, Liang; Deng, Can-Min; Qin, Song-Mei; Tang, Qing-Wen; Kann, D Alexander; Ryde, Felix; Kumar, Pawan

    2015-01-01

    The external forward shock (EFS) models have been the standard paradigm to interpret the broad-band afterglow data of gamma-ray bursts (GRBs). One prediction of the models is that some afterglow temporal breaks at different energy bands should be achromatic. Observations in the Swift era have revealed chromatic afterglow behaviors at least in some GRBs, casting doubts on the EFS origin of GRB afterglows. In this paper, we perform a systematic study to address the question: how bad/good are the external forward shock models? Our sample includes 85 GRBs well-monitored X-ray and optical lightcurves. Based on how well the data abide by the EFS models, we categorize them as: Gold sample: (Grade I and II) include 45/85 GRBs. They show evidence of, or are consistent with having, an achromatic break. The temporal/spectral behaviors in each afterglow segment are consistent with the predictions (closure relations) of the EFS models. Silver sample: (Grade III and IV) include 37/85 GRBs. They are also consistent with hav...

  10. A viscoelastic-plastic constitutive model with Mohr-Coulomb yielding criterion for sea ice dynamics

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    A new viscoelastic-plastic (VEP) constitutive model for sea ice dynamics was developed based on continuum mechanics. This model consists of four components: Kelvin-Vogit viscoelastic model, Mohr-Coulomb yielding criterion, associated normality flow rule for plastic rehololgy, and hydrostatic pressure. The numerical simulations for ice motion in an idealized rectangular basin were made using smoothed particle hydrodynamics (SPH) method, and compared with the analytical solution as well as those based on the modified viscous plastic(VP) model and static ice jam theory. These simulations show that the new VEP modelcan simulate ice dynamics accurately. The new constitutive model was further applied to simulate ice dynamics of the Bohai Sea and compared with the traditional VP, and modified VP models. The results of the VEP model are compared better with the satellite remote images, and the simulated ice conditions in the JZ20-2 oil platform area were more reasonable.

  11. Good modeling practice for PAT applications: propagation of input uncertainty and sensitivity analysis.

    Science.gov (United States)

    Sin, Gürkan; Gernaey, Krist V; Lantz, Anna Eliasson

    2009-01-01

    The uncertainty and sensitivity analysis are evaluated for their usefulness as part of the model-building within Process Analytical Technology applications. A mechanistic model describing a batch cultivation of Streptomyces coelicolor for antibiotic production was used as case study. The input uncertainty resulting from assumptions of the model was propagated using the Monte Carlo procedure to estimate the output uncertainty. The results showed that significant uncertainty exists in the model outputs. Moreover the uncertainty in the biomass, glucose, ammonium and base-consumption were found low compared to the large uncertainty observed in the antibiotic and off-gas CO(2) predictions. The output uncertainty was observed to be lower during the exponential growth phase, while higher in the stationary and death phases - meaning the model describes some periods better than others. To understand which input parameters are responsible for the output uncertainty, three sensitivity methods (Standardized Regression Coefficients, Morris and differential analysis) were evaluated and compared. The results from these methods were mostly in agreement with each other and revealed that only few parameters (about 10) out of a total 56 were mainly responsible for the output uncertainty. Among these significant parameters, one finds parameters related to fermentation characteristics such as biomass metabolism, chemical equilibria and mass-transfer. Overall the uncertainty and sensitivity analysis are found promising for helping to build reliable mechanistic models and to interpret the model outputs properly. These tools make part of good modeling practice, which can contribute to successful PAT applications for increased process understanding, operation and control purposes.

  12. Simulating potential growth and yield of oil palm (Elaeis guineensis) with PALMSIM: Model description, evaluation and application

    NARCIS (Netherlands)

    Hoffmann, M.; Castaneda Vera, A.; Wijk, van M.T.; Giller, K.E.; Oberthür, T.; Donough, C.; Whitbread, A.M.

    2014-01-01

    Reducing the gap between water-limited potential yield and actual yield in oil palm production systems through intensification is seen as an important option for sustainably increasing palm oil production. Simulation models can play an important role in quantifying water-limited potential yield, and

  13. Simulating yield response of rice to salinity stress with the AquaCrop model.

    Science.gov (United States)

    Mondal, M Shahjahan; Saleh, Abul Fazal M; Razzaque Akanda, Md Abdur; Biswas, Sujit K; Md Moslehuddin, Abu Zofar; Zaman, Sinora; Lazar, Attila N; Clarke, Derek

    2015-06-01

    The FAO AquaCrop model has been widely applied throughout the world to simulate crop responses to deficit water applications. However, its application to saline conditions is not yet reported, though saline soils are common in coastal areas. In this study, we parameterized and tested AquaCrop to simulate rice yield under different salinity regimes. The data and information required in the model were collected through a field experiment at the Bangladesh Agricultural Research Institute, Gazipur. The experiment was conducted with the BRRI Dhan28, a popular boro rice variety in Bangladesh, with five levels of saline water irrigation, three replicates for each level. In addition, field monitoring was carried out at Satkhira in the southwest coastal region of Bangladesh to collect data and information based on farmers' practices and to further validate the model. The results indicated that the AquaCrop model with most of its default parameters could replicate the variation of rice yield with the variation of salinity reasonably well. The root mean square error and mean absolute error of the model yield were only 0.12 t per ha and 0.03 t per ha, respectively. The crop response versus soil salinity stress curve was found to be convex in shape with a lower threshold of 2 dS m(-1), an upper threshold of 10 dS m(-1) and a shape factor of 2.4. As the crop production system in the coastal belt of Bangladesh has become vulnerable to climate induced sea-level rise and the consequent increase in water and soil salinity, the AquaCrop would be a useful tool in assessing the potential impact of these future changes as well as other climatic parameters on rice yield in the coastal region.

  14. Modelling the long term water yield impact of fire in Eucalypt forests

    Science.gov (United States)

    Lane, Patrick; Fiekema, Paul; Sherwin, Chris; Peel, Murray; Freebairn, Andrew

    2010-05-01

    Disturbance of forested catchments by fire, logging, or other natural or human induced events that alter the evapotranspiration regime may be a substantial threat to domestic, environmental and industrial water supplies. This study involves physically-based modelling of the long term changes in water yield from two wild fire affected catchments in north-eastern Victoria, Australia, and of fire and climate change scenarios in Melbourne's principal water supply catchment. The effect of scale, data availability and quality, and of forest species parameterisation are explored. The modelling demonstrates the importance of precipitation inputs, with Nash and Sutcliffe Coefficients of Efficiency of predicted versus observed monthly flows increasing from 0.5 to 0.8 with a higher density of rainfall stations, and where forest types are well parameterised. Total predicted flow volumes for the calibrations were within 1% of the observed for the Mitta Mitta River catchment and wildfire and climate change. For example, for the catchments modelled the moderate climate change impact on water yield was more pronounced than the worst fire scenario. Both modelled cases resulted in long term water yield declines exceeding 20%, with the climate change impact nearing 30%. A simulation using observed data for the first four post-fire years at the Mitta Mitta River catchment showed Macaque was able to accurately predict total flow.

  15. Application of a CROPWAT Model to Analyze Crop Yields in Nicaragua

    Science.gov (United States)

    Doria, R.; Byrne, J. M.

    2013-12-01

    ABSTRACT Changes in climate are likely to influence crop yields due to varying evapotranspiration and precipitation over agricultural regions. In Nicaragua, agriculture is extensive, with new areas of land brought into production as the population increases. Nicaraguan staple food items (maize and beans) are produced mostly by small scale farmers with less than 10 hectares, but they are critical for income generation and food security for rural communities. Given that the majority of these farmers are dependent on rain for crop irrigation, and that maize and beans are sensitive to variations in temperature and rainfall patterns, the present study was undertaken to assess the impact of climate change on these crop yields. Climate data were generated per municipio representing the three major climatic zones of the country: the wet Pacific lowland, the cooler Central highland, and the Caribbean lowland. Historical normal climate data from 1970-2000 (baseline period) were used as input to CROPWAT model to analyze the potential and actual evapotranspiration (ETo and ETa, respectively) that affects crop yields. Further, generated local climatic data of future years (2030-2099) under various scenarios were inputted to the CROPWAT to determine changes in ETo and ETa from the baseline period. Spatial variability maps of both ETo and ETa as well as crop yields were created. Results indicated significant variation in seasonal rainfall depth during the baseline period and predicted decreasing trend in the future years that eventually affects yields. These maps enable us to generate appropriate adaptation measures and best management practices for small scale farmers under future climate change scenarios. KEY WORDS: Climate change, evapotranspiration, CROPWAT, yield, Nicaragua

  16. MODELLING GROWTH AND YIELD OF Pinus taeda L. USING DIFUSION PROCESS

    Directory of Open Access Journals (Sweden)

    Rozane de Loyola Eisfeld

    2005-06-01

    Full Text Available This work tested a methodology for growth and yield modeling. The diffusion process is not yet widely used incommercial plantations in Brazil, but it can provide predictions comparable to others methodologies, producing satisfactory resultsto simulate growth and yield. For this purpose, 325 permanent samples established in unthinned Pinus taeda L. (loblolly pine standsowned by the International Paper of Brazil Co were used. The diffusion process methodology consists in connecting growthincrement and mortality models in Kolmogorov equation . Seventy sample plots were randomly chosen in order to make thecomparison among the observed and predicted values. In general, the diffusion process provided satisfactory estimates of number oftrees, basal area per hectare and stem volume.

  17. Dynamic visco-plastic memorial nested yield surface model of soil

    Institute of Scientific and Technical Information of China (English)

    Haiyang ZHUANG; Guoxing CHEN; Dinghua ZHU

    2008-01-01

    Under cyclic loadings, the plastic strain of soft soil will take place under very small shear strain. So the viscoplastic model is appropriate to be used to model the dynamic characteristics of soft soil. Based on the principles of geotechnical plastic mechanics, the incremental visco-plastic memorial nested yield surface model is developed by using the field theory of nonlinear isotropic materials and the theory of kinematical hardening modulus. At the end of anyone time increment, the inverted loading surface, the damaged surface and the initial loading surface which is tangent with the inside of inverted loading surface are memorized respectively. The kinematical behavior of yield surface is defined by using these three surfaces. The developed model in this paper is successfully implemented in ABAQUS using FORTRAN subroutine. The predicted stress-strain relationships of soft soil are compared with the test results given by dynamic triaxial tests. It is proved that the cyclic undrained stress-strain relation of soils can be fairly simulated by the model. At last, the nonlinear earthquake response of a representative soft site in Nanjing city is calculated with the dynamic behavior of soils modeled by the new developed model. The results are accordant to the earthquake response of soft site given by other scholars.

  18. Analysis of a Regularized Bingham Model with Pressure-Dependent Yield Stress

    Science.gov (United States)

    El Khouja, Nazek; Roquet, Nicolas; Cazacliu, Bogdan

    2015-12-01

    The goal of this article is to provide some essential results for the solution of a regularized viscoplastic frictional flow model adapted from the extensive mathematical analysis of the Bingham model. The Bingham model is a standard for the description of viscoplastic flows and it is widely used in many application areas. However, wet granular viscoplastic flows necessitate the introduction of additional non-linearities and coupling between velocity and stress fields. This article proposes a step toward a frictional coupling, characterized by a dependence of the yield stress to the pressure field. A regularized version of this viscoplastic frictional model is analysed in the framework of stationary flows. Existence, uniqueness and regularity are investigated, as well as finite-dimensional and algorithmic approximations. It is shown that the model can be solved and approximated as far as a frictional parameter is small enough. Getting similar results for the non-regularized model remains an issue. Numerical investigations are postponed to further works.

  19. Predicting the ratcheting strain of 304 stainless steel by considering yield surface distortion and using a viscoplastic model

    Energy Technology Data Exchange (ETDEWEB)

    Ahmadi, Nabi; Nayebi, Ali [Shiraz University, Shiraz (Iran, Islamic Republic of)

    2015-07-15

    Yield surface distortion and its center movement were employed in a unified viscoplastic model to predict the ratcheting behavior of the 304 stainless steel. A combination of the Ohno-Wang model and the yield surface distortion model of Baltov and Sawczuk was used in uniaxial loading. Stress amplitude and the mean stress were varied in the tests to verify the model. Uniaxial loadings were simulated with and without consideration of yield surface distortion. Results from both simulations were compared. Yield surface distortion showed a significant effect on the simulation of the ratcheting responses.

  20. Bayesian inference of baseline fertility and treatment effects via a crop yield-fertility model.

    Directory of Open Access Journals (Sweden)

    Hungyen Chen

    Full Text Available To effectively manage soil fertility, knowledge is needed of how a crop uses nutrients from fertilizer applied to the soil. Soil quality is a combination of biological, chemical and physical properties and is hard to assess directly because of collective and multiple functional effects. In this paper, we focus on the application of these concepts to agriculture. We define the baseline fertility of soil as the level of fertility that a crop can acquire for growth from the soil. With this strict definition, we propose a new crop yield-fertility model that enables quantification of the process of improving baseline fertility and the effects of treatments solely from the time series of crop yields. The model was modified from Michaelis-Menten kinetics and measured the additional effects of the treatments given the baseline fertility. Using more than 30 years of experimental data, we used the Bayesian framework to estimate the improvements in baseline fertility and the effects of fertilizer and farmyard manure (FYM on maize (Zea mays, barley (Hordeum vulgare, and soybean (Glycine max yields. Fertilizer contributed the most to the barley yield and FYM contributed the most to the soybean yield among the three crops. The baseline fertility of the subsurface soil was very low for maize and barley prior to fertilization. In contrast, the baseline fertility in this soil approximated half-saturated fertility for the soybean crop. The long-term soil fertility was increased by adding FYM, but the effect of FYM addition was reduced by the addition of fertilizer. Our results provide evidence that long-term soil fertility under continuous farming was maintained, or increased, by the application of natural nutrients compared with the application of synthetic fertilizer.

  1. An RF Performance Sensitivity and Process Yield Model for MIMIC CAD applications. MIMIC Program. Phase 3

    Science.gov (United States)

    1991-09-16

    center of a hypersphere which is contained within the polyhedron. Bandler and Abdel-Malek [25, 26, 27] approximated the acceptability region with...multicircuit approach to modeling the region of acceptability was introduced by Bandler et al. [28] who used a group of circuit designs to approximate...the region of acceptability. Bandler and Chen [29] then used generalized 4, centering to optimize yield. In generalized 4p centering, a 4p error

  2. Genetic Parameters for Milk Yield and Lactation Persistency Using Random Regression Models in Girolando Cattle.

    Science.gov (United States)

    Canaza-Cayo, Ali William; Lopes, Paulo Sávio; da Silva, Marcos Vinicius Gualberto Barbosa; de Almeida Torres, Robledo; Martins, Marta Fonseca; Arbex, Wagner Antonio; Cobuci, Jaime Araujo

    2015-10-01

    A total of 32,817 test-day milk yield (TDMY) records of the first lactation of 4,056 Girolando cows daughters of 276 sires, collected from 118 herds between 2000 and 2011 were utilized to estimate the genetic parameters for TDMY via random regression models (RRM) using Legendre's polynomial functions whose orders varied from 3 to 5. In addition, nine measures of persistency in milk yield (PSi) and the genetic trend of 305-day milk yield (305MY) were evaluated. The fit quality criteria used indicated RRM employing the Legendre's polynomial of orders 3 and 5 for fitting the genetic additive and permanent environment effects, respectively, as the best model. The heritability and genetic correlation for TDMY throughout the lactation, obtained with the best model, varied from 0.18 to 0.23 and from -0.03 to 1.00, respectively. The heritability and genetic correlation for persistency and 305MY varied from 0.10 to 0.33 and from -0.98 to 1.00, respectively. The use of PS7 would be the most suitable option for the evaluation of Girolando cattle. The estimated breeding values for 305MY of sires and cows showed significant and positive genetic trends. Thus, the use of selection indices would be indicated in the genetic evaluation of Girolando cattle for both traits.

  3. Modeling the Impacts of Soil Organic Carbon Content of Croplands on Crop Yields in China

    Institute of Scientific and Technical Information of China (English)

    QIU Jian-jun; WANG Li-gang; LI Hu; TANG Hua-jun; LI Chang-sheng; Eric Van Ranst

    2009-01-01

    This study quantified the impacts of soil organic carbon(SOC)content on the grain yield of crops using a biogeochemical model(DNDC,denitrification-decomposition).Data on climate,soil properties,and farming management regimes of cropping systems were collected from six typical agricultural zones(northeast,north,northwest,mid-south,east and southwest regions of China,respectively)and integrated into a GIS database to support the model runs.According to the model,if the initial SOC content in the cropland was increased by 1g C kg-1,the crop yield may be increased by 176 kg ha-1 for maize in the northeast region,454 kg ha-1 for a maize-wheat rotation in the north region,328 kg ha-1 for maize in the northwest region,185 kg ha-1 for single-rice in the mid-south region,266 kg ha-1 for double-rice in east region,and 229 kg ha-1 for rice and wheat rotation in southwest region.There is a great potential for enhancing the crop yield by improving the SOC content in each region of China.

  4. Sorghum production under future climate in the Southwestern USA: model projections of yield, greenhouse gas emissions and soil C fluxes

    Science.gov (United States)

    Duval, B.; Ghimire, R.; Hartman, M. D.; Marsalis, M.

    2016-12-01

    Large tracts of semi-arid land in the Southwestern USA are relatively less important for food production than the US Corn Belt, and represent a promising area for expansion of biofuel/bioproduct crops. However, high temperatures, low available water and high solar radiation in the SW represent a challenge to suitable feedstock development, and future climate change scenarios predict that portions of the SW will experience increased temperature and temporal shifts in precipitation distribution. Sorghum (Sorghum bicolor) is a valuable forage crop with promise as a biofuel feedstock, given its high biomass under semi-arid conditions, relatively lower N fertilizer requirements compared to corn, and salinity tolerance. To evaluate the environmental impact of expanded sorghum cultivation under future climate in the SW USA, we used the DayCent model in concert with a suite of downscaled future weather projections to predict biogeochemical consequences (greenhouse gas flux and impacts on soil carbon) of sorghum cultivation in New Mexico. The model showed good correspondence with yield data from field trials including both dryland and irrigated sorghum (measured vs. modeled; r2 = 0.75). Simulation experiments tested the effect of dryland production versus irrigation, low N versus high N inputs and delayed fertilizer application. Nitrogen application timing and irrigation impacted yield and N2O emissions less than N rate and climate. Across N and irrigation treatments, future climate simulations resulted in 6% increased yield and 20% lower N2O emissions compared to current climate. Soil C pools declined under future climate. The greatest declines in soil C were from low N input sorghum simulations, regardless of irrigation (>20% declines in SOM in both cases), and requires further evaluation to determine if changing future climate is driving these declines, or if they are a function of prolonged sorghum-fallow rotations in the model. The relatively small gain in yield for

  5. A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.

    Directory of Open Access Journals (Sweden)

    M Irfan Ashraf

    Full Text Available Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model. Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2 5-year(-1 and volume: 0.0008 m(3 5-year(-1. Model variability described by root mean squared error (RMSE in basal area prediction was 40.53 cm(2 5-year(-1 and 0.0393 m(3 5-year(-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence

  6. Warren-Spring based model for the shear yield locus of cohesive biomass powders

    Science.gov (United States)

    Vanneste-Ibarcq, Clément; Melkior, Thierry; de Ryck, Alain

    2017-06-01

    The objectives of this work are to determine accurately the cohesion of biomass powders from simple measures and to propose a new method for the description of the yield locus of powders with easy to measure parameters. The cohesion of 32 powders (wood, other biomasses and inorganic powders) have been analysed with two methods. The first method is the determination of the yield locus from shear tests at 3 kPa, performed with a powder rheometer, which gives an access to parameters such as cohesion (Y-intercept) and traction (X-intercept). The second method is the measurement of avalanche angles in a rotating drum. A linear relation is found between this angle and the cohesion length, ratio of the cohesion derived from the yield locus and the aerated density. Finally, a model is proposed for the prediction of the cohesion and the yield locus at 3 kPa, using only 2 parameters easy to measure: the avalanche angle and the aerated density.

  7. Goodness-of-fit tests for vector autoregressive models in time series

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The paper proposes and studies some diagnostic tools for checking the goodness-of-fit of general parametric vector autoregressive models in time series. The resulted tests are asymptotically chi-squared under the null hypothesis and can detect the alternatives converging to the null at a parametric rate. The tests involve weight functions,which provides us with the flexibility to choose scores for enhancing power performance,especially under directional alternatives. When the alternatives are not directional,we construct asymptotically distribution-free maximin tests for a large class of alternatives. A possibility to construct score-based omnibus tests is discussed when the alternative is saturated. The power performance is also investigated. In addition,when the sample size is small,a nonparametric Monte Carlo test approach for dependent data is proposed to improve the performance of the tests. The algorithm is easy to implement. Simulation studies and real applications are carried out for illustration.

  8. Identification of Amino Acid Sequences with Good Folding Properties in an Off-Lattice Model

    CERN Document Server

    Irbäck, Anders; Potthast, Frank

    2008-01-01

    Folding properties of a two-dimensional toy protein model containing only two amino-acid types, hydrophobic and hydrophilic, respectively, are analyzed. An efficient Monte Carlo procedure is employed to ensure that the ground states are found. The thermodynamic properties are found to be strongly sequence dependent in contrast to the kinetic ones. Hence, criteria for good folders are defined entirely in terms of thermodynamic fluctuations. With these criteria sequence patterns that fold well are isolated. For 300 chains with 20 randomly chosen binary residues approximately 10% meet these criteria. Also, an analysis is performed by means of statistical and artificial neural network methods from which it is concluded that the folding properties can be predicted to a certain degree given the binary numbers characterizing the sequences.

  9. How Bad or Good Are the External Forward Shock Afterglow Models of Gamma-Ray Bursts?

    Science.gov (United States)

    Wang, Xiang-Gao; Zhang, Bing; Liang, En-Wei; Gao, He; Li, Liang; Deng, Can-Min; Qin, Song-Mei; Tang, Qing-Wen; Kann, D. Alexander; Ryde, Felix; Kumar, Pawan

    2015-07-01

    The external forward shock models have been the standard paradigm to interpret the broadband afterglow data of gamma-ray bursts (GRBs). One prediction of the models is that some afterglow temporal breaks at different energy bands should be achromatic; that is, the break times should be the same in different frequencies. Multiwavelength observations in the Swift era have revealed chromatic afterglow behaviors at least in some GRBs, casting doubts on the external forward shock origin of GRB afterglows. In this paper, using a large sample of GRBs with both X-ray and optical afterglow data, we perform a systematic study to address the question: how bad or good are the external forward shock models? Our sample includes 85 GRBs up to 2014 March with well-monitored X-ray and optical light curves. Based on how well the data abide by the external forward shock models, we categorize them into five grades and three samples. The first two grades (Grade I and II) include 45 of 85 GRBs. They show evidence of, or are consistent with having, an achromatic break. The temporal and spectral behaviors in each afterglow segment are consistent with the predictions (the “closure relations”) of the forward shock models. These GRBs are included in the Gold sample. The next two grades (Grade III and IV) include 37 of 85 GRBs. They are also consistent with having an achromatic break, even though one or more afterglow segments do not comply with the closure relations. These GRBs are included in the Silver sample. Finally, Grade V (3/85) shows direct evidence of chromatic behaviors, suggesting that the external shock models are inconsistent with the data. These are included in the Bad sample. We further perform statistical analyses of various observational properties (temporal index α, spectral index β, break time tb) and model parameters (energy injection index q, electron spectral index p, jet opening angle {θ }j, radiative efficiency ηγ, and so on) of the GRBs in the Gold sample

  10. Advanced model for the prediction of the neutron-rich fission product yields

    Directory of Open Access Journals (Sweden)

    Rubchenya V. A.

    2013-12-01

    Full Text Available The consistent models for the description of the independent fission product formation cross sections in the spontaneous fission and in the neutron and proton induced fission at the energies up to 100 MeV is developed. This model is a combination of new version of the two-component exciton model and a time-dependent statistical model for fusion-fission process with inclusion of dynamical effects for accurate calculations of nucleon composition and excitation energy of the fissioning nucleus at the scission point. For each member of the compound nucleus ensemble at the scission point, the primary fission fragment characteristics: kinetic and excitation energies and their yields are calculated using the scission-point fission model with inclusion of the nuclear shell and pairing effects, and multimodal approach. The charge distribution of the primary fragment isobaric chains was considered as a result of the frozen quantal fluctuations of the isovector nuclear matter density at the scission point with the finite neck radius. Model parameters were obtained from the comparison of the predicted independent product fission yields with the experimental results and with the neutron-rich fission product data measured with a Penning trap at the Accelerator Laboratory of the University of Jyväskylä (JYFLTRAP.

  11. Evaluation of Thompson-type trend and monthly weather data models for corn yields in Iowa, Illinois, and Indiana

    Science.gov (United States)

    French, V. (Principal Investigator)

    1982-01-01

    An evaluation was made of Thompson-Type models which use trend terms (as a surrogate for technology), meteorological variables based on monthly average temperature, and total precipitation to forecast and estimate corn yields in Iowa, Illinois, and Indiana. Pooled and unpooled Thompson-type models were compared. Neither was found to be consistently superior to the other. Yield reliability indicators show that the models are of limited use for large area yield estimation. The models are objective and consistent with scientific knowledge. Timely yield forecasts and estimates can be made during the growing season by using normals or long range weather forecasts. The models are not costly to operate and are easy to use and understand. The model standard errors of prediction do not provide a useful current measure of modeled yield reliability.

  12. Safety assessment of dangerous goods transport enterprise based on the relative entropy aggregation in group decision making model.

    Science.gov (United States)

    Wu, Jun; Li, Chengbing; Huo, Yueying

    2014-01-01

    Safety of dangerous goods transport is directly related to the operation safety of dangerous goods transport enterprise. Aiming at the problem of the high accident rate and large harm in dangerous goods logistics transportation, this paper took the group decision making problem based on integration and coordination thought into a multiagent multiobjective group decision making problem; a secondary decision model was established and applied to the safety assessment of dangerous goods transport enterprise. First of all, we used dynamic multivalue background and entropy theory building the first level multiobjective decision model. Secondly, experts were to empower according to the principle of clustering analysis, and combining with the relative entropy theory to establish a secondary rally optimization model based on relative entropy in group decision making, and discuss the solution of the model. Then, after investigation and analysis, we establish the dangerous goods transport enterprise safety evaluation index system. Finally, case analysis to five dangerous goods transport enterprises in the Inner Mongolia Autonomous Region validates the feasibility and effectiveness of this model for dangerous goods transport enterprise recognition, which provides vital decision making basis for recognizing the dangerous goods transport enterprises.

  13. Comparing the Goodness of Different Statistical Criteria for Evaluating the Soil Water Infiltration Models

    Directory of Open Access Journals (Sweden)

    S. Mirzaee

    2016-02-01

    Full Text Available Introduction: The infiltration process is one of the most important components of the hydrologic cycle. Quantifying the infiltration water into soil is of great importance in watershed management. Prediction of flooding, erosion and pollutant transport all depends on the rate of runoff which is directly affected by the rate of infiltration. Quantification of infiltration water into soil is also necessary to determine the availability of water for crop growth and to estimate the amount of additional water needed for irrigation. Thus, an accurate model is required to estimate infiltration of water into soil. The ability of physical and empirical models in simulation of soil processes is commonly measured through comparisons of simulated and observed values. For these reasons, a large variety of indices have been proposed and used over the years in comparison of infiltration water into soil models. Among the proposed indices, some are absolute criteria such as the widely used root mean square error (RMSE, while others are relative criteria (i.e. normalized such as the Nash and Sutcliffe (1970 efficiency criterion (NSE. Selecting and using appropriate statistical criteria to evaluate and interpretation of the results for infiltration water into soil models is essential because each of the used criteria focus on specific types of errors. Also, descriptions of various goodness of fit indices or indicators including their advantages and shortcomings, and rigorous discussions on the suitability of each index are very important. The objective of this study is to compare the goodness of different statistical criteria to evaluate infiltration of water into soil models. Comparison techniques were considered to define the best models: coefficient of determination (R2, root mean square error (RMSE, efficiency criteria (NSEI and modified forms (such as NSEjI, NSESQRTI, NSElnI and NSEiI. Comparatively little work has been carried out on the meaning and

  14. Decay t {yields} bWZ within the context of the left-right mirror model

    Energy Technology Data Exchange (ETDEWEB)

    Fernandez de Cordoba, P. [Departamento de Matematica Aplicada, Universidad Politecnica de Valencia, Spain (Spain); Gaitan L, R. [Centro de Investigaciones Teoricas, Facultad de Estudios Superiores, Universidad Nacional Autonoma de Mexico, Apartado Postal 142, Cuautitlan-lzcalli, 54700 Estado de Mexico (Mexico); Hernandez G, A.; Rivera R, J.M. [Departamento de Fisica, Escuela Superior de Fisica y Matematicas, Instituto Politecnico Nacional, U.P. Adolfo Lopez Mateos, 07738 Mexico, D.F. (Mexico)

    2004-07-01

    In this paper the left-right mirror model is applied to the decay t {yields} bWZ, according to the Feynman rules given by the model. We write the corresponding width in compact form in terms of the Standard Model width by assuming the contribution to the WZW vertex being of the same order of magnitude as that of the t Zt and b Zb vertices. The width has to be compared with recent experimental data in order to get preliminary values for the parameters of the model, since these quantities have not been measured yet. With the appropriate rules given by the model we can deal with other related decays and improve results.

  15. Modeling Long Term Corn Yield Response to Nitrogen Rate and Crop Rotation

    Directory of Open Access Journals (Sweden)

    Laila Alejandra Puntel

    2016-11-01

    Full Text Available Improved prediction of optimal N fertilizer rates for corn (Zea mays L. can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM to simulate corn and soybean (Glycine max L. yields, the economic optimum N rate (EONR using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha-1 applied to corn. Our objectives were to: a quantify model prediction accuracy before and after calibration, and report calibration steps; b compare crop model-based techniques in estimating optimal N rate for corn; and c utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simultaneously simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration, which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration. For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-yr mean differences in EONR’s were within the historical N rate error range (40 to 50 kg N ha-1. However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching with precipitation. We concluded that long term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add

  16. Modeling Long-Term Corn Yield Response to Nitrogen Rate and Crop Rotation.

    Science.gov (United States)

    Puntel, Laila A; Sawyer, John E; Barker, Daniel W; Dietzel, Ranae; Poffenbarger, Hanna; Castellano, Michael J; Moore, Kenneth J; Thorburn, Peter; Archontoulis, Sotirios V

    2016-01-01

    Improved prediction of optimal N fertilizer rates for corn (Zea mays L.) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean (Glycine max L.) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha(-1)) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR's were within the historical N rate error range (40-50 kg N ha(-1)). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward

  17. Applying the Bollen-Stine Bootstrap for Goodness-of-Fit Measures to Structural Equation Models with Missing Data.

    Science.gov (United States)

    Enders, Craig K.

    2002-01-01

    Proposed a method for extending the Bollen-Stine bootstrap model (K. Bollen and R. Stine, 1992) fit to structural equation models with missing data. Developed a Statistical Analysis System macro program to implement this procedure, and assessed its usefulness in a simulation. The new method yielded model rejection rates close to the nominal 5%…

  18. Linking individual-tree and whole-stand models for forest growth and yield prediction

    Directory of Open Access Journals (Sweden)

    Quang V Cao

    2014-10-01

    Full Text Available Background Different types of growth and yield models provide essential information for making informed decisions on how to manage forests. Whole-stand models often provide well-behaved outputs at the stand level, but lack information on stand structures. Detailed information from individual-tree models and size-class models typically suffers from accumulation of errors. The disaggregation method, in assuming that predictions from a whole-stand model are reliable, partitions these outputs to individual trees. On the other hand, the combination method seeks to improve stand-level predictions from both whole-stand and individual-tree models by combining them. Methods Data from 100 plots randomly selected from the Southwide Seed Source Study of loblolly pine (Pinus taeda L. were used to evaluate the unadjusted individual-tree model against the disaggregation and combination methods. Results Compared to the whole-stand model, the combination method did not show improvements in predicting stand attributes in this study. The combination method also did not perform as well as the disaggregation method in tree-level predictions. The disaggregation method provided the best predictions of tree- and stand-level survival and growth. Conclusions The disaggregation approach provides a link between individual-tree models and whole-stand models, and should be considered as a better alternative to the unadjusted tree model.

  19. Modelling and Forecasting of Rice Yield in support of Crop Insurance

    Science.gov (United States)

    Weerts, A.; van Verseveld, W.; Trambauer, P.; de Vries, S.; Conijn, S.; van Valkengoed, E.; Hoekman, D.; Hengsdijk, H.; Schrevel, A.

    2016-12-01

    The Government of Indonesia has embarked on a policy to bring crop insurance to all of Indonesia's farmers. To support the Indonesian government, the G4INDO project (www.g4indo.org) is developing/constructing an integrated platform for judging and handling insurance claims. The platform consists of bringing together remote sensed data (both visible and radar) and hydrologic and crop modelling and forecasting to improve predictions in one forecasting platform (i.e. Delft-FEWS, Werner et al., 2013). The hydrological model and crop model (LINTUL) are coupled on time stepping basis in the OpenStreams framework (see https://github.com/openstreams/wflow) and deployed in a Delft-FEWS forecasting platform to support seasonal forecasting of water availability and crop yield. First we will show the general idea about the project, the integrated platform (including Sentinel 1 & 2 data) followed by first (reforecast) results of the coupled models for predicting water availability and crop yield in the Brantas catchment in Java, Indonesia. Werner, M., Schellekens, J., Gijsbers, P., Van Dijk, M., Van den Akker, O. and Heynert K, 2013. The Delft-FEWS flow forecasting system, Environmental Modelling & Software; 40:65-77. DOI: 10.1016/j.envsoft.2012.07.010 .

  20. Optimization of grapevine yield by applying mathematical models to obtain quality wine products

    Science.gov (United States)

    Alina, Dobrei; Alin, Dobrei; Eleonora, Nistor; Teodor, Cristea; Marius, Boldea; Florin, Sala

    2016-06-01

    Relationship between the crop load and the grape yield and quality is a dynamic process, specific for wine cultivars and for fresh consumption varieties. Modeling these relations is important for the improvement of technological works. This study evaluated the interrelationship of crop load (B - buds number) and several production parameters (Y - yield; S - sugar; A - acidity; GaI - Glucoacidimetric index; AP - alcoholic potential; F - flavorings, WA - wine alcohol; SR - sugar residue, in Muscat Ottonel wine cultivar and Y - yield; S - sugar; A - acidity; GaI - Glucoacidimetric Index; CP - commercial production; BS - berries size in the Victoria table grape cultivar). In both varieties have been identified correlations between the independent variable (B - buds number as a result of pruning and training practices) and quality parameters analyzed (r = -0.699 for B vsY relationship; r = 0.961 for the relationship B vs S; r = -0.959 for B vs AP relationship; r = 0.743 for the relationship Y vs S, p <0.01, in the Muscat Ottonel cultivar, respectively r = -0.907 for relationship B vs Y; r = -0.975 for B vs CP relationship; r = -0.971 for relationship B vs BS; r = 0.990 for CP vs BS relationship in the Victoria cultivar. Through regression analysis were obtained models that describe the variation concerning production and quality parameters in relation to the independent variable (B - buds number) with statistical significance results.

  1. Modeling of Reduced Effective Secondary Electron Emission Yield from a Velvet Surface

    CERN Document Server

    Swanson, Charles

    2016-01-01

    Complex structures on a material surface can significantly reduce total secondary electron emission from that surface. A velvet is a surface that consists of an array of vertically standing whiskers. The reduction occurs due to the capture of low-energy, true secondary electrons emitted at the bottom of the structure and on the sides of the velvet whiskers. We performed numerical simulations and developed an approximate analytical model that calculates the net secondary electron emission yield from a velvet surface as a function of the velvet whisker length and packing density, and the angle of incidence of primary electrons. The values of optimal velvet whisker packing density that maximally suppresses secondary electron emission yield are determined as a function of velvet aspect ratio and electron angle of incidence.

  2. Optimization of parameters for maximization of plateletpheresis and lymphocytapheresis yields on the Haemonetics Model V50.

    Science.gov (United States)

    AuBuchon, J P; Carter, C S; Adde, M A; Meyer, D R; Klein, H G

    1986-01-01

    Automated apheresis techniques afford the opportunity of tailoring collection parameters for each donor's hematologic profile. This study investigated the effect of various settings of the volume offset parameter as utilized in the Haemonetics Model V50 instrumentation during platelet- and lymphocytapheresis to optimize product yield, purity, and collection efficiency. In both types of procedures, increased product yield could be obtained by using an increased volume offset for donors having lower hematocrits. This improvement was related to an increase in collection efficiency. Platelet products also contained fewer contaminating lymphocytes with this approach. Adjustment of the volume offset parameter can be utilized to make the most efficient use of donors and provide higher-quality products.

  3. Summary goodness-of-fit statistics for binary generalized linear models with noncanonical link functions.

    Science.gov (United States)

    Canary, Jana D; Blizzard, Leigh; Barry, Ronald P; Hosmer, David W; Quinn, Stephen J

    2016-05-01

    Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) .

  4. A good resuscitation model of non-transthoracic cardiopulmonary bypass in rats

    Institute of Scientific and Technical Information of China (English)

    AN Yong; XIAO Ying-bin; ZHONG Qian-jin

    2007-01-01

    Objective:To establish a good recoverable rat model of cardiopulmonary bypass (CPB) to lay the foundation for studying the pathophysiology of CPB.Methods:Twenty adult male Sprague-Dawley rats weighing 480 g um via the right jugular vein and further transferred by a miniaturized roller pump to a hollow fiber oxgenator and back to the rat via the left carotid artery. Priming consisted of 8 ml of homologous blood and 6 ml of colloid. The surface of the hollow fiber oxgenator was 0.075 m2. Rats were catheterized and brought in bypass for 120 min at a flow rate of 100-120 ml/kg/min. Oxygen flow/ perfusion flow was 0. 8 to 1. 0, the mean arterial pressure (MAP) kept in 60-80 mmHg. Blood gas analysis, lactate dehydrogenase (LDH), and survival rate were examined subsequently.Results: All CPB rats recovered from the operative process without incident and remained uneventful within one week. Normal cardiac function after successful weaning was confirmed by electrocardiography and blood pressure measurements. MAP remained stable. The results of blood gas analysis at different time points were within a normal range. No significant haemolysis could be detected in the given time frame under bypass condition by using LDH.Conclusions: The rat model of CPB can principally simulate the clinical setting of human CPB. The nontransthoracic model is easy to establish and is associated with excellent recovery. This well reproducible model may open the field for various studies on pathophysiological process of CPB and also of systemic ischemia-reperfusion injury in vivo.

  5. Relevance of the Lin's and Host hydropedological models to predict grape yield and wine quality

    Science.gov (United States)

    Costantini, E. A. C.; Pellegrini, S.; Bucelli, P.; Storchi, P.; Vignozzi, N.; Barbetti, R.; Campagnolo, S.

    2009-09-01

    The adoption of precision agriculture in viticulture could be greatly enhanced by the diffusion of straightforward and easy to be applied hydropedological models, able to predict the spatial variability of available soil water. The Lin's and Host hydropedological models were applied to standard soil series descriptions and hillslope position, to predict the distribution of hydrological functional units in two vineyard and their relevance for grape yield and wine quality. A three-years trial was carried out in Chianti (Central Italy) on Sangiovese. The soils of the vineyards differentiated in structure, porosity and related hydropedological characteristics, as well as in salinity. Soil spatial variability was deeply affected by earth movement carried out before vine plantation. Six plots were selected in the different hydrological functional units of the two vineyards, that is, at summit, backslope and footslope morphological positions, to monitor soil hydrology, grape production and wine quality. Plot selection was based upon a cluster analysis of local slope, topographic wetness index (TWI), and cumulative moisture up to the root limiting layer, appreciated by means of a detailed combined geophysical survey. Water content, redox processes and temperature were monitored, as well as yield, phenological phases, and chemical analysis of grapes. The isotopic ratio δ13C was measured in the wine ethanol upon harvesting to evaluate the degree of stress suffered by vines. The grapes in each plot were collected for wine making in small barrels. The wines obtained were analysed and submitted to a blind organoleptic testing. The results demonstrated that the combined application of the two hydropedological models can be used for the prevision of the moisture status of soils cultivated with grape during summertime in Mediterranean climate. As correctly foreseen by the models, the amount of mean daily transpirable soil water (TSW) during the growing season differed

  6. Relevance of the Lin's and Host hydropedological models to predict grape yield and wine quality

    Directory of Open Access Journals (Sweden)

    E. A. C. Costantini

    2009-09-01

    Full Text Available The adoption of precision agriculture in viticulture could be greatly enhanced by the diffusion of straightforward and easy to be applied hydropedological models, able to predict the spatial variability of available soil water. The Lin's and Host hydropedological models were applied to standard soil series descriptions and hillslope position, to predict the distribution of hydrological functional units in two vineyard and their relevance for grape yield and wine quality. A three-years trial was carried out in Chianti (Central Italy on Sangiovese. The soils of the vineyards differentiated in structure, porosity and related hydropedological characteristics, as well as in salinity. Soil spatial variability was deeply affected by earth movement carried out before vine plantation. Six plots were selected in the different hydrological functional units of the two vineyards, that is, at summit, backslope and footslope morphological positions, to monitor soil hydrology, grape production and wine quality. Plot selection was based upon a cluster analysis of local slope, topographic wetness index (TWI, and cumulative moisture up to the root limiting layer, appreciated by means of a detailed combined geophysical survey. Water content, redox processes and temperature were monitored, as well as yield, phenological phases, and chemical analysis of grapes. The isotopic ratio δ13C was measured in the wine ethanol upon harvesting to evaluate the degree of stress suffered by vines. The grapes in each plot were collected for wine making in small barrels. The wines obtained were analysed and submitted to a blind organoleptic testing.

    The results demonstrated that the combined application of the two hydropedological models can be used for the prevision of the moisture status of soils cultivated with grape during summertime in Mediterranean climate. As correctly foreseen by the models, the amount of mean daily transpirable soil water (TSW during

  7. A theoretical framework of good health status of Jamaicans: using econometric analysis to model good health status over the life course

    Directory of Open Access Journals (Sweden)

    Paul A Bourne

    2009-07-01

    Full Text Available Background: In recent times, the World Health Organization has increasing drawn attention to the pivotal role of social conditions in determining health status. The non-biological factors produced inequalities in health and need to be considered in health development. In spite of this, extensive review of health Caribbean revealed that no study has examined health status over the life course of Jamaicans. With the value of research in public health, this study is timely and will add value to understand the elderly, middle age and young adults in Jamaica. Objective: The aim of this study is to develop models that can be used to examine (or evaluate health of Jamaicans, elderly, middle age and young adults. Method: The current study used data from a cross-sectional survey which was conducted between July and October 2002. Stratified random probability sampling technique was used to collect the data from 25,018 respondents across the island. The non-response rate for the survey was 29.7% with 20.5% who did not respond to particular questions, 9.0% did not participated in the survey and another 0.2% was rejected due to data cleaning. Logistic regression analyses were used to model health status of Jamaicans, young adults, middle age adults and elderly. The predictive power of the model was tested using Omnibus Test of Model and Hosmer and Lemeshow (24 was used to examine goodness of fit of the model. The correlation matrix was examined in order to ascertain whether autocorrelation (or multi-collinearity existed between variables. Results: Using logistic regression analysis, eleven variables emerged as statistically significant predictors of current good health Status of Jamaicans (p<0.05. The factors are retirement income (95%CI=0.487-0.958, logged medical expenditure (95% Confidence Interval, CI =0.907-0.993, marital status (Separated or widowed or divorced: 95%CI=0.309-0.464; married: 95%CI=0.495-0.667; Never married, health insurance (95%CI=0

  8. Quantification of the specific yield in a two-layer hard-rock aquifer model

    Science.gov (United States)

    Durand, Véronique; Léonardi, Véronique; de Marsily, Ghislain; Lachassagne, Patrick

    2017-08-01

    Hard rock aquifers (HRA) have long been considered to be two-layer systems, with a mostly capacitive layer just below the surface, the saprolite layer, and a mainly transmissive layer underneath, the fractured layer. Although this hydrogeological conceptual model is widely accepted today within the scientific community, it is difficult to quantify the respective storage properties of each layer with an equivalent porous medium model. Based on an HRA field site, this paper attempts to quantify in a distinct manner the respective values of the specific yield (Sy) in the saprolite and the fractured layer, with the help of a deterministic hydrogeological model. The study site is the Plancoët migmatitic aquifer located in north-western Brittany, France, with piezometric data from 36 observation wells surveyed every two weeks for eight years. Whereas most of the piezometers (26) are located where the water table lies within the saprolite, thus representing the specific yield of the unconfined layer (Sy1), 10 of them are representative of the unconfined fractured layer (Sy2), due to their position where the saprolite is eroded or unsaturated. The two-layer model, based on field observations of the layer geometry, runs with the MODFLOW code. 81 values of the Sy1/Sy2 parameter sets were tested manually, as an inverse calibration was not able to calibrate these parameters. In order to calibrate the storage properties, a new quality-of-fit criterion called ;AdVar; was also developed, equal to the mean squared deviation of the seasonal piezometric amplitude variation. Contrary to the variance, AdVar is able to select the best values for the specific yield in each layer. It is demonstrated that the saprolite layer is about 2.5 times more capacitive than the fractured layer, with Sy1 = 10% (7% < Sy1 < 15%) against Sy2 = 2% (1% < Sy2 < 3%), in this particular example.

  9. Modeling contribution of shallow groundwater to evapotranspiration and yield of maize in an arid area

    Science.gov (United States)

    Gao, Xiaoyu; Huo, Zailin; Qu, Zhongyi; Xu, Xu; Huang, Guanhua; Steenhuis, Tammo S.

    2017-01-01

    Capillary rise from shallow groundwater can decrease the need for irrigation water. However, simple techniques do not exist to quantify the contribution of capillary flux to crop water use. In this study we develop the Agricultural Water Productivity Model for Shallow Groundwater (AWPM-SG) for calculating capillary fluxes from shallow groundwater using readily available data. The model combines an analytical solution of upward flux from groundwater with the EPIC crop growth model. AWPM-SG was calibrated and validated with 2-year lysimetric experiment with maize. Predicted soil moisture, groundwater depth and leaf area index agreed with the observations. To investigate the response of model, various scenarios were run in which the irrigation amount and groundwater depth were varied. Simulations shows that at groundwater depth of 1 m capillary upward supplied 41% of the evapotranspiration. This reduced to 6% at groundwater depth of 2 m. The yield per unit water consumed (water productivity) was nearly constant for 2.3 kg/m3. The yield per unit water applied (irrigation water productivity) increased with decreasing irrigation water because capillary rise made up in part for the lack of irrigation water. Consequently, using AWPM-SG in irrigation scheduling will be beneficial to save more water in areas with shallow groundwater. PMID:28220874

  10. Modeling and Numerical Simulation of Yield Viscoplastic Fluid Flow in Concentric and Eccentric Annuli

    Institute of Scientific and Technical Information of China (English)

    毛在砂; 杨超; Vassilios C. Kelessidis

    2012-01-01

    Numerical solution of yield viscoplastic fluid flow is hindered by the singularity inherent to the Herschel-Bulkley model. A finite difference method over the boundary-fitted orthogonal coordinate system is util- ized to investigate numerically the fully developed steady flow of non-Newtonian yield viscoplastic fluid through concentric and eccentric annuli. The fluid rheology is described with the Herschel-Bulkley model. The numerical simulation based on a continuous viscoplastic approach to the Herschel-Bulkley model is found in poor accordance with the experimental data on volumetric flow rate of a bentonite suspension. A strict mathematical model for Herschel-Bulkley fluid flow is established and the corresponding numerical procedures are proposed. However, only the case of flow of a Herschel-Bulkley fluid in a concentric annulus is resolved based on the presumed flow stnicture by using the common optimization technique. Possible flow structures in an eccentric afinulus are presumed, and further challenges in numerical simulation of the Herschel-Bulkley fluid flow are suggested.

  11. Sediment yield computation of the sandy and gritty area based on the digital watershed model

    Institute of Scientific and Technical Information of China (English)

    LIU; Jiahong; WANG; Guangqian; LI; Tiejian; XUE; Hai

    2006-01-01

    The Yellow River is well known as a sediment-laden river, which is the main reason that it cannot be controlled as easily as other rivers. Many researchers, such as Qian Ning et al., have found that the sediment load of the Yellow River comes mainly from the sandy and gritty area of the Loess Plateau. Therefore, it is very important to simulate the sediment yield in this area. This paper proposes a method to compute the sediment production in the sandy and gritty area based on the digital watershed model. The suggested model is calibrated and validated in the Chabagou basin, which is a small catchment in the study area. Finally, the model simulates the sediment yield of the sandy and gritty area in 1967, 1978, 1983, 1994 and 1997, which represents a high water and high sediment year, a mean water and mean sediment year, a high water and low sediment year, a low water and high sediment year, and a low water and low sediment year separately. The simulation results, including the runoff depth and erosion modulus, can well explain the "low water and high sediment" phenomena in the Yellow River basin. The total amount of the sediment production and its distribution generated by the model is very useful for water and soil conservation in the sandy and gritty area of the Loess Plateau.

  12. Modeling Survival, Yield, Volume Partitioning and Their Response to Thinning for Longleaf Pine Plantations

    Directory of Open Access Journals (Sweden)

    Lisa J. Samuelson

    2012-12-01

    Full Text Available Longleaf pine (Pinus palustris Mill. is an important tree species of the southeast U.S. Currently there is no comprehensive stand-level growth and yield model for the species. The model system described here estimates site index (SI if dominant height (Hdom and stand age are known (inversely, the model can project Hdom at any given age if SI is known. The survival (N equation was dependent on stand age and Hdom, predicting greater mortality on stands with larger Hdom. The function that predicts stand basal area (BA for unthinned stands was dependent on N and Hdom. For thinned stands BA was predicted with a competition index that was dependent on stand age. The function that best predicted stand stem volume (outside or inside bark was dependent on BA and Hdom. All functions performed well for a wide range of stand ages and productivity, with coefficients of determination ranging between 0.946 (BA and 0.998 (N. We also developed equations to estimate merchantable volume yield consisting of different combinations of threshold diameter at breast height and top diameter for longleaf pine stands. The equations presented in this study performed similarly or slightly better than other reported models to estimate future N, Hdom and BA. The system presented here provides important new tools for supporting future longleaf pine management and research.

  13. Global modeling of secondary organic aerosol formation from aromatic hydrocarbons: high- vs. low-yield pathways

    Directory of Open Access Journals (Sweden)

    D. K. Henze

    2008-05-01

    Full Text Available Formation of SOA from the aromatic species toluene, xylene, and, for the first time, benzene, is added to a global chemical transport model. A simple mechanism is presented that accounts for competition between low and high-yield pathways of SOA formation, wherein secondary gas-phase products react further with either nitric oxide (NO or hydroperoxy radical (HO2 to yield semi- or non-volatile products, respectively. Aromatic species yield more SOA when they react with OH in regions where the [NO]/[HO2] ratios are lower. The SOA yield thus depends upon the distribution of aromatic emissions, with biomass burning emissions being in areas with lower [NO]/[HO2] ratios, and the reactivity of the aromatic with respect to OH, as a lower initial reactivity allows transport away from industrial source regions, where [NO]/[HO2] ratios are higher, to more remote regions, where this ratio is lower and, hence, the ultimate yield of SOA is higher. As a result, benzene is estimated to be the most important aromatic species with regards to global formation of SOA, with a total production nearly equal that of toluene and xylene combined. Global production of SOA from aromatic sources via the mechanisms identified here is estimated at 3.5 Tg/yr, resulting in a global burden of 0.08 Tg, twice as large as previous estimates. The contribution of these largely anthropogenic sources to global SOA is still small relative to biogenic sources, which are estimated to comprise 90% of the global SOA burden, about half of which comes from isoprene. Uncertainty in these estimates owing to factors ranging from the atmospheric relevance of chamber conditions to model deficiencies result in an estimated range of SOA production from aromatics of 2–12 Tg/yr. Though this uncertainty range affords a significant anthropogenic contribution to global SOA, it is evident from comparisons to recent observations that additional pathways for

  14. Models for predicting potential yield loss of wheat caused by stripe rust in the U.S. Pacific Northwest.

    Science.gov (United States)

    Sharma-Poudyal, D; Chen, X M

    2011-05-01

    Climatic variation in the U.S. Pacific Northwest (PNW) affects epidemics of wheat stripe rust caused by Puccinia striiformis f. sp. tritici. Previous models only estimated disease severity at the flowering stage, which may not predict the actual yield loss. To identify weather factors correlated to stripe rust epidemics and develop models for predicting potential yield loss, correlation and regression analyses were conducted using weather parameters and historical yield loss data from 1993 to 2007 for winter wheat and 1995 to 2007 for spring wheat. Among 1,376 weather variables, 54 were correlated to yield loss of winter wheat and 18 to yield loss of spring wheat. Among the seasons, winter temperature variables were more highly correlated to wheat yield loss than the other seasons. The sum of daily temperatures and accumulated negative degree days of February were more highly correlated to winter wheat yield loss than the other monthly winter variables. In addition, the number of winter rainfall days was found correlated with yield loss. Six yield loss models were selected for each of winter and spring wheats based on their better correlation coefficients, time of weather data availability during the crop season, and better performance in validation tests. Compared with previous models, the new system of using a series of the selected models has advantages that should make it more suitable for forecasting and managing stripe rust in the major wheat growing areas in the U.S. PNW, where the weather conditions have become more favorable to stripe rust.

  15. Sediment yield model implementation based on check dam infill stratigraphy in a semiarid Mediterranean catchment

    Directory of Open Access Journals (Sweden)

    G. Bussi

    2013-08-01

    Full Text Available Soil loss and sediment transport in Mediterranean areas are driven by complex non-linear processes which have been only partially understood. Distributed models can be very helpful tools for understanding the catchment-scale phenomena which lead to soil erosion and sediment transport. In this study, a modelling approach is proposed to reproduce and evaluate erosion and sediment yield processes in a Mediterranean catchment (Rambla del Poyo, Valencia, Spain. Due to the lack of sediment transport records for model calibration and validation, a detailed description of the alluvial stratigraphy infilling a check dam that drains a 12.9 km2 sub-catchment was used as indirect information of sediment yield data. These dam infill sediments showed evidences of at least 15 depositional events (floods over the time period 1990–2009. The TETIS model, a distributed conceptual hydrological and sediment model, was coupled to the Sediment Trap Efficiency for Small Ponds (STEP model for reproducing reservoir retention, and it was calibrated and validated using the sedimentation volume estimated for the depositional units associated with discrete runoff events. The results show relatively low net erosion rates compared to other Mediterranean catchments (0.136 Mg ha−1 yr−1, probably due to the extensive outcrops of limestone bedrock, thin soils and rather homogeneous vegetation cover. The simulated sediment production and transport rates offer model satisfactory results, further supported by in-site palaeohydrological evidences and spatial validation using additional check dams, showing the great potential of the presented data assimilation methodology for the quantitative analysis of sediment dynamics in ungauged Mediterranean basins.

  16. Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models.

    Science.gov (United States)

    Torres, F E; Teodoro, P E; Rodrigues, E V; Santos, A; Corrêa, A M; Ceccon, G

    2016-04-29

    The aim of this study was to select erect cowpea (Vigna unguiculata L.) genotypes simultaneously for high adaptability, stability, and yield grain in Mato Grosso do Sul, Brazil using mixed models. We conducted six trials of different cowpea genotypes in 2005 and 2006 in Aquidauana, Chapadão do Sul, Dourados, and Primavera do Leste. The experimental design was randomized complete blocks with four replications and 20 genotypes. Genetic parameters were estimated by restricted maximum likelihood/best linear unbiased prediction, and selection was based on the harmonic mean of the relative performance of genetic values method using three strategies: selection based on the predicted breeding value, having considered the performance mean of the genotypes in all environments (no interaction effect); the performance in each environment (with an interaction effect); and the simultaneous selection for grain yield, stability, and adaptability. The MNC99542F-5 and MNC99-537F-4 genotypes could be grown in various environments, as they exhibited high grain yield, adaptability, and stability. The average heritability of the genotypes was moderate to high and the selective accuracy was 82%, indicating an excellent potential for selection.

  17. Statistical model analysis of hadron yields in proton-nucleus and heavy-ion collisions at SIS 18 energies

    CERN Document Server

    Agakishiev, G; Balanda, A; Belver, D; Belyaev, A; Berger-Chen, J C; Blanco, A; Böhmer, M; Boyard, J L; Cabanelas, P; Castro, E; Chernenko, S; Destefanis, M; Dohrmann, F; Dybczak, A; Epple, E; Fabbietti, L; Fateev, O; Finocchiaro, P; Fonte, P; Friese, J; Fröhlich, I; Galatyuk, T; Garzon, J A; Gernhäuser, R; Gilardi, C; Göbel, K; Golubeva, M; Gonzalez-Diaz, D; Guber, F; Gumberidze, M; Heinz, T; Hennino, T; Holzmann, R; Ierusalimov, A; Iori, I; Ivashkin, A; Jurkovic, M; Kämpfer, B; Karavicheva, T; Koenig, I; Koenig, W; Kolb, B W; Kornakov, G; Kotte, R; Krasa, A; Krizek, F; Krücken, R; Kuc, H; Kühn, W; Kugler, A; Kurepin, A; Ladygin, V; Lalik, R; Lange, J S; Lang, S; Lapidus, K; Lebedev, A; Liu, T; Lopes, L; Lorenz, M; Maier, L; Mangiarotti, A; Markert, J; Metag, V; Michalska, B; Michel, J; Moriniere, E; Mousa, J; Müntz, C; Münzer, R; Naumann, L; Pachmayer, Y C; Palka, M; Parpottas, Y; Pechenov, V; Pechenova, O; Pietraszko, J; Przygoda, W; Ramstein, B; Rehnisch, L; Reshetin, A; Rustamov, A; Sadovsky, A; Salabura, P; Scheib, T; Schmah, A; Schuldes, H; Schwab, E; Siebenson, J; Sobolev, Yu G; Spataro, S; Spruck, B; Ströbele, H; Stroth, J; Sturm, C; Tarantola, A; Teilab, K; Tlusty, P; Traxler, M; Trebacz, R; Tsertos, H; Vasiliev, T; Wagner, V; Weber, M; Wendisch, C; Wisniowski, M; Wüstenfeld, J; Yurevich, S; Zanevsky, Y

    2015-01-01

    The HADES data from p+Nb collisions at center of mass energy of $\\sqrt{s_{NN}}$= 3.2 GeV are analyzed by employing a statistical model. Accounting for the identified hadrons $\\pi^0$, $\\eta$, $\\Lambda$, $K^{0}_{s}$, $\\omega$ allows a surprisingly good description of their abundances with parameters $T_{chem}=(99\\pm11)$ MeV and $\\mu_{b}=(619\\pm34)$ MeV, which fits well in the chemical freeze-out systematics found in heavy-ion collisions. In supplement we reanalyze our previous HADES data from Ar+KCl collisions at $\\sqrt{s_{NN}}$= 2.6 GeV with an updated version of the statistical model. We address equilibration in heavy-ion collisions by testing two aspects: the description of yields and the regularity of freeze-out parameters from a statistical model fit. Special emphasis is put on feed-down contributions from higher-lying resonance states which have been proposed to explain the experimentally observed $\\Xi^-$ excess present in both data samples.

  18. Modelling climate change impacts on viticultural yield, phenology and stress conditions in Europe.

    Science.gov (United States)

    Fraga, Helder; García de Cortázar Atauri, Iñaki; Malheiro, Aureliano C; Santos, João A

    2016-11-01

    Viticulture is a key socio-economic sector in Europe. Owing to the strong sensitivity of grapevines to atmospheric factors, climate change may represent an important challenge for this sector. This study analyses viticultural suitability, yield, phenology, and water and nitrogen stress indices in Europe, for present climates (1980-2005) and future (2041-2070) climate change scenarios (RCP4.5 and 8.5). The STICS crop model is coupled with climate, soil and terrain databases, also taking into account CO2 physiological effects, and simulations are validated against observational data sets. A clear agreement between simulated and observed phenology, leaf area index, yield and water and nitrogen stress indices, including the spatial differences throughout Europe, is shown. The projected changes highlight an extension of the climatic suitability for grapevines up to 55°N, which may represent the emergence of new winemaking regions. Despite strong regional heterogeneity, mean phenological timings (budburst, flowering, veraison and harvest) are projected to undergo significant advancements (e.g. budburst/harvest can be >1 month earlier), with implications also in the corresponding phenophase intervals. Enhanced dryness throughout Europe is also projected, with severe water stress over several regions in southern regions (e.g. southern Iberia and Italy), locally reducing yield and leaf area. Increased atmospheric CO2 partially offsets dryness effects, promoting yield and leaf area index increases in central/northern Europe. Future biomass changes may lead to modifications in nitrogen demands, with higher stress in northern/central Europe and weaker stress in southern Europe. These findings are critical decision support systems for stakeholders from the European winemaking sector.

  19. Metabolic energy-based modelling explains product yielding in anaerobic mixed culture fermentations.

    Directory of Open Access Journals (Sweden)

    Rebeca González-Cabaleiro

    Full Text Available The fermentation of glucose using microbial mixed cultures is of great interest given its potential to convert wastes into valuable products at low cost, however, the difficulties associated with the control of the process still pose important challenges for its industrial implementation. A deeper understanding of the fermentation process involving metabolic and biochemical principles is very necessary to overcome these difficulties. In this work a novel metabolic energy based model is presented that accurately predicts for the first time the experimentally observed changes in product spectrum with pH. The model predicts the observed shift towards formate production at high pH, accompanied with ethanol and acetate production. Acetate (accompanied with a more reduced product and butyrate are predicted main products at low pH. The production of propionate between pH 6 and 8 is also predicted. These results are mechanistically explained for the first time considering the impact that variable proton motive potential and active transport energy costs have in terms of energy harvest over different products yielding. The model results, in line with numerous reported experiments, validate the mechanistic and bioenergetics hypotheses that fermentative mixed cultures products yielding appears to be controlled by the principle of maximum energy harvest and the necessity of balancing the redox equivalents in absence of external electron acceptors.

  20. A distribution-free newsvendor model with balking penalty and random yield

    Directory of Open Access Journals (Sweden)

    Chongfeng Lan

    2015-05-01

    Full Text Available Purpose: The purpose of this paper is to extend the analysis of the distribution-free newsvendor problem in an environment of customer balking, which occurs when customers are reluctant to buy a product if its available inventory falls below a threshold level. Design/methodology/approach: We provide a new tradeoff tool as a replacement of the traditional one to weigh the holding cost and the goodwill costs segment: in addition to the shortage penalty, we also introduce the balking penalty. Furthermore, we extend our model to the case of random yield. Findings: A model is presented for determining both an optimal order quantity and a lower bound on the profit under the worst possible distribution of the demand. We also study the effects of shortage penalty and the balking penalty on the optimal order quantity, which have been largely bypassed in the existing distribution free single period models with balking. Numerical examples are presented to illustrate the result. Originality/value: The incorporation of balking penalty and random yield represents an important improvement in inventory policy performance for distribution-free newsvendor problem when customer balking occurs and the distributional form of demand is unknown.

  1. Yield Improvement and Advanced Defect Control——Driving Forces for Modeling of Bulk Crystal Growth

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Yield improvement and advanced defect control can be identified as the driving forces for modeling of industrial bulk crystal growth. Yield improvement is mainly achieved by upscaling of the whole crystal growth apparatus and increased processing windows with more tolerances for parameter variations. Advanced defect control means on one hand a reduction of the number of deficient crystal defects and on the other hand the formation of beneficial crystal defects with a uniform distribution and well defined concentrations in the whole crystal. This "defect engineering" relates to the whole crystal growth process as well as the following cooling and optional annealing processes, respectively. These topics were illustrated in the paper by examples of modeling and experimental results of bulk growth of silicon (Si), gallium arsenide (GaAs), indium phosphide (InP) and calcium fluoride (CaF2). These examples also involve the state of the art of modeling of the most important melt growth techniques, crystal pulling (Czochralski methods) and vertical gradient freeze (Bridgman-type methods).

  2. Regressions by leaps and bounds and biased estimation techniques in yield modeling

    Science.gov (United States)

    Marquina, N. E. (Principal Investigator)

    1979-01-01

    The author has identified the following significant results. It was observed that OLS was not adequate as an estimation procedure when the independent or regressor variables were involved in multicollinearities. This was shown to cause the presence of small eigenvalues of the extended correlation matrix A'A. It was demonstrated that the biased estimation techniques and the all-possible subset regression could help in finding a suitable model for predicting yield. Latent root regression was an excellent tool that found how many predictive and nonpredictive multicollinearities there were.

  3. A comprehensively quantitative method of evaluating the impact of drought on crop yield using daily multi-scale SPEI and crop growth process model

    Science.gov (United States)

    Wang, Qianfeng; Wu, Jianjun; Li, Xiaohan; Zhou, Hongkui; Yang, Jianhua; Geng, Guangpo; An, Xueli; Liu, Leizhen; Tang, Zhenghong

    2017-04-01

    The quantitative evaluation of the impact of drought on crop yield is one of the most important aspects in agricultural water resource management. To assess the impact of drought on wheat yield, the Environmental Policy Integrated Climate (EPIC) crop growth model and daily Standardized Precipitation Evapotranspiration Index (SPEI), which is based on daily meteorological data, are adopted in the Huang Huai Hai Plain. The winter wheat crop yields are estimated at 28 stations, after calibrating the cultivar coefficients based on the experimental site data, and SPEI data was taken 11 times across the growth season from 1981 to 2010. The relationship between estimated yield and multi-scale SPEI were analyzed. The optimum time scale SPEI to monitor drought during the crop growth period was determined. The reference yield was determined by averaging the yields from numerous non-drought years. From this data, we propose a comprehensive quantitative method which can be used to predict the impact of drought on wheat yields by combining the daily multi-scale SPEI and crop growth process model. This method was tested in the Huang Huai Hai Plain. The results suggested that estimation of calibrated EPIC was a good predictor of crop yield in the Huang Huai Hai Plain, with lower RMSE (15.4 %) between estimated yield and observed yield at six agrometeorological stations. The soil moisture at planting time was affected by the precipitation and evapotranspiration during the previous 90 days (about 3 months) in the Huang Huai Hai Plain. SPEIG90 was adopted as the optimum time scale SPEI to identify the drought and non-drought years, and identified a drought year in 2000. The water deficit in the year 2000 was significant, and the rate of crop yield reduction did not completely correspond with the volume of water deficit. Our proposed comprehensive method which quantitatively evaluates the impact of drought on crop yield is reliable. The results of this study further our understanding

  4. A comprehensively quantitative method of evaluating the impact of drought on crop yield using daily multi-scale SPEI and crop growth process model

    Science.gov (United States)

    Wang, Qianfeng; Wu, Jianjun; Li, Xiaohan; Zhou, Hongkui; Yang, Jianhua; Geng, Guangpo; An, Xueli; Liu, Leizhen; Tang, Zhenghong

    2016-11-01

    The quantitative evaluation of the impact of drought on crop yield is one of the most important aspects in agricultural water resource management. To assess the impact of drought on wheat yield, the Environmental Policy Integrated Climate (EPIC) crop growth model and daily Standardized Precipitation Evapotranspiration Index (SPEI), which is based on daily meteorological data, are adopted in the Huang Huai Hai Plain. The winter wheat crop yields are estimated at 28 stations, after calibrating the cultivar coefficients based on the experimental site data, and SPEI data was taken 11 times across the growth season from 1981 to 2010. The relationship between estimated yield and multi-scale SPEI were analyzed. The optimum time scale SPEI to monitor drought during the crop growth period was determined. The reference yield was determined by averaging the yields from numerous non-drought years. From this data, we propose a comprehensive quantitative method which can be used to predict the impact of drought on wheat yields by combining the daily multi-scale SPEI and crop growth process model. This method was tested in the Huang Huai Hai Plain. The results suggested that estimation of calibrated EPIC was a good predictor of crop yield in the Huang Huai Hai Plain, with lower RMSE (15.4 %) between estimated yield and observed yield at six agrometeorological stations. The soil moisture at planting time was affected by the precipitation and evapotranspiration during the previous 90 days (about 3 months) in the Huang Huai Hai Plain. SPEIG90 was adopted as the optimum time scale SPEI to identify the drought and non-drought years, and identified a drought year in 2000. The water deficit in the year 2000 was significant, and the rate of crop yield reduction did not completely correspond with the volume of water deficit. Our proposed comprehensive method which quantitatively evaluates the impact of drought on crop yield is reliable. The results of this study further our understanding

  5. Lindahl Equilibrium and Schweitzer's Open Club Model Semi-Public Goods

    NARCIS (Netherlands)

    Ten Raa, T.; Gilles, R.P.

    2003-01-01

    Limit core allocations are the ones that remain in the core of a replicated economy.An equivalent notion for economies with public goods is Schweizer s concept of club e ciency under a variable number of economic agents.We extend this notion to economies with goods that have a semi-public nature.We

  6. Assessment model for the transport of dangerous goods through road tunnels

    NARCIS (Netherlands)

    Nelisse, R.M.L.; Vrouwenvelder, A.C.W.M.

    2012-01-01

    In many cases decisions have to be made with respect to the safety level that has to be maintained in tunnels. In this paper the central question is how one can decide between (a) a tunnel with limited allowance for dangerous goods and a deviation route for the prohibited goods or (b) a tunnel

  7. Lindahl Equilibrium and Schweitzer's Open Club Model Semi-Public Goods

    NARCIS (Netherlands)

    Ten Raa, T.; Gilles, R.P.

    2003-01-01

    Limit core allocations are the ones that remain in the core of a replicated economy.An equivalent notion for economies with public goods is Schweizer s concept of club e ciency under a variable number of economic agents.We extend this notion to economies with goods that have a semi-public nature.We

  8. Development of a benchmark parameter scan for Higgs bosons in the NMSSM Model and a study of the sensitivity for H{yields}AA{yields}4{tau} in vector boson fusion with the ATLAS detector

    Energy Technology Data Exchange (ETDEWEB)

    Rottlaender, Iris

    2008-08-15

    An evaluation of the discovery potential for NMSSM Higgs bosons of the ATLAS experiment at the LHC is presented. For this purpose, seven two-dimensional benchmark planes in the six-dimensional parameter space of the NMSSM Higgs sector are defined. These planes include different types of phenomenology for which the discovery of NMSSM Higgs bosons is especially challenging and which are considered typical for the NMSSM. They are subsequently used to give a detailed evaluation of the Higgs boson discovery potential based on Monte Carlo studies from the ATLAS collaboration. Afterwards, the possibility of discovering NMSSM Higgs bosons via the H{sub 1}{yields}A{sub 1}A{sub 1}{yields}4{tau}{yields}4{mu}+8{nu} decay chain and with the vector boson fusion production mode is investigated. A particular emphasis is put on the mass reconstruction from the complex final state. Furthermore, a study of the jet reconstruction performance at the ATLAS experiment which is of crucial relevance for vector boson fusion searches is presented. A good detectability of the so-called tagging jets that originate from the scattered partons in the vector boson fusion process is of critical importance for an early Higgs boson discovery in many models and also within the framework of the NMSSM. (orig.)

  9. An individual reproduction model sensitive to milk yield and body condition in Holstein dairy cows.

    Science.gov (United States)

    Brun-Lafleur, L; Cutullic, E; Faverdin, P; Delaby, L; Disenhaus, C

    2013-08-01

    To simulate the consequences of management in dairy herds, the use of individual-based herd models is very useful and has become common. Reproduction is a key driver of milk production and herd dynamics, whose influence has been magnified by the decrease in reproductive performance over the last decades. Moreover, feeding management influences milk yield (MY) and body reserves, which in turn influence reproductive performance. Therefore, our objective was to build an up-to-date animal reproduction model sensitive to both MY and body condition score (BCS). A dynamic and stochastic individual reproduction model was built mainly from data of a single recent long-term experiment. This model covers the whole reproductive process and is composed of a succession of discrete stochastic events, mainly calving, ovulations, conception and embryonic loss. Each reproductive step is sensitive to MY or BCS levels or changes. The model takes into account recent evolutions of reproductive performance, particularly concerning calving-to-first ovulation interval, cyclicity (normal cycle length, prevalence of prolonged luteal phase), oestrus expression and pregnancy (conception, early and late embryonic loss). A sensitivity analysis of the model to MY and BCS at calving was performed. The simulated performance was compared with observed data from the database used to build the model and from the bibliography to validate the model. Despite comprising a whole series of reproductive steps, the model made it possible to simulate realistic global reproduction outputs. It was able to well simulate the overall reproductive performance observed in farms in terms of both success rate (recalving rate) and reproduction delays (calving interval). This model has the purpose to be integrated in herd simulation models to usefully test the impact of management strategies on herd reproductive performance, and thus on calving patterns and culling rates.

  10. Modeling dependence structure between stock market volatility and sukuk yields: A nonlinear study in the case of Saudi Arabia

    Directory of Open Access Journals (Sweden)

    Nader Naifar

    2016-09-01

    Full Text Available The aim of this paper is to investigate the dependence structure between sukuk (Islamic bonds yields and stock market (returns and volatility in the case of Saudi Arabia. We consider three Archimedean copula models with different tail dependence structures namely Gumbel, Clayton, and Frank. This study shows that the sukuk yields exhibit significant dependence only with stock market volatility. In addition, the dependence structure between sukuk yields and stock market volatility are symmetric and linked with the same intensity.

  11. Global modeling of secondary organic aerosol formation from aromatic hydrocarbons: high- vs low-yield pathways

    Directory of Open Access Journals (Sweden)

    D. K. Henze

    2007-10-01

    Full Text Available Formation of SOA from the aromatic species toluene, xylene, and, for the first time, benzene, is added to a global chemical transport model. A simple mechanism is presented that accounts for competition between low and high-yield pathways of SOA formation, wherein secondary gas-phase products react further with either nitrogen oxide (NO or hydroperoxy radical (HO2 to yield semi- or non-volatile products, respectively. Aromatic species yield more SOA when they react with OH in regions where the [NO]/[HO2] ratios are lower. The SOA yield thus depends upon the distribution of aromatic emissions, with biomass burning emissions being in areas with lower [NO]/[HO2] ratios, and the reactivity of the aromatic with respect to OH, as a lower initial reactivity allows transport away from industrial source regions, where [NO]/[HO2] ratios are higher, to more remote regions, where this ratio is lower and, hence, the ultimate yield of SOA is higher. As a result, benzene is estimated to be the most important aromatic species with regards to formation of SOA, with a total production nearly equal that of toluene and xylene combined. In total, while only 39% percent of the aromatic species react via the low-NOx pathway, 72% of the aromatic SOA is formed via this mechanism. Predicted SOA concentrations from aromatics in the Eastern United States and Eastern Europe are actually largest during the summer, when the [NO]/[HO2] ratio is lower. Global production of SOA from aromatic sources is estimated at 3.5 Tg/yr, resulting in a global burden of 0.08 Tg, twice as large as previous estimates. The contribution of these largely anthropogenic sources to global SOA is still small relative to biogenic sources, which are estimated to comprise 90% of the global SOA burden, about half of which comes from isoprene. Compared to recent observations, it would appear there are additional pathways beyond those

  12. Quantum Yields from Stationary States: Cis-Trans Isomerization of Model Retinal

    CERN Document Server

    Tscherbul, T V

    2014-01-01

    Cis-trans isomerization in retinal, the first step in vision, is often computationally studied from a time dependent viewpoint. Motivation for such studies lies in coherent pulsed laser experiments that explore the isomerization dynamics. However, such biological processes take place naturally in the presence of incoherent light, which excites a non-evolving mixture of stationary states. Here the isomerization problem is considered from the latter viewpoint and applied to a standard two-state, two-mode linear vibronic coupling model of retinal that explicitly includes a conical intersection between the ground and first excited electronic states. The calculated quantum yield at 500 nm agrees well with both the previous time-dependent calculations of Hahn and Stock (0.63) and with experiment ($0.65\\pm0.01$), as does its wavelength dependence. Significantly, the effects of environmental relaxation on the quantum yield in this well-established model are found to be negligible. The results make clear the connectio...

  13. Optimal salinity for dominant copepods in the East China Sea, determined using a yield density model

    Institute of Scientific and Technical Information of China (English)

    XU Zhaoli; GAO Qian

    2011-01-01

    From 1997 to 2000, four field surveys were conducted in the East China Sea (ECS)(23°30′ 33°00′N, 118°30′-128°00′E). A field data yield density model was used to determine the optimal salinities for 19 dominant copepod species to establish the relationship between surface salinities and abundance of those species. In addition, ecological groups of the copepods were classified based on optimal salinity and geographical distribution. The results indicate that the yield density model is suitable for determining the relationship between salinity and abundance. Cosmocalanus darwini, Euchaeta rimana,Pleuromamma gracilis, Rhincalanus cornutus, Scolecithrix danae and Pareucalanus attenuatus were determined as oceanic species, with optimal salinities of >34.0. They were stenohaline and mainly distributed in waters influenced by the Kuroshio or Taiwan warm current. Temoa discaudata, T. stylifera and Canthocalanus pauper were nearshore species with optimal salinities of <33.0 and most abundant in coastal waters. The remaining 10 species, including Undinula vulgaris and Subeucalanus subcrassus, were offshore species, with optimal salinity ranging from 33.0-34.0. They were widely distributed in nearshore,offshore and oceanic waters but mainly in the mixed water of the ECS.

  14. Optimal salinity for dominant copepods in the East China Sea, determined using a yield density model

    Science.gov (United States)

    Xu, Zhaoli; Gao, Qian

    2011-05-01

    From 1997 to 2000, four field surveys were conducted in the East China Sea (ECS) (23°30'-33°00'N, 118°30'-128°00'E). A field data yield density model was used to determine the optimal salinities for 19 dominant copepod species to establish the relationship between surface salinities and abundance of those species. In addition, ecological groups of the copepods were classified based on optimal salinity and geographical distribution. The results indicate that the yield density model is suitable for determining the relationship between salinity and abundance. Cosmocalanus darwini, Euchaeta rimana, Pleuromamma gracilis, Rhincalanus cornutus, Scolecithrix danae and Pareucalanus attenuatus were determined as oceanic species, with optimal salinities of >34.0. They were stenohaline and mainly distributed in waters influenced by the Kuroshio or Taiwan warm current. Temora discaudata, T. stylifera and Canthocalanus pauper were nearshore species with optimal salinities of <33.0 and most abundant in coastal waters. The remaining 10 species, including Undinula vulgaris and Subeucalanus subcrassus, were offshore species, with optimal salinity ranging from 33.0-34.0. They were widely distributed in nearshore, offshore and oceanic waters but mainly in the mixed water of the ECS.

  15. Random regressions models to describe the genetic variation of milk yield over multiple parities in Buffaloes

    Directory of Open Access Journals (Sweden)

    H. Tonhati

    2010-02-01

    Full Text Available The objectives of this study were to estimate (covariance functions for additive genetic and permanent environmental effects, as well as the genetic parameters for milk yield over multiple parities, using random regressions models (RRM. Records of 4,757 complete lactations of Murrah breed buffaloes from 12 herds were analyzed. Ages at calving were between 2 and 11 years. The model included the additive genetic and permanent environmental random effects and the fixed effects of contemporary groups (herd, year and calving season and milking frequency (1 or 2. A cubic regression on Legendre orthogonal polynomials of ages was used to model the mean trend. The additive genetic and permanent environmental effects were modeled by Legendre orthogonal polynomials. Residual variances were considered homogenous or heterogeneous, modeled through variance functions or step functions with 5, 7 or 10 classes. Results from Akaike’s and Schwarz’s Bayesian information criterion indicated that a RRM considering a third order polynomial for the additive genetic and permanent environmental effects and a step function with 5 classes for residual variances fitted best. Heritability estimates obtained by this model varied from 0.10 to 0.28. Genetic correlations were high between consecutive ages, but decreased when intervals between ages increased

  16. A multi-model analysis of change in potential yield of major crops in China under climate change

    Science.gov (United States)

    Yin, Y.; Tang, Q.; Liu, X.

    2015-02-01

    Climate change may affect crop growth and yield, which consequently casts a shadow of doubt over China's food self-sufficiency efforts. In this study, we used the projections derived from four global gridded crop models (GGCropMs) to assess the effects of future climate change on the yields of the major crops (i.e., maize, rice, soybean and wheat) in China. The GGCropMs were forced with the bias-corrected climate data from five global climate models (GCMs) under Representative Concentration Pathway (RCP) 8.5, which were made available through the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The results show that the potential yields of the crops would decrease in the 21st century without carbon dioxide (CO2) fertilization effect. With the CO2 effect, the potential yields of rice and soybean would increase, while the potential yields of maize and wheat would decrease. The uncertainty in yields resulting from the GGCropMs is larger than the uncertainty derived from GCMs in the greater part of China. Climate change may benefit rice and soybean yields in high-altitude and cold regions which are not in the current main agricultural area. However, the potential yields of maize, soybean and wheat may decrease in the major food production area. Development of new agronomic management strategies may be useful for coping with climate change in the areas with a high risk of yield reduction.

  17. Yield curve event tree construction for multi stage stochastic programming models

    DEFF Research Database (Denmark)

    Rasmussen, Kourosh Marjani; Poulsen, Rolf

    by the quality and size of the event trees representing the underlying uncertainty. Most often the DSP literature assumes existence of ``appropriate'' event trees without defining and examining qualities that must be met (ex--ante) in such an event tree in order for the results of the DSP model to be reliable....... Indeed defining a universal and tractable framework for fully ``appropriate'' event trees is in our opinion an impossible task. A problem specific approach to designing such event trees is the way ahead. In this paper we propose a number of desirable properties which should be present in an event tree...... of yield curves. Such trees may then be used to represent the underlying uncertainty in DSP models of fixed income risk and portfolio management....

  18. Investigation and modeling of the anomalous yield point phenomenon in pure tantalum

    Energy Technology Data Exchange (ETDEWEB)

    Colas, D. [Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR 5209 CNRS, Université de Bourgogne, 9 avenue Alain Savary, BP 17870, 21078 Dijon Cedex (France); CEA Valduc, 21120 Is-sur-Tille (France); Mines ParisTech, Centre des Matériaux, CNRS, UMR 7633, BP 87, 91003 Evry Cedex (France); Finot, E. [Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR 5209 CNRS, Université de Bourgogne, 9 avenue Alain Savary, BP 17870, 21078 Dijon Cedex (France); Flouriot, S. [CEA Valduc, 21120 Is-sur-Tille (France); Forest, S. [Mines ParisTech, Centre des Matériaux, CNRS, UMR 7633, BP 87, 91003 Evry Cedex (France); Mazière, M., E-mail: matthieu.maziere@mines-paristech.fr [Mines ParisTech, Centre des Matériaux, CNRS, UMR 7633, BP 87, 91003 Evry Cedex (France); Paris, T. [CEA Valduc, 21120 Is-sur-Tille (France)

    2014-10-06

    The monotonic and cyclic behavior of commercially pure tantalum has been investigated at room temperature, in order to capture and understand the occurrence of the anomalous yield point phenomenon. Interrupted tests have been performed, with strain reversals (tensile or compressive loading) after an aging period. The stress drop is attributed to the interactions between dislocations and solute atoms (oxygen) and its macroscopic occurrence is not systematically observed. InfraRed Thermography (IRT) measurements supported by Scanning Electron Microscopy (SEM) pictures of the polished gauge length of a specimen during an interrupted tensile test reveal the nucleation and propagation of a strain localization band. The KEMC (Kubin–Estrin–McCormick) phenomenological model accounting for strain aging has been identified for several loadings and strain rates at room temperature. Simulations on full specimen using the KEMC model do not show strain localization, because of the competition between viscosity and strain localization. However, a slight misalignment of the sample can promote strain localization.

  19. Modeling Integrated High-Yield IFE Target Explosions in Xenon Filled Chambers

    Science.gov (United States)

    Fatenejad, Milad; Moses, Gregory

    2010-11-01

    We will present the results of several radiation-hydrodynamics simulations which model the aftermath of an exploding high yield (200 MJ) indirect drive target in a xenon filled reactor chamber. The goal is to determine the radial extent to which debris from the target and hohlraum expands into the target chamber. The 1D radiation-hydrodynamics code BUCKY is used to perform integrated simulations of the target explosion beginning from ignition and includes interactions between the chamber gas and tungsten first wall. The 3D radiation-hydrodynamics code Cooper will be used to model the growth of fluid instabilities as the target material expands into the xenon gas. Cooper will also be used to investigate the early-time interaction between the burning target and hohlraum shortly after ignition.

  20. Mental health advocacy and African and Caribbean men: good practice principles and organizational models for delivery.

    Science.gov (United States)

    Newbigging, Karen; McKeown, Mick; French, Beverley

    2013-03-01

    Advocacy has a critical role to play in addressing concerns about access to appropriate mental health care and treatment for African and Caribbean men. To investigate good practice principles and organizational models for mental health advocacy provision for African and Caribbean men. The study consisted of: (i) A systematic literature review. Bibliographic and internet searching was undertaken from 1994 to 2006. The inclusion criteria related to mental health, advocacy provision for African and Caribbean men. (ii) Four focus groups with African and Caribbean men to explore needs for and experiences of mental health advocacy. (iii) An investigation into current advocacy provision through a survey of advocacy provision in England, Wales and Northern Ireland. (iv) Twenty-two qualitative stakeholder interviews to investigate the operation of mental health advocacy for this client group. The study was undertaken in partnership with two service user-led organizations and an African Caribbean mental health service. Primary research in this area is scant. Mainstream mental health advocacy services are often poor at providing appropriate services. Services developed by the Black Community and voluntary sector are grounded in different conceptualizations of advocacy and sharper understanding of the needs of African and Caribbean men. The lack of sustainable funding for these organizations is a major barrier to the development of high-quality advocacy for this group, reflecting a lack of understanding about their distinctive role. The commissioning and provision of mental health advocacy needs to recognize the distinct experiences of African and Caribbean men and develop capacity in the range of organizations to ensure equitable access. © 2011 Blackwell Publishing Ltd.

  1. High quantum-yield CdSexS1-x/ZnS core/shell quantum dots for warm white light-emitting diodes with good color rendering.

    Science.gov (United States)

    Duan, Hongyan; Jiang, Yang; Zhang, Yugang; Sun, Dapeng; Liu, Chao; Huang, Jian; Lan, Xinzheng; Zhou, Hongyang; Chen, Lei; Zhong, Honghai

    2013-07-19

    Composition-controllable ternary CdSe(x)S(1-x) quantum dots (QDs) with multiple emission colors were obtained via a hot-injection-like method at a relatively low injection temperature (230 ° C) in octadecene. Then highly fluorescent CdSe(x)S(1-x)/ZnS core/shell (CS) QDs were synthesized by a facile single-molecular precursor approach. The fluorescent quantum yield of the resulting green (λ(em) = 523 nm), yellow (λ(em) = 565 nm) and red (λ(em) = 621 nm) emission of CS QDs in toluene reached up to 85%, 55% and 39%, respectively. Moreover, a QDs white light-emitting diode (QDs-WLED) was fabricated by hybridizing green-, yellow- and red-emitting CdSe(x)S(1-x)/ZnS CS QDs/epoxy composites on a blue InGaN chip. The resulting four-band RYGB QDs-WLED showed good performance with CIE-1931 coordinates of (0.4137, 0.3955), an R(a) of 81, and a T(c) of 3360 K at 30 mA, which indicated the combination of multiple-color QDs with high fluorescence QYs in LEDs as a promising approach to obtain warm WLEDs with good color rendering.

  2. Facile Size-controllable Aqueous Synthesis of Water Soluble CdTe/Cd(OH)2 Core/Shell Nanoparticles with Tunable Optical Property, High Quantum Yield and Good Stability

    Institute of Scientific and Technical Information of China (English)

    CAI,Zhao-Xia; CHEN,Ying-Jun; YAN,Xiu-Ping

    2008-01-01

    A facile procedure was developed to prepare size-tunable and water soluble CdTe/Cd(OH)2 core/shell nanopar-ticles with high quantum yields and good stability using inexpensive inorganic precursors (CdCl2 and elemental Te). The emission colors of the prepared CdTe/Cd(OH)2 core/shell nanoparticles can be readily tuned from cyan to salmon pink by varying incubation time to control the growth of the Cd(OH)2 shell onto the CdTe nanoparticles. The CdTe/Cd(OH)2 core/shell nanoparticles were characterized by transmission electron microscopy, high-resolution transmission electron microscopy, X-ray powder diffraction spectrometry, photoluminescence and UV-Vis spec-trometry. The good water-soluble nature of the CdTe/Cd(OH)2 core/shell nanoparticles offers great potentiality for their bio-labeling application. This approach is simple, mild and readily scaled up, affording a simple way for synthesis of size-tunable inorganic metal hydroxide capped core/shell nanoparticles.

  3. Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces

    NARCIS (Netherlands)

    Pirttioja, N.; Carter, T.R.; Fronzek, S.; Bindi, M.; Hoffmann, H.; Palosuo, T.; Ruiz-Ramos, M.; Tao, F.; Trnka, M.; Acutis, M.; Supit, I.

    2015-01-01

    This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop sim

  4. Economic impact of clinical mastitis in a dairy herd assessed by stochastic simulation using different methods to model yield losses

    DEFF Research Database (Denmark)

    Hagnestam-Nielsen, Christel; Østergaard, Søren

    2009-01-01

    losses was investigated by comparing the results obtained using the potential yield of mastitic cows, had they not developed CM, with those obtained using the yield of non-mastitic cows. The yearly maximum avoidable cost of CM at herd level was estimated at €14 504, corresponding to 6.9% of the net...... and the conventional modelling strategy, with the exception of the cost per case of CM. Similarities between the results obtained using the two methods were particularly evident when the mastitic cows' own yield level, had they not developed CM, was used as the reference for production in healthy cows when yield...

  5. A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus

    2006-01-01

    The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...

  6. A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus Plenge

    The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...

  7. Impact of climate change on crop yield and role of model for achieving food security.

    Science.gov (United States)

    Kumar, Manoj

    2016-08-01

    In recent times, several studies around the globe indicate that climatic changes are likely to impact the food production and poses serious challenge to food security. In the face of climate change, agricultural systems need to adapt measures for not only increasing food supply catering to the growing population worldwide with changing dietary patterns but also to negate the negative environmental impacts on the earth. Crop simulation models are the primary tools available to assess the potential consequences of climate change on crop production and informative adaptive strategies in agriculture risk management. In consideration with the important issue, this is an attempt to provide a review on the relationship between climate change impacts and crop production. It also emphasizes the role of crop simulation models in achieving food security. Significant progress has been made in understanding the potential consequences of environment-related temperature and precipitation effect on agricultural production during the last half century. Increased CO2 fertilization has enhanced the potential impacts of climate change, but its feasibility is still in doubt and debates among researchers. To assess the potential consequences of climate change on agriculture, different crop simulation models have been developed, to provide informative strategies to avoid risks and understand the physical and biological processes. Furthermore, they can help in crop improvement programmes by identifying appropriate future crop management practises and recognizing the traits having the greatest impact on yield. Nonetheless, climate change assessment through model is subjected to a range of uncertainties. The prediction uncertainty can be reduced by using multimodel, incorporating crop modelling with plant physiology, biochemistry and gene-based modelling. For devloping new model, there is a need to generate and compile high-quality field data for model testing. Therefore, assessment of

  8. Modelling and computation in the valuation of carbon derivatives with stochastic convenience yields.

    Directory of Open Access Journals (Sweden)

    Shuhua Chang

    Full Text Available The anthropogenic greenhouse gas (GHG emission has risen dramatically during the last few decades, which mainstream researchers believe to be the main cause of climate change, especially the global warming. The mechanism of market-based carbon emission trading is regarded as a policy instrument to deal with global climate change. Although several empirical researches about the carbon allowance and its derivatives price have been made, theoretical results seem to be sparse. In this paper, we theoretically develop a mathematical model to price the CO2 emission allowance derivatives with stochastic convenience yields by the principle of absence of arbitrage opportunities. In the case of American options, we formulate the pricing problem to a linear parabolic variational inequality (VI in two spatial dimensions and develop a power penalty method to solve it. Then, a fitted finite volume method is designed to solve the nonlinear partial differential equation (PDE resulting from the power penalty method and governing the futures, European and American option valuation. Moreover, some numerical results are performed to illustrate the efficiency and usefulness of this method. We find that the stochastic convenience yield does effect the valuation of carbon emission derivatives. In addition, some sensitivity analyses are also made to examine the effects of some parameters on the valuation results.

  9. Modelling and computation in the valuation of carbon derivatives with stochastic convenience yields.

    Science.gov (United States)

    Chang, Shuhua; Wang, Xinyu

    2015-01-01

    The anthropogenic greenhouse gas (GHG) emission has risen dramatically during the last few decades, which mainstream researchers believe to be the main cause of climate change, especially the global warming. The mechanism of market-based carbon emission trading is regarded as a policy instrument to deal with global climate change. Although several empirical researches about the carbon allowance and its derivatives price have been made, theoretical results seem to be sparse. In this paper, we theoretically develop a mathematical model to price the CO2 emission allowance derivatives with stochastic convenience yields by the principle of absence of arbitrage opportunities. In the case of American options, we formulate the pricing problem to a linear parabolic variational inequality (VI) in two spatial dimensions and develop a power penalty method to solve it. Then, a fitted finite volume method is designed to solve the nonlinear partial differential equation (PDE) resulting from the power penalty method and governing the futures, European and American option valuation. Moreover, some numerical results are performed to illustrate the efficiency and usefulness of this method. We find that the stochastic convenience yield does effect the valuation of carbon emission derivatives. In addition, some sensitivity analyses are also made to examine the effects of some parameters on the valuation results.

  10. Supporting good practice in the provision of services to people with comorbid mental health and alcohol and other drug problems in Australia: describing key elements of good service models

    National Research Council Canada - National Science Library

    Merkes, Monika; Lewis, Virginia; Canaway, Rachel

    2010-01-01

    ... the range of service delivery models is apparent internationally or at the national level. The aims of the current research were to identify and describe elements of good practice in current service models of treatment of comorbidity in Australia...

  11. AN APPROACH TO THE MODEL USE FOR MEASURING SUSPENDED SEDIMENT YIELD IN UNGAUGED CATCHMENTS

    Directory of Open Access Journals (Sweden)

    Sokchhay Heng

    2013-01-01

    Full Text Available Different types of water resources studies require the information of Suspended Sediment Yield (SSY in different time resolutions. In ungauged watersheds where hydrometeorogical time series are not available, the mean annual SSY (SSYa is solely predictable and catchment area is traditionally used as the predictor because it is the most important variable and generally determined during project planning. Firstly, this research tried to advance the traditional SSYa model by additionally associating global topographic data. Based on the jack-knife procedure, the modified method considering catchment area with slope greater than 15% was evaluated in 17 gauged catchments in the Lower Mekong Basin and the overall predictive accuracy was improved about 66% in term of mean absolute percentage error. Secondly, the predicted SSYa in each modeled catchment was monthly distributed using Unit mean annual Sedimentograph (USGa. The double-average USGa superior to the single-average one provides overall better quality results than the regionalized USGa dependent upon the spatial proximity approach. The model performance measured by Nash-Sutcliffe Efficiency (NSE is about 0.66 in median value and satisfactory results (NSE >0.50 are obtained in 11 catchments. Lastly, the validated regional model was regarded as a potential and feasible tool in solving sediment-ungauged issues in the basin.

  12. Solution of the spatial neutral model yields new bounds on the Amazonian species richness

    Science.gov (United States)

    Shem-Tov, Yahav; Danino, Matan; Shnerb, Nadav M.

    2017-02-01

    Neutral models, in which individual agents with equal fitness undergo a birth-death-mutation process, are very popular in population genetics and community ecology. Usually these models are applied to populations and communities with spatial structure, but the analytic results presented so far are limited to well-mixed or mainland-island scenarios. Here we combine analytic results and numerics to obtain an approximate solution for the species abundance distribution and the species richness for the neutral model on continuous landscape. We show how the regional diversity increases when the recruitment length decreases and the spatial segregation of species grows. Our results are supported by extensive numerical simulations and allow one to probe the numerically inaccessible regime of large-scale systems with extremely small mutation/speciation rates. Model predictions are compared with the findings of recent large-scale surveys of tropical trees across the Amazon basin, yielding new bounds for the species richness (between 13100 and 15000) and the number of singleton species (between 455 and 690).

  13. Intrinsic autotrophic biomass yield and productivity in algae: modeling spectral and mixing-rate dependence.

    Science.gov (United States)

    Holland, Alexandra D; Wheeler, Dean R

    2011-05-01

    For non-inhibitory irradiances, the rate of algal biomass synthesis was modeled as the product of the algal autotrophic yield Φ(DW) and the flux of photons absorbed by the culture, as described using Beer-Lambert law. As a contrast to earlier attempts, the use of scatter-corrected extinction coefficients enabled the validation of such approach, which bypasses determination of photosynthesis-irradiance (PI) kinetic parameters. The broad misconception that PI curves, or the equivalent use of specific growth rate expressions independent of the biomass concentration, can be extended to adequately model biomass production under light-limitation is addressed. For inhibitory irradiances, a proposed mechanistic model, based on the photosynthetic units (PSU) concept, allows one to estimate a target speed νT across the photic zone in order to limit the flux of photons per cell to levels averting significant reductions in Φ(DW) . These modeled target speeds, on the order of 5-20 m s(-1) for high outdoor irradiances, call for fundamental changes in reactor design to optimize biomass productivity. The presented analysis enables a straightforward bioreactor parameterization, which, in-turn, guides the establishment of conditions ensuring maximum productivity and complete nutrients consumption. Additionally, solar and fluorescent lighting spectra were used to calculate energy to photon-counts conversion factors.

  14. Is the Linear Modeling Technique Good Enough for Optimal Form Design? A Comparison of Quantitative Analysis Models

    Directory of Open Access Journals (Sweden)

    Yang-Cheng Lin

    2012-01-01

    Full Text Available How to design highly reputable and hot-selling products is an essential issue in product design. Whether consumers choose a product depends largely on their perception of the product image. A consumer-oriented design approach presented in this paper helps product designers incorporate consumers’ perceptions of product forms in the design process. The consumer-oriented design approach uses quantification theory type I, grey prediction (the linear modeling technique, and neural networks (the nonlinear modeling technique to determine the optimal form combination of product design for matching a given product image. An experimental study based on the concept of Kansei Engineering is conducted to collect numerical data for examining the relationship between consumers’ perception of product image and product form elements of personal digital assistants (PDAs. The result of performance comparison shows that the QTTI model is good enough to help product designers determine the optimal form combination of product design. Although the PDA form design is used as a case study, the approach is applicable to other consumer products with various design elements and product images. The approach provides an effective mechanism for facilitating the consumer-oriented product design process.

  15. Is the linear modeling technique good enough for optimal form design? A comparison of quantitative analysis models.

    Science.gov (United States)

    Lin, Yang-Cheng; Yeh, Chung-Hsing; Wang, Chen-Cheng; Wei, Chun-Chun

    2012-01-01

    How to design highly reputable and hot-selling products is an essential issue in product design. Whether consumers choose a product depends largely on their perception of the product image. A consumer-oriented design approach presented in this paper helps product designers incorporate consumers' perceptions of product forms in the design process. The consumer-oriented design approach uses quantification theory type I, grey prediction (the linear modeling technique), and neural networks (the nonlinear modeling technique) to determine the optimal form combination of product design for matching a given product image. An experimental study based on the concept of Kansei Engineering is conducted to collect numerical data for examining the relationship between consumers' perception of product image and product form elements of personal digital assistants (PDAs). The result of performance comparison shows that the QTTI model is good enough to help product designers determine the optimal form combination of product design. Although the PDA form design is used as a case study, the approach is applicable to other consumer products with various design elements and product images. The approach provides an effective mechanism for facilitating the consumer-oriented product design process.

  16. Assessments of Maize Yield Potential in the Korean Peninsula Using Multiple Crop Models

    Science.gov (United States)

    Kim, S. H.; Myoung, B.; Lim, C. H.; Lee, S. G.; Lee, W. K.; Kafatos, M.

    2015-12-01

    The Korean Peninsular has unique agricultural environments due to the differences in the political and socio-economical systems between the Republic of Korea (SK, hereafter) and the Democratic Peoples' Republic of Korea (NK, hereafter). NK has been suffering from the lack of food supplies caused by natural disasters, land degradation and failed political system. The neighboring developed country SK has a better agricultural system but very low food self-sufficiency rate (around 1% of maize). Maize is an important crop in both countries since it is staple food for NK and SK is No. 2 maize importing country in the world after Japan. Therefore evaluating maize yield potential (Yp) in the two distinct regions is essential to assess food security under climate change and variability. In this study, we have utilized multiple process-based crop models capable of regional-scale assessments to evaluate maize Yp over the Korean Peninsula - the GIS version of EPIC model (GEPIC) and APSIM model that can be expanded to regional scales (APSIM regions). First we evaluated model performance and skill for 20 years from 1991 to 2010 using reanalysis data (Local Data Assimilation and Prediction System (LDAPS); 1.5km resolution) and observed data. Each model's performances were compared over different regions within the Korean Peninsula of different regional climate characteristics. To quantify the major influence of individual climate variables, we also conducted a sensitivity test using 20 years of climatology. Lastly, a multi-model ensemble analysis was performed to reduce crop model uncertainties. The results will provide valuable information for estimating the climate change or variability impacts on Yp over the Korean Peninsula.

  17. Prediction of 305 d milk yield in Jersey Cattle Using ANN Modelling

    African Journals Online (AJOL)

    ozcan_eren

    Prediction of 305-day milk yield in Brown Swiss cattle using artificial ... of milk yield is important, in that much of the selection of genetically superior bulls is based ... have been successfully applied in many disciplines, such as engineering, and.

  18. Simulation of Rainfed Wheat Yield using AquaCrop Model, Case Study: Sisab Rainfed Researches Station, Northern Khorasan

    Directory of Open Access Journals (Sweden)

    N. Khalili

    2015-06-01

    Full Text Available Modeling of crop growth plays an important role in evaluation of drought impacts on rainfed yield, choosing an optimum sowing date, and managerial decision-makings. Aquacrop model is a new crop model that developed by Food and Agriculture Organization (FAO, that is a model for simulation of crop yield based on “yield response to water“ with meteorological, crop, soli and management practices data as inputs. This model has to be calibrated and validated for each crop species and each location. In this paper, the Aquacrop has been calibrated and evaluated for rainfed wheat in Sisab station (Northern Khorasan. For this purpose, daily meteorological data and historical yield data from two cropping season (2007-2008 and 2008-2009 in the Sisab station have been used to calibrate this model. Next, meteorological data and historical yield data of five cropping season (2002-2003 to 2006-2007 are used to validate the model. The result shows that the Aqucrop can accurately predict crop yield as R2, RMSE, NRMSE, ME, and D-Index are achieved 0.86, 0.062, 5.235, 0.917 and 0.877, respectively.

  19. Assessment of Potential Yield andClimate Change Sensitivity of Peanut Crop in Cagayan Valley, Philippines using DSSAT Simulation Model

    Science.gov (United States)

    Balderama, O. F.

    2013-12-01

    Peanut is a major upland crop in Cagayan Valley and a leguminous crop that requires less water and therefore, considered an important crop in improving productivity of upland and rainfed areas. However, little information is available on the potential productivity of the crop and analysis on the production constraints including climate change sensitivity. This study was aimed to determine yield potential and production constraints of peanut crop in Cagayan Valley through the use of Decision Support System for Agrotechnology Transfer (DSSAT) simulation modeling; analyze yield gaps between simulated and actual yield levels and to provide decision support to further optimize peanut production under climate change condition. Site of experiment for model calibration and validation was located on-station at Isabela State University, Echague, Isabela. Rainfall and other climatic variables were monitored using a HOBO weather station (Automatic Weather Station) which is strategically installed inside experimental zone.The inputs required to run the CSM model include information on soil and weather conditions, crop management practices and cultivar specific genetic coefficients. In the first step,a model calibration was conducted to determine the cultivar coefficients for certain peanut cultivar that are normally grown in Cagayan Valley. Crop growth and yield simulation modeling was undertaken using the Decision Support System for Agro-Technology Transfer (DSSAT) for small seeded peanut (Pn9). An evaluation of the CSM-CROPGRO-peanut model was performed with data sets from peanut experiment conducted from December 2011 to April 2012. The model was evaluated in the estimation of potential yield of peanut under rainfed condition and low-nitrogen application. Yield potential for peanut limited only by temperature and solar radiation and no-water and nutrient stress, ranged from 3274 to 4805 kg per hectare for six planting dates (October 1, October 15, November 1, November 15

  20. Bifactor models and rotations: exploring the extent to which multidimensional data yield univocal scale scores.

    Science.gov (United States)

    Reise, Steven P; Moore, Tyler M; Haviland, Mark G

    2010-11-01

    The application of psychological measures often results in item response data that arguably are consistent with both unidimensional (a single common factor) and multidimensional latent structures (typically caused by parcels of items that tap similar content domains). As such, structural ambiguity leads to seemingly endless "confirmatory" factor analytic studies in which the research question is whether scale scores can be interpreted as reflecting variation on a single trait. An alternative to the more commonly observed unidimensional, correlated traits, or second-order representations of a measure's latent structure is a bifactor model. Bifactor structures, however, are not well understood in the personality assessment community and thus rarely are applied. To address this, herein we (a) describe issues that arise in conceptualizing and modeling multidimensionality, (b) describe exploratory (including Schmid-Leiman [Schmid & Leiman, 1957] and target bifactor rotations) and confirmatory bifactor modeling, (c) differentiate between bifactor and second-order models, and (d) suggest contexts where bifactor analysis is particularly valuable (e.g., for evaluating the plausibility of subscales, determining the extent to which scores reflect a single variable even when the data are multidimensional, and evaluating the feasibility of applying a unidimensional item response theory (IRT) measurement model). We emphasize that the determination of dimensionality is a related but distinct question from either determining the extent to which scores reflect a single individual difference variable or determining the effect of multidimensionality on IRT item parameter estimates. Indeed, we suggest that in many contexts, multidimensional data can yield interpretable scale scores and be appropriately fitted to unidimensional IRT models.

  1. Determining Prediction Model of the Canola Brassica napus L.( Yields Based on Agrometeorological and Climatic Parameters in Mashhad Region of Iran

    Directory of Open Access Journals (Sweden)

    seyed javad rasooli

    2017-02-01

    Full Text Available Introduction: Environmental factors whichaffect crop yield areone of the most important factors in increasing yield.Accurate prediction of crop yield for economic management and farming systems is of particular importance. Materials and Methods: This research was done in order to statistically model and predict the canola growth and yield in Mashhad region based on 5 agricultural meteorology indicesand 12 climatic parameters during 1999 - 2014period. The date of planting determined with regard to the optimum temperature at planting with probability of 75% based on Weibull formula. Beginning and the end of the phenological stages of canola (germination, emergence, Single leaf, rosette, stemming, flower, poddingand ripening were calculated on the basis of growing degree days (GDD for each set. Calculation and statistical equations was done usingMinitab Ver. 13.0, 16.Ver SPSS and Excelsoftwares. Correlation analysis,statistical models andmultivariate models were used to determine the relationship between the annual yield of canolaand independent variables, includingclimaticparameters and agricultural meteorologyindices during the growing season between 1999- 2000 and2009-2010for each phenological stage (8stages.The bestmodel was selected with respect to the values of the coefficient of determination (R2 and root mean square error (RMSE.If the predictive power is estimated of the model RMSE values of less than 10% excellent, between 10 and 20% good, 20 to 30% average, and higher than 30% weak. The model tested by estimating the yield of canola for the 2010 to2014 years and the correction factor was calculated and the effect. Results and Discussion: Canola planting date wascalculated for 23 September in Mashhad region. The phenology of canola was calculated based on growing degree days (GDD above 5 ° C.Germination calculatedfor25 September, emergence in 3 October, appearance single leaf in 7 October, rosette in 6 March, stemming in 4 April

  2. SEDIMENT YIELD MODELING FOR SINGLE STORM EVENTS BASED ON HEAVY-DISCHARGE STAGE CHARACTERIZED BY STABLE SEDIMENT CONCENTRATION

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The relation between runoff volume and sediment yield for individual events in a given watershed receives little attention compared to the relation between water discharge and sediment yield, though it may underlie the event-based sediment-yield model for large-size watershed. The data observed at 12 experimental subwatersheds in the Dalihe river watershed in hilly areas of Loess Plateau, North China,was selected to develop and validate the relation. The peak flow is often considered as an important factor affecting event sediment yield. However, in the study areas, sediment concentration remains relatively constant when water discharge exceeds a certain critical value, implying that the heavier flow is not accompanied with the higher sediment transport capacity. Hence, only the runoff volume factor was considered in the sediment-yield model. As both the total sediment and runoff discharge were largely produced during the heavy-discharge stage, and the sediment concentration was negligibly variable during this stage, a proportional function can be used to model the relation between event runoff volume and sediment yield for a given subwatershed. The applicability of this model at larger spatial scales was also discussed, and it was found that for the Yaoxinzhuang station at the Puhe River basin, which controls a drainage area of 2264km2, a directly proportional relation between event runoff volume and sediment yield may also exist.

  3. Estimating the impact of mineral aerosols on crop yields in food insecure regions using statistical crop models

    Science.gov (United States)

    Hoffman, A.; Forest, C. E.; Kemanian, A.

    2016-12-01

    A significant number of food-insecure nations exist in regions of the world where dust plays a large role in the climate system. While the impacts of common climate variables (e.g. temperature, precipitation, ozone, and carbon dioxide) on crop yields are relatively well understood, the impact of mineral aerosols on yields have not yet been thoroughly investigated. This research aims to develop the data and tools to progress our understanding of mineral aerosol impacts on crop yields. Suspended dust affects crop yields by altering the amount and type of radiation reaching the plant, modifying local temperature and precipitation. While dust events (i.e. dust storms) affect crop yields by depleting the soil of nutrients or by defoliation via particle abrasion. The impact of dust on yields is modeled statistically because we are uncertain which impacts will dominate the response on national and regional scales considered in this study. Multiple linear regression is used in a number of large-scale statistical crop modeling studies to estimate yield responses to various climate variables. In alignment with previous work, we develop linear crop models, but build upon this simple method of regression with machine-learning techniques (e.g. random forests) to identify important statistical predictors and isolate how dust affects yields on the scales of interest. To perform this analysis, we develop a crop-climate dataset for maize, soybean, groundnut, sorghum, rice, and wheat for the regions of West Africa, East Africa, South Africa, and the Sahel. Random forest regression models consistently model historic crop yields better than the linear models. In several instances, the random forest models accurately capture the temperature and precipitation threshold behavior in crops. Additionally, improving agricultural technology has caused a well-documented positive trend that dominates time series of global and regional yields. This trend is often removed before regression with

  4. The Shared Supervision Model: "Let's Start at the Very Beginning. A Very Good Place to Start!"

    Science.gov (United States)

    Eberly, Jody L.; Joshi, Arti; Galen, Harlene

    2009-01-01

    Periodic reexamination of existing professional development school forms is good practice to ascertain whether goals are being met. Such an assessment was sparked by a request from a superintendent in a 14-year-old professional development school structure at a public college in the Northeast. This assessment revealed that although the…

  5. A Simple Model for Yielding and Strain Hardening in Glassy Polymers

    Science.gov (United States)

    Larson, Ron

    2013-03-01

    Strain hardening has long been an observed feature of polymer glasses in extension; explanations to date have often been phenomenological. Ediger and coworkers (Lee et al. Science 323, 231, 2009) have shown in experiments on PMMA glasses that, in addition to strain hardening, polymeric glasses show a remarkable non-monotonicity in the segmental relaxation time both in loading and unloading of stress. Here, we develop a simple constitutive equation that combines recent theories for yielding in simple glasses (Brader et al. PNAS, 106, 15186, 2009) to represent local segmental modes in the polymer, with a dumbbell model for the slow polymer relaxation modes. For a polymer glass under uniaxial loading, the model predicts that the liquefaction of the segmental modes permits strain hardening of the polymer modes to emerge, and once this emerges, it slows the deformation of the material under constant load enough to partially re-vitrify the segmental modes even though the sample remains under stress. In this way, the observed non-monotonicity in the segmental relaxation modes is produced. We show the extension of the work to simple shearing flows, and make (as yet) untested predictions about segmental relaxation rates in shear flows. We also show how to extend the model to include Rouse chain dynamics in place of the over-simplified dumbbell.

  6. Impulsive perturbation and bifurcation of solutions for a model of chemostat with variable yield

    Institute of Scientific and Technical Information of China (English)

    Hong ZHANG; Paul Georgescu; Juan J.Nieto; Lan-sun CHEN

    2009-01-01

    In this paper,we consider a variable yield model of a single-species growth in a well-stirred tank containing fresh medium,assuming the instances of time as triggering factors in which the nutrient refilling process and the removal of microorganisms by the uptake of lethal external antibiotic are initiated.It is also assumed that the periodic nutrient refilling and the periodic antibiotic injection occur with the same periodicity,but not simultaneously.The model is then formulated in terms of autonomous differential equations subject to impulsive perturbations.It is observed that either the population of microorganisms essentially washes out,or more favorably,the system is permanent.To describe this dichotomy,some biologically significant integral conditions are introduced.Further,it is shown that in a certain critical situation,a nontrivial periodic solution emerges via a bifurcation phenomenon.Finally,the dynamics of the model is illustrated with numerical experiments and computer simulations.

  7. Inflow, Outflow, Yields, and Stellar Population Mixing in Chemical Evolution Models

    CERN Document Server

    Andrews, Brett H; Schönrich, Ralph; Johnson, Jennifer A

    2016-01-01

    Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the IMF, the SNIa delay time distribution, stellar yields, and mixing of stellar populations. Using flexCE, a new, flexible one-zone chemical evolution code, we investigate the effects of individual parameters and the trade-offs between them. Two of the most important parameters are the SFE and outflow mass-loading parameter, which shift the knee in [O/Fe]-[Fe/H] and the equilibrium abundances, respectively. One-zone models with simple star formation histories follow narrow tracks in [O/Fe]-[Fe/H] that do not match the observed bimodality in this plane. A mix of one-zone models with variations in their inflow timescales and outflow mass-loading parameters, as motivated by the inside-out galaxy formation scenario with radial mixing, reproduces the high- and low-alpha sequences b...

  8. Approximating uncertainty of annual runoff and reservoir yield using stochastic replicates of global climate model data

    Science.gov (United States)

    Peel, M. C.; Srikanthan, R.; McMahon, T. A.; Karoly, D. J.

    2015-04-01

    Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between global climate models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) data sets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to present a proof-of-concept approximation of within-GCM uncertainty for monthly precipitation and temperature projections and to assess the impact of within-GCM uncertainty on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. We adopt stochastic replicates of available GCM runs to approximate within-GCM uncertainty because large ensembles, hundreds of runs, for a given GCM and scenario are unavailable, other than the Climateprediction.net data set for the Hadley Centre GCM. To date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2015) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from

  9. Application of Gray Metabolic GM (1,1) Model in Prediction of Annual Total Yields of Chinese Aquatic Products

    Institute of Scientific and Technical Information of China (English)

    Songqian; HUANG; Weimin; WANG; Cong; ZENG; Shuang; HAO; Xiaojuan; CAO

    2013-01-01

    To predict the annual total yields of Chinese aquatic products in future five years ( 2011-2015) ,based on the theory and method of gray system,this paper firstly establishes a conventional GM ( 1,1) model and a gray metabolic GM ( 1,1) model respectively to predict the annual total yields of Chinese aquatic products in 2006-2009 and compare the prediction accuracy between these two models. Then,it selects the model with higher accuracy to predict the annual total yields of Chinese aquatic products in future five years. The comparison indicates that gray metabolic GM ( 1,1) model has higher prediction accuracy and smaller error,thus it is more suitable for prediction of annual total yields of aquatic products. Therefore,it adopts the gray metabolic GM ( 1,1) model to predict annual total yields of Chinese aquatic products in 2011-2015. The prediction results of annual total yields are 55. 32,57. 46,59. 72,62. 02 and 64. 43 million tons respectively in future five years with annual average increase rate of about 3. 7% ,much higher than the objective of 2. 2% specified in the Twelfth Five-Year Plan of the National Fishery Development ( 2011 to 2015) . The results of this research show that the gray metabolic GM ( 1,1) model is suitable for prediction of yields of aquatic products and the total yields of Chinese aquatic products in 2011-2015 will totally be able to realize the objective of the Twelfth Five-Year Plan.

  10. 早熟高产优质小花生新品种冀花10号的选育%Breeding of a New Peanut Variety Jihua No. 10 with Early Maturity, High Yield and Good Quality

    Institute of Scientific and Technical Information of China (English)

    王瑾; 李玉荣; 封树平; 程增书; 陈四龙; 宋亚辉; 张嘉楠; 刘吉生; 张强

    2012-01-01

    冀花10号系河北省农林科学院粮油作物研究所以冀9102为母本、87-77为父本,通过人工杂交和改良系谱法选育而成的早熟、高产、油用型小果花生新品种。该品种具有早熟、高产、优质、抗病和适应性强等特性。在河北省区域试验中,平均荚果产量为4128.00 kg/hm2,较对照鲁花12号增产20.71%;在河北省生产试验中,平均荚果产量为3694.20 kg/hm2,较对照鲁花12号增产22.60%。该品种籽仁脂肪含量为56.82%。2012年通过河北省科学技术厅组织的新品种审定。%Jihua No. 10, a new small peanut variety was derived from Ji9102 (female parent) × 87-77 early maturity, high oil content and high yield, which (male parent ) . It was developed through artificial hybridization and modified pedigree selection by Institute of Cereal and Oil Crops, Hebei Academy of Agriculture and Forestry Sciences. It had the properties of early maturity, high yield, good quality, disease resistance and strong adaptability. The pod yield averaged 4 128.00 kg/hm2 and 3 694.20 kg/hm2 in the regional tests and production test in Hebei, which increased by 20. 71% and 22. 60%, respectively, than the control Luhua No. 12. The fat content was 56.82%. It passed the appraisal by Hebei Science and Technology Department in 2012.

  11. A viscoplastic micromechanical model for the yield strength of nanocrystalline materials

    Energy Technology Data Exchange (ETDEWEB)

    Lebensohn, R; Bringa, E; Caro, A

    2006-03-14

    In this paper we present a micromechanical approach based on Fast Fourier Transforms to study the role played by dislocation glide and grain boundary (GB) accommodation in the determination of the plastic behavior of nanostructured materials. For this, we construct unit cells representing self-similar polycrystals with different grain sizes in the nanometer range and use local constitutive equations for slip and GB accommodation. We study the effect of grain size, strain rate and pressure on the local and effective behavior of nanostructured fcc materials with parameters obtained from experiments and atomistic simulations. Predictions of a previous qualitative pressure-sensitive model for the effective yield strength behind a shock front are substantially improved by considering strain partition between slip and GB activity. Under quasiestatic conditions, assuming diffusion-controlled mechanisms at GB, the model predicts a strain-rate sensitivity increase in nanocrystalline samples with respect to the same coarse-grained material of the same order as in recently published experiments.

  12. Brownian localization: A generalized coupling model yielding a nonergodic Langevin equation description

    Institute of Scientific and Technical Information of China (English)

    Liu Jian; Wang Hai-Yan; Bao Jing-Dong

    2013-01-01

    A minimal system-plus-reservoir model yielding a nonergodic Langevin equation is proposed,which originates from the cubic-spectral density of environmental oscillators and momentum-dependent coupling.This model allows ballistic diffusion and classical localization simultaneously,in which the fluctuation-dissipation relation is still satisfied but the Khinchin theorem is broken.The asymptotical equilibrium for a nonergodic system requires the initial thermal equilibrium,however,when the system starts from nonthermal conditions,it does not approach the equilibration even though a nonlinear potential is used to bound the particle,this can be confirmed by the zeroth law of thermodynamics.In the dynamics of Brownian localization,due to the memory damping function inducing a constant term,our results show that the stationary distribution of the system depends on its initial preparation of coordinate rather than momentum.The coupled oscillator chain with a fixed end boundary acts as a heat bath,which has long been used in studies of collinear atom/solid-surface scattering and lattice vibration,we investigate this problem from the viewpoint of nonergodicity.

  13. 高产 优质 抗病虫棉花新品种邯685选育%Breeding of New Cotton Variety Han 685 with High Yield, Good Quality and Pest and Disease Resistance

    Institute of Scientific and Technical Information of China (English)

    杨玉枫; 李世云; 韩永亮; 路正营; 崔红印

    2011-01-01

    The new cotton variety Han 685, which was bred by crossing Handan 284 (female parent) and Han 97HS-62 (GK12) (male parent) by Handan Academy of Agricultural Sciences, showed the characteristics of high yield, good quality, pest resistance and disease resistance. Han 685 was suitable for spring planting in eastern Hebei and other similar cotton area. It was released by Hebei Crop Variety Approval Committee in 2007.%邯685是邯郸市农业科学院以邯郸284为母本、邯97HS-62(GK12选系)为父本通过杂交选育而成的,集高产、优质、抗病虫于一体的棉花新品种。该品种适宜在冀东早熟棉区春棉种植以及其他同类型棉区种植,2007年通过河北省品种审定委员会审定。

  14. Evaluating long-term annual sediment yield estimating potential of GIS interfaced MUSLE model on two micro-watersheds.

    Science.gov (United States)

    Arekhi, Saleh

    2008-01-15

    Use of an event scale MUSLE model for obtaining accurate long-term annual sediment yield estimates from micro-watersheds was evaluated. Such estimates are extremely important for designing appropriate soil/water conserving measures. For easy extraction and inputting of model input parameters, the proposed model was interfaced to an Arc-View/Spatial Analyst geographic information system. Application of this GIS interfaced MUSLE model on two gauged (pine and oak forest) hilly micro-watersheds viz., Salla Rautella (0.47 km2) and Naula (0.42 km2), in Almora district of Uttaranchal, India showed that it could estimate annual sediment yields with absolute mean relative errors ranging between 12-14%. Even long-term average sediment yields for Salla Rautella (observed: 9.58 tons and estimated: 10.92 tons) and Naula: (Observed: 23.89 tons and estimated: 26.61 tons) micro-watersheds could be quite realistically simulated by the proposed model.

  15. Agro-climatic zonation of Khouzestan province based on potential yield of irrigated wheat using WOFOST model

    Directory of Open Access Journals (Sweden)

    M.H. Gharineh

    2016-05-01

    Full Text Available By application of climatic zoning methods, it is possible to study different agricultural aspects and then with harmony this aspects, determined similar states in a zone. Today, simulation models are widely used around the world in agricultural research and education and cropland management. Due to the vast extent of the agricultural activities in Iran, application of such models seems to be quite necessary for optimization objectives. The primary focus of this research was climatic zoning of Khouzestan region based on the results from wheat yield potential by means of WOFOST model. First, model performance and the accuracy of its results were evaluated. The findings showed that WOFOST model can adequately simulate phenological phases and grain and dry matter yields. The calculated Root Mean Square Error (RMSE values from blooming and physiologic maturity of crop were 1.97 per day and for seed and dry matter performances 810 and 810 kg ha-1, respectively. Also, one-to-one linear regression values for these stages were 0.96, 0.97, 0.93 and 0.91, respectively. The results of simulations indicated that the potentials of crop yield and the actual yield of farmlands are considerably different. Determination of the yield potentials of crop and its restricting factors were considered as the first step toward higher yield of crop. The results emphasized the fact that maximum and minimum yield potentials were found near the cities of Izeh (9247 kg. ha-1 and Shushtar (7538 kg. ha-1. A comparison of potential and actual crop yield trends revealed that the latter has been decreased might be due to the global warming phenomena resulting from green gases release into atmosphere while the increase of the farmer has been related to genetic modification of crop and management strategic. The results also showed that the poor yield of Mahshahr croplands (65.8% was because of unsuitable soil and high level ground water resources. The lowest performance was found in

  16. Percentile Analysis for Goodness-of-Fit Comparisons of Models to Data

    Science.gov (United States)

    2014-07-01

    obtaining a high R2. One solution to the problem is to consider a metric that is both sensitive to the number of data points under investigation as well...other facets of the model (e.g., its parsimony, breath, and ability; see Cassimatis, Bello , & Langley, 2008). 4. Model A and Model B have...278. Busemeyer, J. R. & Diederich, A. (2010). Cognitive Modeling. Sage. Cassimatis, N., Bello , P. & Langley, P. (2008). Ability, breadth and

  17. Four-Parameter Hybrid-Bishop-Hill Model Applied to OFE Copper for the Evaluation of Elastic/Yield Limit

    Science.gov (United States)

    Takahashi, Ribeka; Fullwood, David T.; Adams, Brent L.

    2014-09-01

    This study employs a novel stress-based Hybrid-Bishop-Hill yield model approach to evaluate the yield surface of oxygen-free electronic copper samples. The local yield surface is determined from three parameters of crystal orientation and one parameter of geometrically necessary dislocation (GND). All four local state variables can be rapidly determined by analysis of measured electron backscatter diffraction patterns. Estimates for the polycrystalline yield surface are obtained by standard averaging procedures. The shape of the yield surface is most influenced by the texture of the material, while the volume of the envelope scales with the average GND density. However, correlations between crystal orientation and GND content modify the yield surface shape and size. While correlations between GND density and crystal orientation are not strong for most copper samples, there are sufficient dependencies to demonstrate the benefits of the detailed four-parameter model. The four-parameter approach has potential for improving estimates of elastic-yield limit in all polycrystalline materials.

  18. What Is Good Communication?

    Science.gov (United States)

    Spitzberg, Brian H.

    2000-01-01

    Explores issues entailed in defining good communication including multiple reasonable criteria, competency bias, and communication as a function of context, locus, and abstraction. Claims good communication is a subjective evaluation and not subject to being codified in reductionist models. (NH)

  19. Study of Z' {yields} e{sup +}e{sup -} in full simulation with regard to discrimination between models beyond the standard model

    Energy Technology Data Exchange (ETDEWEB)

    Schafer, M

    2004-09-01

    Although experimental results so far agree with predictions of the standard model, it is widely felt to be incomplete. Many prospective theories beyond the standard model predict extra neutral gauge bosons, denoted by Z', which might be light enough to be accessible at the LHC. Observables sensitive to the properties of these extra gauge bosons might be used to discriminate between the different theories beyond the standard model. In the present work several of these observables (total decay width, leptonic cross-section and forward-backward asymmetries) are studied at generation level and with a full simulation in the ATLAS detector. The Z' {yields} e{sup +}e{sup -} decay channel was chosen and 2 values for the mass of Z': 1.5 TeV and 4 TeV. Background is studied as well and it is confirmed that a Z' boson could easily be discovered at the chosen masses. It is shown that even in full simulation the studied observables can be determined with a good precision. In a next step a discrimination strategy has to be developed given the presented methods to extract the variables and their precision. (author)

  20. Using statistical model to simulate the impact of climate change on maize yield with climate and crop uncertainties

    Science.gov (United States)

    Zhang, Yi; Zhao, Yanxia; Wang, Chunyi; Chen, Sining

    2016-09-01

    Assessment of the impact of climate change on crop productions with considering uncertainties is essential for properly identifying and decision-making agricultural practices that are sustainable. In this study, we employed 24 climate projections consisting of the combinations of eight GCMs and three emission scenarios representing the climate projections uncertainty, and two crop statistical models with 100 sets of parameters in each model representing parameter uncertainty within the crop models. The goal of this study was to evaluate the impact of climate change on maize (Zea mays L.) yield at three locations (Benxi, Changling, and Hailun) across Northeast China (NEC) in periods 2010-2039 and 2040-2069, taking 1976-2005 as the baseline period. The multi-models ensembles method is an effective way to deal with the uncertainties. The results of ensemble simulations showed that maize yield reductions were less than 5 % in both future periods relative to the baseline. To further understand the contributions of individual sources of uncertainty, such as climate projections and crop model parameters, in ensemble yield simulations, variance decomposition was performed. The results indicated that the uncertainty from climate projections was much larger than that contributed by crop model parameters. Increased ensemble yield variance revealed the increasing uncertainty in the yield simulation in the future periods.

  1. Runoff-yield model based on statistical theory%基于统计理论的产流模型

    Institute of Scientific and Technical Information of China (English)

    梁忠民; 施晔; 李彬权; 余钟波

    2009-01-01

    Based on statistical theory, a runoff-yield model, considering the spatial variations of rainfall, soil infiltration capacity and water storage capacity, is proposed in this paper. It is supposed that the spatial variations of a rainfall event could be described using a Probability Density Function(PDF) or a Cumulative Distribution Function(CDF), and the specific PDF or CDF at every time step of the rainfall event is estimated by adopting the goodness-of-fit approach to match the curve with the real rainfall data. The parabolic types of mathematical functions are used to represent the spatial distributions of soil infiltration capacity and water storage capacity. According to the joint probability distribution of rainfall and soil infiltration capacity, the distribution of surface runoff is deduced from the infiltration excess mechanism, and the further analytical solution to surface runoff is obtained. Infiltration supplements soil moisture, and when infiltration reaches the field capacity, it yields the groundwater flow which is calculated with the amounts of infiltration and the distribution of the water storage capacity. For instance, the proposed model is applied to Dongwan Basin, a semi-humid region located at the middle reach of Yellow River. Results are also compared with those obtained by the Xinanjiang model. It turns out that the statistically-based runoff-yield model could achieve the promising results with acceptable accuracy for flood events' simulation and forecast.%提出了一个基于统计理论的产流模型,该模型考虑了降雨、土壤下渗能力及土壤蓄水容量的空间变异性.假定每个时段的降雨量在空间上可以用概率密度函数或分布函数描述,根据实测降雨资料通过统计拟合优度途径估计各时段降雨的空间概率分布;采用抛物线型函数分别描述土壤下渗能力和土壤蓄水容量的空间分布.按照超渗产流机制计算地表产流量,通过降雨

  2. Promoting pollution prevention through community-industry dialogues: the good neighbor model in Minnesota.

    Science.gov (United States)

    Murdock, Barbara Scott; Sexton, Ken

    2002-05-15

    This article examines five attempts by communities to promote pollution prevention through direct negotiations with local manufacturing plants. These projects were Good Neighbor Dialogues spearheaded by Citizens for a Better Environment-Minnesota, an environmental advocacy organization. Three community-company partnerships (a container plant, a foundry, and a cabinet manufacturer) were successful and two (a munitions plant and a petroleum refinery) were not. Successful dialogues all shared certain characteristics: the company was open to negotiating with the community; there was an effective "champion" within the company; a skilled, independent facilitator served as moderator; community participants received independent technical assistance; and both the company and community understood the value of cooperative environmental decision making. Results suggest that Good Neighbor Dialogues can, under the right settings and circumstances, be an effective mechanism for building social capital by fostering greater understanding and trust between companies and communities. They offer the prospect of community-company partnerships that promote pollution prevention and other environmental improvements, while at the same time reinforcing and amplifying traditional pollution control strategies.

  3. A Generalized Yield Criterion

    Institute of Scientific and Technical Information of China (English)

    Shijian YUAN; Dazhi XIAO; Zhubin HE

    2004-01-01

    A generalized yield criterion is proposed based on the metal plastic deformation mechanics and the fundamental formula in theory of plasticity. Using the generalized yield criterion, the reason is explained that Mises yield criterion and Tresca yield criterion do not completely match with experimental data. It has been shown that the yield criteria of ductile metals depend not only on the quadratic invariant of the deviatoric stress tensor J2, but also on the cubic invariant of the deviatoric stress tensor J3 and the ratio of the yield stress in pure shear to the yield stress in uniaxial tension k/σs. The reason that Mises yield criterion and Tresca yield criterion are not in good agreement with the experimental data is that the effect of J3 and k/σs is neglected.

  4. Hydraulic pressing of oilseeds: Experimental determination and modeling of yield and pressing rates

    NARCIS (Netherlands)

    Willems, P.; Kuipers, N.J.M.; de Haan, A.B.

    2008-01-01

    The influence of pressure, temperature and moisture content on the oil yield and rate of conventional hydraulic expression of sesame and linseed is discussed as well as the influence of pressure and temperature for rapeseed, palm kernel, jatropha and dehulled jatropha. Yield increased with increase

  5. Hydraulic pressing of oilseeds: Experimental determination and modeling of yield and pressing rates

    NARCIS (Netherlands)

    Willems, P.; Kuipers, N.J.M.; Haan, de A.B.

    2008-01-01

    The influence of pressure, temperature and moisture content on the oil yield and rate of conventional hydraulic expression of sesame and linseed is discussed as well as the influence of pressure and temperature for rapeseed, palm kernel, jatropha and dehulled jatropha. Yield increased with increase

  6. Predicting yields of short-rotation hybrid poplar (Populus spp.) for the United States through model-data synthesis.

    Science.gov (United States)

    Wang, Dan; LeBauer, David; Dietze, Michael

    2013-06-01

    Hybrid poplar (Populus spp.) is an important biomass crop being evaluated for cellulosic ethanol production. Predictions of poplar growth, rotation period, and soil carbon sequestration under various growing conditions, soils, and climates are critical for farmers and managers planning to establish short-rotation forestry (SRF) plantations. In this study, we used an ecoinformatics workflow, the Predictive Ecosystem Analyzer (PEcAn), to integrate literature data and field measurements into the Ecosystem Demography 2 (ED2) model to estimate yield potential of poplar plantations. Within PEcAn 164 records of seven different traits from the literature were assimilated using a Bayesian meta-analysis. Next, variance decomposition identified seven variables for further constraint that contributed > 80% to the uncertainty in modeled yields: growth respiration, dark respiration, quantum efficiency, mortality coefficient, water conductance, fine-root allocation, and root turnover rate. Assimilation of observed yields further constrained uncertainty in model parameters (especially dark respiration and root turnover rate) and biomass estimates. Additional measurements of growth respiration, mortality, water conductance, and quantum efficiency would provide the most efficient path toward further constraint of modeled yields. Modeled validation demonstrated that ED2 successfully captured the interannual and spatial variability of poplar yield observed at nine independent sites. Site-level analyses were conducted to estimate the effect of land use change to SRF poplar on soil C sequestration compared to alternate land uses. These suggest that poplar plantations became a C sink within 18 years of conversion from corn production or existing forest. Finally, poplar yields were estimated for the contiguous United States at a half degree resolution in order to determine potential productivity, estimate the optimal rotation period, and compare poplar to perennial grass yields. This

  7. A one dimensional model for the prediction of extraction yields in a two phases modified twin-screw extruder

    OpenAIRE

    2002-01-01

    Solid/liquid extraction is performed on raw plant substrate with a modified twin-screw extruder (TSE) used as a thermo-mecanochemical reactor. Visual observations and experimental residence time distributions (RTD) are used to develop a solid transport model based on classical chemical engineering method. Modeled and experimental residence times are compared. The transport model is then coupled with a reactive extraction model in order to predict extraction yields.

  8. Simulation with Ideal Switch Models Combined with Measured Loss Data Provides a Good Estimate of Power Loss

    Institute of Scientific and Technical Information of China (English)

    StigMunk-Nielsen; Lucian; N; Tutelea; Ulrik; Jager

    2007-01-01

    Ideally, converter losses should be determined without using an excessive amount of simulation time. State-of-the-art power semiconductor models provide good accuracy,unfortunately they often require a very long simulation time. This paper describes how to estimate power losses from simulation using ideal switches combined with measured power loss data. The semiconductor behavior is put into a look-up table,which replaces the advanced semiconductor models and shortens the simulation time.To extract switching and conduction losses, a converter is simulated and the semiconductor power losses are estimated. Measurement results on a laboratory converter are compared with the estimated losses and a good agreement is shown. Using the ideal switch simulation and the post processing power estimation program,a ten to twenty fold increase in simulation speed is obtained,compared to simulations using advanced models of semiconductors.

  9. Toward a user's toolkit for modeling scintillator proportionality and light yield

    Science.gov (United States)

    Li, Qi

    Intrinsic nonproportionality is a material-dependent phenomenon that sets an ultimate limit on energy resolution of radiation detectors. In general, anything that causes light yield to change along the particle track (e.g., the primary electron track in gamma-ray detectors) contributes to nonproportionality. Most of the physics of nonproportionality lies in the host-transport and transfer-to-activator term. The main physical phenomena involved are carrier diffusion, trapping, drift in internal electric fields, and nonlinear rates of radiative and nonradiative recombination. Some complexity is added by the now well-established fact that the electron temperature is changing during important parts of the physical processes listed above. It has consequences, but is tractable by application of electron-phonon interaction theory and first-principles calculation of trap structures checked by experiment. Determination of coefficients and rate "constants" as functions of electron temperature T e for diffusion, D(Te( t)); capture on multiple (i) radiative and nonradiative centers, Ali(Te(t)); bimolecular exciton formation, B2(T e(t)); and nonlinear quenching, K2( Te(t)), K3( Te(t)) in specific scintillator materials will enable computational prediction of energy-dependent response from standard rate equations solved in the electron track for initial excitation distributions calculated by standard methods such as Geant4. Te( t) itself is a function of time. Determination of these parameters can be combined with models describing carrier transport in scintillators, which is able to build a user's toolkit for analyzing any existing and potential scintillators. In the dissertation, progress in calculating electronic structure of traps and activators, diffusion coefficients and rate functions, and testing the model will be described.

  10. Helen Huntingdon——A Good Model for Women of All Times

    Institute of Scientific and Technical Information of China (English)

    李兆平; 仲锡

    2008-01-01

    Anne Bront? was the youngest of the Bront? sisters.Together the three sisters left a brilliant page in the history of English literature.Her work The Tenant of Wildfell Hall was a great success the moment it was published and was highly praised by many outstanding British critics.He heroine in the book,Helen Huntingdon,was a young lady with noble-minded and gentle nature.With her spirit of self-esteem and self-reliance as well as her wonderful deed of slamming her bedroom door against her husband,Helen fought bravely with the inequality between men and women in the old British society in the mid 19th century.The purpose of this article is to pay good tribute to Helen's great personality,and moreover,to acknowledge and reorganize the almost forgotten literary genius Anne Bront?.

  11. How good is the Prevent model for estimating the health benefits of prevention?

    DEFF Research Database (Denmark)

    Brønnum-Hansen, Henrik

    1999-01-01

    Prevent is a public health model for estimating the effect on mortality of changes in exposure to risk factors. When the model is tested by simulating a development that has already taken place, the results may differ considerably from the actual situation. The purpose of this study is to test th...

  12. Goodness-of-fit tests and model diagnostics for negative binomial regression of RNA sequencing data.

    Directory of Open Access Journals (Sweden)

    Gu Mi

    Full Text Available This work is about assessing model adequacy for negative binomial (NB regression, particularly (1 assessing the adequacy of the NB assumption, and (2 assessing the appropriateness of models for NB dispersion parameters. Tools for the first are appropriate for NB regression generally; those for the second are primarily intended for RNA sequencing (RNA-Seq data analysis. The typically small number of biological samples and large number of genes in RNA-Seq analysis motivate us to address the trade-offs between robustness and statistical power using NB regression models. One widely-used power-saving strategy, for example, is to assume some commonalities of NB dispersion parameters across genes via simple models relating them to mean expression rates, and many such models have been proposed. As RNA-Seq analysis is becoming ever more popular, it is appropriate to make more thorough investigations into power and robustness of the resulting methods, and into practical tools for model assessment. In this article, we propose simulation-based statistical tests and diagnostic graphics to address model adequacy. We provide simulated and real data examples to illustrate that our proposed methods are effective for detecting the misspecification of the NB mean-variance relationship as well as judging the adequacy of fit of several NB dispersion models.

  13. Goodness-of-fit tests and model diagnostics for negative binomial regression of RNA sequencing data.

    Science.gov (United States)

    Mi, Gu; Di, Yanming; Schafer, Daniel W

    2015-01-01

    This work is about assessing model adequacy for negative binomial (NB) regression, particularly (1) assessing the adequacy of the NB assumption, and (2) assessing the appropriateness of models for NB dispersion parameters. Tools for the first are appropriate for NB regression generally; those for the second are primarily intended for RNA sequencing (RNA-Seq) data analysis. The typically small number of biological samples and large number of genes in RNA-Seq analysis motivate us to address the trade-offs between robustness and statistical power using NB regression models. One widely-used power-saving strategy, for example, is to assume some commonalities of NB dispersion parameters across genes via simple models relating them to mean expression rates, and many such models have been proposed. As RNA-Seq analysis is becoming ever more popular, it is appropriate to make more thorough investigations into power and robustness of the resulting methods, and into practical tools for model assessment. In this article, we propose simulation-based statistical tests and diagnostic graphics to address model adequacy. We provide simulated and real data examples to illustrate that our proposed methods are effective for detecting the misspecification of the NB mean-variance relationship as well as judging the adequacy of fit of several NB dispersion models.

  14. Every good regulator of a system must be a model of that system

    Directory of Open Access Journals (Sweden)

    Pieter Eykhoff

    1994-07-01

    Full Text Available A model for the process under control - do or don't we really need it? Some elementary philosophical considerations confirming such a need, are well supported by examples of various 'optimal' control schemes. How does this affirmation influence the requirements to identification and the implemcntation of control using such a model?

  15. Preserving the Public Good: Presenting an Organizational Model for the Changing Future of Higher Education

    Science.gov (United States)

    Garcia, Stephanie Parra

    2011-01-01

    Institutions of higher education face financial pressure to become self-sustaining (Gumport, 2001; 2000). This rapidly growing economic demand is negatively affecting the social mission of higher education (Kezar, 2004). Scholars suggest the implementation of a new model of higher education, one that blends a for-profit model with the traditional…

  16. Good Modeling Practice for PAT Applications: Propagation of Input Uncertainty and Sensitivity Analysis

    DEFF Research Database (Denmark)

    Sin, Gürkan; Gernaey, Krist; Eliasson Lantz, Anna

    2009-01-01

    The uncertainty and sensitivity analysis are evaluated for their usefulness as part of the model-building within Process Analytical Technology applications. A mechanistic model describing a batch cultivation of Streptomyces coelicolor for antibiotic production was used as case study. The input...

  17. Modeling the impact of climate change on watershed discharge and sediment yield in the black soil region, northeastern China

    Science.gov (United States)

    Li, Zhiying; Fang, Haiyan

    2017-09-01

    Climate change is expected to impact discharge and sediment yield in watersheds. The purpose of this paper is to assess the potential impacts of climate change on water discharge and sediment yield for the Yi'an watershed of the black soil region, northeastern China, based on the newly released Representative Concentration Pathways (RCPs) during 2071-2099. For this purpose, the TETIS model was implemented to simulate the hydrological and sedimentological responses to climate change. The model calibration (1971-1977) and validation (1978-1987) performances were rated as satisfactory. The modeling results for the four RCP scenarios relative to the control scenario under the same land use configuration indicated an increase in discharge of 16.3% (RCP 2.6), 14.3% (RCP 4.5), 36.7% (RCP 6.0) and 71.4% (RCP 8.5) and an increase in the sediment yield of 16.5% (RCP 2.6), 32.4% (RCP 4.5), 81.8% (RCP 6.0) and 170% (RCP 8.5). This implies that the negative impact of climate change on sediment yield is generally greater than that on discharge. At the monthly scale, both discharge and sediment yield increased dramatically in April to June and August to September. A more vigorous hydrological cycle and an increase in high values of sediment yield are also expected. These changes in annual discharge and sediment yield were closely linked with changes in precipitation, whereas monthly changes in late spring and autumn were mainly related to temperature. This study highlights the possible adverse impact of climate change on discharge and sediment yield in the black soil region of northeastern China and could provide scientific basis for adaptive management.

  18. Selecting a Dynamic Simulation Modeling Method for Health Care Delivery Research—Part 2: Report of the ISPOR Dynamic Simulation Modeling Emerging Good Practices Task Force

    NARCIS (Netherlands)

    Marshall, Deborah A.; Burgos-Liz, Lina; IJzerman, Maarten Joost; Crown, William; Padula, William V.; Wong, Peter K.; Pasupathy, Kalyan S.; Higashi, Mitchell K.; Osgood, Nathaniel D.

    2015-01-01

    In a previous report, the ISPOR Task Force on Dynamic Simulation Modeling Applications in Health Care Delivery Research Emerging Good Practices introduced the fundamentals of dynamic simulation modeling and identified the types of health care delivery problems for which dynamic simulation modeling

  19. Selecting a Dynamic Simulation Modeling Method for Health Care Delivery Research—Part 2: Report of the ISPOR Dynamic Simulation Modeling Emerging Good Practices Task Force

    NARCIS (Netherlands)

    Marshall, Deborah A.; Burgos-Liz, Lina; IJzerman, Maarten Joost; Crown, William; Padula, William V.; Wong, Peter K.; Pasupathy, Kalyan S.; Higashi, Mitchell K.; Osgood, Nathaniel D.

    2015-01-01

    In a previous report, the ISPOR Task Force on Dynamic Simulation Modeling Applications in Health Care Delivery Research Emerging Good Practices introduced the fundamentals of dynamic simulation modeling and identified the types of health care delivery problems for which dynamic simulation modeling c

  20. Winter wheat yield estimation based on multi-source medium resolution optical and radar imaging data and the AquaCrop model using the particle swarm optimization algorithm

    Science.gov (United States)

    Jin, Xiuliang; Li, Zhenhai; Yang, Guijun; Yang, Hao; Feng, Haikuan; Xu, Xingang; Wang, Jihua; Li, Xinchuan; Luo, Juhua

    2017-04-01

    Timely and accurate estimation of winter wheat yield at a regional scale is crucial for national food policy and security assessments. Near-infrared reflectance is not sensitive to the leaf area index (LAI) and biomass of winter wheat at medium to high canopy cover (CC), and most of the vegetation indices displayed saturation phenomenon. However, LAI and biomass at medium to high CC can be efficiently estimated using imaging data from radar with stronger penetration, such as RADARSAT-2. This study had the following three objectives: (i) to combine vegetation indices based on our previous studies for estimating CC and biomass for winter wheat using HJ-1A/B and RADARSAT-2 imaging data; (ii) to combine HJ-1A/B and RADARSAT-2 imaging data with the AquaCrop model using the particle swarm optimization (PSO) algorithm to estimate winter wheat yield; and (iii) to compare the results from the assimilation of HJ-1A/B + RADARSAT-2 imaging data, HJ-1A/B imaging data, and RADARSAT-2 imaging data into the AquaCrop model using the PSO algorithm. Remote sensing data and concurrent LAI, biomass, and yield of sample fields were acquired in Yangling District, Shaanxi, China, during the 2014 winter wheat growing season. The PSO optimization algorithm was used to integrate the AquaCrop model and remote sensing data for yield estimation. The modified triangular vegetation index 2 (MTVI2) × radar vegetation index (RVI) and the enhanced vegetation index (EVI) × RVI had good relationships with CC and biomass, respectively. The results indicated that the predicted and measured yield (R2 = 0.31 and RMSE = 0.94 ton/ha) had agreement when the estimated CC from the HJ-1A/B and RADARSAT-2 data was used as the dynamic input variable for the AquaCrop model. When the estimated biomass from the HJ-1A/B and RADARSAT-2 data was used as the dynamic input variable for the AquaCrop model, the predicted yield showed agreement with the measured yield (R2 = 0.42 and RMSE = 0.81 ton/ha). These results show

  1. Modeling the Seasonal Response of Sediment Yield to Climate Change in the Laos-Vietnam Transnational Upper Ca River Watershed

    Directory of Open Access Journals (Sweden)

    Pham Quy Giang

    2014-06-01

    Full Text Available Changes in stream sediment yield impact material fluxes, water quality, aquatic geochemistry, stream morphology, and aquatic habitats. Quantifying sediment yield is important for predicting watershed erosion and understanding sediment transport processes. In the context of a changing climate, this is important for the management and conservation of soil and water to cope with the effects of increasingly severe climate conditions that are likely to occur in the near future. This study aims to predict seasonal trends in sediment yield under climate change impacts in the Laos-Vietnam transnational Upper Ca River Watershed. The SWAT model was used for hydrological simulation, coupled with future climate projections under three IPCC emission scenarios, B1, B2, and A2. We found an increase in the seasonality of sediment yield due to increases in the seasonality of both rainfall and runoff. However, the increase of sediment yield in the wet season appeared more significant than its decrease in the dry season, due to more significant increases in rainfall as well as runoff in that season compared to decreases in these factors in the dry season. Consequently, annual sediment yield is predicted to increase, with a rate ranging from 12.1% to 16.5% by the end of this century, depending on emission scenario. The seasonal sensitivity of sediment yield to climate change found in this study is expected to be useful in collaborative management initiatives related to soil and water resources in the watershed.

  2. Modeling long-term yield trends of Miscanthusxgiganteus using experimental data from across Europe

    DEFF Research Database (Denmark)

    Lesur, Claire; Jeuffroy, Marie-Hélène; Makowski, David;

    2013-01-01

    Miscanthus × giganteus is a perennial grass that is considered to have a high feedstock potential for bioenergy production. Assessment of that potential is however highly related to the crop yields and to their change through the crop lifetime, which is expected to be longer than 20 years. M....... giganteus is known to have an establishment phase during which annual yields increased as a function of crop age, followed by a ceiling phase, the duration of which is unknown. We built a database including 16 European long-term experiments (i) to describe the yield evolution during the establishment...

  3. Economic Order Quality Model for Determining the Sales Prices of Fresh Goods at Various Points in Time

    Directory of Open Access Journals (Sweden)

    Po-Yu Chen

    2017-01-01

    Full Text Available Although the safe consumption of goods such as food products, medicine, and vaccines is related to their freshness, consumers frequently understand less than suppliers about the freshness of goods when they purchase them. Because of this lack of information, apart from sales prices, consumers refer only to the manufacturing and expiration dates when deciding whether to purchase and how many of these goods to buy. If dealers could determine the sales price at each point in time and customers’ intention to buy goods of varying freshness, then dealers could set an optimal inventory cycle and allocate a weekly sales price for each point in time, thereby maximizing the profit per unit time. Therefore, in this study, an economic order quality model was established to enable discussion of the optimal control of sales prices. The technique for identifying the optimal solution for the model was determined, the characteristics of the optimal solution were demonstrated, and the implications of the solution’s sensitivity analysis were explained.

  4. Crop Yields and Climate Change to the Year 2000. Volume 2: Climate Model and Technical Appendixes.

    Science.gov (United States)

    1988-01-01

    increasing demand for spring wheat milling characteristics and quality. Varietal improvement, suppressed photorespiration , development of N-fixing organisms...of yield breakthroughs, especially suppression of photorespiration and development of N-fixing organisms symbiotic with wheat. The midline indicates

  5. Good Cell Culture Practice for stem cells and stem-cell-derived models.

    Science.gov (United States)

    Pamies, David; Bal-Price, Anna; Simeonov, Anton; Tagle, Danilo; Allen, Dave; Gerhold, David; Yin, Dezhong; Pistollato, Francesca; Inutsuka, Takashi; Sullivan, Kristie; Stacey, Glyn; Salem, Harry; Leist, Marcel; Daneshian, Mardas; Vemuri, Mohan C; McFarland, Richard; Coecke, Sandra; Fitzpatrick, Suzanne C; Lakshmipathy, Uma; Mack, Amanda; Wang, Wen Bo; Yamazaki, Daiju; Sekino, Yuko; Kanda, Yasunari; Smirnova, Lena; Hartung, Thomas

    2017-01-01

    The first guidance on Good Cell Culture Practice (GCCP) dates back to 2005. This document expands this to include aspects of quality assurance for in vitro cell culture focusing on the increasingly diverse cell types and culture formats used in research, product development, testing and manufacture of biotechnology products and cell-based medicines. It provides a set of basic principles of best practice that can be used in training new personnel, reviewing and improving local procedures, and helping to assure standard practices and conditions for the comparison of data between laboratories and experimentation performed at different times. This includes recommendations for the documentation and reporting of culture conditions. It is intended as guidance to facilitate the generation of reliable data from cell culture systems, and is not intended to conflict with local or higher level legislation or regulatory requirements. It may not be possible to meet all recommendations in this guidance for practical, legal or other reasons. However, when it is necessary to divert from the principles of GCCP, the risk of decreasing the quality of work and the safety of laboratory staff should be addressed and any conclusions or alternative approaches justified. This workshop report is considered a first step toward a revised GCCP 2.0.

  6. Modelling crop yield, soil organic C and P under variable long-term fertilizer management in China

    Science.gov (United States)

    Zhang, Jie; Xu, Guang; Xu, Minggang; Balkovič, Juraj; Azevedo, Ligia B.; Skalský, Rastislav; Wang, Jinzhou; Yu, Chaoqing

    2016-04-01

    Phosphorus (P) is a major limiting nutrient for plant growth. P, as a nonrenewable resource and the controlling factor of aquatic entrophication, is critical for food security and human future, and concerns sustainable resource use and environmental impacts. It is thus essential to find an integrated and effective approach to optimize phosphorus fertilizer application in the agro-ecosystem while maintaining crop yield and minimizing environmental risk. Crop P models have been used to simulate plant-soil interactions but are rarely validated with scattered long-term fertilizer control field experiments. We employed a process-based model named Environmental Policy Integrated Climate model (EPIC) to simulate grain yield, soil organic carbon (SOC) and soil available P based upon 8 field experiments in China with 11 years dataset, representing the typical Chinese soil types and agro-ecosystems of different regions. 4 treatments, including N, P, and K fertilizer (NPK), no fertilizer (CK), N and K fertilizer (NK) and N, P, K and manure (NPKM) were measured and modelled. A series of sensitivity tests were conducted to analyze the sensitivity of grain yields and soil available P to sequential fertilizer rates in typical humid, normal and drought years. Our results indicated that the EPIC model showed a significant agreement for simulating grain yields with R2=0.72, index of agreement (d)=0.87, modeling efficiency (EF)=0.68, pmanagement practices.

  7. Building of Reusable Reverse Logistics Model and its Optimization Considering the Decision of Backorder or Next Arrival of Goods

    Science.gov (United States)

    Lee, Jeong-Eun; Gen, Mitsuo; Rhee, Kyong-Gu; Lee, Hee-Hyol

    This paper deals with the building of the reusable reverse logistics model considering the decision of the backorder or the next arrival of goods. The optimization method to minimize the transportation cost and to minimize the volume of the backorder or the next arrival of goods occurred by the Just in Time delivery of the final delivery stage between the manufacturer and the processing center is proposed. Through the optimization algorithms using the priority-based genetic algorithm and the hybrid genetic algorithm, the sub-optimal delivery routes are determined. Based on the case study of a distilling and sale company in Busan in Korea, the new model of the reusable reverse logistics of empty bottles is built and the effectiveness of the proposed method is verified.

  8. Application of neural network model coupling with the partial least-squares method for forecasting watre yield of mine

    Institute of Scientific and Technical Information of China (English)

    CHEN Nan-xiang; CAO Lian-hai; HUANG Qiang

    2005-01-01

    Scientific forecasting water yield of mine is of great significance to the safety production of mine and the colligated using of water resources. The paper established the forecasting model for water yield of mine, combining neural network with the partial least square method. Dealt with independent variables by the partial least square method, it can not only solve the relationship between independent variables but also reduce the input dimensions in neural network model, and then use the neural network which can solve the non-linear problem better. The result of an example shows that the prediction has higher precision in forecasting and fitting.

  9. Robust goodness-of-fit tests for AR(p) models based on L1-norm fitting

    Institute of Scientific and Technical Information of China (English)

    蒋建成; 郑忠国

    1999-01-01

    A robustified residual autocorrelation is defined based on L1-regression. Under very general conditions,the asymptotic distribution of the robust residual autocorrelation is obtained. A robustified portmanteau statistic is then constructed which can be used in checking the goodness-of-fit of AR(p) models when using L1-norm fitting. Empirical results show that L1-norm estimators and the proposed portmanteau statistic are robust against outliers, error distributions, and accuracy for a given finite sample.

  10. Regression models of ultimate methane yields of fruits and vegetable solid wastes, sorghum and napiergrass on chemical composition

    Energy Technology Data Exchange (ETDEWEB)

    Gunaseelan, V.N. [PSG College of Arts and Science, Coimbatore (India). Department of Zoology

    2007-04-15

    Several fractions of fruits and vegetable solid wastes (FVSW), sorghum and napiergrass were analyzed for total solids (TS), volatile solids (VS), total organic carbon, total kjeldahl nitrogen, total soluble carbohydrate, extractable protein, acid-detergent fiber (ADF), lignin, cellulose and ash contents. Their ultimate methane yields (B{sub o}) were determined using the biochemical methane potential (BMP) assay. A series of simple and multiple regression models relating the B{sub o} to the various substrate constituents were generated and evaluated using computer statistical software, Statistical Package for Social Sciences (SPSS). The results of simple regression analyses revealed that, only weak relationship existed between the individual components such as carbohydrate, protein, ADF, lignin and cellulose versus B{sub o}. A regression of B{sub o} versus combination of two variables as a single independent variable such as carbohydrate/ADF and carbohydrate + protein/ADF also showed that the relationship is not strong. Thus it does not appear possible to relate the B{sub o} of FVSW, sorghum and napiergrass with single compositional characteristics. The results of multiple regression analyses showed promise and the relationship appeared to be good. When ADF and lignin/ADF were used as independent variables, the percentage of variation accounted for by the model is low for FVSW (r{sup 2}=0.665) and sorghum and napiergrass (r{sup 2}=0.746). Addition of nitrogen, ash and total soluble carbohydrate data to the model had a significantly higher effect on prediction of B{sub o} of these wastes with the r{sup 2} values ranging from 0.9 to 0.99. More than 90% of variation in B{sub o} of FVSW could be accounted for by the models when the variables carbohydrate, lignin, lignin/ADF, nitrogen and ash (r{sup 2}=0.904), carbohydrate, ADF, lignin/ADF, nitrogen and ash (r{sup 2}=0.90) and carbohydrate/ADF, lignin/ADF, lignin and ash (r{sup 2}=0.901) were used. All the models have

  11. TEACHING AND LEARNING WITH TECHNOLOGY: A THEORETICAL MODEL FOR GOOD EDUCATIONAL PRACTICES WITH ICT

    Directory of Open Access Journals (Sweden)

    Jesús Valverde Berrocoso

    2010-02-01

    Full Text Available This article aims to define a theoretical explanatory framework for the integration of information technologies and communication technologies (ICT in education from the perspective of teacher education. The initial and continuing training of teachers is characterized by a tendency towards "essentialisation" of technology and generation of users who do not usually think about educational uses of technology in their own contexts. Our research on the integration of ICT in the classroom has allowed us to observe the lack of connection between the personal and professional use of teachers of these technological tools, as well as the need for training is geared towards developing skills and knowledge to examine, in a critical manner, the educational implications of these new teaching aids. This article is based on the proposed Koehler & Mishra (2005, 2006, 2007 and 2008 called TPCK (Technological Pedagogical Content Knowledge which is based on the construct of PCK Shulman (1987 to which is added the concept of "Technology" (T to those of "Pedagogy" (P and "Curriculum Content" (C. Connections and dynamic interactions between these three key components leading to different components to be considered in understanding the processes of integration of ICT in schools. Good educational practices with ICT are multidimensional and complex actions that require (1 understand the representation and formulation of concepts and procedures for their understanding through ICT, (2 develop constructivist teaching strategies that use ICT for teaching content curriculum, (3 know the difficulties in learning concepts and how ICT can help overcome them, and (4 knowing the students' prior knowledge and the epistemology of the curriculum to understand how ICT can be used to build on pre-existing knowledge and develop new epistemologies. These skills clearly go beyond the isolation that has an expert in a curriculum (teacher of a discipline, an expert in IT (engineer, or an

  12. As Good as Married? A Model of Premarital Cohabitation and Learning

    NARCIS (Netherlands)

    Sahib, Padma Rao; Gu, Xinhua

    2013-01-01

    This article develops a two-sided search-matching model with imperfectly observed types and sequential learning. We use the metaphor of premarital cohabitation and assume that it is initiated to learn more about one's prospective spouse. We show that couples match within classes and that the classes

  13. An Application of Structural Equation Modeling for Developing Good Teaching Characteristics Ontology

    Science.gov (United States)

    Phiakoksong, Somjin; Niwattanakul, Suphakit; Angskun, Thara

    2013-01-01

    Ontology is a knowledge representation technique which aims to make knowledge explicit by defining the core concepts and their relationships. The Structural Equation Modeling (SEM) is a statistical technique which aims to explore the core factors from empirical data and estimates the relationship between these factors. This article presents an…

  14. Have Cognitive Diagnostic Models Delivered Their Goods? Some Substantial and Methodological Concerns

    Science.gov (United States)

    Wilhelm, Oliver; Robitzsch, Alexander

    2009-01-01

    The paper by Rupp and Templin (2008) is an excellent work on the characteristics and features of cognitive diagnostic models (CDM). In this article, the authors comment on some substantial and methodological aspects of this focus paper. They organize their comments by going through issues associated with the terms "cognitive," "diagnostic" and…

  15. As Good as Married? A Model of Premarital Cohabitation and Learning

    NARCIS (Netherlands)

    Sahib, Padma Rao; Gu, Xinhua

    2013-01-01

    This article develops a two-sided search-matching model with imperfectly observed types and sequential learning. We use the metaphor of premarital cohabitation and assume that it is initiated to learn more about one's prospective spouse. We show that couples match within classes and that the classes

  16. Lack of predictability of classical animal models for hypolipidemic activity: A good time for mice?

    NARCIS (Netherlands)

    Krause, B.R.; Princen, H.M.G.

    1998-01-01

    Hypolipidemic drugs that are efficacious in man are not always active in classical animal models of dyslipidemia. Inhibitors of HMG-CoA reductase (statins) do not lower plasma cholesterol in rats, but yet this species was alone in providing activity for fibrate-type drugs. Nicotinic acid possesses m

  17. Substandard model? At last, a good reason to opt for a sexier theory of particle physics

    CERN Multimedia

    Cho, A

    2001-01-01

    According to experimenters at Brookhaven, a tiny discrepancy in the magnetism of the muon may signal a crack in the Standard Model. The deviation could be the first piece of hard evidence for a more complete theory called supersymmetry (1 page).

  18. Design of an integrated forward and reverse logistics network optimi-zation model for commercial goods management

    Directory of Open Access Journals (Sweden)

    Eva Ponce-Cueto

    2015-01-01

    Full Text Available In this study, an optimization model is formulated for designing an integrated forward and reverse logistics network in the consumer goods industry. The resultant model is a mixed-integer linear programming model (MILP. Its purpose is to minimize the total costs of the closed-loop supply chain network. It is important to note that the design of the logistics network may involve a trade-off between the total costs and the optimality in commercial goods management. The model comprises a discrete set as potential locations of unlimited capacity warehouses and fixed locations of customers’ zones. It provides decisions related to the facility location and customers’ requirements satisfaction, all of this related with the inventory and shipment decisions of the supply chain. Finally, an application of this model is illustrated by a real-life case in the food and drinks industry. We can conclude that this model can significantly help companies to make decisions about problems associated with logistics network design.

  19. Genetic evaluation using random regression models with different covariance functions for test-day milk yield in an admixture population of Thailand goats.

    Science.gov (United States)

    Thepparat, Mongkol; Boonkum, Wuttigrai; Duangjinda, Monchai; Tumwasorn, Sornthep; Nakavisut, Sansak; Thongchumroon, Thumrong

    2015-07-01

    The objectives of this study were to compare covariance functions (CF) and estimate the heritability of milk yield from test-day records among exotic (Saanen, Anglo-Nubian, Toggenburg and Alpine) and crossbred goats (Thai native and exotic breed), using a random regression model. A total of 1472 records of test-day milk yield were used, collected from 112 does between 2003 and 2006. CF of the study were Wilmink function, second- and third-order Legendre polynomials, and linear splines 4 knots located at 5, 25, 90 and 155 days in milk (SP25-90) and 5, 35, 95 and 155 of days in milk (SP35-95). Variance components were estimated by restricted maximum likelihood method (REML). Goodness of fit, Akaike information criterion (AIC), percentage of squared bias (PSB), mean square error (MSE), and empirical correlation (RHO) between the observed and predicted values were used to compare models. The results showed that CF had an impact on (co)variance estimation in random regression models (RRM). The RRM with splines 4 knots located at 5, 25, 90 and 155 of days in milk had the lowest AIC, PSB and MSE, and the highest RHO. The heritability estimated throughout lactation obtained with this model ranged from 0.13 to 0.23. © 2014 Japanese Society of Animal Science.

  20. Mathematical modeling-guided evaluation of biochemical, developmental, environmental, and genotypic determinants of essential oil composition and yield in peppermint leaves.

    Science.gov (United States)

    Rios-Estepa, Rigoberto; Lange, Iris; Lee, James M; Lange, B Markus

    2010-04-01

    We have previously reported the use of a combination of computational simulations and targeted experiments to build a first generation mathematical model of peppermint (Menthaxpiperita) essential oil biosynthesis. Here, we report on the expansion of this approach to identify the key factors controlling monoterpenoid essential oil biosynthesis under adverse environmental conditions. We also investigated determinants of essential oil biosynthesis in transgenic peppermint lines with modulated essential oil profiles. A computational perturbation analysis, which was implemented to identify the variables that exert prominent control over the outputs of the model, indicated that the essential oil composition should be highly dependent on certain biosynthetic enzyme concentrations [(+)-pulegone reductase and (+)-menthofuran synthase], whereas oil yield should be particularly sensitive to the density and/or distribution of leaf glandular trichomes, the specialized anatomical structures responsible for the synthesis and storage of essential oils. A microscopic evaluation of leaf surfaces demonstrated that the final mature size of glandular trichomes was the same across all experiments. However, as predicted by the perturbation analysis, differences in the size distribution and the total number of glandular trichomes strongly correlated with differences in monoterpenoid essential oil yield. Building on various experimental data sets, appropriate mathematical functions were selected to approximate the dynamics of glandular trichome distribution/density and enzyme concentrations in our kinetic model. Based on a chi2 statistical analysis, simulated and measured essential oil profiles were in very good agreement, indicating that modeling is a valuable tool for guiding metabolic engineering efforts aimed at improving essential oil quality and quantity.

  1. DRUCKER-PRAGER YIELD CRITERIA IN VISCOELASTIC-PLASTIC CONSTITUTIVE MODEL FOR THE STUDY OF SEA ICE DYNAMICS

    Institute of Scientific and Technical Information of China (English)

    WANG Gang; JI Shun-ying; LV He-xiang; YUE Qian-jin

    2006-01-01

    Based on the characteristics of sea ice drifting and ridging at meso-small scale, the Drucker-Prager (D-P) yield criteria was introduced into the Viscoelastic-Plastic (VEP) constitutive model for the study of sea ice dynamics. In this model, the Kelvin-Vogit viscoelastic model was adopted in the elastic stage, and the associated normal flow rule was used in the plastic stage. Using the VEP model, the sea ice ridging process was simulated in an idealized rectangular basin, and the simulation results show that the simulated ice ridge thickness is consistent with the analytical solution. Moreover, the VEP model with the D-P yield criteria was also applied for the sea ice simulation of Bohai Sea, and the ice thickness, concentration, velocity, and ice stress were obtained in 48 h. The simulated thickness distributions agree well with the satellite images. The singular problem in the Mohr-Coulomb (M-C) yield criteria was overcome by the D-P yield criteria, and the computational efficiency was also improved. In the numerical simulations described above, the smoothed particle hydrodynamics was applied.

  2. Good and bad consequences of altered fatty acid metabolism in heart failure: evidence from mouse models.

    Science.gov (United States)

    Abdurrachim, Desiree; Luiken, Joost J F P; Nicolay, Klaas; Glatz, Jan F C; Prompers, Jeanine J; Nabben, Miranda

    2015-05-01

    The shift in substrate preference away from fatty acid oxidation (FAO) towards increased glucose utilization in heart failure has long been interpreted as an oxygen-sparing mechanism. Inhibition of FAO has therefore evolved as an accepted approach to treat heart failure. However, recent data indicate that increased reliance on glucose might be detrimental rather than beneficial for the failing heart. This review discusses new insights into metabolic adaptations in heart failure. A particular focus lies on data obtained from mouse models with modulations of cardiac FA metabolism at different levels of the FA metabolic pathway and how these differently affect cardiac function. Based on studies in which these mouse models were exposed to ischaemic and non-ischaemic heart failure, we discuss whether and when modulations in FA metabolism are protective against heart failure.

  3. MODELING AND SOLVING A RICH VEHICLE ROUTING PROBLEM FOR THE DELIVERY OF GOODS IN URBAN AREAS

    OpenAIRE

    José Ferreira de Souza Neto; Vitória Pureza

    2016-01-01

    ABSTRACT This work addresses a vehicle routing problem that aims at representing delivery operations of large volumes of products in dense urban areas. Inspired by a case study in a drinks producer and distributor, we propose a mathematical programming model and solution approaches that take into account costs with own and chartered vehicles, multiple deliverymen, time windows in customers, compatibility of vehicles and customers, time limitations for the circulation of large vehicles in city...

  4. Good Governance

    Directory of Open Access Journals (Sweden)

    S de la Harpe

    2008-08-01

    Full Text Available This issue of the Potchefstroom Electronic Law Journal (PELJ is entirely dedicated to the concept of good governance. It is the outcome of the first Summer/Winter school on Good Governance which was held at North-West University, Potchefstroom (SA in January 2006 and at Tilburg University, Tilburg (NL in January 2007. This Summer/Winter school has now become a yearly event with a bi-annual theme. Academic staff from both universities collaborate in teaching this course. Students from the two universities who participate in the Summer/Winter school have the unique possibility to deepen their knowledge on a particular subject while enjoying a cross-cultural learning environment. The subject of good governance was not selected by chance but was chosen because of its impact in many fields and the many ways in which the concept is used. It was time for a deeper insight into this multiple role of the concept of good governance. The contributions to this journal are the analytical outcome of the research done in preparation for the lectures given during the Summer/Winter school. As the contributions directly apply the good governance concept to various specific fields of expertise, this introduction will be used to give a short reflection on the concept as such.

  5. Light- and water-use efficiency model synergy: a revised look at crop yield estimation for agricultural decision-making

    Science.gov (United States)

    Marshall, M.; Tu, K. P.

    2015-12-01

    Large-area crop yield models (LACMs) are commonly employed to address climate-driven changes in crop yield and inform policy makers concerned with climate change adaptation. Production efficiency models (PEMs), a class of LACMs that rely on the conservative response of carbon assimilation to incoming solar radiation absorbed by a crop contingent on environmental conditions, have increasingly been used over large areas with remote sensing spectral information to improve the spatial resolution of crop yield estimates and address important data gaps. Here, we present a new PEM that combines model principles from the remote sensing-based crop yield and evapotranspiration (ET) model literature. One of the major limitations of PEMs is that they are evaluated using data restricted in both space and time. To overcome this obstacle, we first validated the model using 2009-2014 eddy covariance flux tower Gross Primary Production data in a rice field in the Central Valley of California- a critical agro-ecosystem of the United States. This evaluation yielded a Willmot's D and mean absolute error of 0.81 and 5.24 g CO2/d, respectively, using CO2, leaf area, temperature, and moisture constraints from the MOD16 ET model, Priestley-Taylor ET model, and the Global Production Efficiency Model (GLOPEM). A Monte Carlo simulation revealed that the model was most sensitive to the Enhanced Vegetation Index (EVI) input, followed by Photosynthetically Active Radiation, vapor pressure deficit, and air temperature. The model will now be evaluated using 30 x 30m (Landsat resolution) biomass transects developed in 2011 and 2012 from spectroradiometric and other non-destructive in situ metrics for several cotton, maize, and rice fields across the Central Valley. Finally, the model will be driven by Daymet and MODIS data over the entire State of California and compared with county-level crop yield statistics. It is anticipated that the new model will facilitate agro-climatic decision-making in

  6. Constraints on the rare tau decays from {mu} {yields} e{gamma} in the supersymmetric see-saw model

    Energy Technology Data Exchange (ETDEWEB)

    Ibarra, A. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Simonetto, C. [Technische Univ., Muenchen (Germany). Physik-Department

    2008-02-15

    It is now a firmly established fact that all family lepton numbers are violated in Nature. In this paper we discuss the implications of this observation for future searches for rare tau decays in the supersymmetric see-saw model. Using the two loop renormalization group evolution of the soft terms and the Yukawa couplings we show that there exists a lower bound on the rate of the rare process {mu}{yields}e{gamma} of the form BR({mu}{yields}e{gamma})>or similar C x BR({tau}{yields}{mu}{gamma})BR({tau}{yields}e{gamma}), where C is a constant that depends on supersymmetric parameters. Our only assumption is the absence of cancellations among the high-energy see-saw parameters. We also discuss the implications of this bound for future searches for rare tau decays. In particular, for large regions of the mSUGRA parameter space, we show that present B-factories could discover either {tau}{yields}{mu}{gamma} or {tau}{yields}e{gamma}, but not both. (orig.)

  7. Evaluation of root water uptake in the ISBA-A-gs land surface model using agricultural yield statistics over France

    Directory of Open Access Journals (Sweden)

    N. Canal

    2014-05-01

    Full Text Available The interannual variability of cereal grain yield and permanent grassland dry matter yield is simulated over French sites by the Interactions between Soil, Biosphere and Atmosphere, CO2-reactive (ISBA-A-gs generic Land Surface Model (LSM. The two soil profile schemes available in the model are used to simulate the above-ground biomass (Bag of cereals and grasslands: a 2-layer force-restore (FR-2L bulk reservoir model and a multi-layer diffusion (DIF model. The DIF model is implemented with or without deep soil layers below the root-zone. The evaluation of the various root water uptake models is achieved by using the French agricultural statistics of Agreste over the 1994–2010 period at 45 cropland and 48 grassland sites, for a range of rooting depths. The number of sites where the simulated annual maximum Bag presents a significant correlation with the yield observations is used as a metric to benchmark the root water uptake models. Significant correlations (p value < 0.01 are found for up to 29% of the cereal sites and 77% of the grassland sites. It is found that modelling additional subroot zone base flow soil layers does not improve (and may even degrade the representation of the interannual variability of the vegetation above-ground biomass. These results are particularly robust for grasslands as calibrated simulations are able to represent the extreme 2003 and 2007 years corresponding to unfavourable and favourable fodder production, respectively.

  8. Developing a scalable model of recombinant protein yield from Pichia pastoris: the influence of culture conditions, biomass and induction regime

    Directory of Open Access Journals (Sweden)

    Wilks Martin DB

    2009-07-01

    Full Text Available Abstract Background The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors. Results Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from Pichia pastoris, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism. Conclusion We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time.

  9. Modelo de estimativa de rendimento de soja no Estado do Rio Grande do Sul Estimation model for soybean yield in the State of Rio Grande do Sul, Brazil

    Directory of Open Access Journals (Sweden)

    Denise Cybis Fontana

    2001-03-01

    Full Text Available Este trabalho teve como objetivo parametrizar e validar o modelo multiplicativo de Jensen modificado para a estimativa do rendimento da cultura da soja no Estado do Rio Grande do Sul, em condições de lavoura. O ajuste foi feito usando dados meteorológicos de seis estações localizadas na região de produção significativa dessa cultura e dados de rendimento médio de todo o Estado, oriundos de estatísticas oficiais do IBGE, no período 1974/75 a 1994/95. O modelo apresentou bom ajuste, com coeficientes de determinação de 0,86 para o modelo completo (novembro a abril e 0,75 para o modelo reduzido (janeiro a março. A validação do modelo, feita com dados das safras 1995/96, 1996/97, 1997/98 e 1998/99, mostrou um bom desempenho, indicando que a água é o fator isolado que maior influência exerce na definição do rendimento da soja no Rio Grande do Sul e, portanto, pode ser incorporado a programas de previsão de safras.The objective of this study was to fit and validate a modified Jensen multiplicative model to estimate soybean grain yield in the State of Rio Grande do Sul, Brazil, under field conditions. The fitness was done using meteorological data from six weather stations located in the region of major production of this crop and data from averaged soybean grain yield over the whole state. The grain yield was obtained from official government statistics of IBGE (Instituto Brasileiro de Geografia e Estatística, from 1974/75 to 1994/95. The model showed a good fit, with determination coefficients varying from 0.86 for a complete model (November to April to 0.75 for a reduced one (January to March. The model validation, done with independent data of 1995/96, 1996/97, 1997/98 e 1998/99, had a good performance, showing that water is the isolated factor that has the major influence on soybean grain yield definition in Rio Grande do Sul, and, therefore, could be incorporated into programs for predicting the crop harvest.

  10. The development of a tensile-shear punch correlation for yield properties of model austenitic alloys

    Energy Technology Data Exchange (ETDEWEB)

    Hankin, G.L.; Faulkner, R.G. [Loughborough Univ. (United Kingdom); Hamilton, M.L.; Garner, F.A. [Pacific Northwest National Lab., Richland, WA (United States)

    1997-08-01

    The effective shear yield and maximum strengths of a set of neutron-irradiated, isotopically tailored austentic alloys were evaluated using the shear punch test. The dependence on composition and neutron dose showed the same trends as were observed in the corresponding miniature tensile specimen study conducted earlier. A single tensile-shear punch correlation was developed for the three alloys in which the maximum shear stress or Tresca criterion was successfully applied to predict the slope. The correlation will predict the tensile yield strength of the three different austenitic alloys tested to within {+-}53 MPa. The accuracy of the correlation improves with increasing material strength, to within {+-} MPa for predicting tensile yield strengths in the range of 400-800 MPa.

  11. MODELING AND SOLVING A RICH VEHICLE ROUTING PROBLEM FOR THE DELIVERY OF GOODS IN URBAN AREAS

    Directory of Open Access Journals (Sweden)

    José Ferreira de Souza Neto

    Full Text Available ABSTRACT This work addresses a vehicle routing problem that aims at representing delivery operations of large volumes of products in dense urban areas. Inspired by a case study in a drinks producer and distributor, we propose a mathematical programming model and solution approaches that take into account costs with own and chartered vehicles, multiple deliverymen, time windows in customers, compatibility of vehicles and customers, time limitations for the circulation of large vehicles in city centers and multiple daily trips. Results with instances based on real data provided by the company highlight the potential of applicability of some of the proposed methods.

  12. Accidental goodness?

    DEFF Research Database (Denmark)

    Richter, Anne

    In postmodern capitalist market economies, management of the single organisation is bound to be guided by several rationales, which are in conflict with each other. For some writers this perception leads to the argument, that conceptions of management should strive towards goals beyond the present...... society. For others, the handling of plural perspectives is just a management discipline. However these positions seem to share a focus on organization as a the arena for the organization of the good. The contribution looks at the management of occupational accidents as an example of striving for good...

  13. CROP YIELD AND CO2 FIXATION MONITORING IN ASIA USING A PHOTOSYNTHETICSTERILITY MODEL WITH SATELLITES AND METEOROLOGICAL DATA

    Energy Technology Data Exchange (ETDEWEB)

    Daijiro Kaneko [Department of Civil and Environmental Engineering, Matsue National College of Technology, Matsue (Japan); Toshiro Kumakura [Department of Civil and Environmental Engineering, Nagaoka University of Technology, Nagaoka (Japan); Peng Yang [Laboratory of Resources Remote Sensing and Digital Agriculture, Ministry of Agriculture, Beijing (China)

    2008-09-30

    This study is intended to develop a model for estimating carbon dioxide (CO{sub 2}) fixation in the carbon cycle and for monitoring grain yields using a photosynthetic-sterility model, which integrates solar radiation and air temperature effects on photosynthesis, along with grain-filling from heading to ripening. Grain production monitoring would support orderly crisis management to maintain food security in Asia, which is facing climate fluctuation through this century of global warming. The author improved a photosynthesis-and-sterility model to compute both the crop yield and crop situation index CSI, which gives a percentage of rice yields compared to normal annual production. The model calculates photosynthesis rates including biomass effects, lowtemperature sterility, and high-temperature injury by incorporating solar radiation, effective air temperature, the normalized difference vegetation index NDVI, and the effect of temperature on photosynthesis by grain plant leaves. A decision-tree method classifies the distribution of crop fields in Asia using MODIS fundamental landcover and SPOT VEGETATION data, which include the Normalized Vegetation index (NDVI) and Land Surface Water Index (LSWI). This study provides daily distributions of the photosynthesis rate, which is the CO2 fixation in Asian areas combined with the land-cover distribution, the Japanese geostationary meteorological satellite (GMS), and meteorological re-analysis data by National Centers for Environmental Prediction (NCEP). The method is based on routine observation data, enabling automated monitoring of crop yields.

  14. Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation

    Science.gov (United States)

    The scale mismatch between remotely sensed observations and crop growth models simulated state variables decreases the reliability of crop yield estimates. To overcome this problem, we used a two-step data assimilation phases: first we generated a complete leaf area index (LAI) time series by combin...

  15. Potential future fisheries yields in shelf waters: a model study of the effects of climate change and ocean acidification

    Science.gov (United States)

    van Leeuwen, S. M.; Le Quesne, W. F.; Parker, E. R.

    2016-01-01

    We applied a coupled marine water column model to three sites in the North Sea. The three sites represent different hydrodynamic regimes and are thus representative of a wider area. The model consists of a hydro-biogeochemical model (GOTM-ERSEM-BFM) coupled one way upwards to a size-structured model representing pelagic predators and detritivores (Blanchard et al., 2009). Thus, bottom-up pressures like changing abiotic environment (climate change, chemical cycling) will have an impact on fish biomass across the size spectrum. Here, we studied three different impacts of future conditions on fish yield: climatic impacts (medium emission scenario), abiotic ocean acidification impacts (reduced pelagic nitrification), and biotic ocean acidification impacts (reduced detritivore growth rate). The three impacts were studied separately and combined, and results showed that sites within different hydrodynamic regimes can respond very differently. The seasonally stratified site showed an increase in fish yields (occurring in winter and spring), with acidification effects of the same order of magnitude as climatic effects. The permanently mixed site also showed an increase in fish yield (increase in summer, decrease in winter), due to climatic effects moderated by acidification impacts. The third site, which is characterised by large inter-annual variability in thermal stratification duration, showed a decline in fish yields (occurring in winter) due to decline in the benthic system which forms an important carbon pathway at this site. All sites displayed a shift towards a more pelagic-oriented system.

  16. Incorporating uncertainty into the ranking of SPARROW model nutrient yields from Mississippi/Atchafalaya River basin watersheds

    Science.gov (United States)

    Robertson, Dale M.; Schwarz, Gregory E.; Saad, David A.; Alexander, Richard B.

    2009-01-01

    Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient-reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight-digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from

  17. hESCCO: development of good practice models for hES cell derivation.

    Science.gov (United States)

    Franklin, Sarah B; Hunt, Charles; Cornwell, Glenda; Peddie, Valerie; Desousa, Paul; Livie, Morag; Stephenson, Emma L; Braude, Peter R

    2008-01-01

    One response of the UK research community to the public sensitivity and logistical complexity of embryo donation to stem cell research has been the formation of a national network of 'human embryonic stem cell coordinators' (hESCCO). The aim of hESCCO is to contribute to the formation and implementation of national standards for hES cell derivation and banking, in particular the ethical protocols for patient information and informed consent. The hESCCO project is an innovative practical intervention within the broader attempt to establish greater transparency, consistency, efficiency and standardization of hES derivation in the UK. A major outcome of the hESCCO initiative has been the drafting and implementation of a national consent form. The lessons learned in this context may be relevant to other practitioners and regulators as a model of best practice in hES cell derivation.

  18. Is the Mouse a Good Model of Human PPARγ-Related Metabolic Diseases?

    Science.gov (United States)

    Pap, Attila; Cuaranta-Monroy, Ixchelt; Peloquin, Matthew; Nagy, Laszlo

    2016-01-01

    With the increasing number of patients affected with metabolic diseases such as type 2 diabetes, obesity, atherosclerosis and insulin resistance, academic researchers and pharmaceutical companies are eager to better understand metabolic syndrome and develop new drugs for its treatment. Many studies have focused on the nuclear receptor peroxisome proliferator-activated receptor gamma (PPARγ), which plays a crucial role in adipogenesis and lipid metabolism. These studies have been able to connect this transcription factor to several human metabolic diseases. Due to obvious limitations concerning experimentation in humans, animal models—mainly mouse models—have been generated to investigate the role of PPARγ in different tissues. This review focuses on the metabolic features of human and mouse PPARγ-related diseases and the utility of the mouse as a model. PMID:27483259

  19. Semi-empirical Calculation for Yield of 240Pu Spontaneous Fission

    Institute of Scientific and Technical Information of China (English)

    SHU; Neng-chuan; LIU; Li-le; CHEN; Xiao-song; LIU; Ting-jin; SUN; Zheng-jun; CHEN; Yong-jing; QIAN; Jing

    2012-01-01

    <正>The spontaneous fission yield has important implication in the nuclear engineering. This work used semi-empirical model to calculate its chain yield, the result shows good agreement with the measured data. There are only 3 sets of measured data, and only too gave the chain yields and cumulative yields, covering 17 chains. It is not enough to satisfy the requirement of users. So it is needed to use theoretical model to calculate the chain yield without measured data.

  20. Developing a Coffee Yield Prediction and Integrated Soil Fertility Management Recommendation Model for Northern Tanzania

    NARCIS (Netherlands)

    Maro, G.P.; Mrema, J.P.; Msanya, B.M.; Janssen, B.H.; Teri, J.M.

    2014-01-01

    The aim of this study was to develop a simple and quantitative system for coffee yield estimation and nutrient input advice, so as to address the problem of declining annual coffee production in Tanzania (particularly in its Northern coffee zone), which is related to declining soil fertility. The st

  1. Manufacturing of par-fried french-fries. Part 2: Modelling yield efficiency of peeling

    NARCIS (Netherlands)

    Somsen, D.J.; Capelle, A.; Tramper, J.

    2004-01-01

    The paper outlines the yield efficiency of steam peeling. It was proven that peeling potatoes manually with sandpaper results in the lowest possible peel losses. These losses were desired or wanted losses. However, in practice steam peeling results not only in wanted losses but also in substantial u

  2. The estimation of rice paddy yield with GRAMI crop model and Geostationary Ocean Color Imager (GOCI) image over South Korea

    Science.gov (United States)

    Yeom, J. M.; Kim, H. O.

    2014-12-01

    In this study, we estimated the rice paddy yield with moderate geostationary satellite based vegetation products and GRAMI model over South Korea. Rice is the most popular staple food for Asian people. In addition, the effects of climate change are getting stronger especially in Asian region, where the most of rice are cultivated. Therefore, accurate and timely prediction of rice yield is one of the most important to accomplish food security and to prepare natural disasters such as crop defoliation, drought, and pest infestation. In the present study, GOCI, which is world first Geostationary Ocean Color Image, was used for estimating temporal vegetation indices of the rice paddy by adopting atmospheric correction BRDF modeling. For the atmospheric correction with LUT method based on Second Simulation of the Satellite Signal in the Solar Spectrum (6S), MODIS atmospheric products such as MOD04, MOD05, MOD07 from NASA's Earth Observing System Data and Information System (EOSDIS) were used. In order to correct the surface anisotropy effect, Ross-Thick Li-Sparse Reciprocal (RTLSR) BRDF model was performed at daily basis with 16day composite period. The estimated multi-temporal vegetation images was used for crop classification by using high resolution satellite images such as Rapideye, KOMPSAT-2 and KOMPSAT-3 to extract the proportional rice paddy area in corresponding a pixel of GOCI. In the case of GRAMI crop model, initial conditions are determined by performing every 2 weeks field works at Chonnam National University, Gwangju, Korea. The corrected GOCI vegetation products were incorporated with GRAMI model to predict rice yield estimation. The predicted rice yield was compared with field measurement of rice yield.

  3. A sub-canopy structure for simulating oil palm in the Community Land Model: phenology, allocation and yield

    Directory of Open Access Journals (Sweden)

    Y. Fan

    2015-06-01

    Full Text Available Land surface modelling has been widely used to characterize the two-way interactions between climate and human activities in terrestrial ecosystems such as deforestation, agricultural expansion, and urbanization. Towards an effort to quantify the effects of forests to oil palm conversion occurring in the tropics on land–atmosphere carbon, water and energy fluxes, we introduce a new perennial crop plant functional type (PFT for oil palm. Due to the modular and sequential nature of oil palm growth (around 40 stacked phytomers and yield (fruit bunches axillated on each phytomer, we developed a specific sub-canopy structure for simulating palm's growth and yield within the framework of the Community Land Model (CLM4.5. In this structure each phytomer has its own prognostic leaf growth and fruit yield capacity like a PFT but with shared stem and root components among all phytomers. Phenology and carbon and nitrogen allocation operate on the different phytomers in parallel but at unsynchronized steps, so that multiple fruit yields per annum are enabled in terms of carbon and nitrogen outputs. An important phenological phase is identified for the palm PFT – the storage growth period of bud and "spear" leaves which are photosynthetically inactive before expansion. Agricultural practices such as transplanting, fertilization, and leaf pruning are represented. Parameters introduced for the new PFT were calibrated and validated with field measurements of leaf area index (LAI and yield from Sumatra, Indonesia. In calibration with a mature oil palm plantation, the cumulative yields from 2005 to 2014 matched perfectly between simulation and observation (mean percentage error = 4 %. Simulated inter-annual dynamics of PFT-level and phytomer-level LAI were both within the range of field measurements. Validation from eight independent oil palm sites shows the ability of the model to adequately predict the average leaf growth and fruit yield across sites but

  4. A sub-canopy structure for simulating oil palm in the Community Land Model: phenology, allocation and yield

    Science.gov (United States)

    Fan, Y.; Roupsard, O.; Bernoux, M.; Le Maire, G.; Panferov, O.; Kotowska, M. M.; Knohl, A.

    2015-06-01

    Land surface modelling has been widely used to characterize the two-way interactions between climate and human activities in terrestrial ecosystems such as deforestation, agricultural expansion, and urbanization. Towards an effort to quantify the effects of forests to oil palm conversion occurring in the tropics on land-atmosphere carbon, water and energy fluxes, we introduce a new perennial crop plant functional type (PFT) for oil palm. Due to the modular and sequential nature of oil palm growth (around 40 stacked phytomers) and yield (fruit bunches axillated on each phytomer), we developed a specific sub-canopy structure for simulating palm's growth and yield within the framework of the Community Land Model (CLM4.5). In this structure each phytomer has its own prognostic leaf growth and fruit yield capacity like a PFT but with shared stem and root components among all phytomers. Phenology and carbon and nitrogen allocation operate on the different phytomers in parallel but at unsynchronized steps, so that multiple fruit yields per annum are enabled in terms of carbon and nitrogen outputs. An important phenological phase is identified for the palm PFT - the storage growth period of bud and "spear" leaves which are photosynthetically inactive before expansion. Agricultural practices such as transplanting, fertilization, and leaf pruning are represented. Parameters introduced for the new PFT were calibrated and validated with field measurements of leaf area index (LAI) and yield from Sumatra, Indonesia. In calibration with a mature oil palm plantation, the cumulative yields from 2005 to 2014 matched perfectly between simulation and observation (mean percentage error = 4 %). Simulated inter-annual dynamics of PFT-level and phytomer-level LAI were both within the range of field measurements. Validation from eight independent oil palm sites shows the ability of the model to adequately predict the average leaf growth and fruit yield across sites but also indicates that

  5. Is the BEHI Index (Part of the BANCS Model Good for Prediction of Streambank Erosion?

    Directory of Open Access Journals (Sweden)

    Zuzana Allmanová

    2016-01-01

    Full Text Available Sedimentation of waterways and reservoirs, decreasing quality of drinking water and costs necessary for maintenance of these objects directly related to streambank erosion. This study provides a tool for water management that can help with estimation parts of a streambank which are prone to erosion. The Bank erosion hazard index (BEHI part of the BANCS (Bank Assessment for Non‑point source Consequences of Sediment model is one of the several procedures for assessing streambank erosion condition and potential (Rosgen, 2001. On May 15th 2014 a high precipitation occurred in the watershed of Sestrč torrent, in the eastern part of Chočské vrchy (Sp = 27.64 km2. It reached 102.7 mm per 24 hours. The rainfall resulted in extreme streambank erosion. We started the research of annual stream bank erosion on Sestrč in the beginning of May 2014 and we established 19 experimental sections on the stream. Occurrence of heavy rainfall allowed us to erosion rates after flash flood. The aim of this paper was to verify, if BEHI index can really determine the most vulnerable parts of a banks to erosion. We measured erosion rates Eb (m3/m using a bank pins and toe pin (Sass, 2011 on each experimental section and evaluated each section by BEHI index (Rosgen, 2001, 2008. The results were statistically verified and confirmed a strong relationship between BEHI and real damage of banks Eb (m3/m (R: 0.88, R2: 0.78.

  6. How sensitive are the thermal fits to heavy-ion hadron yield data to the modeling of the eigenvolume interactions?

    CERN Document Server

    Vovchenko, Volodymyr

    2016-01-01

    The hadron-resonance gas (HRG) model with eigenvolume corrections is employed to fit the hadron yield data of the NA49 collaboration for central Pb+Pb collisions at $\\sqrt{s_{NN}}$ = 6.3, 7.6, 8.8, 12.3, and 17.3 GeV, the hadron midrapidity yield data of the STAR collaboration for Au+Au collisions at $\\sqrt{s_{NN}}$ = 200 GeV, and the hadron midrapidity yield data of the ALICE collaboration for Pb+Pb collisions at $\\sqrt{s_{NN}}$ = 2760 GeV. The influence of the EV corrections is studied within two different formulations of the EV HRG model. For the case of the point-particle HRG the extracted values of temperature and chemical potential are consistent with previous findings. The situation is very different when we apply the eigenvolume corrections with mass-proportional eigenvolumes $v_i \\sim m_i$, fixed to different values of the proton hard-core radius of $r_p$. At given bombarding energy the EV HRG model fits do not just yield a single $T-\\mu_B$ pair, but a whole range of $T-\\mu_B$ pairs. These pairs form...

  7. Good Vibrations

    OpenAIRE

    Panesar, Lucy

    2007-01-01

    Good Vibrations was a market research exercise conducted by Felicity (my alter-ego) and assistants to help develop marketing and packaging for an electro-therapeutic device (vibrator) used to treat hysteria and other female stress related disorders. It was a live art work commissioned by The Live Art Development Agency for East End Collaborations on 6th May 2007 and the South London Gallery for Bonkersfest on 2nd June 2007.

  8. Weed management through herbicide application in direct-seeded rice and yield modeling by artificial neural network

    Directory of Open Access Journals (Sweden)

    Dibakar Ghosh

    2016-06-01

    Full Text Available In direct seeded rice (DSR cultivation, weed is the major constraint mainly due to absence of puddling in field. The yield loss due to weed interference is huge, may be up to 100%. In this perspective, the present experiment was conducted to study the efficacy of selected herbicides, and to predict the rice yield using artificial neural network (ANN models. The dry weight and density of weeds were recorded at different growth stages and consequently herbicidal efficacy was evaluated. Experimental results revealed that pre-emergence (PRE herbicide effectively controlled the germination of grassy weeds. Application bispyribac-sodium as post-emergence (POST following PRE herbicides (clomazone or pendimethalin or as tank-mixture with clomazone effectively reduced the density and biomass accumulation of diverse weed flora in DSR. Herbicidal treatments improved the plant height, yield attributes and grain yield (2.7 to 5.5 times over weedy check. The sensitivity of the best ANN model clearly depicts that the weed control index (WCI of herbicides was most important than their weed control efficiency (WCE. Besides, the early control of weeds is a better prescription to improve rice yield. Differences in sensitivity values of WCI and WCE across the crop growth stages also suggest that at 15, 30 and 60 days after sowing, herbicides most effectively controlled sedges, broad leaves and grasses, respectively. Based on the grain yield and herbicidal WCE, it can be concluded that the combined application of pendimethalin or clomazone as PRE followed by bispyribac-sodium as POST or tank-mixture of clomazone + bispyribac sodium can effectively control different weed flushes throughout the crop growth period in DSR.

  9. Weed management through herbicide application in direct-seeded rice and yield modeling by artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Ghosh, D.; Singh, U.P.; Ray, K.; Das, A.

    2016-11-01

    In direct seeded rice (DSR) cultivation, weed is the major constraint mainly due to absence of puddling in field. The yield loss due to weed interference is huge, may be up to 100%. In this perspective, the present experiment was conducted to study the efficacy of selected herbicides, and to predict the rice yield using artificial neural network (ANN) models. The dry weight and density of weeds were recorded at different growth stages and consequently herbicidal efficacy was evaluated. Experimental results revealed that pre-emergence (PRE) herbicide effectively controlled the germination of grassy weeds. Application bispyribac-sodium as post-emergence (POST) following PRE herbicides (clomazone or pendimethalin) or as tank-mixture with clomazone effectively reduced the density and biomass accumulation of diverse weed flora in DSR. Herbicidal treatments improved the plant height, yield attributes and grain yield (2.7 to 5.5 times) over weedy check. The sensitivity of the best ANN model clearly depicts that the weed control index (WCI) of herbicides was most important than their weed control efficiency (WCE). Besides, the early control of weeds is a better prescription to improve rice yield. Differences in sensitivity values of WCI and WCE across the crop growth stages also suggest that at 15, 30 and 60 days after sowing, herbicides most effectively controlled sedges, broad leaves and grasses, respectively. Based on the grain yield and herbicidal WCE, it can be concluded that the combined application of pendimethalin or clomazone as PRE followed by bispyribac-sodium as POST or tank-mixture of clomazone + bispyribac sodium can effectively control different weed flushes throughout the crop growth period in DSR. (Author)

  10. The structure of personality of a good teacher from students perspective according to the Big-Five model

    Directory of Open Access Journals (Sweden)

    Genc Lajoš

    2014-01-01

    Full Text Available This paper deals with the identification of desirable personality characteristics of teachers from students perspective in the Big-Five Model of personality from a phenomenological approach. The description of personality of a good teacher was obtained from students of the University of Novi Sad (n=443. The Big Five Inventory (BFI was applied with the instruction to respond to claims as a good teacher would answer. The students’ estimates indicate that a good teacher is expected to have lower emotional instability, but more pronounced extroversion, openness to experience, cooperativeness (pleasantness and consciousness with regard to referent values in general population. For the domain of neuroticism, the difference is either small or medium in size, for cooperativeness of a medium size, and for extroversion, consciousness and openness to experience the difference is large. The gender of students does not influence their expectations. Methodological dilemmas in this area of research and implications of the results for the selection and professional development of teachers are discussed. [Projekat Ministarstva nauke Republike Srbije, br. 179010 i br. 47020

  11. Statistical hadronization model analysis of hadron yields in p + Nb and Ar + KCl at SIS18 energies

    Science.gov (United States)

    Agakishiev, G.; Arnold, O.; Balanda, A.; Belver, D.; Belyaev, A.; Berger-Chen, J. C.; Blanco, A.; Böhmer, M.; Boyard, J. L.; Cabanelas, P.; Castro, E.; Chernenko, S.; Destefanis, M.; Dohrmann, F.; Dybczak, A.; Epple, E.; Fabbietti, L.; Fateev, O.; Finocchiaro, P.; Fonte, P.; Friese, J.; Fröhlich, I.; Galatyuk, T.; Garzón, J. A.; Gernhäuser, R.; Gilardi, C.; Göbel, K.; Golubeva, M.; González-Díaz, D.; Guber, F.; Gumberidze, M.; Heinz, T.; Hennino, T.; Holzmann, R.; Ierusalimov, A.; Iori, I.; Ivashkin, A.; Jurkovic, M.; Kämpfer, B.; Karavicheva, T.; Koenig, I.; Koenig, W.; Kolb, B. W.; Kornakov, G.; Kotte, R.; Krása, A.; Krizek, F.; Krücken, R.; Kuc, H.; Kühn, W.; Kugler, A.; Kurepin, A.; Ladygin, V.; Lalik, R.; Lange, J. S.; Lang, S.; Lapidus, K.; Lebedev, A.; Liu, T.; Lopes, L.; Lorenz, M.; Maier, L.; Mangiarotti, A.; Markert, J.; Metag, V.; Michalska, B.; Mihaylov, D.; Michel, J.; Morinière, E.; Mousa, J.; Müntz, C.; Münzer, R.; Naumann, L.; Pachmayer, Y. C.; Palka, M.; Parpottas, Y.; Pechenov, V.; Pechenova, O.; Pietraszko, J.; Przygoda, W.; Ramstein, B.; Rehnisch, L.; Reshetin, A.; Rustamov, A.; Sadovsky, A.; Salabura, P.; Scheib, T.; Schmah, A.; Schuldes, H.; Schwab, E.; Siebenson, J.; Sobolev, Yu. G.; Spataro, S.; Spruck, B.; Ströbele, H.; Stroth, J.; Sturm, C.; Tarantola, A.; Teilab, K.; Tlusty, P.; Traxler, M.; Trebacz, R.; Tsertos, H.; Vasiliev, T.; Wagner, V.; Weber, M.; Wendisch, C.; Wirth, J.; Wisniowski, M.; Wüstenfeld, J.; Yurevich, S.; Zanevsky, Y.

    2016-06-01

    The HADES data from p + Nb collisions at a center-of-mass energy of √{s_{NN}} = 3.2 GeV are analyzed employing a statistical hadronization model. The model can successfully describe the production yields of the identified hadrons π0, η, Λ, K 0 s, ω with parameters T_{chem} = (99± 11) MeV and μb = (619± 34) MeV, which fit well into the chemical freeze-out systematics found in heavy-ion collisions. In addition, we reanalyze our previous HADES data from Ar + KCl collisions at √{s_{NN}} = 2.6 GeV with an updated version of the model. We address equilibration in heavy-ion collisions by testing two aspects: the description of yields and the regularity of freeze-out parameters from a statistical model fit as a function of colliding energy and system size. Despite its success, the model fails to describe the observed Ξ- yields in both, p + Nb and Ar + KCl . Special emphasis is put on feed-down contributions from higher-lying resonance states as a possible explanation for the observed excess.

  12. Rare three-body decay t {yields} ch{gamma} in the standard model and the two-Higgs doublet model

    Energy Technology Data Exchange (ETDEWEB)

    Cordero-Cid, A [Facultad de Ciencias Fisico Matematicas, Benemerita Universidad Autonoma de Puebla, Apartado Postal 1152, Puebla, Pue. (Mexico); Garcia-Luna, J L [Departamento de Fisica, Centro Universitario de Ciencias Exactas e Ingenierias, Universidad de Guadalajara, Blvd. Marcelino Garcia Barragan 1508, CP 44840, Guadalajara Jal. (Mexico); Ramirez-Zavaleta, F [Departamento de Fisica, CINVESTAV, Apartado Postal 14-740, 07000, Mexico DF (Mexico); Tavares-Velasco, G [Facultad de Ciencias Fisico Matematicas, Benemerita Universidad Autonoma de Puebla, Apartado Postal 1152, Puebla, Pue. (Mexico); Toscano, J J [Facultad de Ciencias Fisico Matematicas, Benemerita Universidad Autonoma de Puebla, Apartado Postal 1152, Puebla, Pue. (Mexico)

    2006-04-01

    A complete calculation of the rare three-body decay t {yields} ch{gamma} is presented in the framework of the standard model. In the unitary gauge, such a calculation involves about 20 Feynman diagrams. We also calculate this decay in the general two-Higgs doublet model (model III), in which it arises at the tree level. While in the standard model the decay t {yields} ch{gamma} is extremely suppressed, with a branching fraction of the order of 10{sup -15} for a Higgs boson mass of the order of 115 GeV, in the model III it may have a branching ratio up to 10{sup -5}. We also discuss the crossed decay h {yields} bs-bar{gamma}.

  13. Integrating remote sensing, geographic information system and modeling for estimating crop yield

    Science.gov (United States)

    Salazar, Luis Alonso

    This thesis explores various aspects of the use of remote sensing, geographic information system and digital signal processing technologies for broad-scale estimation of crop yield in Kansas. Recent dry and drought years in the Great Plains have emphasized the need for new sources of timely, objective and quantitative information on crop conditions. Crop growth monitoring and yield estimation can provide important information for government agencies, commodity traders and producers in planning harvest, storage, transportation and marketing activities. The sooner this information is available the lower the economic risk translating into greater efficiency and increased return on investments. Weather data is normally used when crop yield is forecasted. Such information, to provide adequate detail for effective predictions, is typically feasible only on small research sites due to expensive and time-consuming collections. In order for crop assessment systems to be economical, more efficient methods for data collection and analysis are necessary. The purpose of this research is to use satellite data which provides 50 times more spatial information about the environment than the weather station network in a short amount of time at a relatively low cost. Specifically, we are going to use Advanced Very High Resolution Radiometer (AVHRR) based vegetation health (VH) indices as proxies for characterization of weather conditions.

  14. Economic impacts of climate change on agriculture: a comparison of process-based and statistical yield models

    Science.gov (United States)

    Moore, Frances C.; Baldos, Uris Lantz C.; Hertel, Thomas

    2017-06-01

    A large number of studies have been published examining the implications of climate change for agricultural productivity that, broadly speaking, can be divided into process-based modeling and statistical approaches. Despite a general perception that results from these methods differ substantially, there have been few direct comparisons. Here we use a data-base of yield impact studies compiled for the IPCC Fifth Assessment Report (Porter et al 2014) to systematically compare results from process-based and empirical studies. Controlling for differences in representation of CO2 fertilization between the two methods, we find little evidence for differences in the yield response to warming. The magnitude of CO2 fertilization is instead a much larger source of uncertainty. Based on this set of impact results, we find a very limited potential for on-farm adaptation to reduce yield impacts. We use the Global Trade Analysis Project (GTAP) global economic model to estimate welfare consequences of yield changes and find negligible welfare changes for warming of 1 °C-2 °C if CO2 fertilization is included and large negative effects on welfare without CO2. Uncertainty bounds on welfare changes are highly asymmetric, showing substantial probability of large declines in welfare for warming of 2 °C-3 °C even including the CO2 fertilization effect.

  15. Using ORYZA2000 to model cold rice yield response to climate change in the Heilongjiang province, China

    Institute of Scientific and Technical Information of China (English)

    Jingting; Zhang; Liping; Feng; Haiping; Zou; De; Li; Liu

    2015-01-01

    Rice(Oryza sativa L.) is one of the most important staple crops in China. Increasing atmospheric greenhouse gas concentrations and associated climate change may greatly affect rice production. We assessed the potential impacts of climate change on cold rice production in the Heilongjiang province, one of China’s most important rice production regions. Data for a baseline period(1961–1990) and the period 2010–2050 in A2 and B2 scenarios were used as input to drive the rice model ORYZA2000 with and without accounting for the effects of increasing atmospheric CO2 concentration. The results indicate that mean,maximum, and minimum temperature during the rice growing season, in the future period considered, would increase by 1.8 °C under the A2 scenario and by 2.2 °C under the B2 scenario compared with those in the baseline. The rate of change in average maximum and minimum temperatures would increase by 0.6 °C per 10-year period under the A2 scenario and by 0.4 °C per 10-year period under the B2 scenario. Precipitation would increase slightly in the rice growing season over the next 40 years. The rice growing season would be shortened and the yield would increase in most areas in the Heilongjiang province. Without accounting for CO2 effect, the rice growing season in the period 2010–2050 would be shortened by 4.7 and 5.8 days,and rice yields would increase by 11.9% and 7.9%, under the A2 and B2 scenarios, respectively.Areas with simulated rice yield increases greater than 30.0% were in the Xiaoxing’an Mountain region. The simulation indicated a decrease in yield of less than 15% in the southwestern Songnen Plain. The rate of change in simulated rice yield was 5.0% and 2.5% per 10 years under the A2 and B2 scenarios, respectively. When CO2 effect was accounted for, rice yield increased by 44.5% and 31.3% under the A2 and B2 scenarios, respectively. The areas of increasing yield were sharply expanded. The area of decreasing yield in the western region of

  16. Using ORYZA2000 to model cold rice yield response to climate change in the Heilongjiang province, China

    Institute of Scientific and Technical Information of China (English)

    Jingting Zhang; Liping Feng; Haiping Zou; De Li Liu

    2015-01-01

    Rice (Oryza sativa L.) is one of the most important staple crops in China. Increasing atmospheric greenhouse gas concentrations and associated climate change may greatly affect rice production. We assessed the potential impacts of climate change on cold rice production in the Heilongjiang province, one of China's most important rice production regions. Data for a baseline period (1961–1990) and the period 2010–2050 in A2 and B2 scenarios were used as input to drive the rice model ORYZA2000 with and without accounting for the effects of increasing atmospheric CO2 concentration. The results indicate that mean, maximum, and minimum temperature during the rice growing season, in the future period considered, would increase by 1.8 °C under the A2 scenario and by 2.2 °C under the B2 scenario compared with those in the baseline. The rate of change in average maximum and minimum temperatures would increase by 0.6 °C per 10-year period under the A2 scenario and by 0.4 °C per 10-year period under the B2 scenario. Precipitation would increase slightly in the rice growing season over the next 40 years. The rice growing season would be shortened and the yield would increase in most areas in the Heilongjiang province. Without accounting for CO2 effect, the rice growing season in the period 2010–2050 would be shortened by 4.7 and 5.8 days, and rice yields would increase by 11.9%and 7.9%, under the A2 and B2 scenarios, respectively. Areas with simulated rice yield increases greater than 30.0%were in the Xiaoxing'an Mountain region. The simulation indicated a decrease in yield of less than 15% in the southwestern Songnen Plain. The rate of change in simulated rice yield was 5.0%and 2.5%per 10 years under the A2 and B2 scenarios, respectively. When CO2 effect was accounted for, rice yield increased by 44.5%and 31.3%under the A2 and B2 scenarios, respectively. The areas of increasing yield were sharply expanded. The area of decreasing yield in the western region of Songnen

  17. Stand-level growth and yield component models for red oak-sweetgum forests on Mid-South minor stream bottoms

    Science.gov (United States)

    Emily B. Schultz; J. Clint Iles; Thomas G. Matney; Andrew W. Ezell; James S. Meadows; Theodor D. Leininger; al. et.

    2010-01-01

    Greater emphasis is being placed on Southern bottomland hardwood management, but relatively few growth and yield prediction systems exist that are based on sufficient measurements. We present the aggregate stand-level expected yield and structural component equations for a red oak (Quercus section Lobatae)-sweetgum (Liquidambar styraciflua L.) growth and yield model....

  18. Assessment of the interannual variability of agricultural yields in France using satellite data and a generic land surface model

    Science.gov (United States)

    Canal, Nicolas; Calvet, Jean-Christophe; Szczypta, Camille

    2013-04-01

    The generic ISBA-A-gs Land Surface Model (LSM) is used to simulate the interannual variability of the maximum above-ground biomass (Bagm) of cereals and grasslands in France. Agricultural statistics are used to optimize the maximal available soil water content (MaxAWC) of the model. For a number of administrative units, significant correlations between the simulated Bagm and the agricultural yield statistics are found over the 1994-2010 period. It is shown that the interannual variability of Bagm and of the simulated soil moisture correlate at given key periods. Significant correlations are found between ten-daily averaged simulated soil moisture and the simulated (observed) Bagm (yields). The corresponding plant growth stage is determined through the Leaf Area Index (LAI). Moreover, it is shown that the interannual variability of the modelled LAI and of the new satellite-derived GEOLAND2 LAI are consistent. The predictive value of both simulated and observed LAI on the agricultural yield (10 to 40 days before harvest) is investigated. The scores are used to benchmark different configurations of the model. In particular two contrasting representations of the soil moisture profile are considered: (1) one root-zone layer, (2) several soil layers with an explicit representation of diffusion processes and an exponential root density profile, with or without a deep soil layer below the root-zone.

  19. Model transparency and validation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--7.

    Science.gov (United States)

    Eddy, David M; Hollingworth, William; Caro, J Jaime; Tsevat, Joel; McDonald, Kathryn M; Wong, John B

    2012-01-01

    Trust and confidence are critical to the success of health care models. There are two main methods for achieving this: transparency (people can see how the model is built) and validation (how well the model reproduces reality). This report describes recommendations for achieving transparency and validation developed by a taskforce appointed by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making. Recommendations were developed iteratively by the authors. A nontechnical description--including model type, intended applications, funding sources, structure, intended uses, inputs, outputs, other components that determine function, and their relationships, data sources, validation methods, results, and limitations--should be made available to anyone. Technical documentation, written in sufficient detail to enable a reader with necessary expertise to evaluate the model and potentially reproduce it, should be made available openly or under agreements that protect intellectual property, at the discretion of the modelers. Validation involves face validity (wherein experts evaluate model structure, data sources, assumptions, and results), verification or internal validity (check accuracy of coding), cross validity (comparison of results with other models analyzing the same problem), external validity (comparing model results with real-world results), and predictive validity (comparing model results with prospectively observed events). The last two are the strongest form of validation. Each section of this article contains a number of recommendations that were iterated among the authors, as well as among the wider modeling taskforce, jointly set up by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.

  20. Work, Health, Music: The enduring Rusyn model of a good life amid changing socioeconomic contexts of progress

    Directory of Open Access Journals (Sweden)

    K. M. Cantin

    2013-11-01

    Full Text Available Rusyns in Eastern and Central Europe have experience with two predominant models of “progress”: the Soviet-style communist and the neoliberal.  Proponents of each system promised to better the lives of all but did not take into account what “better” meant to local populations, including Rusyns.  Increasingly, European governmental and nongovernmental organizations are redefining notions of progress and development to accord with values of sustainability and a capability approach (CA to well-being.  Giovanola (2005 and Robeyns (2005 have argued that scholars of the CA need to better develop concepts of “personhood” and “human flourishing”, and to better explain the importance of social group membership and norms to living a valued life.  The emerging anthropological focus on well-being, emphasizing culturally specific definitions of what happiness and a good life mean, can provide these conceptualizations.  As a case in point, I use freelist and interview data obtained from residents in the Prešov Region of Slovakia and the Zakarpattia Oblast of Ukraine along with Rusyn cultural narratives drawn from poems, folktales, plays, songs, interviews, and speeches to identify prevalent models of “personhood” and “a good life”. I discuss how these narratives intersect and diverge with discourses of happiness and progress along with the implications for Rusyns' ability to flourish. 

  1. Model transparency and validation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-7.

    Science.gov (United States)

    Eddy, David M; Hollingworth, William; Caro, J Jaime; Tsevat, Joel; McDonald, Kathryn M; Wong, John B

    2012-01-01

    Trust and confidence are critical to the success of health care models. There are two main methods for achieving this: transparency (people can see how the model is built) and validation (how well it reproduces reality). This report describes recommendations for achieving transparency and validation, developed by a task force appointed by the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM). Recommendations were developed iteratively by the authors. A nontechnical description should be made available to anyone-including model type and intended applications; funding sources; structure; inputs, outputs, other components that determine function, and their relationships; data sources; validation methods and results; and limitations. Technical documentation, written in sufficient detail to enable a reader with necessary expertise to evaluate the model and potentially reproduce it, should be made available openly or under agreements that protect intellectual property, at the discretion of the modelers. Validation involves face validity (wherein experts evaluate model structure, data sources, assumptions, and results), verification or internal validity (check accuracy of coding), cross validity (comparison of results with other models analyzing same problem), external validity (comparing model results to real-world results), and predictive validity (comparing model results with prospectively observed events). The last two are the strongest form of validation. Each section of this paper contains a number of recommendations that were iterated among the authors, as well as the wider modeling task force jointly set up by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.

  2. COMPARISON OF THREE MODELS TO PREDICT ANNUAL SEDIMENT YIELD IN CARONI RIVER BASIN, VENEZUELA

    OpenAIRE

    Edilberto Guevara-Pérez; Adriana M. Márquez

    2007-01-01

    Caroní River Basin is located in the south-eastern part of Venezuela; with an area of 92.000 km2, 40% of which belongs to the main affluent, the Paragua River. Caroní basin is the source of 66% of energy of the country. About 85% of the hydro electrical energy is generated in Guri reservoir located in the lower part of the watershed. To take provisions to avoid the reservoir silting it is very important the study of sediment yield of the basin. In this paper result of three empirical sediment...

  3. COMPARISON OF THREE MODELS TO PREDICT ANNUAL SEDIMENT YIELD IN CARONI RIVER BASIN, VENEZUELA

    OpenAIRE

    Edilberto Guevara-Pérez; Adriana M. Márquez

    2007-01-01

    Caroní River Basin is located in the south-eastern part of Venezuela; with an area of 92.000 km², 40% of which belongs to the main affluent, the Paragua River. Caroní basin is the source of 66% of energy of the country. About 85% of the hydro electrical energy is generated in Guri reservoir located in the lower part of the watershed. To take provisions to avoid the reservoir silting it is very important the study of sediment yield of the basin. In this paper result of three empirical sediment...

  4. Is my model good enough? Best practices for verification and validation of musculoskeletal models and simulations of movement.

    Science.gov (United States)

    Hicks, Jennifer L; Uchida, Thomas K; Seth, Ajay; Rajagopal, Apoorva; Delp, Scott L

    2015-02-01

    Computational modeling and simulation of neuromusculoskeletal (NMS) systems enables researchers and clinicians to study the complex dynamics underlying human and animal movement. NMS models use equations derived from physical laws and biology to help solve challenging real-world problems, from designing prosthetics that maximize running speed to developing exoskeletal devices that enable walking after a stroke. NMS modeling and simulation has proliferated in the biomechanics research community over the past 25 years, but the lack of verification and validation standards remains a major barrier to wider adoption and impact. The goal of this paper is to establish practical guidelines for verification and validation of NMS models and simulations that researchers, clinicians, reviewers, and others can adopt to evaluate the accuracy and credibility of modeling studies. In particular, we review a general process for verification and validation applied to NMS models and simulations, including careful formulation of a research question and methods, traditional verification and validation steps, and documentation and sharing of results for use and testing by other researchers. Modeling the NMS system and simulating its motion involves methods to represent neural control, musculoskeletal geometry, muscle-tendon dynamics, contact forces, and multibody dynamics. For each of these components, we review modeling choices and software verification guidelines; discuss variability, errors, uncertainty, and sensitivity relationships; and provide recommendations for verification and validation by comparing experimental data and testing robustness. We present a series of case studies to illustrate key principles. In closing, we discuss challenges the community must overcome to ensure that modeling and simulation are successfully used to solve the broad spectrum of problems that limit human mobility.

  5. A methodology for model-based greenhouse design: Part 3, sensitivity analysis of a combined greenhouse climate-crop yield model

    NARCIS (Netherlands)

    Vanthoor, B.H.E.; Henten, van E.J.; Stanghellini, C.; Visser, de P.H.B.

    2011-01-01

    Greenhouse design is an optimisation problem that might be solved by a model-based greenhouse design method. A sensitivity analysis of a combined greenhouse climate-crop yield model of tomato was done to identify the parameters, i.e. greenhouse design parameters, outdoor climate and climate set-poin

  6. Energy Efficiency Analysis and Modeling the Relationship between Energy Inputs and Wheat Yield in Iran

    Directory of Open Access Journals (Sweden)

    Fakher Kardoni

    2015-12-01

    Full Text Available Wheat is the dominant cereal crop constituting the first staple food in Iran. This paper studies the energy consumption patterns and the relationship between energy inputs and yield for Wheat production in Iranian agriculture during the period 1986 – 2008. The results indicated that total energy inputs in irrigated and dryland wheat production increased from 29.01 and 9.81 GJ ha-1 in 1986 to 44.67 and 12.35 GJ ha-1 in 2008, respectively. Similarly, total output energy rose from 28.87 and 10.43 GJ ha-1 in 1986 to 58.53 and 15.77 GJ ha-1 in 2008, in the same period. Energy efficiency indicators, input– output ratio, energy productivity, and net energy have improved over the examined period. The results also revealed that nonrenewable, direct, and indirect energy forms had a positive impact on the output level. Moreover, the regression results showed the significant effect of irrigation water and seed energies in irrigated wheat and human labor and fertilizer in dryland wheat on crop yield. Results of this study indicated that improvement of fertilizer efficiency and reduction of fuel consumption by modifying tillage, harvest method, and other agronomic operations can significantly affect the energy efficiency of wheat production in Iran.

  7. Yields of AGB and SAGB models with chemistry of low- and high-metallicity Globular Clusters

    CERN Document Server

    Ventura, P; Carini, R; D'Antona, F

    2013-01-01

    We present yields from stars of mass in the range Moyields are based on full evolutionary computations, following the evolution of the stars from the pre-Main Sequence through the Asymptotic Giant Branch phase, until the external envelope is lost. Independently of metallicity, stars with M<3Mo are dominated by Third Dredge-Up, thus ejecting into their surroundings gas enriched in carbon and nitrogen. Conversely, Hot Bottom Burning is the main responsible for the modification of the surface chemistry of more massive stars, whose mass exceeds 3Mo: their gas shows traces of proton-capture nucleosynthesis. The extent of Hot Bottom Burning turns out to be strongly dependent on metallicity. In this paper we analyze the consequences of this fact. These results can be used to understand the role played by intermediate mass stars in the self-enrichment scenario of globular clusters: the resu...

  8. Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

    Science.gov (United States)

    Chen, Huili; Liang, Zhongyao; Liu, Yong; Liang, Qiuhua; Xie, Shuguang

    2017-10-01

    The projected frequent occurrences of extreme flood events will cause significant losses to crops and will threaten food security. To reduce the potential risk and provide support for agricultural flood management, prevention, and mitigation, it is important to account for flood damage to crop production and to understand the relationship between flood characteristics and crop losses. A quantitative and effective evaluation tool is therefore essential to explore what and how flood characteristics will affect the associated crop loss, based on accurately understanding the spatiotemporal dynamics of flood evolution and crop growth. Current evaluation methods are generally integrally or qualitatively based on statistic data or ex-post survey with less diagnosis into the process and dynamics of historical flood events. Therefore, a quantitative and spatial evaluation framework is presented in this study that integrates remote sensing imagery and hydraulic model simulation to facilitate the identification of historical flood characteristics that influence crop losses. Remote sensing imagery can capture the spatial variation of crop yields and yield losses from floods on a grid scale over large areas; however, it is incapable of providing spatial information regarding flood progress. Two-dimensional hydraulic model can simulate the dynamics of surface runoff and accomplish spatial and temporal quantification of flood characteristics on a grid scale over watersheds, i.e., flow velocity and flood duration. The methodological framework developed herein includes the following: (a) Vegetation indices for the critical period of crop growth from mid-high temporal and spatial remote sensing imagery in association with agricultural statistics data were used to develop empirical models to monitor the crop yield and evaluate yield losses from flood; (b) The two-dimensional hydraulic model coupled with the SCS-CN hydrologic model was employed to simulate the flood evolution process

  9. stock yield in Shenzhen, China: The search of best prediction model

    Directory of Open Access Journals (Sweden)

    Clemente Hernández Rodríguez

    2010-05-01

    Full Text Available This paper focuses on the analysis of forecasting models of financial returns. Particularly, the Capm Model, Reward Beta Model and the Three-factors Model of Fama & French are studied. Through this analysis, the aim is to determine what Model explains better the outcomes of the returns of the China’s Shenzhen Stock Exchange. Tests are performed under the portfolio formation procedure, following the methodology of Fama & French (1992, 1995, 1996, and the two-step regression used by Fama & MacBeth (1973, adapted in the devolving of the Beta Reward Model (Bornholt, 2007. After the analysis, it is concluded that the best forecasting Model of returns for the Shenzhen Stock Exchange is Three-factors Model of Fama & French.

  10. Agrometeorological models for groundnut crop yield forecasting in the Jaboticabal, São Paulo State region, Brazil

    Directory of Open Access Journals (Sweden)

    Victor Brunini Moreto

    2015-10-01

    Full Text Available Forecast is the act of estimating a future event based on current data. Ten-day period (TDP meteorological data were used for modeling: mean air temperature, precipitation and water balance components (water deficit (DEF and surplus (EXC and soil water storage (SWS. Meteorological and yield data from 1990-2004 were used for calibration, and 2005-2010 were used for testing. First step was the selection of variables via correlation analysis to determine which TDP and climatic variables have more influence on the crop yield. The selected variables were used to construct models by multiple linear regression, using a stepwise backwards process. Among all analyzed models, the following was notable: Yield = - 4.964 x [SWS of 2° TDP of December of the previous year (OPY] – 1.123 x [SWS of 2° TDP of November OPY] + 0.949 x [EXC of 1° TDP of February of the productive year (PY] + 2.5 x [SWS of 2° TDP of February OPY] + 19.125 x [EXC of 1° TDP of May OPY] – 3.113 x [EXC of 3° TDP of January OPY] + 1.469 x [EXC of 3 TDP of January of PY] + 3920.526, with MAPE = 5.22%, R2 = 0.58 and RMSEs = 111.03 kg ha-1.

  11. Prediction of winter wheat yield with the SWAP model using pedotransfer functions

    NARCIS (Netherlands)

    Jong van Lier, De Quirijn; Wendroth, Ole; Dam, van J.C.

    2015-01-01

    In agronomy and hydrology, models are used to analyze experimental data, whereas experiments are needed to parameterize models. The sensitivity of model outcomes to input parameters is a key issue in this context. As a contribution to the subject, the objective of this study was to evaluate some

  12. Milk Yield of Holstein Cows Induced into Lactation Twice Consecutively and Lactation Curve Models Fitted to Artiifcial Lactations

    Institute of Scientific and Technical Information of China (English)

    Jesus Mellado; Edgar Sepulveda; Jose E Garcia; Alvaro Rodriguez; Maria A De Santiago; Francisco G Veliz; Miguel Mellado

    2014-01-01

    Nineteen multiparous barren Holstein cows were subjected to an induction of lactation protocol for 21 d administering estradiol cypionate (2 mg kg-1 of body weight (BW) d-1, on day 1 to 14), progesterone (0.10 mg kg-1 of BW, on day 1 to 7), lfumethasone (0.03 mg kg-1 of BW, on day 18 to 20) and recombinant bovine somatotropin (rbST;500 mg per cow, on day 1, 6, 16 and 21). At the end of lactation and with a minimum of a 2-mon dry period, the same cows were again hormonally induced into lactation. Cows in both lactations were not artiifcially inseminated, they were milked 3 times daily and received rbST throughout lactation. Mean accumulated milk yield at 305 d in milk (DIM) did not differ between the ifrst and second induced lactations ((9 710 ±1 728) vs. (9 309±2 150) kg;mean±SD). Total milk yield ((12 707±3 406) vs. (12 306±4 218) kg;mean±SD) and lactation length ((405±100) vs. (410±91) d;mean±SD) were not different between the ifrst and second induced lactations. In a second study, 15 empirical models including exponential, power law, yield-density, sigmoidal and miscellaneous models were compared for their suitability by modeling 12-mon (n=334), 18-mon (n=164) and 29-mon (n=22) lactation cycles of Holsteins cows induced into lactation and treated with rbST throughout the lactation. Hoerl (Y=ab1/xxc), Wood (Y=axb exp(cx)) and Dhanoa (Y=ax(bc)exp(cx)) models were equally suitable to describe 12-mon lactations. An exponential model with ifve parameters (Y=exp(a+bx+cd2+e/x)) showed the best ift for milk yield for 18-mon lactations. The rational model (Y=a+bx/1+cx+dx2) was found to produce the closest ift for 29-mon lactations. It was concluded that, with the protocol used in the present study, multiparous cows respond favorably to a second cycle of induced lactation, with milk yield similar to that experienced during the ifrst cycle. Thus, dairy producers might be able to lengthen the productive life of infertile high producing cows with a renewal of

  13. A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

    Science.gov (United States)

    Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

    2015-12-01

    Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

  14. Plateletpheresis efficiency and mathematical correction of software-derived platelet yield prediction: A linear regression and ROC modeling approach.

    Science.gov (United States)

    Jaime-Pérez, José Carlos; Jiménez-Castillo, Raúl Alberto; Vázquez-Hernández, Karina Elizabeth; Salazar-Riojas, Rosario; Méndez-Ramírez, Nereida; Gómez-Almaguer, David

    2017-10-01

    Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP. © 2016 Wiley Periodicals, Inc.

  15. A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns

    KAUST Repository

    Dao, Ngocanh

    2014-04-03

    Assessing the goodness-of-fit (GOF) for intricate parametric spatial point process models is important for many application fields. When the probability density of the statistic of the GOF test is intractable, a commonly used procedure is the Monte Carlo GOF test. Additionally, if the data comprise a single dataset, a popular version of the test plugs a parameter estimate in the hypothesized parametric model to generate data for theMonte Carlo GOF test. In this case, the test is invalid because the resulting empirical level does not reach the nominal level. In this article, we propose a method consisting of nested Monte Carlo simulations which has the following advantages: the bias of the resulting empirical level of the test is eliminated, hence the empirical levels can always reach the nominal level, and information about inhomogeneity of the data can be provided.We theoretically justify our testing procedure using Taylor expansions and demonstrate that it is correctly sized through various simulation studies. In our first data application, we discover, in agreement with Illian et al., that Phlebocarya filifolia plants near Perth, Australia, can follow a homogeneous Poisson clustered process that provides insight into the propagation mechanism of these plants. In our second data application, we find, in contrast to Diggle, that a pairwise interaction model provides a good fit to the micro-anatomy data of amacrine cells designed for analyzing the developmental growth of immature retina cells in rabbits. This article has supplementary material online. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

  16. Growth and yield models in Spain: Historical overview, Contemporary Examples and perspectives

    Energy Technology Data Exchange (ETDEWEB)

    Bravo, F.; Alvarez-Gonzalez, J. G.; Rio, M. del; Barrio, M.; Bonet, J. a.; Bravo-Oviedo, A.; Calama, R.; Castedo-Dorado, F.; Crecente-Campo, F.; Condes, S.; Dieguez-Aranda, U.; Gonzalez-Martinez, S. C.; Lizarralde, I.; Nanos, N.; Madrigal, A.; Martinez-Millan, F. J.; Montero, G.; Ordonez, C.; Palahi, M.; Pique, M.; Rodriguez, F.; Rodriguez-Soalleiro, R.; Rojo, A.; Ruiz-Peinado, R.; Sanchez-Gonzalez, M.; Trasobares, A.; Vazquez-Pique, J.

    2011-07-01

    In this paper we present a review of forest models developed in Spain in recent years for both timber and non timber production and forest dynamics (regeneration, mortality,..). Models developed are whole stand, size (diameter) class and individual-tree. The models developed to date have been developed using data from permanent plots, experimental sites and the National Forest Inventory. In this paper we show the different sub-models developed so far and the friendly use software. Main perspectives of forest modelling in Spain are presented. (Author) 107 refs.

  17. Modeling and characterization of X-ray yield in a polychromatic, lab-scale, X-ray computed tomography system

    Energy Technology Data Exchange (ETDEWEB)

    Mertens, J.C.E.; Chawla, Nikhilesh, E-mail: nchawla@asu.edu

    2015-05-21

    A modular X-ray computed micro-tomography (µXCT) system is characterized in terms of X-ray yield resulting both from the generated X-ray spectrum and from X-ray detection with an energy-sensitive detector. The X-ray computed tomography system is composed of a commercially available cone-beam microfocus X-ray source and a modular optically-coupled-CCD-scintillator X-ray detector. The X-ray yield is measured and reported in units independent from exposure time, X-ray tube beam target current, and cone-beam-to-detector geometry. The polychromatic X-ray source is modeled as a broad Bremsstrahlung X-ray spectrum in order to understand the effect of the controllable parameters, that is, X-ray tube accelerating voltage and X-ray beam filtering. An approach is adopted which expresses the absolute number of emitted X-rays. The response of the energy-sensitive detector to the modeled spectrum is modeled as a function of scintillator composition and thickness. The detection efficiency model for the polychromatic X-ray detector considers the response of the light collection system and the electronic imaging array in order to predict absolute count yield under the studied conditions. The modeling approach is applied to the specific hardware implemented in the current µXCT system. The model's predictions for absolute detection rate are in reasonable agreement with measured values under a range of conditions applied to the system for X-ray microtomography imaging, particularly for the LuAG:Ce scintillator material.

  18. Dynamic transmission modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group-5.

    NARCIS (Netherlands)

    Pitman, Richard; Fisman, David; Zaric, Gregory S; Postma, Maarten; Kretzschmar, Mirjam; Edmunds, John; Brisson, Marc; ISPOR-SMDM Modeling Good Research Practices Task Force, [No Value

    2012-01-01

    The transmissible nature of communicable diseases is what sets them apart from other diseases modeled by health economists. The probability of a susceptible individual becoming infected at any one point in time (the force of infection) is related to the number of infectious individuals in the popula

  19. Dynamic transmission modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group-5.

    NARCIS (Netherlands)

    Pitman, Richard; Fisman, David; Zaric, Gregory S; Postma, Maarten; Kretzschmar, Mirjam; Edmunds, John; Brisson, Marc; ISPOR-SMDM Modeling Good Research Practices Task Force, [No Value

    2012-01-01

    The transmissible nature of communicable diseases is what sets them apart from other diseases modeled by health economists. The probability of a susceptible individual becoming infected at any one point in time (the force of infection) is related to the number of infectious individuals in the popula

  20. Dynamic transmission modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group-5.

    NARCIS (Netherlands)

    Pitman, Richard; Fisman, David; Zaric, Gregory S; Postma, Maarten; Kretzschmar, Mirjam; Edmunds, John; Brisson, Marc; ISPOR-SMDM Modeling Good Research Practices Task Force, [No Value

    2012-01-01

    The transmissible nature of communicable diseases is what sets them apart from other diseases modeled by health economists. The probability of a susceptible individual becoming infected at any one point in time (the force of infection) is related to the number of infectious individuals in the

  1. Forecasting the Yield Curve in a Data-Rich Environment Using the Factor-Augmented Nelson-Siegel Model

    DEFF Research Database (Denmark)

    Exterkate, Peter; Dijk, Dick van; Heij, Christiaan;

    2013-01-01

    This paper compares various ways of extracting macroeconomic information from a data-rich environment for forecasting the yield curve using the Nelson–Siegel model. Five issues in extracting factors from a large panel of macro variables are addressed; namely, selection of a subset of the available...... forecast accuracy, especially for the shortest and longest maturities. Factor-augmented methods perform well in relatively volatile periods, including the crisis period in 2008–9, when simpler models do not suffice. The macroeconomic information is exploited best by partial least squares methods...

  2. Mathematical Modeling-Guided Evaluation of Biochemical, Developmental, Environmental, and Genotypic Determinants of Essential Oil Composition and Yield in Peppermint Leaves1[W][OA

    Science.gov (United States)

    Rios-Estepa, Rigoberto; Lange, Iris; Lee, James M.; Lange, B. Markus

    2010-01-01

    We have previously reported the use of a combination of computational simulations and targeted experiments to build a first generation mathematical model of peppermint (Mentha × piperita) essential oil biosynthesis. Here, we report on the expansion of this approach to identify the key factors controlling monoterpenoid essential oil biosynthesis under adverse environmental conditions. We also investigated determinants of essential oil biosynthesis in transgenic peppermint lines with modulated essential oil profiles. A computational perturbation analysis, which was implemented to identify the variables that exert prominent control over the outputs of the model, indicated that the essential oil composition should be highly dependent on certain biosynthetic enzyme concentrations [(+)-pulegone reductase and (+)-menthofuran synthase], whereas oil yield should be particularly sensitive to the density and/or distribution of leaf glandular trichomes, the specialized anatomical structures responsible for the synthesis and storage of essential oils. A microscopic evaluation of leaf surfaces demonstrated that the final mature size of glandular trichomes was the same across all experiments. However, as predicted by the perturbation analysis, differences in the size distribution and the total number of glandular trichomes strongly correlated with differences in monoterpenoid essential oil yield. Building on various experimental data sets, appropriate mathematical functions were selected to approximate the dynamics of glandular trichome distribution/density and enzyme concentrations in our kinetic model. Based on a χ2 statistical analysis, simulated and measured essential oil profiles were in very good agreement, indicating that modeling is a valuable tool for guiding metabolic engineering efforts aimed at improving essential oil quality and quantity. PMID:20147490

  3. Observed light yield of scintillation pixels: Extending the two-ray model

    Science.gov (United States)

    Kantorski, Igor; Jurkowski, Jacek; Drozdowski, Winicjusz

    2016-09-01

    In this paper we propose an extended, two dimensional model describing the propagation of scintillation photons inside a cuboid crystal until they reach a PMT window. In the simplest approach the model considers two main reasons for light losses: standard absorption obeying the classical Lambert-Beer law and non-ideal reflectivity of the "mummy" covering formed by several layers of Teflon tape wrapping the sample. Results of the model calculations are juxtaposed with experimental data as well as with predictions of an earlier, one dimensional model.

  4. Prediction of grain yield using optical remote sensing and a growth model: application on Merguellil catchment (Tunisia)

    Science.gov (United States)

    Chahbi, A.; Zribi, M.; Lili-Chabaane, Z.; Duchemin, B.; Shabou, M.; Mougenot, B.; Boulet, G.

    2012-04-01

    In semi-arid region and especially in irrigated areas, agriculture represents a major contribution to food security. These areas significantly contribute to the increase of global production. A challenging objective is thus to ensure food security. Therefore an operational forecasting system for the grain yields is required and could help decision-makers to make early decisions and plan annual imports. In this context, remote sensing is a very interesting tool for giving information on the development of vegetation. The main objective is to analyze and predict the average grain yield, based on different indices measured or modelled during the growing season. Thus, we used three lines of research: the first is based on analysing a relationship between normalized vegetation index (NDVI) which is determined from optical satellite imagery and the leaf area index (LAI) measured in situ. The second axis is based on the estimation of the relation between wheat yields and normalized vegetation index NDVI. The third axis is based on the application of a growth model SAFY « Simple Algorithm For Yield Estimate » developed to simulate LAI, dry aboveground phytomass (DAM) and the grain yield (GY). For the first axis, we used optical data at high resolution. A series of 7 SPOT / HRV during the 2010-2011 agricultural seasons was acquired in the Merguellil catchment (Tunisia). At the same time we realised experimental measurements made on 27 test plots of dry or irrigated cereals carried out in study area. These measurements are mainly: the water content of the vegetation, the vegetation height, wheat density and leaf area index LAI (estimated using a hemispherical camera). From satellite data, a profile of the normalized difference vegetation index (NDVI) was generated for each pixel. For both types of cereal, a relationship is established between NDVI and leaf area index LAI. This relationship is exponential and it allows connecting the satellite observations with a variable

  5. Impacts of extreme heat and drought on crop yields in China: an assessment by using the DLEM-AG2 model

    Science.gov (United States)

    Zhang, J.; Yang, J.; Pan, S.; Tian, H.

    2016-12-01

    China is not only one of the major agricultural production countries with the largest population in the world, but it is also the most susceptible to climate change and extreme events. Much concern has been raised about how extreme climate has affected crop yield, which is crucial for China's food supply security. However, the quantitative assessment of extreme heat and drought impacts on crop yield in China has rarely been investigated. By using the Dynamic Land Ecosystem Model (DLEM-AG2), a highly integrated process-based ecosystem model with crop-specific simulation, here we quantified spatial and temporal patterns of extreme climatic heat and drought stress and their impacts on the yields of major food crops (rice, wheat, maize, and soybean) across China during 1981-2015, and further investigated the underlying mechanisms. Simulated results showed that extreme heat and drought stress significantly reduced national cereal production and increased the yield gaps between potential yield and rain-fed yield. The drought stress was the primary factor to reduce crop yields in the semi-arid and arid regions, and extreme heat stress slightly aggravated the yield loss. The yield gap between potential yield and rain-fed yield was larger at locations with lower precipitation. Our results suggest that a large exploitable yield gap in response to extreme climatic heat-drought stress offers an opportunity to increase productivity in China by optimizing agronomic practices, such as irrigation, fertilizer use, sowing density, and sowing date.

  6. High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling

    Science.gov (United States)

    Rollin, Joseph A.; Martin del Campo, Julia; Myung, Suwan; Sun, Fangfang; You, Chun; Bakovic, Allison; Castro, Roberto; Chandrayan, Sanjeev K.; Wu, Chang-Hao; Adams, Michael W. W.; Senger, Ryan S.; Zhang, Y.-H. Percival

    2015-01-01

    The use of hydrogen (H2) as a fuel offers enhanced energy conversion efficiency and tremendous potential to decrease greenhouse gas emissions, but producing it in a distributed, carbon-neutral, low-cost manner requires new technologies. Herein we demonstrate the complete conversion of glucose and xylose from plant biomass to H2 and CO2 based on an in vitro synthetic enzymatic pathway. Glucose and xylose were simultaneously converted to H2 with a yield of two H2 per carbon, the maximum possible yield. Parameters of a nonlinear kinetic model were fitted with experimental data using a genetic algorithm, and a global sensitivity analysis was used to identify the enzymes that have the greatest impact on reaction rate and yield. After optimizing enzyme loadings using this model, volumetric H2 productivity was increased 3-fold to 32 mmol H2⋅L−1⋅h−1. The productivity was further enhanced to 54 mmol H2⋅L−1⋅h−1 by increasing reaction temperature, substrate, and enzyme concentrations—an increase of 67-fold compared with the initial studies using this method. The production of hydrogen from locally produced biomass is a promising means to achieve global green energy production. PMID:25848015

  7. High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling.

    Science.gov (United States)

    Rollin, Joseph A; Martin del Campo, Julia; Myung, Suwan; Sun, Fangfang; You, Chun; Bakovic, Allison; Castro, Roberto; Chandrayan, Sanjeev K; Wu, Chang-Hao; Adams, Michael W W; Senger, Ryan S; Zhang, Y-H Percival

    2015-04-21

    The use of hydrogen (H2) as a fuel offers enhanced energy conversion efficiency and tremendous potential to decrease greenhouse gas emissions, but producing it in a distributed, carbon-neutral, low-cost manner requires new technologies. Herein we demonstrate the complete conversion of glucose and xylose from plant biomass to H2 and CO2 based on an in vitro synthetic enzymatic pathway. Glucose and xylose were simultaneously converted to H2 with a yield of two H2 per carbon, the maximum possible yield. Parameters of a nonlinear kinetic model were fitted with experimental data using a genetic algorithm, and a global sensitivity analysis was used to identify the enzymes that have the greatest impact on reaction rate and yield. After optimizing enzyme loadings using this model, volumetric H2 productivity was increased 3-fold to 32 mmol H2⋅L(-1)⋅h(-1). The productivity was further enhanced to 54 mmol H2⋅L(-1)⋅h(-1) by increasing reaction temperature, substrate, and enzyme concentrations--an increase of 67-fold compared with the initial studies using this method. The production of hydrogen from locally produced biomass is a promising means to achieve global green energy production.

  8. Estimating Sediment Yield on Disturbed Rangeland Using the Rangeland Hydrology and Erosion Model (RHEM)

    Science.gov (United States)

    The Rangeland Hydrology and Erosion Model (RHEM) is an event-based model that estimates runoff, erosion, and sediment delivery rates and volumes at the spatial scale of the hillslope and the temporal scale of a single rainfall event. It represents erosion processes on normal rangeland, as well as, r...

  9. Uncertainty modelling and analysis of environmental systems: a river sediment yield example

    NARCIS (Netherlands)

    Keesman, K.J.; Koskela, J.; Guillaume, J.H.; Norton, J.P.; Croke, B.; Jakeman, A.

    2011-01-01

    Abstract: Throughout the last decades uncertainty analysis has become an essential part of environmental model building (e.g. Beck 1987; Refsgaard et al., 2007). The objective of the paper is to introduce stochastic and setmembership uncertainty modelling concepts, which basically differ in the assu

  10. A model for prediction of yield and quality of cucumber fruits

    NARCIS (Netherlands)

    Marcelis, L.F.M.; Gijzen, H.

    1998-01-01

    The mechanistic model KOSI was developed to predict the weekly fresh weight harvest of cucumber fruits and their quality. The model consists of modules for greenhouse climate, greenhouse light transmission, light interception by the crop, leaf and canopy photosynthesis, assimilate partitioning, dry

  11. Agroclimatic modeling for the simulation of phenology, yield and quality of crop production

    Science.gov (United States)

    Mechlia, Netij Ben; Carroll, John J.

    1989-03-01

    This paper describes the development of basic simulation concepts that can be used in models aimed at forecasting. The objective is to demonstrate the utility of considering the crop's basic environmental requirements or “climatic normals” in producing a self-contained comprehensive model. We seek to develop a model in which regularly measured weather data can be used to provide information on the crop performance. Following an abbreviated overview of modeling alternatives, the model design is described. The results of this study are a set of criteria and functions needed to predict the temporal evolution of phenological stages, fruit growth, fruit maturation, and fruit coloration for two varieties of oranges (Navel and Valencia). The major factors considered are the effect of temperature and solar radiation on flowering time, and flowering duration and the number of flowers; the effect of past stress, temperature, evaporation, wind, and rain, planting density, and tree age on fruit set. Given the number of fruits set, growth, maturation and coloration are modeled as responding primarily to temperature and water balance. Possible damage due to freezes is also modeled. These form the basis of a time dependent model (reported elsewhere) which uses daily air temperature and wind data for the prediction of these quantities. These criteria and functions are derived from an extensive body of published observations from many parts of the world, and are selected to be variety specific and independent of local climatology or other site-specific effects.

  12. Object-Oriented Agricultural System Modeling: Component-Driven Nutrient Dynamics and Crop Yield Simulations

    Science.gov (United States)

    Challenges in agro-ecosystem conservation management have created demand for state-of-the-art, integrated, and flexible modeling tools. For example, agricultural system modeling tools are needed which are robust and fast enough to be applied on large watershed scales, but which are also able to sim...

  13. Simulated crop yield in response to changes in climate and agricultural practices: results from a simple process based model

    Science.gov (United States)

    Caldararu, S.; Smith, M. J.; Purves, D.; Emmott, S.

    2013-12-01

    Global agriculture will, in the future, be faced with two main challenges: climate change and an increase in global food demand driven by an increase in population and changes in consumption habits. To be able to predict both the impacts of changes in climate on crop yields and the changes in agricultural practices necessary to respond to such impacts we currently need to improve our understanding of crop responses to climate and the predictive capability of our models. Ideally, what we would have at our disposal is a modelling tool which, given certain climatic conditions and agricultural practices, can predict the growth pattern and final yield of any of the major crops across the globe. We present a simple, process-based crop growth model based on the assumption that plants allocate above- and below-ground biomass to maintain overall carbon optimality and that, to maintain this optimality, the reproductive stage begins at peak nitrogen uptake. The model includes responses to available light, water, temperature and carbon dioxide concentration as well as nitrogen fertilisation and irrigation. The model is data constrained at two sites, the Yaqui Valley, Mexico for wheat and the Southern Great Plains flux site for maize and soybean, using a robust combination of space-based vegetation data (including data from the MODIS and Landsat TM and ETM+ instruments), as well as ground-based biomass and yield measurements. We show a number of climate response scenarios, including increases in temperature and carbon dioxide concentrations as well as responses to irrigation and fertiliser application.

  14. Intraperitoneal Administration of Low Dose Aluminium in The Rat: How Good is It to Produce a Model for Alzheimer Disease.

    Science.gov (United States)

    Ulusoy, H B; Sonmez, M F; Kilic, E; Caliskan, K; Karaca, B; Kara, M; Ercal, O; Gunduz, Y; Karabulut, D; Bitiktas, S; Tan, B; Kavraal, S; İnal, A; Suer, C

    2015-12-01

    Since neurotoxicity of aluminium (Al) resembles the progressive neurodegeneration observed in Alzheimer Disease (AD), Al administration in several ways has been used to produce AD model. Intraperitoneal (ip) low dose (4.2 mg/ kg) Al injection in rats for long periods is the preferred method by some researchers. In this paper, the efficiency of this method for producing an AD model was evaluated. In this study, we looked at the neuropathology of Al and the characteristic lesions of AD by histological and immunohistochemical techniques and determined oxidative stress markers in the brains of Al-treated and control rats. We also made electrophysiological recordings at the hippocampus and evaluated possible behavioural changes by Morris water maze test. However, no pathologic changes occurred in the animals except for an impairment in long-term potentiation (LTP) in the hippocampus (e.g. the LTPs of population spike (PS) amplitude at 15 min post-tetanus were measured as 217±27% in Al-treated rats and as 240±42% in sham-treated rats, of baseline PS amplitude). According to the findings of the present study, low dose of ip Al in rats is not sufficient to produce a good AD model. Higher doses (≥10 mg/kg) should be used.

  15. Artificial neural network based modeling to evaluate methane yield from biogas in a laboratory-scale anaerobic bioreactor.

    Science.gov (United States)

    Nair, Vijay V; Dhar, Hiya; Kumar, Sunil; Thalla, Arun Kumar; Mukherjee, Somnath; Wong, Jonathan W C

    2016-10-01

    The performance of a laboratory-scale anaerobic bioreactor was investigated in the present study to determine methane (CH4) content in biogas yield from digestion of organic fraction of municipal solid waste (OFMSW). OFMSW consists of food waste, vegetable waste and yard trimming. An organic loading between 40 and 120kgVS/m(3) was applied in different runs of the bioreactor. The study was aimed to focus on the effects of various factors, such as pH, moisture content (MC), total volatile solids (TVS), volatile fatty acids (VFAs), and CH4 fraction on biogas production. OFMSW witnessed high CH4 yield as 346.65LCH4/kgVS added. A target of 60-70% of CH4 fraction in biogas was set as an optimized condition. The experimental results were statistically optimized by application of ANN model using free forward back propagation in MATLAB environment.

  16. A state space transformation can yield identifiable models for tracer kinetic studies with enrichment data.

    Science.gov (United States)

    Ramakrishnan, Rajasekhar; Ramakrishnan, Janak D

    2010-11-01

    Tracer studies are analyzed almost universally by multicompartmental models where the state variables are tracer amounts or activities in the different pools. The model parameters are rate constants, defined naturally by expressing fluxes as fractions of the source pools. We consider an alternative state space with tracer enrichments or specific activities as the state variables, with the rate constants redefined by expressing fluxes as fractions of the destination pools. Although the redefinition may seem unphysiological, the commonly computed fractional synthetic rate actually expresses synthetic flux as a fraction of the product mass (destination pool). We show that, for a variety of structures, provided the structure is linear and stationary, the model in the enrichment state space has fewer parameters than that in the activities state space, and is hence better both to study identifiability and to estimate parameters. The superiority of enrichment modeling is shown for structures where activity model unidentifiability is caused by multiple exit pathways; on the other hand, with a single exit pathway but with multiple untraced entry pathways, activity modeling is shown to be superior. With the present-day emphasis on mass isotopes, the tracer in human studies is often of a precursor, labeling most or all entry pathways. It is shown that for these tracer studies, models in the activities state space are always unidentifiable when there are multiple exit pathways, even if the enrichment in every pool is observed; on the other hand, the corresponding models in the enrichment state space have fewer parameters and are more often identifiable. Our results suggest that studies with labeled precursors are modeled best with enrichments.

  17. USA National Phenology Network’s volunteer-contributed observations yield predictive models of phenological transitions

    Science.gov (United States)

    Crimmins, Theresa M.; Crimmins, Michael A.; Gerst, Katherine L.; Rosemartin, Alyssa H.; Weltzin, Jake

    2017-01-01

    In support of science and society, the USA National Phenology Network (USA-NPN) maintains a rapidly growing, continental-scale, species-rich dataset of plant and animal phenology observations that with over 10 million records is the largest such database in the United States. Contributed voluntarily by professional and citizen scientists, these opportunistically collected observations are characterized by spatial clustering, inconsistent spatial and temporal sampling, and short temporal depth. We explore the potential for developing models of phenophase transitions suitable for use at the continental scale, which could be applied to a wide range of resource management contexts. We constructed predictive models of the onset of breaking leaf buds, leaves, open flowers, and ripe fruits – phenophases that are the most abundant in the database and also relevant to management applications – for all species with available data, regardless of plant growth habit, location, geographic extent, or temporal depth of the observations. We implemented a very basic model formulation - thermal time models with a fixed start date. Sufficient data were available to construct 107 individual species × phenophase models. Of these, fifteen models (14%) met our criteria for model fit and error and were suitable for use across the majority of the species’ geographic ranges. These findings indicate that the USA-NPN dataset holds promise for further and more refined modeling efforts. Further, the candidate models that emerged could be used to produce real-time and short-term forecast maps of the timing of such transitions to directly support natural resource management.

  18. Good Manufacturing Practices (GMP) manufacturing of advanced therapy medicinal products: a novel tailored model for optimizing performance and estimating costs.

    Science.gov (United States)

    Abou-El-Enein, Mohamed; Römhild, Andy; Kaiser, Daniel; Beier, Carola; Bauer, Gerhard; Volk, Hans-Dieter; Reinke, Petra

    2013-03-01

    Advanced therapy medicinal products (ATMP) have gained considerable attention in academia due to their therapeutic potential. Good Manufacturing Practice (GMP) principles ensure the quality and sterility of manufacturing these products. We developed a model for estimating the manufacturing costs of cell therapy products and optimizing the performance of academic GMP-facilities. The "Clean-Room Technology Assessment Technique" (CTAT) was tested prospectively in the GMP facility of BCRT, Berlin, Germany, then retrospectively in the GMP facility of the University of California-Davis, California, USA. CTAT is a two-level model: level one identifies operational (core) processes and measures their fixed costs; level two identifies production (supporting) processes and measures their variable costs. The model comprises several tools to measure and optimize performance of these processes. Manufacturing costs were itemized using adjusted micro-costing system. CTAT identified GMP activities with strong correlation to the manufacturing process of cell-based products. Building best practice standards allowed for performance improvement and elimination of human errors. The model also demonstrated the unidirectional dependencies that may exist among the core GMP activities. When compared to traditional business models, the CTAT assessment resulted in a more accurate allocation of annual expenses. The estimated expenses were used to set a fee structure for both GMP facilities. A mathematical equation was also developed to provide the final product cost. CTAT can be a useful tool in estimating accurate costs for the ATMPs manufactured in an optimized GMP process. These estimates are useful when analyzing the cost-effectiveness of these novel interventions. Copyright © 2013 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

  19. Genetic parameters of different measures of cheese yield and milk nutrient recovery from an individual model cheese-manufacturing process.

    Science.gov (United States)

    Bittante, G; Cipolat-Gotet, C; Cecchinato, A

    2013-01-01

    Cheese yield (CY) is an important technological trait in the dairy industry, and the objective of this study was to estimate the genetic parameters of cheese yield in a dairy cattle population using an individual model-cheese production procedure. A total of 1,167 Brown Swiss cows belonging to 85 herds were sampled once (a maximum of 15 cows were sampled per herd on a single test day, 1 or 2 herds per week). From each cow, 1,500 mL of milk was processed according to the following steps: milk sampling and heating, culture addition, rennet addition, gelation-time recording, curd cutting, whey draining and sampling, wheel formation, pressing, salting in brine, weighing, and cheese sampling. The compositions of individual milk, whey, and curd samples were determined. Three measures of percentage cheese yield (%CY) were calculated: %CY(CURD), %CY(SOLIDS), and %CY(WATER), which represented the ratios between the weight of fresh curd, the total solids of the curd, and the water content of the curd, respectively, and the weight of the milk processed. In addition, 3 measures of daily cheese yield (dCY, kg/d) were defined, considering the daily milk yield. Three measures of nutrient recovery (REC) were computed: REC(FAT), REC(PROTEIN), and REC(SOLIDS), which represented the ratio between the weights of the fat, protein, and total solids in the curd, respectively, and the corresponding nutrient in the milk. Energy recovery, REC(ENERGY), represented the energy content of the cheese versus that in the milk. For statistical analysis, a Bayesian animal model was implemented via Gibbs sampling. The effects of parity (1 to ≥4), days in milk (6 classes), and laboratory vat (15 vats) were assigned flat priors; those of herd-test-date, animal, and residual were given Gaussian prior distributions. Intra-herd heritability estimates of %CY(CURD), %CY(SOLIDS), and %CY(WATER) ranged from 0.224 to 0.267; these were larger than the estimates obtained for milk yield (0.182) and milk fat

  20. Combined Spectral and Spatial Modeling of Corn Yield Based on Aerial Images and Crop Surface Models Acquired with an Unmanned Aircraft System

    Directory of Open Access Journals (Sweden)

    Jakob Geipel

    2014-10-01

    Full Text Available Precision Farming (PF management strategies are commonly based on estimations of within-field yield potential, often derived from remotely-sensed products, e.g., Vegetation Index (VI maps. These well-established means, however, lack important information, like crop height. Combinations of VI-maps and detailed 3D Crop Surface Models (CSMs enable advanced methods for crop yield prediction. This work utilizes an Unmanned Aircraft System (UAS to capture standard RGB imagery datasets for corn grain yield prediction at three early- to mid-season growth stages. The imagery is processed into simple VI-orthoimages for crop/non-crop classification and 3D CSMs for crop height determination at different spatial resolutions. Three linear regression models are tested on their prediction ability using site-specific (i unclassified mean heights, (ii crop-classified mean heights and (iii a combination of crop-classified mean heights with according crop coverages. The models show determination coefficients \\({R}^{2}\\ of up to 0.74, whereas model (iii performs best with imagery captured at the end of stem elongation and intermediate spatial resolution (0.04m\\(\\cdot\\px\\(^{-1}\\.Following these results, combined spectral and spatial modeling, based on aerial images and CSMs, proves to be a suitable method for mid-season corn yield prediction.

  1. Development of a CSP plant energy yield calculation tool applying predictive models to analyze plant performance sensitivities

    Science.gov (United States)

    Haack, Lukas; Peniche, Ricardo; Sommer, Lutz; Kather, Alfons

    2017-06-01

    At early project stages, the main CSP plant design parameters such as turbine capacity, solar field size, and thermal storage capacity are varied during the techno-economic optimization to determine most suitable plant configurations. In general, a typical meteorological year with at least hourly time resolution is used to analyze each plant configuration. Different software tools are available to simulate the annual energy yield. Software tools offering a thermodynamic modeling approach of the power block and the CSP thermal cycle, such as EBSILONProfessional®, allow a flexible definition of plant topologies. In EBSILON, the thermodynamic equilibrium for each time step is calculated iteratively (quasi steady state), which requires approximately 45 minutes to process one year with hourly time resolution. For better presentation of gradients, 10 min time resolution is recommended, which increases processing time by a factor of 5. Therefore, analyzing a large number of plant sensitivities, as required during the techno-economic optimization procedure, the detailed thermodynamic simulation approach becomes impracticable. Suntrace has developed an in-house CSP-Simulation tool (CSPsim), based on EBSILON and applying predictive models, to approximate the CSP plant performance for central receiver and parabolic trough technology. CSPsim significantly increases the speed of energy yield calculations by factor ≥ 35 and has automated the simulation run of all predefined design configurations in sequential order during the optimization procedure. To develop the predictive models, multiple linear regression techniques and Design of Experiment methods are applied. The annual energy yield and derived LCOE calculated by the predictive model deviates less than ±1.5 % from the thermodynamic simulation in EBSILON and effectively identifies the optimal range of main design parameters for further, more specific analysis.

  2. Atmospheric CO2 concentration impacts on maize yield performance under dry conditions: do crop model simulate it right ?

    Science.gov (United States)

    Durand, Jean-Louis; Delusca, Kénel; Boote, Ken; Lizaso, Jon; Manderscheid, Remy; Jochaim Weigel, Hans; Ruane, Alex C.; Rosenzweig, Cynthia; Jones, Jim; Ahuja, Laj; Anapalli, Saseendran; Basso, Bruno; Baron, Christian; Bertuzzi, Patrick; Biernath, Christian; Deryng, Delphine; Ewert, Frank; Gaiser, Thomas; Gayler, Sebastian; Heinlein, Florian; Kersebaum, Kurt Christian; Kim, Soo-Hyung; Müller, Christoph; Nendel, Claas; Olioso, Albert; Priesack, Eckhart; Ramirez-Villegas, Julian; Ripoche, Dominique; Rötter, Reimund; Seidel, Sabine; Srivastava, Amit; Tao, Fulu; Timlin, Dennis; Twine, Tracy; Wang, Enli; Webber, Heidi; Zhao, Shigan

    2017-04-01

    In most regions of the world, maize yields are at risk of be reduced due to rising temperatures and reduced water availability. Rising temperature tends to reduce the length of the growth cycle and the amount of intercepted solar energy. Water deficits reduce the leaf area expansion, photosynthesis and sometimes, with an even more pronounced impact, severely reduce the efficiency of kernel set. In maize, the major consequence of atmospheric CO2 concentration ([CO2]) is the stomatal closure-induced reduction of leaf transpiration rate, which tends to mitigate those negative impacts. Indeed FACE studies report significant positive responses to CO2 of maize yields (and other C4 crops) under dry conditions only. Given the projections by climatologists (typically doubling of [CO2] by the end of this century) projected impacts must take that climate variable into account. However, several studies show a large incertitude in estimating the impact of increasing [CO2] on maize remains using the main crop models. The aim of this work was to compare the simulations of different models using input data from a FACE experiment conducted in Braunschweig during 2 years under limiting and non-limiting water conditions. Twenty modelling groups using different maize models were given the same instructions and input data. Following calibration of cultivar parameters under non-limiting water conditions and under ambient [CO2] treatments of both years, simulations were undertaken for the other treatments: High [ CO2 ] (550 ppm) 2007 and 2008 in both irrigation regimes, and DRY AMBIENT 2007 and 2008. Only under severe water deficits did models simulate an increase in yield for CO2 enrichment, which was associated with higher harvest index and, for those models which simulated it, higher grain number. However, the CO2 enhancement under water deficit simulated by the 20 models was 20 % at most and 10 % on average only, i.e. twice less than observed in that experiment. As in the experiment

  3. Growth and yield models, assortment type and analysis of deadwood in chestnut coppice

    Directory of Open Access Journals (Sweden)

    Marziliano PA

    2013-02-01

    Full Text Available Chestnut (Castanea sativa MILL. is one of the most important forest tree species in Europe, and it is considered a symbol of the natural vegetation in southern Europe. In Calabria (southern Italy chestnut forest covers an area of approximately 87000 hectares, most of which (about 80% managed as coppice. In this study a growth and yield table has been elaborated. Thurthermore, assortment type and quantity of deadwood have been evaluated according to age of coppice and forest fire prevention, respectively. The study site is located in the “Presila of Catanzaro” and the research was carried out in 15 plots; the age of the examined stands ranged from 2 to 50 years old. More than 30000 shoots per hectare were recorded in the first two years after coppicing. As opposed, about 2300 and 1000 shoots per hectare were observed 15 and 50 years after coppicing, respectively. The culmination of the mean annual increment of the forest standing volume (16 m3 ha-1 year-1 was highlighted 25 years after coppicing, while the current annual increment culmination (21 m3 ha-1 year-1 was observed at 15 years. Fifteen years after coppicing, most of the wood production was constituted by small dimension assortments. Twenty five years after coppicing small and large poles were the prevailing assortments while telegraph poles and timber beams increased after 50 years. The amount of deadwood in forest ranged between 11.9 and 68.7 m3 ha-1. The largest component was represented by standing dead shoots. The results show that coppice management can be adopted even if the main purpose of the chestnut stand is the production of large size assortments. In chestnut coppice, highly vulnerable to fire, the reduction of stand density with silvicultural practices (thinning and displacement is the main way to promote the efficiency of forest and a higher strength and resiliency against forest fire.

  4. Validation of AquaCrop Model for Simulation of Winter Wheat Yield and Water Use Efficiency under Simultaneous Salinity and Water Stress

    Directory of Open Access Journals (Sweden)

    M. Mohammadi

    2016-02-01

    simulation of soil salinity. In general, the model accuracy for simulation yield and WP was better than simulation of biomass. The d (index of agreement values were very close to one for both varieties, which means that simulated reduction in grain yield and biomass was similar to those of measured ones. In most cases the R2 values were about one, confirming a good correlation between simulated and measured values. The NRMSE values in most cases were lower than 10% which seems to be good. The CRM values were close to zero (under- and over-estimation were negligible. Based on higher WP under deficit irrigation treatments (e.g. I3 compared to full irrigation treatments (e.g. I1 and I2, it seems logical to adopt I3 treatment, especially in Birjand as a water-short region, assigning the remaining 25% to another piece of land. By such strategy, WP would be optimized at the regional scale. Conclusion: The AquaCrop was separately and simultaneously nested calibrated and validated for all salinity treatments. The model accuracy under simultaneous case was slightly lower than that for separate case. According to the results, if the model is well calibrated for minimum and maximum irrigation treatments (full irrigation and maximum deficit irrigation, it could simulate grain yield for any other irrigation treatment in between these two limits. Adopting this approach may reduce the cost of field studies for calibrating the model, since only two irrigation treatments should be conducted in the field. AquaCrop model can be a valuable tool for modelling winter wheat grain yield, WP and biomass. The simplicity of AquaCrop, as it is less data dependent, made it to be user-friendly. Nevertheless, the performance of the model has to be evaluated, validated and fine-tuned under a wider range of conditions and crops. Keywords: Biomass, Plant modeling, Sensitivity analysis

  5. Asymptotics of the goodness-of-fit test for a partial linear model with randomly censored data

    Institute of Scientific and Technical Information of China (English)

    CHEN; Min(

    2003-01-01

    (semiparametric) partial and generalized spline models, Ann. Statist., 1988, 16: 113.[16]Eubank, R. L., Spiegeman, C. H., Testing the goodness of fit of a linear model via nonparametric regression techniques, J. Amer. Statist. Assoc., 1990, 85: 387.[17]Hardle, W., Mammen, E., Comparing non-parametric versus parametric regression fits, Ann. Statist., 1993,21: 1926.[18]Hardle, W., Mammen, E., Müller, M., Testing parametric versus semiparametric modeling in generalized linear models, J. Amer. Statist. Assoc., 1998, 93: 1461.[19]Hardle, W., Marron, J. S., Semiparametric comparison of regression curves, Ann. Statist., 1990, 18: 63.[20]King, G., Testing the equality of two regression curves using linear smoothers, Statist. & Probab. Lett., 1991,12: 239.[21]Miiller, H. G., Goodness-of-fit diagnostic for regression models, Sand. J. Statist., 1993, 19: 157.[22]Stute, W., Nonparametric model checks for regression, Ann. Statist., 1997, 25: 613.[23]Stute, W., Mantetga, G., Quindimil, M. P., Bootstrap approximations in model cheeks for regression, J. Amer.Statist. Assoc., 1998, 93: 141.[24]Stute, W., Thies, S., Zhu, L. X., Model checks for regression: An innovation process approach, Ann. Statist.,1998, 26: 1916.[25]Stute, W., Nonlinear censored regression, Statistica Sinica, 1999, 9:1089.[26]Wang, Q. H., Zhu, L. X., Estimation in partial linear error-in-variables models with censored data, Commun.in Statist. The. and Meth., 2001, .[27]Lo, S. H., Singh, K., The product-limit estimator and the bootstrap: some asymptotic representations, Probab.Theory and Related Fields, 1986, 71: 455.[28]Zhou, M., Some properties of the Kaplan-Meier estimator for independent, nonidentically distributed random variables, Ann. Statist., 1991, 19: 2266.[29]Hall, P., Heyde, C. C., Martingale Limit Theory and Its Applications, New York: Academic Press, 1980.[30]Pollard, D., Convergence of Stochastic Processes, New York: Springer-Verlag, 1984.[31

  6. Two different network topologies yield bistability in models of mesoderm and anterior mesendoderm specification in amphibians.

    Science.gov (United States)

    Brown, L E; King, J R; Loose, M

    2014-07-21

    Understanding the Gene Regulatory Networks (GRNs) that underlie development is a major question for systems biology. The establishment of the germ layers is amongst the earliest events of development and has been characterised in numerous model systems. The establishment of the mesoderm is best characterised in the frog Xenopus laevis and has been well studied both experimentally and mathematically. However, the Xenopus network has significant differences from that in mouse and humans, including the presence of multiple copies of two key genes in the network, Mix and Nodal. The axolotl, a urodele amphibian, provides a model with all the benefits of amphibian embryology but crucially only a single Mix and Nodal gene required for the specification of the mesoderm. Remarkably, the number of genes within the network is not the only difference. The interaction between Mix and Brachyury, two transcription factors involved in the establishment of the endoderm and mesoderm respectively, is not conserved. While Mix represses Brachyury in Xenopus, it activates Brachyury in axolotl. Thus, whilst the topology of the networks in the two species differs, both are able to form mesoderm and endoderm in vivo. Based on current knowledge of the structure of the mesendoderm GRN we develop deterministic models that describe the time evolution of transcription factors in a single axolotl cell and compare numerical simulations with previous results from Xenopus. The models are shown to have stable steady states corresponding to mesoderm and anterior mesendoderm, with the in vitro model showing how the concentration of Activin can determine cell fate, while the in vivo model shows that β-catenin concentration can determine cell fate. Moreover, our analysis suggests that additional components must be important in the axolotl network in the specification of the full range of tissues.

  7. Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield

    Science.gov (United States)

    Xiong, Wei; Skalský, Rastislav; Porter, Cheryl H.; Balkovič, Juraj; Jones, James W.; Yang, Di

    2016-09-01

    Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical data sets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global-gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter result in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation.

  8. Combining different functions to describe milk, fat, and protein yield in goats using Bayesian multiple-trait random regression models.

    Science.gov (United States)

    Oliveira, H R; Silva, F F; Siqueira, O H G B D; Souza, N O; Junqueira, V S; Resende, M D V; Borquis, R R A; Rodrigues, M T

    2016-05-01

    We proposed multiple-trait random regression models (MTRRM) combining different functions to describe milk yield (MY) and fat (FP) and protein (PP) percentage in dairy goat genetic evaluation by using Bayesian inference. A total of 3,856 MY, FP, and PP test-day records, measured between 2000 and 2014, from 535 first lactations of Saanen and Alpine goats, including their cross, were used in this study. The initial analyses were performed using the following single-trait random regression models (STRRM): third- and fifth-order Legendre polynomials (Leg3 and Leg5), linear B-splines with 3 and 5 knots, the Ali and Schaeffer function (Ali), and Wilmink function. Heterogeneity of residual variances was modeled considering 3 classes. After the selection of the best STRRM to describe each trait on the basis of the deviance information criterion (DIC) and posterior model probabilities (PMP), the functions were combined to compose the MTRRM. All combined MTRRM presented lower DIC values and higher PMP, showing the superiority of these models when compared to other MTRRM based only on the same function assumed for all traits. Among the combined MTRRM, those considering Ali to describe MY and PP and Leg5 to describe FP (Ali_Leg5_Ali model) presented the best fit. From the Ali_Leg5_Ali model, heritability estimates over time for MY, FP. and PP ranged from 0.25 to 0.54, 0.27 to 0.48, and 0.35 to 0.51, respectively. Genetic correlation between MY and FP, MY and PP, and FP and PP ranged from -0.58 to 0.03, -0.46 to 0.12, and 0.37 to 0.64, respectively. We concluded that combining different functions under a MTRRM approach can be a plausible alternative for joint genetic evaluation of milk yield and milk constituents in goats.

  9. Remote sensing and modelling of vegetation dynamics for early estimation and spatial analysis of grain yields in semiarid context in central Tunisia

    Science.gov (United States)

    Chahbi, Aicha; Zribi, Mehrez; Lili-Chabaane, Zohra

    2016-04-01

    In arid and semi-arid areas, population growth, urbanization, food security and climate change have an impact on agriculture in general and particular on the cereal production. Therefore to improve food security in arid countries, crop canopy monitoring and yield forecasting cereals are needed. Many models, based on the use of remote sensing or agro-meteorological models, have been developed to estimate the biomass and grain yield of cereals. Through the use of a rich database, acquired over a period of two years for more than 80 test fields, and from optical satellite SPOT/HRV images, the aim of the present study is to evaluate the feasibility of two yield prediction approaches. The first approach is based on the application of the semi-empirical growth model SAFY, developed to simulate the dynamics of the LAI and the grain yield, at the field scale. The model is able to reproduce the time evolution of the leaf area index of all fields with acceptable error. However, an inter-comparison between ground yield measurements and SAFY model simulations reveals that the yields are under-estimated by this model. We can explain the limits of the semi-empirical model SAFY by its simplicity and also by various factors that were not considered (fertilization, irrigation,...). To improve the yield estimation, a new approach is proposed: the grain yield is estimated in function of the LAI in the growth period between 25 March and 5 April. The LAI of this period is estimated by SAFY model. A linear relationship is developed between the measured grain yield and the LAI area of the maximum growth period.This approach is robust, the measured and estimated grain yields are well correlated. Following the validation of this approach, yield estimations are proposed for the entire studied site using the SPOT/HRV images.

  10. Measurement of Consumer Based Brand Equity Using Structural Equation Modeling and A Research in Durable Consumer Goods Sector

    Directory of Open Access Journals (Sweden)

    Cagatan Taskin

    2010-04-01

    Full Text Available In today’s markets, many products are perceived to be similar because of information and commuication technologies that are developing fastly. In spite of this, enterprises should make their products different and unique to compete in a sustainable manner. Besides, marketing strategies based solely on concepts such as price, quality, product differentiation and appropriate payment options, may not always provide sustainable competitive advantages under today’s severe competition conditions. Consumer based brand equity, which can be also defined as the meaning of a brand to the consumer, is one of the basic ways of developing sustainable and efficient marketing srategies. The aim of this research is to explore the relationships between consumer based brand equity of a durable consumer good brand, namely Bosch and its dimensions by means of structural equation modeling and to show how to use the model for developing efficient marketing strategies with strategy propositions. The research is conducted in Bursa, so the results of this study can not be generalized to Turkey or any other cities.

  11. Models for Broad Area Event Identification and Yield Estimation: Multiple Coda Types

    Science.gov (United States)

    2011-09-01

    microearthquakes accompanying hydraulic fracturing in granitic rock, Bull. Seism . Soc. Am., 81, 553-575, 1991. Fisk, M. and S. R. Taylor, (2007...146882, pp. 13. Yang, X., T. Lay, X.-B. Xie, and M. S. Thorne (2007). Geometric spreading of Pn and Sn in a spherical Earth model, Bull. Seism . Soc

  12. Intercropping reduces nitrate leaching from under field crops without loss of yield: A modelling study

    NARCIS (Netherlands)

    Whitmore, A.P.; Schröder, J.J.

    2007-01-01

    A model of soil nitrogen dynamics under competing intercrops is described and used to interpret two sets of experimental field data from the literature. In one series of experiments, maize received slurry and mineral nitrogen (N) fertiliser or mineral N alone and was grown either alone or intercropp

  13. Remote Sensing Protocols for Parameterizing an Individual, Tree-Based, Forest Growth and Yield Model

    Science.gov (United States)

    2014-09-01

    IT TO THE ORIGINATOR . ERDC/CERL TR-14-18 iii Contents Abstract... original pixel size of 0.25m, the following segmenta- tion parameters seemed to generate the best (visually compared to origi- nal imagery...Penelope Morgan. 2006. “Regression Modeling and Mapping of Coniferous Forest Basal Area and Tree Density from Discrete- Return LIDAR and

  14. On the spatial convergence and transient behaviour of lattice Boltzmann methods for modelling fluids with yield stress

    CERN Document Server

    Regulski, Wojciech; Szumbarski, Jacek

    2016-01-01

    In this paper, the performance of two lattice Boltzmann method formulations for yield-stress (i.e. viscoplastic) fluids has been investigated. The first approach is based on the popular Papanastasiou regularisation of the fluid rheology in conjunction with explicit modification of the lattice Boltzmann relaxation rate. The second approach uses a locally-implicit formulation to simultaneously solve for the fluid stress and the underlying particle distribution functions. After investigating issues related to the lattice symmetry and non-hydrodynamic Burnett stresses, the two models were compared in terms of spatial convergence and their behaviour in transient and inertial flows. The choice of lattice and the presence of Burnett stresses was found to influence the results of both models, however the latter did not significantly degrade the velocity field. Using Bingham flows in ducts and synthetic porous media, it was found that the implicitly-regularised model was superior in capturing transient and inertial fl...

  15. [Analyzing and modeling methods of near infrared spectroscopy for in-situ prediction of oil yield from oil shale].

    Science.gov (United States)

    Liu, Jie; Zhang, Fu-Dong; Teng, Fei; Li, Jun; Wang, Zhi-Hong

    2014-10-01

    In order to in-situ detect the oil yield of oil shale, based on portable near infrared spectroscopy analytical technology, with 66 rock core samples from No. 2 well drilling of Fuyu oil shale base in Jilin, the modeling and analyzing methods for in-situ detection were researched. By the developed portable spectrometer, 3 data formats (reflectance, absorbance and K-M function) spectra were acquired. With 4 different modeling data optimization methods: principal component-mahalanobis distance (PCA-MD) for eliminating abnormal samples, uninformative variables elimination (UVE) for wavelength selection and their combina- tions: PCA-MD + UVE and UVE + PCA-MD, 2 modeling methods: partial least square (PLS) and back propagation artificial neural network (BPANN), and the same data pre-processing, the modeling and analyzing experiment were performed to determine the optimum analysis model and method. The results show that the data format, modeling data optimization method and modeling method all affect the analysis precision of model. Results show that whether or not using the optimization method, reflectance or K-M function is the proper spectrum format of the modeling database for two modeling methods. Using two different modeling methods and four different data optimization methods, the model precisions of the same modeling database are different. For PLS modeling method, the PCA-MD and UVE + PCA-MD data optimization methods can improve the modeling precision of database using K-M function spectrum data format. For BPANN modeling method, UVE, UVE + PCA-MD and PCA- MD + UVE data optimization methods can improve the modeling precision of database using any of the 3 spectrum data formats. In addition to using the reflectance spectra and PCA-MD data optimization method, modeling precision by BPANN method is better than that by PLS method. And modeling with reflectance spectra, UVE optimization method and BPANN modeling method, the model gets the highest analysis precision

  16. A Simple Model to Estimate the Yield Strength of Silicon Carbide Particulate Reinforced Aluminium Alloy Matrix Composites

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    In the present study, a modified Hall-Petch correlation on the basis of dislocation pile-up model was used to estimate the yield strength of SiCp/Al composites. The experimental results show that the modified Hall-Petch correlation expressed as σcy=244+371λ-1/2 fits very well with the experimental data, which indicated that the strength increase of SiCp/Al composites might be due to the direct blocking of dislocation motion by the particulate-matrix interface,namely, the dislocation pile-up is the most possible strengthening mechanism for SiCp/Al composites.

  17. Genomics approaches to unlock the high yield potential of cassava, a tropical model plant

    Directory of Open Access Journals (Sweden)

    Shengkui ZHANG,Ping'an MA,Haiyan WANG,Cheng LU,Xin CHEN,Zhiqiang XIA,Meiling ZOU,Xinchen ZHOU,Wenquan WANG

    2014-12-01

    Full Text Available Cassava, a tropical food, feed and biofuel crop, has great capacity for biomass accumulation and an extraordinary efficiency in water use and mineral nutrition, which makes it highly suitable as a model plant for tropical crops. However, the understanding of the metabolism and genomics of this important crop is limited. The recent breakthroughs in the genomics of cassava, including whole-genome sequencing and transcriptome analysis, as well as advances in the biology of photosynthesis, starch biosynthesis, adaptation to drought and high temperature, and resistance to virus and bacterial diseases, are reviewed here. Many of the new developments have come from comparative analyses between a wild ancestor and existing cultivars. Finally, the current challenges and future potential of cassava as a model plant are discussed.

  18. A COMPARATIVE STUDY OF FORECASTING MODELS FOR TREND AND SEASONAL TIME SERIES DOES COMPLEX MODEL ALWAYS YIELD BETTER FORECAST THAN SIMPLE MODELS

    Directory of Open Access Journals (Sweden)

    Suhartono Suhartono

    2005-01-01

    Full Text Available Many business and economic time series are non-stationary time series that contain trend and seasonal variations. Seasonality is a periodic and recurrent pattern caused by factors such as weather, holidays, or repeating promotions. A stochastic trend is often accompanied with the seasonal variations and can have a significant impact on various forecasting methods. In this paper, we will investigate and compare some forecasting methods for modeling time series with both trend and seasonal patterns. These methods are Winter's, Decomposition, Time Series Regression, ARIMA and Neural Networks models. In this empirical research, we study on the effectiveness of the forecasting performance, particularly to answer whether a complex method always give a better forecast than a simpler method. We use a real data, that is airline passenger data. The result shows that the more complex model does not always yield a better result than a simpler one. Additionally, we also find the possibility to do further research especially the use of hybrid model by combining some forecasting method to get better forecast, for example combination between decomposition (as data preprocessing and neural network model.

  19. Sensitivity of the ATLAS experiment to discover the decay H{yields} {tau}{tau} {yields}ll+4{nu} of the Standard Model Higgs Boson produced in vector boson fusion

    Energy Technology Data Exchange (ETDEWEB)

    Schmitz, Martin

    2011-05-17

    A study of the expected sensitivity of the ATLAS experiment to discover the Standard Model Higgs boson produced via vector boson fusion (VBF) and its decay to H{yields} {tau}{tau}{yields} ll+4{nu} is presented. The study is based on simulated proton-proton collisions at a centre-of-mass energy of 14 TeV. For the first time the discovery potential is evaluated in the presence of additional proton-proton interactions (pile-up) to the process of interest in a complete and consistent way. Special emphasis is placed on the development of background estimation techniques to extract the main background processes Z{yields}{tau}{tau} and t anti t production using data. The t anti t background is estimated using a control sample selected with the VBF analysis cuts and the inverted b-jet veto. The dominant background process Z{yields}{tau}{tau} is estimated using Z{yields}{mu}{mu} events. Replacing the muons of the Z{yields}{mu}{mu} event with simulated {tau}-leptons, Z{yields}{tau}{tau} events are modelled to high precision. For the replacement of the Z boson decay products a dedicated method based on tracks and calorimeter cells is developed. Without pile-up a discovery potential of 3{sigma} to 3.4{sigma} in the mass range 115 GeV

  20. Use of a crop climate modeling system to evaluate climate change adaptation practices: maize yield in East Africa

    Science.gov (United States)

    Moore, N. J.; Alagarswamy, G.; Andresen, J.; Olson, J.; Thornton, P.

    2013-12-01

    Sub Saharan African agriculture is dominated by small-scale farmers and is heavily depend on growing season precipitation. Recent studies indicate that anthropogenic- induced warming including the Indian Ocean sea surface significantly influences precipitation in East Africa. East Africa is a useful region to assess impacts of future climate because of its large rainfall gradient, large percentage of its area being sub-humid or semi-arid, complex climatology and topography, varied soils, and because the population is particularly vulnerable to shifts in climate. Agronomic adaptation practices most commonly being considered include include a shift to short season, drought resistant maize varieties, better management practices especially fertilizer use, and irrigation. The effectiveness of these practices with climate change had not previously been tested. We used the WorldClim data set to represent current climate and compared the current and future climate scenarios of 4 Global Climate Models (GCMs) including a wetter (CCSM) and drier (HadCM3) GCM downscaled to 6 km resolution. The climate data was then used in the process-based CERES maize crop model to simulate the current period (representing 1960- 1990) and change in future maize production (from 2000 to 2050s). The effectiveness of agronomic practices, including short duration maize variety, fertilizer use and irrigation, to reduce projected future yield losses due to climate change were simulated. The GCMs project an increase in maximum temperature during growing season ranging from 1.5 to 3°C. Changes in precipitation were dependent on the GCM, with high variability across different topographies land cover types and elevations. Projected warmer temperatures in the future scenarios accelerated plant development and led to a reduction in growing season length and yields even where moisture was sufficient Maize yield changes in 2050 relative to the historical period were highly varied, in excess of +/- 500 kg

  1. Using the UKCP09 probabilistic scenarios to model the amplified impact of climate change on river basin sediment yield

    Directory of Open Access Journals (Sweden)

    T. J. Coulthard

    2012-07-01

    Full Text Available Precipitation intensities and the frequency of extreme events are projected to increase under climate change. These rainfall changes will lead to increases in the magnitude and frequency of flood events that will, in turn, affect patterns of erosion and deposition within river basins. These geomorphic changes to river systems may affect flood conveyance, infrastructure resilience, channel pattern, and habitat status, as well as sediment, nutrient and carbon fluxes. Previous research modelling climatic influences on geomorphic changes has been limited by how climate variability and change are represented by downscaling from Global or Regional Climate Models. Furthermore, the non-linearity of the climatic, hydrological and geomorphic systems involved generate large uncertainties at each stage of the modelling process creating an uncertainty "cascade".

    This study integrates state-of-the-art approaches from the climate change and geomorphic communities to address these issues in a probabilistic modelling study of the Swale catchment, UK. The UKCP09 weather generator is used to simulate hourly rainfall for the baseline and climate change scenarios up to 2099, and used to drive the CAESAR landscape evolution model to simulate geomorphic change. Results show that winter rainfall is projected to increase, with larger increases at the extremes. The impact of the increasing rainfall is amplified through the translation into catchment runoff and in turn sediment yield with a 100% increase in catchment mean sediment yield predicted between the baseline and the 2070–2099 High emissions scenario. Significant increases are shown between all climate change scenarios and baseline values. Analysis of extreme events also shows the amplification effect from rainfall to sediment delivery with even greater amplification associated with higher return period events. Furthermore, for the 2070–2099 High emissions scenario, sediment discharges from 50 yr

  2. Using the UKCP09 probabilistic scenarios to model the amplified impact of climate change on drainage basin sediment yield

    Directory of Open Access Journals (Sweden)

    T. J. Coulthard

    2012-11-01

    Full Text Available Precipitation intensities and the frequency of extreme events are projected to increase under climate change. These rainfall changes will lead to increases in the magnitude and frequency of flood events that will, in turn, affect patterns of erosion and deposition within river basins. These geomorphic changes to river systems may affect flood conveyance, infrastructure resilience, channel pattern, and habitat status as well as sediment, nutrient and carbon fluxes. Previous research modelling climatic influences on geomorphic changes has been limited by how climate variability and change are represented by downscaling from global or regional climate models. Furthermore, the non-linearity of the climatic, hydrological and geomorphic systems involved generate large uncertainties at each stage of the modelling process creating an uncertainty "cascade".

    This study integrates state-of-the-art approaches from the climate change and geomorphic communities to address these issues in a probabilistic modelling study of the Swale catchment, UK. The UKCP09 weather generator is used to simulate hourly rainfall for the baseline and climate change scenarios up to 2099, and used to drive the CAESAR landscape evolution model to simulate geomorphic change. Results show that winter rainfall is projected to increase, with larger increases at the extremes. The impact of the increasing rainfall is amplified through the translation into catchment runoff and in turn sediment yield with a 100% increase in catchment mean sediment yield predicted between the baseline and the 2070–2099 High emissions scenario. Significant increases are shown between all climate change scenarios and baseline values. Analysis of extreme events also shows the amplification effect from rainfall to sediment delivery with even greater amplification associated with higher return period events. Furthermore, for the 2070–2099 High emissions scenario, sediment discharges from 50-yr

  3. Optimizing selective cutting strategies for maximum carbon stocks and yield of Moso bamboo forest using BIOME-BGC model.

    Science.gov (United States)

    Mao, Fangjie; Zhou, Guomo; Li, Pingheng; Du, Huaqiang; Xu, Xiaojun; Shi, Yongjun; Mo, Lufeng; Zhou, Yufeng; Tu, Guoqing

    2017-04-15

    The selective cutting method currently used in Moso bamboo forests has resulted in a reduction of stand productivity and carbon sequestration capacity. Given the time and labor expense involved in addressing this problem manually, simulation using an ecosystem model is the most suitable approach. The BIOME-BGC model was improved to suit managed Moso bamboo forests, which was adapted to include age structure, specific ecological processes and management measures of Moso bamboo forest. A field selective cutting experiment was done in nine plots with three cutting intensities (high-intensity, moderate-intensity and low-intensity) during 2010-2013, and biomass of these plots was measured for model validation. Then four selective cutting scenarios were simulated by the improved BIOME-BGC model to optimize the selective cutting timings, intervals, retained ages and intensities. The improved model matched the observed aboveground carbon density and yield of different plots, with a range of relative error from 9.83% to 15.74%. The results of different selective cutting scenarios suggested that the optimal selective cutting measure should be cutting 30% culms of age 6, 80% culms of age 7, and all culms thereafter (above age 8) in winter every other year. The vegetation carbon density and harvested carbon density of this selective cutting method can increase by 74.63% and 21.5%, respectively, compared with the current selective cutting measure. The optimized selective cutting measure developed in this study can significantly promote carbon density, yield, and carbon sink capacity in Moso bamboo forests.

  4. Ozone uptake modelling and flux-response relationships—an assessment of ozone-induced yield loss in spring wheat

    Science.gov (United States)

    Danielsson, Helena; Karlsson, Gunilla Pihl; Karlsson, Per Erik; Håkan Pleijel, H.

    Measurements of stomatal conductance on field grown spring wheat ( Triticum aestivum L.) from two experiments conducted in southwest Sweden were combined to validate and adjust the Jarvis type of multiplicative stomatal conductance model presented by Emberson et al. (Environ. Pollut. 109 (2000) 403). The adjusted model (Östad model) and the Emberson model are based on the boundary line technique. The aging of the flag leaf became important for stomatal conductance at about 500 degrees days after anthesis, on average 30 days after anthesis. Elevated ozone concentrations were assumed to influence the stomatal conductance in relation to the effect on the leaf life span. During the hours after noon the stomata tended to close to an extent that could not be explained by the combined effects of leaf temperature, leaf-to-air vapour pressure difference (VPD LA) or solar radiation. For these reasons factors describing the reduction of stomatal conductance caused by ozone and time of day were introduced in the calibration of the Östad stomatal conductance model. VPD LA induced closure of stomata at ≈1.5 kPa. In elevated carbon dioxide concentration (680 μmol mol -1) the stomatal conductance was reduced by approximately 60%. Test with the data from Östad showed that the Östad multiplicative model had an r2-value of 0.59 for the relationship between calculated and observed conductance. The Östad as well as the Emberson models were used to estimate the cumulated uptake of ozone (CUO) by the wheat flag leaves. The relationship between CUO based on the Östad model cumulated from anthesis to harvest, with a threshold for the uptake rate of 5 nmol m -2 s -1 and relative yield loss, resulted in a higher r2-value (0.90) than any other CUO model or relationships based on the accumulated ozone exposure over 40 nmol mol -1 (AOT40). The corresponding relationships between relative yield and CUO based on the Emberson model and with AOT40 were however also statistically

  5. Customs control of goods

    Directory of Open Access Journals (Sweden)

    Mentor Gashi

    2015-11-01

    Full Text Available Customs control, is regulated by law in different countries. Different countries define through the law, the control of goods.. Main purpose of this paper is to analyze two types of customs controls, and their effect in reducing avoidance of duty or tax evasion which may be caused by the import of goods of certain companies. For this reason we researched which model is implemented in developing countries and what results were reached through questionnaires. In this sense the next research question, consists in defining the moment of customs control pre or post-clearance control of goods.

  6. Automatic calibration of an erosion and sediment yield distributed conceptual model: application to the Goodwin Creek experimental river basin (USA)

    Science.gov (United States)

    Bussi, G.; Francés, F.

    2010-05-01

    In the last decades, distributed hydrological models have achieved a fundamental importance in Hydrology, mainly for their capacity to describe the spatial variability of the basin processes. TETIS is a distributed conceptual model created to simulate rainfall-runoff processes. In the same way, a distributed approach to erosion and sediment yield modelling can lead to improvements for the solution of several sedimentological and geomorphological problems, such as sediment redistribution, localization of heavy erosion and soil loss zones, estimation of soil erosion and sediment yield and assessment of land use change effects on the sediment cycle. Following these considerations, the TETIS model has been coupled with a sediment cycle module with the purpose of representing erosion and sediment transport at basin scale. TETIS-SED is the result of integrating the erosion submodel of CASC2D-SED into the hydrological model TETIS. In the TETIS-SED model, the erosion/sedimentation rates are calculated as a function of the hydraulic properties of the flow, the physical properties of the soil and the surface characteristics. The modified Kilinc-Richardson equation is used to determine the upland sediment transport by grain size (silt, clay, and sand) from one cell into the next one. Sediment by size fraction is routed in the channels and the Engelund and Hansen equation is used to compute the transport capacity in one dimension. This formulation in both cases depends on hydraulic parameters (hydraulic radius, flow velocity and friction slope) and particle characteristics (specific gravity and particle diameter). Due to the uncertainty affecting the sediment parameters, the calibration stage may be a key issue in erosion and sediment yield modelling. In the TETIS model, automatic calibration is carried out by adjusting up to 9 hydrological correction factors with an automatic calibration algorithm, the Shuffled Complex Evolution (SCE-UA). In this work, 3 sedimentological

  7. Customs control of goods

    OpenAIRE

    Mentor Gashi; Ramadan Gashi

    2015-01-01

    Customs control, is regulated by law in different countries. Different countries define through the law, the control of goods.. Main purpose of this paper is to analyze two types of customs controls, and their effect in reducing avoidance of duty or tax evasion which may be caused by the import of goods of certain companies. For this reason we researched which model is implemented in developing countries and what results were reached through questionnaires. In this sense the next research que...

  8. Quality of life in relation to future mental health problems and offending: Testing the good lives model among detained girls.

    Science.gov (United States)

    Van Damme, Lore; Hoeve, Machteld; Vermeiren, Robert; Vanderplasschen, Wouter; Colins, Olivier F

    2016-06-01

    Detained girls bear high levels of criminal behavior and mental health problems that are likely to persist into young adulthood. Research with these girls began primarily from a risk management perspective, whereas a strength-based empowering perspective may increase knowledge that could improve rehabilitation. This study examines detained girls' quality of life (QoL) in relation to future mental health problems and offending, thereby testing the strength-based good lives model of offender rehabilitation (GLM). At baseline, 95 girls (Mage = 16.25) completed the World Health Organization QoL instrument to assess their QoL prior to detention in the domains of physical