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Sample records for model yields promising

  1. Yielding and its adaptability of several promising bulk cocoa clones

    Directory of Open Access Journals (Sweden)

    Dedy Suhendi

    2005-05-01

    Full Text Available Yielding and its adaptability are considered to be an important criteria for clones recommendation. An experiment to evaluate yield and its adaptability of several promising bulk cocoa clones has been executed during 1996—2003 in three locations having different altitude and type of climate, consisted of Jatirono(450 m asl., B type of climate, Kalisepanjang (275 m asl., C type of climate and Kalitelepak (145 m asl., B type of climate. Randomized completely block design (RCBD was used in each location with 14 promising clones and four replications. Recommended clones of ICS 60 and GC 7 were used as standard. The promising clones were originated from mother trees selection with the main criteria of yield. Observations were conducted on yield and its components as well as bean characteristics. Determination of adaptability of each clone by using yield performance and its stability. Statistical analysis was done by using combined analysis. The results showed that KW 30 and KW 48 perform higher yield (2.3 ton/ha than that of standard clone (1.7 ton/ha as well as consistant yield stability between location and over years. There for, the two clones performed good adaptability. KW 30 and KW 48 also perform good yield components, and high percentage of fat content i.e 55%. So, those clones are potential to be recommended for commercial planting materials. Key words : bulk cocoa, yield, clone, stability, adaptability.

  2. Review of Some Promising Fractional Physical Models

    CERN Document Server

    Tarasov, Vasily E

    2015-01-01

    Fractional dynamics is a field of study in physics and mechanics investigating the behavior of objects and systems that are characterized by power-law non-locality, power-law long-term memory or fractal properties by using integrations and differentiation of non-integer orders, i.e., by methods of the fractional calculus. This paper is a review of physical models that look very promising for future development of fractional dynamics. We suggest a short introduction to fractional calculus as a theory of integration and differentiation of non-integer order. Some applications of integro-differentiations of fractional orders in physics are discussed. Models of discrete systems with memory, lattice with long-range inter-particle interaction, dynamics of fractal media are presented. Quantum analogs of fractional derivatives and model of open nano-system systems with memory are also discussed.

  3. Promises

    Institute of Scientific and Technical Information of China (English)

    1998-01-01

    AT dusk, I switched on my radio. What I heard was a special call-in program entitled "New Air of the City," on a local music channel; the two silver-tongued hosts were discussing the topic of promises. A young woman with a soft voice managed to get through first. She said that she had been in love for many years. She and her fiance often went to the banks of the Yangtze River in their spare time, lifting stones to look for small crabs, as tiny as fingernails. They liked to raise the crabs in a glass bowl. But one day, there were few stones by the river; they searched for a long time, but found nothing. An old man who was catching fish told them that it was difficult to find those crabs on the bank. Then he took several crabs out of his

  4. THE GENOTYPES X ENVIRONMENT INTERACTION FOR STARCH YIELD IN NINE-MONTH OLD CASSAVA PROMISING CLONES

    Directory of Open Access Journals (Sweden)

    Sholihin Sholihin

    2016-10-01

    Full Text Available Cassava (Manihot esculenta is planted in dry areas with different environmental conditions, therefore the yield is varied. The aim of the study was to analyze the genotype x environment interaction for starch yield in 9-month old cassava promising clones. The experiment was conducted on mineral soils in four different locations, i.e. Lumajang-East Java (Inceptisols, Kediri-East Java (Entisols, Pati-Central Java (Alfisols, and Tulangbawang-Lampung (Ultisols during 2004- 2005. The experiment was arranged in split plot design with three replications. The main plots were cultivation techniques, i.e. simple technology and improved technology, whereas the subplots were 15 cassava promising clones. Starch yield of 9- month old cassava plants was analysed using the additive maineffects and multiplicative interaction (AMMI. The results showed that environmental factors determined the stability of starch yield were soil bulk density on subsoil, the number of rainy days at fifth month, minimum air temperature at fourth month, and minimum air humidity at seventh month. CMM97002-183, Adira 4, CMM97007-145, CMM97007-235, Malang 2, CMM97002-36, and CMM97006-44 were identified as the stable cassava clones for starch yield in 9-month old. Average starch yield of Adira 4 was the third after MLG 10311 and CMM 97006-52. The CMM97006-52 was adapted to the soils having high P2O5 content on topsoil, high minimum air temperature at 4 and 5 months after planting, high minimum relative humidity at 7 months after planting, low total rainfall at 5 months after planting, and low number of rainy days at 5 and 8 months after planting. MLG 10311 was adapted to low soil bulk density. The average starch yield of MLG 10311 was the highest at 9 months after planting. The study implies that advanced trials for CMM 977006-52 and MLG 10311 clones are needed, so the clones can be released as new varieties of cassava. In selection and evaluation, the bulk density on subsoil is needed

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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...

  10. 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...

  11. 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.

  12. 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).

  13. 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).

  14. 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.

  15. Models for prevention and treatment of cancer: problems vs promises.

    Science.gov (United States)

    Aggarwal, Bharat B; Danda, Divya; Gupta, Shan; Gehlot, Prashasnika

    2009-11-01

    Current estimates from the American Cancer Society and from the International Union Against Cancer indicate that 12 million cases of cancer were diagnosed last year, with 7 million deaths worldwide; these numbers are expected to double by 2030 (27 million cases with 17 million deaths). Despite tremendous technological developments in all areas, and President Richard Nixon's initiative in the 1974 "War against Cancer", the US cancer incidence is the highest in the world and the cancer death rate has not significantly changed in the last 50 years (193.9 per 100,000 in 1950 vs 193.4 per 100,000 in 2002). Extensive research during the same time, however, has revealed that cancer is a preventable disease that requires major changes in life style; with one third of all cancers assigned to Tobacco, one third to diet, and remaining one third to the environment. Approximately 20 billion dollars are spent annually to find a cure for cancer. We propose that our inability to find a cure to cancer lies in the models used. Whether cell culture or animal studies, no model has yet been found that can reproduce the pathogenesis of the disease in the laboratory. Mono-targeted therapies, till know in most cases, have done a little to make a difference in cancer treatment. Similarly, molecular signatures/predictors of the diagnosis of the disease and response are also lacking. This review discusses the pros and cons of current cancer models based on cancer genetics, cell culture, animal models, cancer biomarkers/signature, cancer stem cells, cancer cell signaling, targeted therapies, therapeutic targets, clinical trials, cancer prevention, personalized medicine, and off-label uses to find a cure for cancer and demonstrates an urgent need for "out of the box" approaches.

  16. Beyond pure parasystole: promises and problems in modeling complex arrhythmias.

    Science.gov (United States)

    Courtemanche, M; Glass, L; Rosengarten, M D; Goldberger, A L

    1989-08-01

    The dynamics of pure parasystole, a cardiac arrhythmia in which two competing pacemakers fire independently, have recently been fully characterized. This model is now extended in an attempt to account for the more complex dynamics occurring with modulated parasystole, in which there exists nonlinear interaction between the sinus node and the ectopic ventricular focus. Theoretical analysis of modulated parasystole reveals three types of dynamics: entrainment, quasiperiodicity, and chaos. Rhythms associated with quasiperiodicity obey a set of rules derived from pure parasystole. This model is applied to the interpretation of continuous electrocardiographic data sets from three patients with complicated patterns of ventricular ectopic activity. We describe several new statistical properties of these records, related to the number of intervening sinus beats between ectopic events, that are essential in characterizing the dynamics and testing mathematical models. Detailed comparison between data and theory in these cases show substantial areas of agreement as well as potentially important discrepancies. These findings have implications for understanding the dynamics of the heartbeat in normal and pathological conditions.

  17. 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.

  18. 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....

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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%.``

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. 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

  9. 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.``

  10. 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.

  11. 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.

  12. 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)

  13. 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...

  14. 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.

  15. 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

  16. 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.

  17. 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...

  18. 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.

  19. 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.

  20. Model validation through long-term promising sustainable maize/pigeon pea residue management in Malawi

    NARCIS (Netherlands)

    Mwale, C.D.; Kabambe, V.H.; Sakale, W.D.; Giller, K.E.; Kauwa, A.A.; Ligowe, I.; Kamalongo, D.

    2013-01-01

    In the 2005/2006 season, the Model Validation Through Long-Term Promising Sustainable Maize/Pigeon Pea Residue Management experiment was in the 11th year at Chitedze and Chitala, and in the 8th year at Makoka and Zombwe. The experiment was a split-plot design with cropping system as the main plot an

  1. 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.

  2. 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...

  3. 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%.

  4. 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.

  5. 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.

  6. 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)

  7. 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.

  8. 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

  9. Pricing equity warrants with a promised lowest price in Merton's jump-diffusion model

    Science.gov (United States)

    Xiao, Weilin; Zhang, Xili

    2016-09-01

    Motivated by the empirical evidence of jumps in the dynamics of firm behavior, this paper considers the problem of pricing equity warrants in the presence of a promised lowest price when the price of the underlying asset follows the Merton's jump-diffusion process. Using the Martingale approach, we propose a valuation model of equity warrants based on the firm value, its volatility, and parameters of the jump component, which are not directly observable. To implement our pricing model empirically, this paper also provides a promising estimation method for obtaining these desired variables based on observable data, such as stock prices and the book value of total liability. We conduct an empirical study to ascertain the performance of our proposed model using the data of Changdian warrant collected from 25 May 2006 (the listing date) to 29 January 2007 (the expiration date). Furthermore, the comparison of traditional models (such as the Black-Scholes model, the Noreen-Wolfson model, the Lauterbach-Schultz model, and the Ukhov model) with our model is presented. From the empirical study, we can see that the mean absolute error of our pricing model is 16.75%. By contrast, the Black-Scholes model, the Noreen-Wolfson model, the Lauterbach-Schultz model, and the Ukhov model applied to the same warrant produce mean absolute errors of 92.24%, 45.38%, 87.34%, 76.12%, respectively. Thus both the dilution effect and the jump feature cannot be ignored in determining the valuation of equity warrants.

  10. 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...

  11. 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.

  12. CRISPR-Cas9 systems: versatile cancer modelling platforms and promising therapeutic strategies.

    Science.gov (United States)

    Wen, Wan-Shun; Yuan, Zhi-Min; Ma, Shi-Jie; Xu, Jiang; Yuan, Dong-Tang

    2016-03-15

    The RNA-guided nuclease CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats-CRISPR associated nuclease 9) and its variants such as nickase Cas9, dead Cas9, guide RNA scaffolds and RNA-targeting Cas9 are convenient and versatile platforms for site-specific genome editing and epigenome modulation. They are easy-to-use, simple-to-design and capable of targeting multiple loci simultaneously. Given that cancer develops from cumulative genetic and epigenetic alterations, CRISPR-Cas9 and its variants (hereafter referred to as CRISPR-Cas9 systems) hold extensive application potentials in cancer modeling and therapy. To date, they have already been applied to model oncogenic mutations in cell lines (e.g., Choi and Meyerson, Nat Commun 2014;5:3728) and in adult animals (e.g., Xue et al., Nature 2014;514:380-4), as well as to combat cancer by disabling oncogenic viruses (e.g., Hu et al., Biomed Res Int 2014;2014:612823) or by manipulating cancer genome (e.g., Liu et al., Nat Commun 2014;5:5393). Given the importance of epigenome and transcriptome in tumourigenesis, manipulation of cancer epigenome and transcriptome for cancer modeling and therapy is a promising area in the future. Whereas (epi)genetic modifications of cancer microenvironment with CRISPR-Cas9 systems for therapeutic purposes represent another promising area in cancer research. Herein, we introduce the functions and mechanisms of CRISPR-Cas9 systems in genome editing and epigenome modulation, retrospect their applications in cancer modelling and therapy, discuss limitations and possible solutions and propose future directions, in hope of providing concise and enlightening information for readers interested in this area.

  13. 3-Self behavior modification programs base on the PROMISE Model for clients at metabolic risk.

    Science.gov (United States)

    Intarakamhang, Ungsinun

    2011-12-29

    The objectives of this mixed methods research were 1) to study effects of the health behavior modification program (HBMP) conducted under the principles of the PROMISE Model and the CIPP Model and 2) to compare the 3-self health behaviors and the biomedical indicators before with after the program completion. During the program, three sample groups including 30 program leaders, 30 commanders and 120 clients were assessed, and there were assessments taken on 4,649 volunteers who were at risk of metabolic syndrome before and after the program conducted in 17 hospitals. The collected data were analyzed by the t-test and the path analysis. The research instruments were questionnaires used for program evaluation, structuralized interview forms, and questionnaires used for 3-self health behavior assessment. The findings were as follows: 1) During the program, the assessment result deriving from comparing the overall opinions toward the program among the three sample groups showed no difference (F=2.219), 2) The program management factors based on the PROMISE Model (positive reinforcement, optimism, context, and process or activity provision) had an overall influence on the product or success of the HBMP (p< 0.05) with size effects at 0.37, 0.13, 0.31 and 0.88 respectively. All of the factors could predict the product of the program by 69%. 3) After participating in the program, the clients' 3-self health behaviors (self-efficacy, self-regulation, and self-care) were significantly higher than those appeared before the participation (p< 0.05), and their biomedical indicators (BMI, blood pressure, waistline, blood glucose, lipid profiles, cholesterol, and HbA1c) were significantly lower than those measured before the program (p< 0.05).

  14. 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).

  15. 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

  16. Fuzzy promises

    DEFF Research Database (Denmark)

    Anker, Thomas Boysen; Kappel, Klemens; Eadie, Douglas

    2012-01-01

    This article clarifies the commonplace assumption that brands make promises by developing definitions of brand promise delivery. Distinguishing between clear and fuzzy brand promises, we develop definitions of what it is for a brand to deliver on fuzzy functional, symbolic, and experiential...

  17. 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.

  18. The copepod Tigriopus: a promising marine model organism for ecotoxicology and environmental genomics.

    Science.gov (United States)

    Raisuddin, Sheikh; Kwok, Kevin W H; Leung, Kenneth M Y; Schlenk, Daniel; Lee, Jae-Seong

    2007-07-20

    There is an increasing body of evidence to support the significant role of invertebrates in assessing impacts of environmental contaminants on marine ecosystems. Therefore, in recent years massive efforts have been directed to identify viable and ecologically relevant invertebrate toxicity testing models. Tigriopus, a harpacticoid copepod has a number of promising characteristics which make it a candidate worth consideration in such efforts. Tigriopus and other copepods are widely distributed and ecologically important organisms. Their position in marine food chains is very prominent, especially with regard to the transfer of energy. Copepods also play an important role in the transportation of aquatic pollutants across the food chains. In recent years there has been a phenomenal increase in the knowledge base of Tigriopus spp., particularly in the areas of their ecology, geophylogeny, genomics and their behavioural, biochemical and molecular responses following exposure to environmental stressors and chemicals. Sequences of a number of important marker genes have been studied in various Tigriopus spp., notably T. californicus and T. japonicus. These genes belong to normal biophysiological functions (e.g. electron transport system enzymes) as well as stress and toxic chemical exposure responses (heat shock protein 20, glutathione reductase, glutathione S-transferase). Recently, 40,740 expressed sequenced tags (ESTs) from T. japonicus, have been sequenced and of them, 5,673 ESTs showed significant hits (E-value, >1.0E-05) to the red flour beetle Tribolium genome database. Metals and organic pollutants such as antifouling agents, pesticides, polycyclic aromatic hydrocarbons (PAH) and polychrlorinated biphenyls (PCB) have shown reproducible biological responses when tested in Tigriopus spp. Promising results have been obtained when Tigriopus was used for assessment of risk associated with exposure to endocrine-disrupting chemicals (EDCs). Application of environmental

  19. The copepod Tigriopus: A promising marine model organism for ecotoxicology and environmental genomics

    Energy Technology Data Exchange (ETDEWEB)

    Raisuddin, Sheikh [Department of Chemistry and the National Research Lab of Marine Molecular and Environmental Bioscience, College of Natural Sciences, Hanyang University, Seoul 133-791 (Korea, Republic of); Kwok, Kevin W.H. [Swire Institute of Marine Science, Department of Ecology and Biodiversity, University of Hong Kong, Pokfulam, Hong Kong (China); Leung, Kenneth M.Y. [Swire Institute of Marine Science, Department of Ecology and Biodiversity, University of Hong Kong, Pokfulam, Hong Kong (China); Schlenk, Daniel [Department of Environmental Sciences, University of California, Riverside, CA 92521 (United States); Lee, Jae-Seong [Department of Chemistry and the National Research Lab of Marine Molecular and Environmental Bioscience, College of Natural Sciences, Hanyang University, Seoul 133-791 (Korea, Republic of)]. E-mail: jslee2@hanyang.ac.kr

    2007-07-20

    There is an increasing body of evidence to support the significant role of invertebrates in assessing impacts of environmental contaminants on marine ecosystems. Therefore, in recent years massive efforts have been directed to identify viable and ecologically relevant invertebrate toxicity testing models. Tigriopus, a harpacticoid copepod has a number of promising characteristics which make it a candidate worth consideration in such efforts. Tigriopus and other copepods are widely distributed and ecologically important organisms. Their position in marine food chains is very prominent, especially with regard to the transfer of energy. Copepods also play an important role in the transportation of aquatic pollutants across the food chains. In recent years there has been a phenomenal increase in the knowledge base of Tigriopus spp., particularly in the areas of their ecology, geophylogeny, genomics and their behavioural, biochemical and molecular responses following exposure to environmental stressors and chemicals. Sequences of a number of important marker genes have been studied in various Tigriopus spp., notably T. californicus and T. japonicus. These genes belong to normal biophysiological functions (e.g. electron transport system enzymes) as well as stress and toxic chemical exposure responses (heat shock protein 20, glutathione reductase, glutathione S-transferase). Recently, 40,740 expressed sequenced tags (ESTs) from T. japonicus, have been sequenced and of them, 5673 ESTs showed significant hits (E-value, >1.0E-05) to the red flour beetle Tribolium genome database. Metals and organic pollutants such as antifouling agents, pesticides, polycyclic aromatic hydrocarbons (PAH) and polychrlorinated biphenyls (PCB) have shown reproducible biological responses when tested in Tigriopus spp. Promising results have been obtained when Tigriopus was used for assessment of risk associated with exposure to endocrine-disrupting chemicals (EDCs). Application of environmental

  20. The Oklahoma's Promise Program: A National Model to Promote College Persistence

    Science.gov (United States)

    Mendoza, Pilar; Mendez, Jesse P.

    2013-01-01

    Using a multi-method approach involving fixed effects and logistic regressions, this study examined the effect of the Oklahoma's Promise Program on student persistence in relation to the Pell and Stafford federal programs and according to socio-economic characteristics and class level. The Oklahoma's Promise is a hybrid state program that pays…

  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. 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

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. In vitro psoriasis models with focus on reconstructed skin models as promising tools in psoriasis research.

    Science.gov (United States)

    Desmet, Eline; Ramadhas, Anesh; Lambert, Jo; Van Gele, Mireille

    2017-06-01

    Psoriasis is a complex chronic immune-mediated inflammatory cutaneous disease associated with the development of inflammatory plaques on the skin. Studies proved that the disease results from a deregulated interplay between skin keratinocytes, immune cells and the environment leading to a persisting inflammatory process modulated by pro-inflammatory cytokines and activation of T cells. However, a major hindrance to study the pathogenesis of psoriasis more in depth and subsequent development of novel therapies is the lack of suitable pre-clinical models mimicking the complex phenotype of this skin disorder. Recent advances in and optimization of three-dimensional skin equivalent models have made them attractive and promising alternatives to the simplistic monolayer cultures, immunological different in vivo models and scarce ex vivo skin explants. Moreover, human skin equivalents are increasing in complexity level to match human biology as closely as possible. Here, we critically review the different types of three-dimensional skin models of psoriasis with relevance to their application potential and advantages over other models. This will guide researchers in choosing the most suitable psoriasis skin model for therapeutic drug testing (including gene therapy via siRNA molecules), or to examine biological features contributing to the pathology of psoriasis. However, the addition of T cells (as recently applied to a de-epidermized dermis-based psoriatic skin model) or other immune cells would make them even more attractive models and broaden their application potential. Eventually, the ultimate goal would be to substitute animal models by three-dimensional psoriatic skin models in the pre-clinical phases of anti-psoriasis candidate drugs. Impact statement The continuous development of novel in vitro models mimicking the psoriasis phenotype is important in the field of psoriasis research, as currently no model exists that completely matches the in vivo psoriasis

  8. 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.

  9. 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.

  10. 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.

  11. The Newark Fairmount Promise Neighborhood: A Collaborative University-Community Partnership Model

    Science.gov (United States)

    Hill, Diane; Herts, Rolando; Devance, Donita

    2014-01-01

    The recent awarding of a Promise Neighborhood Planning Grant to Rutgers University-Newark demonstrates how the institution's leadership has promoted a vision and mission that fosters an institutional climate supportive of community engagement. This paper discusses how Gray's (1989) partnership development framework and Kania and Kramer's (2011)…

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. Cardiac spheroids as promising in vitro models to study the human heart microenvironment

    DEFF Research Database (Denmark)

    Polonchuk, Liudmila; Chabria, Mamta; Badi, Laura

    2017-01-01

    and fibroblasts at ratios approximating those present in vivo. The cellular organisation, extracellular matrix and microvascular network mimic human heart tissue. These spheroids have been employed to investigate the dose-limiting cardiotoxicity of the common anti-cancer drug doxorubicin. Viability......, biochemistry and pharmacology in vitro, offering a promising alternative to animals and standard cell cultures with regard to mechanistic insights and prediction of toxic effects in human heart tissue....

  19. 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.

  20. 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...

  1. 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...

  2. Promising synergies of simulation model management, software engineering, artificial intelligence, and general system theories

    Energy Technology Data Exchange (ETDEWEB)

    Oren, T.I.

    1982-01-01

    Simulation is viewed within the model management paradigm. Major components of simulation systems as well as elements of model management are outlined. Possible synergies of simulation model management, software engineering, artificial intelligence, and general system theories are systematized. 21 references.

  3. 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.

  4. 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.

  5. 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.

  6. Quantitative Genetics and Functional-Structural Plant Growth Models: Simulation of Quantitative Trait Loci Detection for Model Parameters and Application to Potential Yield Optimization

    CERN Document Server

    Letort, Veronique; Cournède, Paul-Henry; De Reffye, Philippe; Courtois, Brigitte; 10.1093/aob/mcm197

    2010-01-01

    Background and Aims: Prediction of phenotypic traits from new genotypes under untested environmental conditions is crucial to build simulations of breeding strategies to improve target traits. Although the plant response to environmental stresses is characterized by both architectural and functional plasticity, recent attempts to integrate biological knowledge into genetics models have mainly concerned specific physiological processes or crop models without architecture, and thus may prove limited when studying genotype x environment interactions. Consequently, this paper presents a simulation study introducing genetics into a functional-structural growth model, which gives access to more fundamental traits for quantitative trait loci (QTL) detection and thus to promising tools for yield optimization. Methods: The GreenLab model was selected as a reasonable choice to link growth model parameters to QTL. Virtual genes and virtual chromosomes were defined to build a simple genetic model that drove the settings ...

  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

    2015-01-01

    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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. 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.

  15. 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.

  16. The promises and pitfalls of applying computational models to neurological and psychiatric disorders.

    Science.gov (United States)

    Teufel, Christoph; Fletcher, Paul C

    2016-10-01

    Computational models have become an integral part of basic neuroscience and have facilitated some of the major advances in the field. More recently, such models have also been applied to the understanding of disruptions in brain function. In this review, using examples and a simple analogy, we discuss the potential for computational models to inform our understanding of brain function and dysfunction. We argue that they may provide, in unprecedented detail, an understanding of the neurobiological and mental basis of brain disorders and that such insights will be key to progress in diagnosis and treatment. However, there are also potential problems attending this approach. We highlight these and identify simple principles that should always govern the use of computational models in clinical neuroscience, noting especially the importance of a clear specification of a model's purpose and of the mapping between mathematical concepts and reality.

  17. Comparative analyses of B{yields}K{sub 2}{sup *}l{sup +}l{sup -} in the standard model and new physics scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Li, Run-Hui [Institute of High Energy Physics, Beijing (China); Yonsei Univ., Seoul (Korea, Republic of). Dept. of Physics and IPAP; Lue, Cai-Dian [Institute of High Energy Physics, Beijing (China); Wang, Wei [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

    2010-12-15

    We analyze the B {yields} K{sub 2}{sup *}({yields} K{pi})l{sup +}l{sup -} (with l=e,{mu},{tau}) decay in the standard model and two new physics scenarios: vector-like quark model and family non-universal Z{sup '} model. We derive the differential angular distributions of the quasi-four-body decay, using the recently calculated form factors in the perturbative QCD approach. Branching ratios, polarizations, forward-backward asymmetries and transversity amplitudes are predicted, from which we find a promising prospective to observe this channel on the future experiment. We also update the constraints on effective Wilson coefficients and/or free parameters in these two new physics scenarios by making use of the experimental data of B{yields}K{sup *}l{sup +}l{sup -} and b{yields}sl{sup +}l{sup -}. Their impact on B{yields}K{sub 2}{sup *}l{sup +}l{sup -} is subsequently explored and in particular the zero-crossing point for the forward-backward asymmetry in these new physics scenarios can sizably deviate from the SM scenario. In addition we also generalize the analysis to a similar mode B{sub s}{yields}f{sup '}{sub 2}(1525)({yields}K{sup +}K{sup -})l{sup +}l{sup -}. (orig.)

  18. 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

  19. 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.

  20. Melanin, a promising radioprotector: Mechanisms of actions in a mice model

    Energy Technology Data Exchange (ETDEWEB)

    Kunwar, A., E-mail: amitbio@rediffmail.com [Radiation and Photochemistry Division, Bhabha Atomic Research Centre, Trombay, Mumbai 400085 (India); Adhikary, B. [Radiation and Photochemistry Division, Bhabha Atomic Research Centre, Trombay, Mumbai 400085 (India); Jayakumar, S. [Radiation Biology and Health Sciences Division, Bhabha Atomic Research Centre, Trombay, Mumbai 400085 (India); Barik, A. [Radiation and Photochemistry Division, Bhabha Atomic Research Centre, Trombay, Mumbai 400085 (India); Chattopadhyay, S. [Bio-Organic Division, Bhabha Atomic Research Centre, Trombay, Mumbai 400085 (India); Raghukumar, S. [Myko Tech Private Limited, Dona Paula, Goa‐403004 (India); Priyadarsini, K.I., E-mail: kindira@barc.gov.in [Radiation and Photochemistry Division, Bhabha Atomic Research Centre, Trombay, Mumbai 400085 (India)

    2012-10-15

    The radioprotective effect of extracellular melanin, a naturally occurring pigment, isolated from the fungus Gliocephalotrichum simplex was examined in BALB/C mice, and the probable mechanism of action was established. At an effective dose of 50 mg/kg body weight, melanin exhibited both prophylactic and mitigative activities, increasing the 30-day survival of mice by 100% and 60%, respectively, after exposure to radiation (7 Gy, whole body irradiation (WBI)). The protective activity of melanin was primarily due to inhibition of radiation-induced hematopoietic damages as evidenced by improvement in spleen parameters such as index, total cellularity, endogenous colony forming units, and maintenance of circulatory white blood cells and platelet counts. Melanin also reversed the radiation-induced decrease in ERK phosphorylation in splenic tissue, which may be the key feature in its radioprotective action. Additionally, our results indicated that the sustained activation of AKT, JNK and P38 proteins in splenic tissue of melanin pre-treated group may also play a secondary role. This was also supported by the fact that melanin could prevent apoptosis in splenic tissue by decreasing BAX/Bcl-XL ratio, and increasing the expressions of the proliferation markers (PCNA and Cyclin D1), compared to the radiation control group. Melanin also reduced the oxidative stress in hepatic tissue and abrogated immune imbalance by reducing the production of pro-inflammatory cytokines (IL6 and TNFα). In conclusion, our results confirmed that fungal melanin is a very effective radioprotector against WBI and the probable mechanisms of radioprotection are due to modulation in pro-survival (ERK) signaling, prevention of oxidative stress and immunomodulation. -- Highlights: ► Melanin showed promising radioprotection under pre and post irradiation condition. ► Melanin protects the hematopoietic system from radiation induced damage. ► Melanin modulates pro-survival pathways, immune system

  1. 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.

  2. 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.

  3. The progress and promise of zebrafish as a model to study mast cells.

    Science.gov (United States)

    Prykhozhij, Sergey V; Berman, Jason N

    2014-09-01

    Immunological and hematological research using the zebrafish (Danio rerio) has significantly advanced our understanding of blood lineage ontology, cellular functions and mechanisms, and provided opportunities for disease modeling. Mast cells are an immunological cell type involved in innate and adaptive immune systems, hypersensitivity reactions and cancer progression. The application of zebrafish to study mast cell biology exploits the developmental and imaging opportunities inherent in this model system to enable detailed genetic and molecular studies of this lineage outside of traditional mammalian models. In this review, we first place the importance of mast cell research in zebrafish into the context of comparative studies of mast cells in other fish species and highlight its advantages due to superior experimental tractability and direct visualization in transparent embryos. We discuss current and future tools for mast cell research in zebrafish and the notable results of using zebrafish for understanding mast cell fate determination and our development of a systemic mastocytosis model.

  4. 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.

  5. 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.

  6. 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.

  7. Chronic Neuroinflammation in Alzheimer’s Disease: New Perspectives on Animal Models and Promising Candidate Drugs

    Directory of Open Access Journals (Sweden)

    Christopher Millington

    2014-01-01

    Full Text Available Chronic neuroinflammation is now considered one of the major factors in the pathogenesis of Alzheimer’s disease (AD. However, the most widely used transgenic AD models (overexpressing mutated forms of amyloid precursor protein, presenilin, and/or tau do not demonstrate the degree of inflammation, neurodegeneration (particularly of the cholinergic system, and cognitive decline that is comparable with the human disease. Hence a more suitable animal model is needed to more closely mimic the resulting cognitive decline and memory loss in humans in order to investigate the effects of neuroinflammation on neurodegeneration. One of these models is the glial fibrillary acidic protein-interleukin 6 (GFAP-IL6 mouse, in which chronic neuroinflammation triggered constitutive expression of the cytokine interleukin-6 (IL-6 in astrocytes. These transgenic mice show substantial and progressive neurodegeneration as well as a decline in motor skills and cognitive function, starting from 6 months of age. This animal model could serve as an excellent tool for drug discovery and validation in vivo. In this review, we have also selected three potential anti-inflammatory drugs, curcumin, apigenin, and tenilsetam, as candidate drugs, which could be tested in this model.

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. Lake Baikal Endemic Sculpins (Cottoidei: A Promising Model to Study Adaptive Plasticity of Blood Cholesterol Metabolism

    Directory of Open Access Journals (Sweden)

    Nikolay P. Sudakov

    2015-08-01

    Full Text Available We analyzed the blood lipid spectra in four closely related sculpin (Cottoidei species endemic to Lake Baikal. These data characterize the Baikal sculpins as a set of model organisms for studying the adaptive plasticity of cholesterol metabolism and also mechanisms of resistance to the development of dyslipidemia and atherosclerosis.

  14. Promises from Afar: A Model of International Student Psychological Contract in Business Education

    Science.gov (United States)

    Bordia, Sarbari; Bordia, Prashant; Restubog, Simon Lloyd D.

    2015-01-01

    Despite their significant presence in western business schools, the needs and experiences of international students have not been adequately reflected in the business education literature. We draw upon psychological contract theory--used to understand employer-employee relationships--to develop a novel theoretical model on the international…

  15. Beyond Boundaries: A Promising New Model for Security and Global Development. Carnegie Results

    Science.gov (United States)

    Theroux, Karen

    2013-01-01

    In 2007, a team of international security experts and researchers at the Henry L. Stimson Center launched an initiative to build an effective model for sustainable nonproliferation of biological, chemical, and nuclear weapons. The project represented an exciting and innovative way of thinking about security: a dual-use approach that operated at…

  16. 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.

  17. 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

  18. 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

  19. 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

  20. Embryonic chicken transplantation is a promising model for studying the invasive behaviour of melanoma cells.

    Directory of Open Access Journals (Sweden)

    Aparna eJayachandran

    2015-02-01

    Full Text Available Epithelial-to-mesenchymal transition is a hallmark event in the metastatic cascade conferring invasive ability to tumor cells. There are ongoing efforts to replicate the physiological events occurring during mobilization of tumor cells in model systems. However, few systems are able to capture these complex in vivo events. The embryonic chicken transplantation model has emerged as a useful system to assess melanoma cells including functions that are relevant to the metastatic process, namely invasion and plasticity. The chicken embryo represents an accessible and economical 3-dimensional in vivo model for investigating melanoma cell invasion as it exploits the ancestral relationship between melanoma and its precursor neural crest cells. We describe a methodology which enables the interrogation of melanoma cell motility within the developing avian embryo. This model involves the injection of melanoma cells into the neural tube of chicken embryos. Melanoma cells are labelled using fluorescent tracker dye, Vybrant DiO, then cultured as hanging drops for 24 hours to aggregate the cells. Groups of approximately 700 cells are placed into the neural tube of chicken embryos prior to the onset of neural crest migration at the hindbrain level (embryonic day 1.5 or trunk level (embryonic day 2.5. Chick embryos are reincubated and analysed after 48 hours for the location of melanoma cells using fluorescent microscopy on whole mounts and cross-sections of the embryos. Using this system, we compared the in vivo invasive behavior of epithelial-like and mesenchymal-like melanoma cells. We report that the developing embryonic microenvironment confers motile abilities to both types of melanoma cells. Hence the embryonic chicken transplantation model has potential to become a valuable tool for in vivo melanoma invasion studies. Importantly, it may provide novel insights into and reveal previously unknown mediators of the metastatic steps of invasion and

  1. Alzheimer's disease in a dish: promises and challenges of human stem cell models.

    Science.gov (United States)

    Young, Jessica E; Goldstein, Lawrence S B

    2012-10-15

    Human pluripotent stem cells can differentiate into disease-relevant cell types, which capture the unique genome of an individual patient and provide insight into pathological mechanisms of human disease. Recently, human stem cell models for Alzheimer's disease (AD), the most common neurodegenerative dementia, have been described. Stem cell-derived neurons from patients with familial and sporadic AD and Down's syndrome recapitulate human disease phenotypes such as amyloid β peptide production, hyperphosphorylation of tau protein and endosomal abnormalities. Treatment of human neurons with small molecules can modulate these phenotypes, demonstrating the utility of this system for drug development and screening. This review will highlight the current AD stem cell models and discuss the remaining challenges and potential future directions of this field.

  2. A brief look at model-based dose calculation principles, practicalities, and promise.

    Science.gov (United States)

    Sloboda, Ron S; Morrison, Hali; Cawston-Grant, Brie; Menon, Geetha V

    2017-02-01

    Model-based dose calculation algorithms (MBDCAs) have recently emerged as potential successors to the highly practical, but sometimes inaccurate TG-43 formalism for brachytherapy treatment planning. So named for their capacity to more accurately calculate dose deposition in a patient using information from medical images, these approaches to solve the linear Boltzmann radiation transport equation include point kernel superposition, the discrete ordinates method, and Monte Carlo simulation. In this overview, we describe three MBDCAs that are commercially available at the present time, and identify guidance from professional societies and the broader peer-reviewed literature intended to facilitate their safe and appropriate use. We also highlight several important considerations to keep in mind when introducing an MBDCA into clinical practice, and look briefly at early applications reported in the literature and selected from our own ongoing work. The enhanced dose calculation accuracy offered by a MBDCA comes at the additional cost of modelling the geometry and material composition of the patient in treatment position (as determined from imaging), and the treatment applicator (as characterized by the vendor). The adequacy of these inputs and of the radiation source model, which needs to be assessed for each treatment site, treatment technique, and radiation source type, determines the accuracy of the resultant dose calculations. Although new challenges associated with their familiarization, commissioning, clinical implementation, and quality assurance exist, MBDCAs clearly afford an opportunity to improve brachytherapy practice, particularly for low-energy sources.

  3. A brief look at model-based dose calculation principles, practicalities, and promise

    Directory of Open Access Journals (Sweden)

    Ron S. Sloboda

    2017-02-01

    Full Text Available Model-based dose calculation algorithms (MBDCAs have recently emerged as potential successors to the highly practical, but sometimes inaccurate TG-43 formalism for brachytherapy treatment planning. So named for their capacity to more accurately calculate dose deposition in a patient using information from medical images, these approaches to solve the linear Boltzmann radiation transport equation include point kernel superposition, the discrete ordinates method, and Monte Carlo simulation. In this overview, we describe three MBDCAs that are commercially available at the present time, and identify guidance from professional societies and the broader peer-reviewed literature intended to facilitate their safe and appropriate use. We also highlight several important considerations to keep in mind when introducing an MBDCA into clinical practice, and look briefly at early applications reported in the literature and selected from our own ongoing work. The enhanced dose calculation accuracy offered by a MBDCA comes at the additional cost of modelling the geometry and material composition of the patient in treatment position (as determined from imaging, and the treatment applicator (as characterized by the vendor. The adequacy of these inputs and of the radiation source model, which needs to be assessed for each treatment site, treatment technique, and radiation source type, determines the accuracy of the resultant dose calculations. Although new challenges associated with their familiarization, commissioning, clinical implementation, and quality assurance exist, MBDCAs clearly afford an opportunity to improve brachytherapy practice, particularly for low-energy sources.

  4. Kind discipline: Developing a conceptual model of a promising school discipline approach.

    Science.gov (United States)

    Winkler, Jennifer L; Walsh, Michele E; de Blois, Madeleine; Maré, Jeannette; Carvajal, Scott C

    2017-02-06

    This formative evaluation develops a novel conceptual model for a discipline approach fostering intrinsic motivation and positive relationships in schools. We used concept mapping to elicit and integrate perspectives on kind discipline from teachers, administrators, and other school staff. Three core themes describing kind discipline emerged from 11 identified clusters: (1) proactively developing a positive school climate, (2) responding to conflict with empathy, accountability, and skill, and (3) supporting staff skills in understanding and sharing expectations. We mapped the identified components of kind discipline onto a social ecological model and found that kind discipline encompasses all levels of that model including the individual, relational, environmental/structural, and even community levels. This contrasts with the dominant individual-behavioral discipline approaches that focus on fewer levels and may not lead to sustained student and staff motivation. The findings illustrate the importance of setting and communicating clear expectations and the need for them to be collaboratively developed. Products of the analysis and synthesis reported here are operationalized materials for teachers grounded in a "be kind" culture code for classrooms.

  5. 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.

  6. 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.

  7. 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...

  8. 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....

  9. 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.

  10. Prenatal Alcohol Exposure in Rodents As a Promising Model for the Study of ADHD Molecular Basis

    Science.gov (United States)

    Rojas-Mayorquín, Argelia E.; Padilla-Velarde, Edgar; Ortuño-Sahagún, Daniel

    2016-01-01

    A physiological parallelism, or even a causal effect relationship, can be deducted from the analysis of the main characteristics of the “Alcohol Related Neurodevelopmental Disorders” (ARND), derived from prenatal alcohol exposure (PAE), and the behavioral performance in the Attention-deficit/hyperactivity disorder (ADHD). These two clinically distinct disease entities, exhibits many common features. They affect neurological shared pathways, and also related neurotransmitter systems. We briefly review here these parallelisms, with their common and uncommon characteristics, and with an emphasis in the subjacent molecular mechanisms of the behavioral manifestations, that lead us to propose that PAE in rats can be considered as a suitable model for the study of ADHD. PMID:28018163

  11. The promise of performative: Relational, genetic and scripted models in architectural design

    Directory of Open Access Journals (Sweden)

    Stojanovic Đorđe

    2013-01-01

    Full Text Available This paper investigates the role of performative models within the context of architectural design. Understanding the performances of the built environment can be postulated in rather different manners. It is commonly expected that the built environment complies with the diverse and changing requirements of its users. It is equally required that buildings are economically constructed, easily maintained, energy efficient, safe and aesthetically pleasing. Yet, such expectations are complex and consist of a great number of intertwined effects that are not easy to synchronize during architectural design process. Although they can be precisely evaluated and quantitatively expressed, the values specifying the performances, such as temperature, humidity and intensity of light or sound, in traditionally established course of architectural design are usually only considered throughout the post-rationalization or correction of the architectural design. The research presented in this paper explores design mechanisms, for direct and formative incorporation of feedback information into the very conception of architectural form.

  12. Translating the WHO 25×25 goals into a UK context: the PROMISE modelling study

    Science.gov (United States)

    Cobiac, Linda J; Scarborough, Peter

    2017-01-01

    Objective Model the impact of targets for obesity, diabetes, raised blood pressure, tobacco use, salt intake, physical inactivity and harmful alcohol use, as outlined in the Global Non-Communicable Disease Action Plan 2013–2020, on mortality and morbidity in the UK population. Design Dynamic population modelling study. Setting UK population. Participants Not available. Main outcome measures Mortality and morbidity (years lived with disability) from non-communicable diseases (NCDs) that are averted or delayed. Probability of achieving a 25% reduction in premature mortality from NCDs by 2025 (current WHO target) and a 33% reduction by 2030 (proposed target). Results The largest improvements in mortality would be achieved by meeting the obesity target and the largest improvements in morbidity would be achieved by meeting the diabetes target. The UK could achieve the 2025 and 2030 targets for reducing premature mortality with only a little additional preventive effort compared with current practice. Achieving all 7 risk targets could avert a total of 300 000 deaths (95% uncertainty interval 250 000 to 350 000) and 1.3 million years lived with disability (1.2–1.4 million) from NCDs by 2025, with the majority of health gains due to reduced mortality and morbidity from heart disease and stroke, and reduced morbidity from diabetes. Potential reductions in morbidity from depression and in morbidity and mortality from dementia at older ages are also substantial. Conclusions The global premature mortality targets are a potentially achievable goal for countries such as the UK that can capitalise on many decades of effort in prevention and treatment. High morbidity diseases and diseases in later life are not addressed in the Global NCD Action Plan and targets, but must also be considered a priority for prevention in the UK where the population is ageing and the costs of health and social care are rising. PMID:28377390

  13. 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...

  14. 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.

  15. 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)

  16. 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...

  17. Promising anticancer activities of Justicia simplex D. Don. in cellular and animal models.

    Science.gov (United States)

    Joseph, Litty; Aranjani, Jesil Mathew; Pai, K Sreedhara Ranganath; Srinivasan, K K

    2017-03-06

    Justicia simplex D. Don. belonging to the family of Acanthaceae has been traditionally used for treatment of rheumatism, inflammation and bronchitis. The plant is traditionally considered as an anticancer medicine and is used by healers of Karnataka to treat various types of cancers. The present study aims at the elucidation of anticancer activity of various extracts of J. simplex, isolation of its active constituents and assessment of the role in growth inhibition and angiogenesis both in vitro and in vivo. Extracts of J. simplex was evaluated for the in vitro cytotoxic effect by Brine Shrimp Lethality assay, Trypan Blue dye exclusion assay and antiproliferative assay. In vivo cytotoxicity of the extracts were determined by liquid tumor model in Swiss albino mice. Tumor prognosis, metastasis and angiogenesis were assessed by VEGF expression of the solid tumor. Phytochemical analysis afforded the isolation of a compound, the chemical structure of which was established using IR, NMR and TOF-MS spectral method. The compound was also evaluated for the growth inhibitory and angiogenic effects. The petroleum ether extract revealed potent anticancer activity in in vitro and in vivo studies. The anti-angiogenic effect is due to the down regulation of VEGF expression. The growth inhibitory assay revealed that the isolated compound namely triacontanoic ester of 5''-hydroxyjustisolin is responsible for the anticancer activity. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. Promise(s of mesenchymal stem cells as an in vitro model system to depict pre-diabetic/diabetic milieu in WNIN/GR-Ob mutant rats.

    Directory of Open Access Journals (Sweden)

    Soundarya L Madhira

    Full Text Available BACKGROUND: Development of model systems have helped to a large extent, in bridging gap to understand the mechanism(s of disease including diabetes. Interestingly, WNIN/GR-Ob rats (Mutants, established at National Centre for Laboratory Animals (NCLAS of National Institute of Nutrition (NIN, form a suitable model system to study obesity with Type 2 diabetes (T2D demonstrating several secondary complications (cataract, cardiovascular complications, infertility, nephropathy etc. The present study has been carried out to explore the potent application(s of multipotent stem cells such as bone marrow mesenchymal stem cells (BM-MSCs, to portray features of pre-diabetic/T2D vis-à-vis featuring obesity, with impaired glucose tolerance (IGT, hyperinsulinemia (HI and insulin resistance (IR seen with Mutant rats akin to human situation. METHODOLOGY/PRINCIPAL FINDINGS: Primary cultures of BM-MSCs (third passage from Mutants, its lean littermate (Lean and parental control (Control were characterized for: proliferation markers, disease memory to mark obesity/T2D/HI/IR which included phased gene expression studies for adipogenic/pancreatic lineages, inflammatory markers and differentiation ability to form mature adipocytes/Insulin-like cellular aggregates (ILCAs. The data showed that BM-MSCs from Mutant demonstrated a state of disease memory, depicted by an upregulated expression of inflammatory markers (IL-6, TNFα; increased stem cell recruitment (Oct-4, Sox-2 and proliferation rates (CD90+/CD29+, PDA, 'S' phase of cell cycle by FACS and BrdU incorporation; accelerated preadipocyte induction (Dact-1, PPARγ2 with a quantitative increase in mature adipocyte formation (Leptin; ILCAs, which were non-responsive to high glucose did confer the Obese/T2D memory in Mutants. Further, these observations were in compliance with the anthropometric data. CONCLUSIONS: Given the ease of accessibility and availability of MSCs, the present study form the basis to report for

  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. 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.

  5. 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.

  6. 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.

  7. Cameroon mid-level providers offer a promising public health dentistry model

    Directory of Open Access Journals (Sweden)

    Achembong Leo

    2012-11-01

    Full Text Available Background Oral health services are inadequate and unevenly distributed in many developing countries, particularly those in sub-Saharan Africa. Rural areas in these countries and poorer sections of the population in urban areas often do not have access to oral health services mainly because of a significant shortage of dentists and the high costs of care. We reviewed Cameroon’s experience with deploying a mid-level cadre of oral health professionals and the feasibility of establishing a more formal and predictable role for these health workers. We anticipate that a task-shifting approach in the provision of dental care will significantly improve the uneven distribution of oral health services particularly in the rural areas of Cameroon, which is currently served by only 3% of the total number of dentists. Methods The setting of this study was the Cameroon Baptist Convention Health Board (BCHB, which has four dentists and 42 mid-level providers. De-identified data were collected manually from the registries of 10 Baptist Convention clinics located in six of Cameroon’s 10 regions and then entered into an Excel format before importing into STATA. A retrospective abstraction of all entries for patient visits starting October 2010, and going back in time until 1500 visits were extracted from each clinic. Results This study showed that mid-level providers in BCHB clinics are offering a full scope of dental work across the 10 clinics, with the exception of treatment for major facial injuries. Mid-level providers alone performed 93.5% of all extractions, 87.5% of all fillings, 96.5% of all root canals, 97.5% of all cleanings, and 98.1% of all dentures. The dentists also typically played a teaching role in training the mid-level providers. Conclusions The Ministry of Health in Cameroon has an opportunity to learn from the BCHB model to expand access to oral health care across the country. This study shows the benefits of using a simple, workable, low

  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. 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.

  16. 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.

  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. 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

  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

    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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  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

    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.

  11. 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.

  12. 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.

  13. 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)

  14. 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.

  15. [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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. Simulating county-level crop yields in the Conterminous United States using the Community Land Model: The effects of optimizing irrigation and fertilization: IMPROVING CROP YIELD SIMULATIONS IN CLM

    Energy Technology Data Exchange (ETDEWEB)

    Leng, Guoyong [Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park Maryland USA; Zhang, Xuesong [Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park Maryland USA; Huang, Maoyi [Earth System Analysis and Modeling Group, Atmospheric Sciences & Global Change Division, Pacific Northwest National Laboratory, Richland Washington USA; Yang, Qichun [Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park Maryland USA; Rafique, Rashid [Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park Maryland USA; Asrar, Ghassem R. [Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park Maryland USA; Ruby Leung, L. [Earth System Analysis and Modeling Group, Atmospheric Sciences & Global Change Division, Pacific Northwest National Laboratory, Richland Washington USA

    2016-12-19

    fixing nitrogen to meet nitrogen demand, the reduced positive bias to 6.9 Bu/acre (or 21% of the country mean) was mainly attributed to consideration of the dynamic interactions between fertilizer demand and supply. Although large bias remains in terms of the spatial pattern (i.e. high county-level RMSE), mainly due to limited performance over the Western US, our results show that optimizing irrigation and fertilization can lead to promising improvement in crop and soybean yield simulations in terms of the mean and variability especially over the Mid-west corn belt, and subsequent evapotranspiration (ET) estimates. This study demonstrates the CLM4.5 capability for predicting crop yields and their interactions with climate, and highlights the value of continued model improvements and development to understand biogeophysical and biogeochemical impacts of land use and land cover change using an Earth system modeling framework.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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 .

  4. 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.

  5. 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.

  6. 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.

  7. 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)

  8. 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

  9. 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

  10. Using the integrative model of behavioral prediction to identify promising message strategies to promote healthy sleep behavior among college students.

    Science.gov (United States)

    Robbins, Rebecca; Niederdeppe, Jeff

    2015-01-01

    This research used the Integrative Model of Behavioral Prediction (IMBP) to examine cognitive predictors of intentions to engage in healthy sleep behavior among a population of college students. In doing so, we identify promising message strategies to increase healthy sleep behavior during college. In Phase 1, members of a small sample of undergraduates (n = 31) were asked to describe their beliefs about expected outcomes, norms, and perceived behavioral control associated with sleep on an open-ended questionnaire. We analyzed these qualitative responses to create a closed-ended survey about sleep-related attitudes, perceived norms, control beliefs, behavioral intentions, and behavior. In Phase 2, a larger sample of undergraduate students (n = 365) completed the survey. Attitudes and perceived behavioral control were the strongest predictors of both intentions to engage in sleep behavior and self-reported sleep behavior. Control beliefs associated with time management and stress also had substantial room to change, suggesting their potential as message strategies to better promote healthy sleep behavior in college. We conclude with a broader discussion of the study's implications for message design and intervention.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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).

  7. 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.

  8. 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.

  9. Dextran sulfate sodium-induced colitis-associated neoplasia: a promising model for the development of chemopreventive interventions

    Institute of Scientific and Technical Information of China (English)

    Margie Lee CLAPPER; Harry Stanley COOPER; Wen-Chi Lee CHANG

    2007-01-01

    Individuals diagnosed with ulcerative colitis face a significantly increased risk of developing colorectal dysplasia and cancer during their lifetime. To date, little attention has been given to the development of a chemopreventive intervention for this high-risk population. The mouse model of dextran sulfate sodium (DSS) -induced colitis represents an excellent preclinical system in which to both charac-terize the molecular events required for tumor formation in the presence of inflam-marion and assess the ability of select agents to inhibit this process. Cyclic admin-istration of DSS in drinking water results in the establishment of chronic colitis and the development of colorectal dysplasias and cancers with pathological fea-tures that resemble those of human colitis-associated neoplasia. The incidence and multiplicity of lesions observed varies depending on the mouse strain used (ie, Swiss Webster, C57BL/6J, CBA, ICR) and the dose (0.7%-5.0%) and schedule (1-15 cycles with or without a subsequent recovery period) of DSS. The incidence of neoplasia can be increased and its progression to invasive cancer accelerated significantly by administering DSS in combination with a known colon carcinogen(azoxymethane (AOM), 2-amino-3-methylimidazo[4,5-f]quinoline (IQ), 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP)) or iron. More recent induction of colitis-associated neoplasia in genetically defined mouse strains has provided new insight into the role of specific genes (ie, adenomatous polyposis coli (Apc),p53, inducible nitric oxide synthase (iNOS), Msh2) in the development of colitis-associated neoplasias. Emerging data from chemopreventive intervention studies document the efficacy of several agents in inhibiting DSS-induced neoplasia and provide great promise that colitis-associated colorectal neoplasia is a pre-ventable disease.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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...

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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....

  20. 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.

  1. 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.

  2. 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.

  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.

    2016-12-01

    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.

  4. 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

  5. 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...

  6. 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

  7. Infusing BSCS 5E Instructional Model with Multimedia: A Promising Approach to Develop 21st Century Skills

    Science.gov (United States)

    Senan, Divya C.

    2013-01-01

    The full promise of class room learning is dependent on its ability to incorporate 21st century skills in its instructional design, delivery and implementation. In this increasingly competitive global economy, it is not enough for students to acquire subject-level mastery alone. Skills like creative thinking, problem-solving, communication and…

  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. 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.

  11. 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).

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. Promises, promises for neuroscience and law.

    Science.gov (United States)

    Buckholtz, Joshua W; Faigman, David L

    2014-09-22

    Stunning technical advances in the ability to image the human brain have provoked excited speculation about the application of neuroscience to other fields. The 'promise' of neuroscience for law has been touted with particular enthusiasm. Here, we contend that this promise elides fundamental conceptual issues that limit the usefulness of neuroscience for law. Recommendations for overcoming these challenges are offered.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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...

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. Cobalt(II), Nickel(II) and Copper(II) complexes of a tetradentate Schiff base as photosensitizers: Quantum yield of 1O2 generation and its promising role in anti-tumor activity

    Science.gov (United States)

    Pradeepa, S. M.; Bhojya Naik, H. S.; Vinay Kumar, B.; Indira Priyadarsini, K.; Barik, Atanu; Ravikumar Naik, T. R.

    2013-01-01

    In the present investigation, a Schiff base N'1,N'3-bis[(E)-(5-bromo-2-hydroxyphenyl)methylidene]benzene-1,3-dicarbohydrazide and its metal complexes have been synthesized and characterized. The DNA-binding studies were performed using absorption spectroscopy, emission spectra, viscosity measurements and thermal denatuaration studies. The experimental evidence indicated that, the Co(II), Ni(II) and Cu(II) complexes interact with calf thymus DNA through intercalation with an intrinsic binding constant Kb of 2.6 × 104 M-1, 5.7 × 104 M-1 and 4.5 × 104 M-1, respectively and they exhibited potent photodamage abilities on pUC19 DNA, through singlet oxygen generation with quantum yields of 0.32, 0.27 and 0.30 respectively. The cytotoxic activity of the complexes resulted that they act as a potent photosensitizers for photochemical reactions.

  13. Cobalt(II), Nickel(II) and Copper(II) complexes of a tetradentate Schiff base as photosensitizers: Quantum yield of 1O2 generation and its promising role in anti-tumor activity.

    Science.gov (United States)

    Pradeepa, S M; Bhojya Naik, H S; Vinay Kumar, B; Indira Priyadarsini, K; Barik, Atanu; Ravikumar Naik, T R

    2013-01-15

    In the present investigation, a Schiff base N'1,N'3-bis[(E)-(5-bromo-2-hydroxyphenyl)methylidene]benzene-1,3-dicarbohydrazide and its metal complexes have been synthesized and characterized. The DNA-binding studies were performed using absorption spectroscopy, emission spectra, viscosity measurements and thermal denatuaration studies. The experimental evidence indicated that, the Co(II), Ni(II) and Cu(II) complexes interact with calf thymus DNA through intercalation with an intrinsic binding constant Kb of 2.6×10(4) M(-1), 5.7×10(4) M(-1) and 4.5×10(4) M(-1), respectively and they exhibited potent photodamage abilities on pUC19 DNA, through singlet oxygen generation with quantum yields of 0.32, 0.27 and 0.30 respectively. The cytotoxic activity of the complexes resulted that they act as a potent photosensitizers for photochemical reactions.

  14. 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.

  15. 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.

  16. 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

  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.

    modified 9Cr-1Mo can be developed for other materials. 3. Due to the assumptions used to develop the strip-yield model, model predictions are expected to show some scatter, especially in some situations. Several areas of future research are proposed from these conclusions: 1. Alternative methods for predicting fatigue crack growth, especially a constitutive fatigue crack growth model, 2. Continued development of new material models and refinement the existing ones, and 3. Implementation of the present creep-fatigue model as a user-defined subroutine in a finite element solver.

  18. 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

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. 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.

  7. 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

  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. 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.

  10. 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.

  11. Photons, Photosynthesis, and High-Performance Computing: Challenges, Progress, and Promise of Modeling Metabolism in Green Algae

    Energy Technology Data Exchange (ETDEWEB)

    Chang, C. H.; Graf, P.; Alber, D. M.; Kim, K.; Murray, G.; Posewitz, M.; Seibert, M.

    2008-01-01

    The complexity associated with biological metabolism considered at a kinetic level presents a challenge to quantitative modeling. In particular, the relatively sparse knowledge of parameters for enzymes with known kinetic responses is problematic. The possible space of these parameters is of high-dimension, and sampling of such a space typifies a combinatorial explosion of possible dynamic states. However, with sufficient quantitative transcriptomics, proteomics, and metabolomics data at hand, these challenges could be met by high-performance software with sampling, fitting, and optimization capabilities. With this in mind, we present the High-Performance Systems Biology Toolkit HiPer SBTK, an evolving software package to simulate, fit, and optimize metabolite concentrations and fluxes within the space of rate and binding parameters associated with detailed enzyme kinetic models. We present our chosen modeling paradigm for the formulation of metabolic pathway models, the means to address the challenge of representing such models in a precise and persistent fashion using the standardized Systems Biology Markup Language, and our second-generation model of H2-associated Chlamydomonas metabolism. Processing of such models for hierarchically parallelized simulation and optimization, job specification by the user through a GUI interface, software capabilities and initial scaling data, and the mapping of the computation to biological questions is also discussed. Moreover, we present near-term future software and model development goals.

  12. 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)

  13. 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.

  14. 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.

  15. 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

  16. 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.)

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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...

  3. 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.

  4. 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

  5. Promises in Different Cultures

    Institute of Scientific and Technical Information of China (English)

    Holly Shi

    2001-01-01

    This paper reports a pilot study, which examines culture differences in a social function of language, i.e.,the function of promise making using Searle′s constitutive rules. It is to argue that different cultures may have the same type of speech-act such as promise, which, however, represents different cultural concepts. Evidence supporting the argument was drawn from a comparison of performance of Americans and Orientals concerning their respective concepts of promise making.

  6. 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.

  7. 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

  8. 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

  9. Experimental studies of heat exchange for sodium boiling in the fuel assembly model: Safety substantiation of a promising fast reactor

    Science.gov (United States)

    Khafizov, R. R.; Poplavskii, V. M.; Rachkov, V. I.; Sorokin, A. P.; Trufanov, A. A.; Ashurko, Yu. M.; Volkov, A. V.; Ivanov, E. F.; Privezentsev, V. V.

    2017-01-01

    Numerical simulation of the ULOF-type accident development in a fast reactor with sodium coolant performed using the COREMELT code indicates that sodium boiling in the active core takes place. The boiling is accompanied by oscillations of the technological parameters of the reactor installation; these oscillations can go on during several tens of seconds. In this case, it is possible that a stable regime of removal of heat from residual energy release is implemented. The model of the two-phase coolant flow applied in the code has an important effect on the numerical results; that is why this model needs experimental verification. For eliminating the development of an accident resulting in destruction of the active core elements, a structural solution is proposed; the essence of it is the application of the sodium void above the reactor active core. The experimental installation was developed and the heat exchange at sodium boiling in the model fuel assembly of the fast reactor in the regimes of natural and forced circulation in the presence of the sodium void and the top end shield was studied. It was demonstrated that, in the presence of the sodium void, it is possible to provide long-term cooling of the fuel assembly for a thermal flux density on the fuel element simulator surface of up to 140 and 170 kW/m2 in the natural and forced circulation modes, respectively. The obtained data are used for more precise determination of the numerical model of sodium boiling in the fuel assembly and verification of the COREMELT code.

  10. 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.

  11. Comparison and evaluation of experimental mediastinitis models: precolonized foreign body implants and bacterial suspension inoculation seems promising

    Directory of Open Access Journals (Sweden)

    Kose Necmi

    2006-04-01

    Full Text Available Abstract Background Post-sternotomy mediastinitis (PSM is a devastating surgical complication affecting 1–3% of patients that undergo cardiac surgery. Staphylococcus aureus is one of the most commonly encountered bacterial pathogen cultured from mediastinal samples obtained from patients with PSM. A component of the membrane of the gram positive bacteria, lipoteichoic acid, stimulates the blood monocytes and macrophages to secrete cytokines, radicals and nitrogen species leading to oxido-inflammatory damage. This seems to be responsible for the high mortality rate in PSM. For the evaluation of the pathogenesis of infection or for the investigation of alternative treatment models in infection, no standard model of mediastinitis seems to be available. In this study, we evaluated four mediastinitis models in rats. Methods The rats were divided into four groups to form different infection models. Group A: A suspension of 1 × 107 colony-forming units Staphylococcus aureus in 0,5 mL was inoculated from the right second intercostal space into the mediastinum. Group B: A hole was created in the right second intercostal space and a piece of stainless-steel implant with a length of 0.5 cm was inserted into the mediastinum and a suspension of 1 × 107 cfu bacteria in 0,5 mL was administered via the tail vein. Group C: Precolonized stainless-steel implant was inserted into the mediastinum. Group D: Precolonized stainless-steel implant was inserted into the mediastinum and the bacteria suspension was also injected into the mediastinum. On the 10th day, rats were sacrificed and the extension of infection in the mediastenae was evaluated by quantitative cultures. Myeloperoxidase activity (MPO and malondialdehyde (MDA levels were determined in the sera to evaluate the neutrophil activation and assess the inflammatory oxidation. Results The degree of infection in group C and D were 83.3% and 100% respectively (P P Conclusion Infected implants and high

  12. 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

  13. 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

  14. 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...

  15. 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.

  16. 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)

  17. The promise of community-based participatory research for health equity: a conceptual model for bridging evidence with policy.

    Science.gov (United States)

    Cacari-Stone, Lisa; Wallerstein, Nina; Garcia, Analilia P; Minkler, Meredith

    2014-09-01

    Insufficient attention has been paid to how research can be leveraged to promote health policy or how locality-based research strategies, in particular community-based participatory research (CBPR), influences health policy to eliminate racial and ethnic health inequities. To address this gap, we highlighted the efforts of 2 CBPR partnerships in California to explore how these initiatives made substantial contributions to policymaking for health equity. We presented a new conceptual model and 2 case studies to illustrate the connections among CBPR contexts and processes, policymaking processes and strategies, and outcomes. We extended the critical role of civic engagement by those communities that were most burdened by health inequities by focusing on their political participation as research brokers in bridging evidence and policymaking.

  18. Neurodegenerative diseases in a dish: the promise of iPSC technology in disease modeling and therapeutic discovery.

    Science.gov (United States)

    Xie, Y Z; Zhang, R X

    2015-01-01

    The study of stem-cell biology has been a flourishing research area because of its multi-differentiation potential. The emergence of induced pluripotent stem cells (iPSCs) open up the possibility of addressing obstructs, such as the limited cell source, inherent complexity of the human brain, and ethical constrains. Though still at its infancy phase, reprogramming of somatic cells has been demonstrating the ability to enhance in vitro study of neurodegenerative diseases and potential treatment. However, iPSCs would not thoroughly translate to the clinic before limitations are addressed. In this review, by summarizing the recent development of iPSC-based models, we will discuss the feasibility of iPSC technology on relevant diseases depth and illustrate how this new tool applies to drug screening and celluar therapy.

  19. 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.

  20. 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}.

  1. 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.

  2. Methods of modeling TCO residential real estate in the life cycles of buildings as a promising energy efficiency management tool

    Directory of Open Access Journals (Sweden)

    Kulakov Kirill

    2017-01-01

    Full Text Available Building and developing an affordable housing market is a huge challenge for Russia’s national economy. Today, the housing construction industry finds itself in a situation torn by a conflict caused by the simultaneous needs to minimize the housing construction costs in order to make housing more affordable for Russians and to increase the energy efficiency of the housing projects, which is associated with additional costs for developers. To find solutions to this contradictory situation, one needs new theoretical and practical approaches and economic tools. The global economic trend of managing goods and services on the basis of the value of goods and services over the life cycle is also manifested in the construction industry in Russia. The problem of forming a new economic thinking in the housing sector predetermines the perception of the value of housing not only as the price of purchased real estate, but as the equivalent of the total cost of ownership of real estate throughout its life cycle. This approach allows to compensate the initial rise in the cost of construction resulting from the introduction of energy-efficient technologies by savings in the operational phase of the life cycle of the property. In this regard, management of the total cost of real estate ownership based on energy modeling is of high research and practical relevance.

  3. 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.

  4. 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

  5. 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

  6. 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....

  7. 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.

  8. 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.

  9. 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...

  10. 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...

  11. Promise Zones for Applicants

    Data.gov (United States)

    Department of Housing and Urban Development — This tool assists applicants to HUD's Promise Zone initiative prepare data to submit with their application by allowing applicants to draw the exact location of the...

  12. 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

  13. 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.

  14. 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...

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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...

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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...

  10. 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

  11. 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

  12. 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.

  13. 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...

  14. 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.

  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. Promising More Information

    Science.gov (United States)

    2003-01-01

    When NASA needed a real-time, online database system capable of tracking documentation changes in its propulsion test facilities, engineers at Stennis Space Center joined with ECT International, of Brookfield, Wisconsin, to create a solution. Through NASA's Dual-Use Program, ECT developed Exdata, a software program that works within the company's existing Promise software. Exdata not only satisfied NASA s requirements, but also expanded ECT s commercial product line. Promise, ECT s primary product, is an intelligent software program with specialized functions for designing and documenting electrical control systems. An addon to AutoCAD software, Promis e generates control system schematics, panel layouts, bills of material, wire lists, and terminal plans. The drawing functions include symbol libraries, macros, and automatic line breaking. Primary Promise customers include manufacturing companies, utilities, and other organizations with complex processes to control.

  17. Simulation model analysis of the most promising geological sequestration formation candidates in the Rocky Mountain region, USA, with focus on uncertainty assessment

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Si-Yong [Univ. of Utah, Salt Lake City, UT (United States); Zaluski, Wade [Schlumberger Carbon Services, Houston, TX (United States); Will, Robert [Schlumberger Carbon Services, Houston, TX (United States); Eisinger, Chris [Colorado Geological Survey, Golden, CO (United States); Matthews, Vince [Colorado Geological Survey, Golden, CO (United States); McPherson, Brian [Univ. of Utah, Salt Lake City, UT (United States)

    2013-12-31

    The purpose of this report is to report results of reservoir model simulation analyses for forecasting subsurface CO2 storage capacity estimation for the most promising formations in the Rocky Mountain region of the USA. A particular emphasis of this project was to assess uncertainty of the simulation-based forecasts. Results illustrate how local-scale data, including well information, number of wells, and location of wells, affect storage capacity estimates and what degree of well density (number of wells over a fixed area) may be required to estimate capacity within a specified degree of confidence. A major outcome of this work was development of a new workflow of simulation analysis, accommodating the addition of “random pseudo wells” to represent virtual characterization wells.

  18. Simulation model analysis of the most promising geological sequestration formation candidates in the Rocky Mountain region, USA, with focus on uncertainty assessment

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Si-Yong [Univ. of Utah, Salt Lake City, UT (United States); Zaluski, Wade [Schlumberger Carbon Services, Houston, TX (United States); Will, Robert [Schlumberger Carbon Services, Houston, TX (United States); Eisinger, Chris [Colorado Geological Survey, Golden, CO (United States); Matthews, Vince [Colorado Geological Survey, Golden, CO (United States); McPherson, Brian [Univ. of Utah, Salt Lake City, UT (United States)

    2013-12-31

    The purpose of this report is to report results of reservoir model simulation analyses for forecasting subsurface CO2 storage capacity estimation for the most promising formations in the Rocky Mountain region of the USA. A particular emphasis of this project was to assess uncertainty of the simulation-based forecasts. Results illustrate how local-scale data, including well information, number of wells, and location of wells, affect storage capacity estimates and what degree of well density (number of wells over a fixed area) may be required to estimate capacity within a specified degree of confidence. A major outcome of this work was development of a new workflow of simulation analysis, accommodating the addition of “random pseudo wells” to represent virtual characterization wells.

  19. 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.

  20. The promise of dialogue

    DEFF Research Database (Denmark)

    Phillips, Louise Jane

    It has become commonplace to employ dialogue-based approaches in producing and communicating knowledge in diverse fields. Here, “dialogue” has become a buzzword that promises democratic, participatory processes of mutual learning and knowledge co-production. But what does “dialogue” actually entail...... in the fields in which it is practised and how can we analyse those practices in ways that take account of their complexities? The Promise of Dialogue presents a novel theoretical framework for analysing the dialogic turn in the production and communication of knowledge that builds bridges across three research...

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. Is Bitcoin Promising?

    Institute of Scientific and Technical Information of China (English)

    张程程

    2014-01-01

    On 26th Feb. 2014, the biggest Bitcoin trading platform al over the world was of line. It was bankrupt due to data theft. Global Bitcoin players got into a panic. Is Bitcoin promising? Below I wil analyze this question on several aspects, which are Bitcoins’ traits, demerits, and contrasts.

  7. Promising change, delivering continuity

    DEFF Research Database (Denmark)

    Lund, Jens Friis; Sungusia, Eliezeri; Mabele, Mathew Bukhi;

    2017-01-01

    have conceptualized REDD+ as an example of ‘‘green grabbing” and have voiced fears of a potential global rush for land and trees. In this paper we argue that, in practice and up until now, REDD+ resembles longstanding dynamics of the development and conservation industry, where the promise of change...

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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...

  16. [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

  17. 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.

  18. 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.

  19. "The molecule's the thing:" the promise of molecular modeling and dynamic simulations in aiding the prioritization and interpretation of genomic testing results.

    Science.gov (United States)

    Oliver, Gavin R; Zimmermann, Michael T; Klee, Eric W; Urrutia, Raul A

    2016-01-01

    Clinical genomics is now a reality and lies at the heart of individualized medicine efforts. The success of these approaches is evidenced by the increasing volume of publications that report causal links between genomic variants and disease. In spite of early success, clinical genomics currently faces significant challenges in establishing the relevance of the majority of variants identified by next generation sequencing tests. Indeed, the majority of mutations identified are harbored by proteins whose functions remain elusive. Herein we describe the current scenario in genomic testing and in particular the burden of variants of uncertain significance (VUSs). We highlight a role for molecular modeling and molecular dynamic simulations as tools that can significantly increase the yield of information to aid in the evaluation of pathogenicity. Though the application of these methodologies to the interpretation of variants identified by genomic testing is not yet widespread, we predict that an increase in their use will significantly benefit the mission of clinical genomics for individualized medicine.

  20. 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.

  1. 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

  2. Amine-modified SBA-15 and MCF mesoporous molecular sieves as promising sorbents for natural antioxidant. Modeling of caffeic acid adsorption.

    Science.gov (United States)

    Moritz, Michał; Geszke-Moritz, Małgorzata

    2016-04-01

    This work presents a detailed study of caffeic acid adsorption on mesoporous SBA-15 and MCF silicas functionalized with (3-aminopropyl)triethoxysilane (APTES) and 3-[2-(aminoethylamino)propyl]trimethoxysilane (AEAPTMS). Synthesized mesoporous adsorbents were characterized using different analytical techniques such as N2 sorption, XRD, TEM, SEM and FT-IR. The adsorption studies of caffeic acid were conducted in various organic solvents. Moreover, the effect of water content in 2-propanol-water mixture on adsorption efficiency was investigated. The experimental data were best fitted to the Langmuir equation, followed by the Temkin, Dubinin-Radushkevich and Freundlich models. The maximum adsorption capacity values calculated from the Langmuir model demonstrated that SBA-15 and MCF silicas modified with AEAPTMS revealed better adsorption properties toward caffeic acid (192.3 and 161.3mg/g, respectively) as compared to the materials modified with APTES (125.0 and 113.6 mg/g, respectively). The obtained results indicate that both SBA-15 and MCF silicas functionalized with AEAPTMS and APTES are promising materials for the entrapment of caffeic acid.

  3. 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

  4. 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

  5. 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

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. Kinetic Model of Biogas Yield Production from Vinasse at Various Initial pH: Comparison between Modified Gompertz Model and First Order Kinetic Model

    Directory of Open Access Journals (Sweden)

    Budiyono

    2014-04-01

    Full Text Available Anaerobic treatment using anaerobic digestion can convert organic materials of vinasse into biogas. The purpose of this study was modeling kinetic of biogas production using modified Gompertz model and first order kinetic model at variation of initial pH. Substrates were consisted of two kinds of compositions, which were vinasse+rumen (VR and vinasse+rumen+urea (VRU. Initial pH in each substrate was 6, 7 and 8. Degradation process was done in 30 days using batch anaerobic digesters at room temperature. Both, at VR and VRU, initial pH of 7 generated the more total biogas than the others two (initial pH of 6 and 8. Biogas formed at substrate of VRU was more than that at substrate of VR. The best condition was substrate of VRU and initial pH of 7. At best condition, kinetic constants of biogas production model using modified Gompertz were ym (biogas production potential = 6.49 mL/g VS; U (maximum biogas production rate = 1.24 mL/g VS. day; &lambda (minimum time to produce biogas = 1.79 days. Whereas kinetic constants of biogas production model using first order kinetic were ym (biogas production potential = 6.78 mL/g VS; k (biogas production rate = 0.176 /day. The difference between the predicted and measured biogas yield (fitting error was higher with the first-order kinetic model (1.54-7.50% than with the modified Gompertz model (0.76-3.14%.

  11. The past and future of modeling forest dynamics: from growth and yield curves to forest landscape models

    Science.gov (United States)

    Stephen R. Shifley; Hong S. He; Heike Lischke; Wen J. Wang; Wenchi Jin; Eric J. Gustafson; Jonathan R. Thompson; Frank R. Thompson; William D. Dijak; Jian Yang

    2017-01-01

    Context. Quantitative models of forest dynamics have followed a progression toward methods with increased detail, complexity, and spatial extent. Objectives. We highlight milestones in the development of forest dynamics models and identify future research and application opportunities. Methods. We reviewed...

  12. Impacts of Future Climate Change on California Perennial Crop Yields: Model Projections with Climate and Crop Uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Lobell, D; Field, C; Cahill, K; Bonfils, C

    2006-01-10

    Most research on the agricultural impacts of climate change has focused on the major annual crops, yet perennial cropping systems are less adaptable and thus potentially more susceptible to damage. Improved assessments of yield responses to future climate are needed to prioritize adaptation strategies in the many regions where perennial crops are economically and culturally important. These impact assessments, in turn, must rely on climate and crop models that contain often poorly defined uncertainties. We evaluated the impact of climate change on six major perennial crops in California: wine grapes, almonds, table grapes, oranges, walnuts, and avocados. Outputs from multiple climate models were used to evaluate climate uncertainty, while multiple statistical crop models, derived by resampling historical databases, were used to address crop response uncertainties. We find that, despite these uncertainties, climate change in California is very likely to put downward pressure on yields of almonds, walnuts, avocados, and table grapes by 2050. Without CO{sub 2} fertilization or adaptation measures, projected losses range from 0 to >40% depending on the crop and the trajectory of climate change. Climate change uncertainty generally had a larger impact on projections than crop model uncertainty, although the latter was substantial for several crops. Opportunities for expansion into cooler regions are identified, but this adaptation would require substantial investments and may be limited by non-climatic constraints. Given the long time scales for growth and production of orchards and vineyards ({approx}30 years), climate change should be an important factor in selecting perennial varieties and deciding whether and where perennials should be planted.

  13. Modeling of Yield Estimation for The Main Crops in Iran Based on Mechanization Index (hp ha-1

    Directory of Open Access Journals (Sweden)

    K Abbasi

    2014-09-01

    Full Text Available Agricultural mechanization is a method for transiting from traditional agriculture towards industrial and sustainable one. Due to the limitation of natural resources and increasing population we need to have economical production of agricultural crops. For reaching this destination; agricultural mechanization has a remarkable role. So it is necessary to have an extensive view for mechanization, because with the help of mechanization the agricultural inputs such as seeds, fertilizer and even water and soil can effectively be managed for an economical and sustainable production. This study has been carried out in many provinces of Iran. The data of agricultural tractors and cereal combine harvesters were firstly gathered by means of questionnaire. The tractors were categorized in four power levels of less than 45, 45 to 80, 80 to 110, and more than 110 hp. In addition, it was also carried out for cereal combine harvesters; it was in three power levels, i.e. between 100 to 110, 110 to 155 and 155 to 210 horse-power in 3 ages, i.e. less than 13, between 13 to 20, and more than 20 years. Information regarding to cultivation areas, production volume, and yield of main crops gathered from statistics of Ministry of Jihad-e-Agriculture. Then agriculture mechanization level index (hp ha-1 in each province was calculated. Four main crops including irrigated and rain-fed wheat and irrigated and rain-fed barley, which met the required criteria to be used in the model, were statistically analyzed. Correlation analysis was carried out in order to get an effective model between yield of the four main crops in Iran and agriculture mechanization level index. Pearson correlation index showed that there is a direct and significant correlation between these variables. Subsequently, outliers were identified in order to get a model with necessary efficiency to predict the yield through mechanization level index, by scatter diagram and estimating regression lines in 1

  14. Crop monitoring & yield forecasting system based on Synthetic Aperture Radar (SAR) and process-based crop growth model: Development and validation in South and South East Asian Countries

    Science.gov (United States)

    Setiyono, T. D.

    2014-12-01

    Accurate and timely information on rice crop growth and yield helps governments and other stakeholders adapting their economic policies and enables relief organizations to better anticipate and coordinate relief efforts in the wake of a natural catastrophe. Such delivery of rice growth and yield information is made possible by regular earth observation using space-born Synthetic Aperture Radar (SAR) technology combined with crop modeling approach to estimate yield. Radar-based remote sensing is capable of observing rice vegetation growth irrespective of cloud coverage, an important feature given that in incidences of flooding the sky is often cloud-covered. The system allows rapid damage assessment over the area of interest. Rice yield monitoring is based on a crop growth simulation and SAR-derived key information, particularly start of season and leaf growth rate. Results from pilot study sites in South and South East Asian countries suggest that incorporation of SAR data into crop model improves yield estimation for actual yields. Remote-sensing data assimilation into crop model effectively capture responses of rice crops to environmental conditions over large spatial coverage, which otherwise is practically impossible to achieve. Such improvement of actual yield estimates offers practical application such as in a crop insurance program. Process-based crop simulation model is used in the system to ensure climate information is adequately captured and to enable mid-season yield forecast.

  15. Modelling soil erosion and associated sediment yield for small headwater catchments of the Daugava spillway valley, Latvia

    Science.gov (United States)

    Soms, Juris

    2015-04-01

    The accelerated soil erosion by water and associated fine sediment transfer in river catchments has various negative environmental as well as economic implications in many EU countries. Hence, the scientific community had recognized and ranked soil erosion among other environmental problems. Moreover, these matters might worsen in the near future in the countries of the Baltic Region, e.g. Latvia considering the predicted climate changes - more precisely, the increase in precipitation and shortening of return periods of extreme rainfall events, which in their turn will enable formation of surface runoff, erosion and increase of sediment delivery to receiving streams. Thereby it is essential to carry out studies focused on these issues in order to obtain reliable data in terms of both scientific and applied aims, e.g. environmental protection and sustainable management of soils as well as water resources. During the past decades, many of such studies of soil erosion had focused on the application of modelling techniques implemented in a GIS environment, allowing indirectly to estimate the potential soil losses and to quantify related sediment yield. According to research results published in the scientific literature, this approach currently is widely used all over the world, and most of these studies are based on the USLE model and its revised and modified versions. Considering that, the aim of this research was to estimate soil erosion rates and sediment transport under different hydro-climatic conditions in south-eastern Latvia by application of GIS-based modelling. For research purposes, empirical RUSLE model and ArcGIS software were applied, and five headwater catchments were chosen as model territories. The selected catchments with different land use are located in the Daugava spillway valley, which belongs to the upper Daugava River drainage basin. Considering lithological diversity of Quaternary deposits, a variety of soils can be identified, i.e., Stagnic

  16. Simulation of Sediment Yield in a Semi-Arid River Basin under Changing Land Use: An Integrated Approach of Hydrologic Modelling and Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Charles Gyamfi

    2016-11-01

    Full Text Available Intensified human activities over the past decades have culminated in the prevalence of dire environmental consequences of sediment yield resulting mainly from land use changes. Understanding the role that land use changes play in the dynamics of sediment yield would greatly enhance decision-making processes related to land use and water resources management. In this study, we investigated the impacts of land use and cover changes on sediment yield dynamics through an integrated approach of hydrologic modelling and principal component analysis (PCA. A three-phase land use scenario (2000, 2007 and 2013 employing the “fix-changing” method was used to simulate the sediment yield of the Olifants Basin. Contributions in the changes in individual land uses to sediment yield were assessed using the component and pattern matrixes of PCA. Our results indicate that sediment yield dynamics in the study area is significantly attributed to the changes in agriculture, urban and forested lands. Changes in agriculture and urban lands were directly proportional to sediment yield dynamics of the Olifants Basin. On the contrary, forested areas had a negative relationship with sediment yield indicating less sediment yield from these areas. The output of this research work provides a simplistic approach of evaluating the impacts of land use changes on sediment yield. The tools and methods used are relevant for policy directions on land and water resources planning and management.

  17. The Ancient Maya Landscape: Facing the Challenges and Embracing the Promise of Integrating Archaeology, Remote Sensing, Soil Science and Hydrologic Modeling for Coupled Natural and Human Systems.

    Science.gov (United States)

    Murtha, T., Jr.; Duffy, C.; Cook, B. D.; Schroder, W.; Webster, D.; French, K. D.; Alcover, O.; Golden, C.; Balzotti, C.; Shaffer, D.

    2016-12-01

    Relying on a niche inheritance perspective, this paper discusses the long-term spatial and temporal dynamics of land-use management, agricultural decision making and patterns of resource availability in the tropical lowlands of Central America. We introduce and describe ongoing research that addresses a series of long standing questions about coupled natural and human history dynamics in the Central Maya lowlands, emphasizing the role of landscape and region to address these questions. First, we summarize the results of a CNH pilot study focused on the evolution of the regional landscape of Tikal, Guatemala. Particular attention is centered on how we integrated landscape survey, traditional archaeology and soil studies to understand the spatial and temporal dynamics of agricultural land use and intensification over a two thousand period. Additionally, we discuss how these results were integrated into remote sensing, hydrological and erosion models to better understand how past changes in available water and productive land compare to what we know about settlement patterns in the Tikal Region over that same time period. We not only describe how the Maya transformed this landscape, but also how the region influenced changing patterns of settlement and land use. We finish this section with a discussion of some of the unique challenges integrating archaeological information to study CNH dynamics during this pilot study. Second, we introduce a new project designed to `scale up' the pilot study for a macro-regional analysis of the lowland Maya landscape. The new project leverages a uniquely sampled LIDAR data set designed to refine measurements of above ground carbon storage. Our new project quantitatively examines these data for evidence for past human activity. Preliminary results offer a promising path for tightly integrating archaeology, natural science, remote sensing and modeling for studying CNH dynamics in the deep and recent past.

  18. Modelling Pasture-based Automatic Milking System Herds: The Impact of Large Herd on Milk Yield and Economics

    Directory of Open Access Journals (Sweden)

    M. R. Islam

    2015-07-01

    Full Text Available The aim of this modelling study was to investigate the effect of large herd size (and land areas on walking distances and milking interval (MI, and their impact on milk yield and economic penalties when 50% of the total diets were provided from home grown feed either as pasture or grazeable complementary forage rotation (CFR in an automatic milking system (AMS. Twelve scenarios consisting of 3 AMS herds (400, 600, 800 cows, 2 levels of pasture utilisation (current AMS utilisation of 15.0 t dry matter [DM]/ha, termed as ‘moderate’; optimum pasture utilisation of 19.7 t DM/ha, termed as ‘high’ and 2 rates of incorporation of grazeable complementary forage system (CFS: 0, 30%; CFS = 65% farm is CFR and 35% of farm is pasture were investigated. Walking distances, energy loss due to walking, MI, reduction in milk yield and income loss were calculated for each treatment based on information available in the literature. With moderate pasture utilisation and 0% CFR, increasing the herd size from 400 to 800 cows resulted in an increase in total walking distances between the parlour and the paddock from 3.5 to 6.3 km. Consequently, MI increased from 15.2 to 16.4 h with increased herd size from 400 to 800 cows. High pasture utilisation (allowing for an increased stocking density reduced the total walking distances up to 1 km, thus reduced the MI by up to 0.5 h compared to the moderate pasture, 800 cow herd combination. The high pasture utilisation combined with 30% of the farm in CFR in the farm reduced the total walking distances by up to 1.7 km and MI by up to 0.8 h compared to the moderate pasture and 800 cow herd combination. For moderate pasture utilisation, increasing the herd size from 400 to 800 cows resulted in more dramatic milk yield penalty as yield increasing from c.f. 2.6 and 5.1 kg/cow/d respectively, which incurred a loss of up to $AU 1.9/cow/d. Milk yield losses of 0.61 kg and 0.25 kg for every km increase in total walking distance

  19. Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle

    Science.gov (United States)

    Singh, Ajay; Singh, Avtar; Singh, Manvendra; Prakash, Ved; Ambhore, G. S.; Sahoo, S. K.; Dash, Soumya

    2016-01-01

    A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM) considering different order of Legendre polynomial for the additive genetic effect (4th order) and the permanent environmental effect (5th order). Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11) to 0.99 (TD-4 and TD-5). The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields. PMID:26954137

  20. e-Cow: an animal model that predicts herbage intake, milk yield and live weight change in dairy cows grazing temperate pastures, with and without supplementary feeding.

    Science.gov (United States)

    Baudracco, J; Lopez-Villalobos, N; Holmes, C W; Comeron, E A; Macdonald, K A; Barry, T N; Friggens, N C

    2012-06-01

    This animal simulation model, named e-Cow, represents a single dairy cow at grazing. The model integrates algorithms from three previously published models: a model that predicts herbage dry matter (DM) intake by grazing dairy cows, a mammary gland model that predicts potential milk yield and a body lipid model that predicts genetically driven live weight (LW) and body condition score (BCS). Both nutritional and genetic drives are accounted for in the prediction of energy intake and its partitioning. The main inputs are herbage allowance (HA; kg DM offered/cow per day), metabolisable energy and NDF concentrations in herbage and supplements, supplements offered (kg DM/cow per day), type of pasture (ryegrass or lucerne), days in milk, days pregnant, lactation number, BCS and LW at calving, breed or strain of cow and genetic merit, that is, potential yields of milk, fat and protein. Separate equations are used to predict herbage intake, depending on the cutting heights at which HA is expressed. The e-Cow model is written in Visual Basic programming language within Microsoft Excel®. The model predicts whole-lactation performance of dairy cows on a daily basis, and the main outputs are the daily and annual DM intake, milk yield and changes in BCS and LW. In the e-Cow model, neither herbage DM intake nor milk yield or LW change are needed as inputs; instead, they are predicted by the e-Cow model. The e-Cow model was validated against experimental data for Holstein-Friesian cows with both North American (NA) and New Zealand (NZ) genetics grazing ryegrass-based pastures, with or without supplementary feeding and for three complete lactations, divided into weekly periods. The model was able to predict animal performance with satisfactory accuracy, with concordance correlation coefficients of 0.81, 0.76 and 0.62 for herbage DM intake, milk yield and LW change, respectively. Simulations performed with the model showed that it is sensitive to genotype by feeding environment

  1. Effects of ocean acidification on fishery yields and profits of red king crab in Bristol Bay from model studies (NCEI Accession 0127395)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This archival package contains model output data that were collected to examine the impact of ocean acidification on fishery yields and profits of red king crab in...

  2. Forecasting of cereals yields in a semi-arid area using the agrometeorological model «SAFY» combined to optical SPOT/HRV images

    Science.gov (United States)

    Chahbi, Aicha; Zribi, Mehrez; Lili-Chabaane, Zohra; Mougenot, Bernard

    2015-10-01

    In semi-arid areas, an operational grain yield forecasting system, which could help decision-makers to plan annual imports, is needed. It can be challenging to monitor the crop canopy and production capacity of plants, especially cereals. 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. Remote sensing has demonstrated its strong potential for the monitoring of the vegetation's dynamics and temporal variations. Through the use of a rich database, acquired over a period of two years for more than 60 test fields, and from 20 optical satellite SPOT/HRV images, the aim of the present study is to evaluate the feasibility of two approaches to estimate the dynamics and yields of cereals in the context of semi-arid, low productivity regions in North Africa. The first approach is based on the application of the semi-empirical growth model SAFY "Simple Algorithm For Yield estimation", developed to simulate the dynamics of the leaf area index and the grain yield, at the field scale. The model is able to reproduce the time evolution of the LAI of all fields. However, the yields are under-estimated. Therefore, we developed a new approach to improve the SAFY model. The grain yield is function of LAI area in the growth period between 25 March and 5 April. This approach is robust, the measured and estimated grain yield are well correlated. Finally, this model is used in combination with remotely sensed LAI measurements to estimate yield for the entire studied site.

  3. Quantifying the effect of heat stress on daily milk yield and monitoring dynamic changes using an adaptive dynamic model.

    Science.gov (United States)

    André, G; Engel, B; Berentsen, P B M; Vellinga, Th V; Lansink, A G J M Oude

    2011-09-01

    Automation and use of robots are increasingly being used within dairy farming and result in large amounts of real time data. This information provides a base for the new management concept of precision livestock farming. From 2003 to 2006, time series of herd mean daily milk yield were collected on 6 experimental research farms in the Netherlands. These time series were analyzed with an adaptive dynamic model following a Bayesian method to quantify the effect of heat stress. The effect of heat stress was quantified in terms of critical temperature above which heat stress occurred, duration of heat stress periods, and resulting loss in milk yield. In addition, dynamic changes in level and trend were monitored, including the estimation of a weekly pattern. Monitoring comprised detection of potential outliers and other deteriorations. The adaptive dynamic model fitted the data well; the root mean squared error of the forecasts ranged from 0.55 to 0.99 kg of milk/d. The percentages of potential outliers and signals for deteriorations ranged from 5.5 to 9.7%. The Bayesian procedure for time series analysis and monitoring provided a useful tool for process control. Online estimates (based on past and present only) and retrospective estimates (determined afterward from all data) of level and trend in daily milk yield showed an almost yearly cycle that was in agreement with the calving pattern: most cows calved in winter and early spring versus summer and autumn. Estimated weekly patterns in terms of weekday effects could be related to specific management actions, such as change of pasture during grazing. For the effect of heat stress, the mean estimated critical temperature above which heat stress was expected was 17.8±0.56°C. The estimated duration of the heat stress periods was 5.5±1.03 d, and the estimated loss was 31.4±12.2 kg of milk/cow per year. Farm-specific estimates are helpful to identify management factors like grazing, housing and feeding, that affect the

  4. Modeling sediment yield and phosphorus in the Lake Tahoe basin with the Water Erosion Prediction Project (WEPP) model

    Science.gov (United States)

    Dobre, M.; Brooks, E. S.; Srivastava, A.; Lew, R.; Elliot, W. J.

    2016-12-01

    Lake Tahoe, an alpine lake situated at the border between California and Nevada, has experienced a decrease in water quality during the last 50 years. Similar to lakes in other developed areas, this decrease in water quality is mainly associated with an increase in sediment and nutrient delivery from the surrounding tributaries. The Water Erosion Prediction Project (WEPP) model is a process-based hydrology and erosion model that can be used at both small scales (hillslopes, roads, small parcels, etc.) and large watershed scales to evaluate impacts of management practices and climate change on runoff and erosion. We developed and assessed new approaches in WEPP to simulate streamflow and sediment transport, and added a new routine to estimate phosphorus delivery from five geologically and climatically diverse watersheds in the Lake Tahoe basin. We used readily-available data to spatially distribute soil, climate, and management input files at a subwatershed level. Consistent with the current efforts in the basin to reduce phosphorus transport to the lake, our recent improvements to the model have also focused on enhancing the model with a phosphorus component that allows users to evaluate the effect of forest managements on phosphorus delivery to the lake. The model was run with minimal calibration to assess WEPP's ability as a physically-based model to predict streamflow, sediment, and phosphorus delivery. The performance of the model was examined against 25 years of observed snow water equivalent depth, streamflow, sediment, and phosphorus load data. Close agreement between simulated and observed snow water equivalent, streamflow, the distribution of fine (20 µm) sediments, and phosphorus load was achieved at each of the major watersheds located in the high-precipitation regions of the basin. Sediment load was adequately simulated in the drier watersheds; however, annual streamflow was overestimated. With the exception of the drier eastern region, the model

  5. “The molecule’s the thing:” the promise of molecular modeling and dynamic simulations in aiding the prioritization and interpretation of genomic testing results

    Science.gov (United States)

    Oliver, Gavin R.; Zimmermann, Michael T.; Klee, Eric W.; Urrutia, Raul A.

    2016-01-01

    Clinical genomics is now a reality and lies at the heart of individualized medicine efforts. The success of these approaches is evidenced by the increasing volume of publications that report causal links between genomic variants and disease. In spite of early success, clinical genomics currently faces significant challenges in establishing the relevance of the majority of variants identified by next generation sequencing tests. Indeed, the majority of mutations identified are harbored by proteins whose functions remain elusive. Herein we describe the current scenario in genomic testing and in particular the burden of variants of uncertain significance (VUSs). We highlight a role for molecular modeling and molecular dynamic simulations as tools that can significantly increase the yield of information to aid in the evaluation of pathogenicity. Though the application of these methodologies to the interpretation of variants identified by genomic testing is not yet widespread, we predict that an increase in their use will significantly benefit the mission of clinical genomics for individualized medicine. PMID:27408685

  6. 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.

  7. 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.

  8. Modeling sugar cane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

    Directory of Open Access Journals (Sweden)

    A. Valade

    2014-01-01

    biomass to input parameters on a continental scale across the large regions of intensive sugar cane cultivation in Australia and Brazil. Ten parameters driving most of the uncertainty in the ORCHIDEE-STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate, radiation interception (extinction coefficient, and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting climate-mediated different sensitivities of modeled sugar cane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.

  9. Modeling sugarcane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

    Science.gov (United States)

    Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Caubel, A.; Huth, N.; Marin, F.; Martiné, J.-F.

    2014-06-01

    parameters on a continental scale across the large regions of intensive sugarcane cultivation in Australia and Brazil. The ten parameters driving most of the uncertainty in the ORCHIDEE-STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI) and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold) in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients) in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting different climate-mediated sensitivities of modeled sugarcane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.

  10. Modeling sugar cane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

    Science.gov (United States)

    Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Huth, N.; Marin, F.; Martiné, J.-F.

    2014-01-01

    parameters on a continental scale across the large regions of intensive sugar cane cultivation in Australia and Brazil. Ten parameters driving most of the uncertainty in the ORCHIDEE-STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI) and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold) in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients) in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting climate-mediated different sensitivities of modeled sugar cane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.

  11. Modeling the impacts of climate change and technical progress on the wheat yield in inland China: An autoregressive distributed lag approach.

    Science.gov (United States)

    Zhai, Shiyan; Song, Genxin; Qin, Yaochen; Ye, Xinyue; Lee, Jay

    2017-01-01

    This study aims to evaluate the impacts of climate change and technical progress on the wheat yield per unit area from 1970 to 2014 in Henan, the largest agricultural province in China, using an autoregressive distributed lag approach. The bounded F-test for cointegration among the model variables yielded evidence of a long-run relationship among climate change, technical progress, and the wheat yield per unit area. In the long run, agricultural machinery and fertilizer use both had significantly positive impacts on the per unit area wheat yield. A 1% increase in the aggregate quantity of fertilizer use increased the wheat yield by 0.19%. Additionally, a 1% increase in machine use increased the wheat yield by 0.21%. In contrast, precipitation during the wheat growth period (from emergence to maturity, consisting of the period from last October to June) led to a decrease in the wheat yield per unit area. In the short run, the coefficient of the aggregate quantity of fertilizer used was negative. Land size had a significantly positive impact on the per unit area wheat yield in the short run. There was no significant short-run or long-run impact of temperature on the wheat yield per unit area in Henan Province. The results of our analysis suggest that climate change had a weak impact on the wheat yield, while technical progress played an important role in increasing the wheat yield per unit area. The results of this study have implications for national and local agriculture policies under climate change. To design well-targeted agriculture adaptation policies for the future and to reduce the adverse effects of climate change on the wheat yield, climate change and technical progress factors should be considered simultaneously. In addition, adaptive measures associated with technical progress should be given more attention.

  12. Climate change, crop yields, and undernutrition: development of a model to quantify the impact of climate scenarios on child undernutrition.

    Science.gov (United States)

    Lloyd, Simon J; Kovats, R Sari; Chalabi, Zaid

    2011-12-01

    Global climate change is anticipated to reduce future cereal yields and threaten food security, thus potentially increasing the risk of undernutrition. The causation of undernutrition is complex, and there is a need to develop models that better quantify the potential impacts of climate change on population health. We developed a model for estimating future undernutrition that accounts for food and nonfood (socioeconomic) causes and can be linked to available regional scenario data. We estimated child stunting attributable to climate change in five regions in South Asia and sub-Saharan Africa (SSA) in 2050. We used current national food availability and undernutrition data to parameterize and validate a global model, using a process-driven approach based on estimations of the physiological relationship between a lack of food and stunting. We estimated stunting in 2050 using published modeled national calorie availability under two climate scenarios and a reference scenario (no climate change). We estimated that climate change will lead to a relative increase in moderate stunting of 1-29% in 2050 compared with a future without climate change. Climate change will have a greater impact on rates of severe stunting, which we estimated will increase by 23% (central SSA) to 62% (South Asia). Climate change is likely to impair future efforts to reduce child malnutrition in South Asia and SSA, even when economic growth is taken into account. Our model suggests that to reduce and prevent future undernutrition, it is necessary to both increase food access and improve socioeconomic conditions, as well as reduce greenhouse gas emissions.

  13. Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in Belgium

    Directory of Open Access Journals (Sweden)

    Pierre Coenraets

    1997-01-01

    Full Text Available Comparison of computation time between single-trait and multiple-trait evaluations showed that with the use of the canonicat transformation associated with multiple diagonalization of (covariance matrices, multiple-trait analysis for milk, fat and protein yields is not more expensive than three single-trait analyzes. Rank correlations between breeding values for 54,820 cows with records (for their 1,406 sires estimated with the single-trait and multiple-trait models were over .98 (.99 in fat yield and over .99 (.99 in milk and protein yields. The relative gain expressed as reduction in mean prediction error variance was 3% (1% in milk yield, 6% (3% in fat yield, and .4% (.2% in protein yield for cows (for sires. Relative genetic gains were 3% (1%, 6% (2% and .5% (.2% respectively in milk, fat and protein yields for cows (for sires. The use of multiple-trait models bas therefore the advantages of improved precision and reduced selection bics. Multiple-trait analysis could be extended for the analyzes of test-day records. Results show that this or similar multiple-trait animal model could be implemented immediately in Belgium at low computing cost, using the proposed algorithme and could be the first step to new, more advanced evaluation methods.

  14. BIM: Promises and reality

    Directory of Open Access Journals (Sweden)

    Svetel Igor

    2014-01-01

    Full Text Available The building information modeling - BIM is a technology developed toward creation of computer based information model that encompasses whole building lifecycle. Toward that goal a number of information technology standards have been developed that enable different professions in AEC to cooperatively develop electronic building model. The paper gives overview of essential technologies, discusses their intended purpose, and gives outline of the currently achieved functionality.

  15. Unsupervised invariance learning of transformation sequences in a model of object recognition yields selectivity for non-accidental properties

    Directory of Open Access Journals (Sweden)

    Thomas eSerre

    2015-10-01

    Full Text Available Non-accidental properties (NAPs correspond to image properties that are invariant to changes in viewpoint (e.g., straight vs. curved contours and are distinguished from metric properties (MPs that can change continuously with in-depth object rotation (e.g., aspect ratio, degree of curvature, etc. Behavioral and electrophysiological studies of shape processing have demonstrated greater sensitivity to differences in NAPs than in MPs. However, previous work has shown that such sensitivity is lacking in multiple-views models of object recognition such as textsc{Hmax}. These models typically assume that object processing is based on populations of view-tuned neurons with distributed symmetrical bell-shaped tuning that are modulated at least as much by differences in MPs as in NAPs.Here, we test the hypothesis that unsupervised learning of invariances to object transformations may increase the sensitivity to differences in NAPs vs. MPs in textsc{Hmax}. We collected a database of video sequences with objects slowly rotating in-depth in an attempt to mimic sequences viewed during object manipulation by young children during early developmental stages. We show that unsupervised learning yields shape-tuning in higher stages with greater sensitivity to differences in NAPs vs. MPs in agreement with monkey IT data. Together, these results suggest that greater NAP sensitivity may arise from experiencing different in-depth rotations of objects.

  16. Calculations to support JET neutron yield calibration: Modelling of neutron emission from a compact DT neutron generator

    Science.gov (United States)

    Čufar, Aljaž; Batistoni, Paola; Conroy, Sean; Ghani, Zamir; Lengar, Igor; Milocco, Alberto; Packer, Lee; Pillon, Mario; Popovichev, Sergey; Snoj, Luka

    2017-03-01

    At the Joint European Torus (JET) the ex-vessel fission chambers and in-vessel activation detectors are used as the neutron production rate and neutron yield monitors respectively. In order to ensure that these detectors produce accurate measurements they need to be experimentally calibrated. A new calibration of neutron detectors to 14 MeV neutrons, resulting from deuterium-tritium (DT) plasmas, is planned at JET using a compact accelerator based neutron generator (NG) in which a D/T beam impinges on a solid target containing T/D, producing neutrons by DT fusion reactions. This paper presents the analysis that was performed to model the neutron source characteristics in terms of energy spectrum, angle-energy distribution and the effect of the neutron generator geometry. Different codes capable of simulating the accelerator based DT neutron sources are compared and sensitivities to uncertainties in the generator's internal structure analysed. The analysis was performed to support preparation to the experimental measurements performed to characterize the NG as a calibration source. Further extensive neutronics analyses, performed with this model of the NG, will be needed to support the neutron calibration experiments and take into account various differences between the calibration experiment and experiments using the plasma as a source of neutrons.

  17. Proposed Model of Predicting the Reduced Yield Axial Load of Reinforced Concrete Columns Due to Casting Deficiency Effect

    Directory of Open Access Journals (Sweden)

    Achillopoulou Dimitra

    2014-12-01

    Full Text Available The study deals with the investigation of the effect of casting deficiencies- both experimentally and analytically on axial yield load or reinforced concrete columns. It includes 6 specimens of square section (150x150x500 mm of 24.37 MPa nominal concrete strength with 4 longitudinal steel bars of 8 mm (500 MPa nominal strength with confinement ratio ωc=0.15. Through casting procedure the necessary provisions defined by International Standards were not applied strictly in order to create construction deficiencies. These deficiencies are quantified geometrically without the use of expensive and expertise non-destructive methods and their effect on the axial load capacity of the concrete columns is calibrated trough a novel and simplified prediction model extracted by an experimental and analytical investigation that included 6 specimens. It is concluded that: a even with suitable repair, load reduction up to 22% is the outcome of the initial construction damage presence, b the lower dispersion is noted for the section damage index proposed, c extended damage alters the failure mode to brittle accompanied with longitudinal bars buckling, d the proposed model presents more than satisfying results to the load capacity prediction of repaired columns.

  18. Temperature dependence of the positronium yields in polar and nonpolar pure liquids; an experimental test of a phenomenological model

    Energy Technology Data Exchange (ETDEWEB)

    Levay, B

    2004-08-02

    A phenomenological model describing the temperature dependence of the positronium yields (I{sub Ps}, %) was tested in pure liquids of different polarity. The investigated solvents were: m-xylene (m-Xy) and iso-octane (i-C8) as aromatic and aliphatic nonpolar hydrocarbons, methanol (MeOH), water and dimethyl formamide as polar solvents with and without OH group. Arrhenius type linear relationship predicted by the model for the lnQ vs 1/T function, where Q=(100/I{sub Ps}-1), was found to be valid in all cases. The slopes of the lines correspond to the activation energy differences ({delta}E{sup *}=E{sub rec}-E{sub Ps}) between the two main competing reaction pathways in the positron spur, i.e., solvent recombination (e{sup -} + M{sup +}) and positronium formation (e{sup -} + e{sup +}). The slopes were positive, i.e., {delta}E{sup *}<0 and E{sub rec}

  19. Assessment of water-limited winter wheat yield potential at spatially contrasting sites in Ireland using a simple growth and development model

    Directory of Open Access Journals (Sweden)

    Lynch J.P.

    2017-09-01

    Full Text Available Although Irish winter wheat yields are among the highest globally, increases in the profitability of this crop are required to maintain its economic viability. However, in order to determine if efforts to further increase Irish wheat yields are likely to be successful, an accurate estimation of the yield potential is required for different regions within Ireland. A winter wheat yield potential model (WWYPM was developed, which estimates the maximum water-limited yield achievable, within the confines of current genetic resources and technologies, using parameters for winter wheat growth and development observed recently in Ireland and a minor amount of daily meteorological input (maximum and minimum daily temperature, total daily rainfall and total daily incident radiation. The WWYPM is composed of three processes: (i an estimation of potential green area index, (ii an estimation of light interception and biomass accumulation and (iii an estimation of biomass partitioning to grain yield. Model validation indicated that WWYPM estimations of water-limited yield potential (YPw were significantly related to maximum yields recorded in variety evaluation trials as well as regional average and maximum farm yields, reflecting the model’s sensitivity to alterations in the climatic environment with spatial and seasonal variations. Simulations of YPw for long-term average weather data at 12 sites located at spatially contrasting regions of Ireland indicated that the typical YPw varied between 15.6 and 17.9 t/ha, with a mean of 16.7 t/ha at 15% moisture content. These results indicate that the majority of sites in Ireland have the potential to grow high-yielding crops of winter wheat when the effects of very high rainfall and other stresses such as disease incidence and nutrient deficits are not considered.

  20. High-throughput analysis of chemical components and theoretical ethanol yield of dedicated bioenergy sorghum using dual-optimized partial least squares calibration models.

    Science.gov (United States)

    Li, Meng; Wang, Jun; Du, Fu; Diallo, Boubacar; Xie, Guang Hui

    2017-01-01

    Due to its chemical composition and abundance, lignocellulosic biomass is an attractive feedstock source for global bioenergy production. However, chemical composition variations interfere with the success of any single methodology for efficient bioenergy extraction from diverse lignocellulosic biomass sources. Although chemical component distributions could guide process design, they are difficult to obtain and vary widely among lignocellulosic biomass types. Therefore, expensive and laborious "one-size-fits-all" processes are still widely used. Here, a non-destructive and rapid analytical technology, near-infrared spectroscopy (NIRS) coupled with multivariate calibration, shows promise for addressing these challenges. Recent advances in molecular spectroscopy analysis have led to methodologies for dual-optimized NIRS using sample subset partitioning and variable selection, which could significantly enhance the robustness and accuracy of partial least squares (PLS) calibration models. Using this methodology, chemical components and theoretical ethanol yield (TEY) values were determined for 70 sweet and 77 biomass sorghum samples from six sweet and six biomass sorghum varieties grown in 2013 and 2014 at two study sites in northern China. Chemical components and TEY of the 147 bioenergy sorghum samples were initially analyzed and compared using wet chemistry methods. Based on linear discriminant analysis, a correct classification assignment rate (either sweet or biomass type) of 99.3% was obtained using 20 principal components. Next, detailed statistical analysis demonstrated that partial optimization using sample set partitioning based on joint X-Y distances (SPXY) for sample subset partitioning enhanced the robustness and accuracy of PLS calibration models. Finally, comparisons between five dual-optimized strategies indicated that competitive adaptive reweighted sampling coupled with the SPXY (CARS-SPXY) was the most efficient and effective method for improving

  1. Assessment of future crop yield and agricultural sustainable water use in north china plain using multiple crop models

    Science.gov (United States)

    Huang, G.

    2016-12-01

    Currently, studying crop-water response mechanism has become an important part in the development of new irrigation technology and optimal water allocation in water-scarce regions, which is of great significance to crop growth guidance, sustainable utilization of agricultural water, as well as the sustainable development of regional agriculture. Using multiple crop models(AquaCrop,SWAP,DNDC), this paper presents the results of simulating crop growth and agricultural water consumption of the winter-wheat and maize cropping system in north china plain. These areas are short of water resources, but generates about 23% of grain production for China. By analyzing the crop yields and the water consumption of the traditional flooding irrigation, the paper demonstrates quantitative evaluation of the potential amount of water use that can be reduced by using high-efficient irrigation approaches, such as drip irrigation. To maintain food supply and conserve water resources, the research concludes sustainable irrigation methods for the three provinces for sustainable utilization of agricultural water.

  2. Affine operations plus symmetry yield perception of metric shape with large perspective changes (≥45°): data and model.

    Science.gov (United States)

    Lind, Mats; Lee, Young Lim; Mazanowski, Janusz; Kountouriotis, Georgios K; Bingham, Geoffrey P

    2014-02-01

    G. P. Bingham and M. Lind (2008, Large continuous perspective transformations are necessary and sufficient for accurate perception of metric shape, Perception & Psychophysics, Vol. 70, pp. 524-540) showed that observers could perceive metric shape, given perspective changes ≥ 45° relative to a principal axis of elliptical cylinders. In this article, we tested (a) arbitrary perspective changes of 45°, (b) whether perception gradually improves with more perspective change, (c) speed of rotation, (d) whether this works with other shapes (asymmetric polyhedrons), (e) different slants, and (f) perspective changes >45°. Experiment 1 compared 45° perspective change away from, versus centered on, a principal axis. Observers adjusted an ellipse to match the cross-section of an elliptical cylinder viewed in a stereo-motion display. Experiment 2 tested whether performance would improve gradually with increases in perspective change, or suddenly with a 45° change. We also tested speed of rotation. Experiment 3 tested (a) asymmetric polyhedrons, (b) perspective change beyond 45°, and (c) the effect of slant. The results showed (a) a particular perspective was not required, (b) judgments only improved with ≥ 45° change, (c) speed was not relevant, (d) it worked with asymmetric polyhedrons, (e) slant was not relevant, and (f) judgments remained accurate beyond 45° of change. A model shows how affine operations, together with a symmetry yielded by 45° perspective change, bootstrap perception of metric shape.

  3. Genetic evaluation of milk yield in Alpine goats for the first four lactations using random regression models.

    Science.gov (United States)

    Silva, F G; Torres, R A; Silva, L P; Ventura, H T; Silva, F F; Carneiro, A P S; Nascimento, M; Rodrigues, M T

    2014-12-19

    Random regression models have been used in evaluating test-day milk yield, providing accurate estimates of genetic values in animals. However, herd evaluation with only information from the first lactation may not be the best option from an economic perspective. Other factors should be taken into account, particularly other lactations. Our objective in this study was to analyze the genetic divergence between the first four lactations of Alpine goats. The RENPED software was used to perform descriptive statistics, check for errors in pedigree, recode the data, and for Pearson's and Spearman's correlations. The WOMBAT software was used to estimate the variance components and predict the breeding values. The CALC software was adopted to calculate the percentage of coincidence between the ranking of the animals and the animals kept in common at each lactation evaluation. The results show that selection using only the first lactation in small herds with a low degree of technology can be employed as a palliative measure, in view of the difficulty in evaluating all lactations. However, the selection of breeding goats and the production of catalogues should not be based only on the first lactation, because the results demonstrate inversions in the classification of the best breeders when other lactations are analyzed.

  4. Application of AquaCrop model for yield and irrigation requirement estimation of sugar beet under climate change conditions in Serbia

    Directory of Open Access Journals (Sweden)

    Stričević Ružica J.

    2014-01-01

    Full Text Available Climate change impact on field production may play a great role in strategic planning on soil and water resources management. Therefore, the aim of this work was to find out the impact of climate change on sugar beet yield, irrigation depth variation and water saving practices. AquaCrop model v.4.0 was used for yield and irrigation requirement estimation. Input data for future climatic parameters were obtained from EBU-POM for four scenarios A1B, A2, A1B* and A* (*>CO2, and periods of observation were first (2010-2039; second (2040-2069, and third (2070-2099. Undoubtedly, yield will not be reduced in the first period by any scenario, on the contrary, it might be increased. In the second period, yield reduction was observed in A1B and A2 scenarios, hence without the increment of CO2 in the Vojvodina region, whereas in Central Serbia, yield reduction might be expected even in scenarios of A1B and A2*. Irrigation could ensure yield increment in both regions, provided that an increase is more considerable in Central Serbia, due to lower soil water capacity. Application of optimal irrigation depth yield could be increased by up to 57-97% in Vojvodina and 77-285% in Central Serbia. Lower values are obtained in the first period and the highest in the third period. Applying deficit irrigation, water saving would reduce yield in scenario A2, otherwise to obtain high yield, irrigation depth of 300-500 mm should be ensured in Central Serbia. In the same scenario, 300-420 mm of water for irrigation is needed in Vojvodina, but its water savings could be 80-120 mm, or 20%. In scenario A1B, to obtain high yield, 80 mm could be saved in both regions. [Projekat Ministarstva nauke Republike Srbije, br. TR 37005

  5. Errors and uncertainties introduced by a regional climate model in climate impact assessments: example of crop yield simulations in West Africa

    Science.gov (United States)

    Ramarohetra, Johanna; Pohl, Benjamin; Sultan, Benjamin

    2015-12-01

    The challenge of estimating the potential impacts of climate change has led to an increasing use of dynamical downscaling to produce fine spatial-scale climate projections for impact assessments. In this work, we analyze if and to what extent the bias in the simulated crop yield can be reduced by using the Weather Research and Forecasting (WRF) regional climate model to downscale ERA-Interim (European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis) rainfall and radiation data. Then, we evaluate the uncertainties resulting from both the choice of the physical parameterizations of the WRF model and its internal variability. Impact assessments were performed at two sites in Sub-Saharan Africa and by using two crop models to simulate Niger pearl millet and Benin maize yields. We find that the use of the WRF model to downscale ERA-Interim climate data generally reduces the bias in the simulated crop yield, yet this reduction in bias strongly depends on the choices in the model setup. Among the physical parameterizations considered, we show that the choice of the land surface model (LSM) is of primary importance. When there is no coupling with a LSM, or when the LSM is too simplistic, the simulated precipitation and then the simulated yield are null, or respectively very low; therefore, coupling with a LSM is necessary. The convective scheme is the second most influential scheme for yield simulation, followed by the shortwave radiation scheme. The uncertainties related to the internal variability of the WRF model are also significant and reach up to 30% of the simulated yields. These results suggest that regional models need to be used more carefully in order to improve the reliability of impact assessments.

  6. 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.)

  7. Using Ridge Regression Models to Estimate Grain Yield from Field Spectral Data in Bread Wheat (Triticum Aestivum L. Grown under Three Water Regimes

    Directory of Open Access Journals (Sweden)

    Javier Hernandez

    2015-02-01

    Full Text Available Plant breeding based on grain yield (GY is an expensive and time-consuming method, so new indirect estimation techniques to evaluate the performance of crops represent an alternative method to improve grain yield. The present study evaluated the ability of canopy reflectance spectroscopy at the range from 350 to 2500 nm to predict GY in a large panel (368 genotypes of wheat (Triticum aestivum L. through multivariate ridge regression models. Plants were treated under three water regimes in the Mediterranean conditions of central Chile: severe water stress (SWS, rain fed, mild water stress (MWS; one irrigation event around booting and full irrigation (FI with mean GYs of 1655, 4739, and 7967 kg∙ha−1, respectively. Models developed from reflectance data during anthesis and grain filling under all water regimes explained between 77% and 91% of the GY variability, with the highest values in SWS condition. When individual models were used to predict yield in the rest of the trials assessed, models fitted during anthesis under MWS performed best. Combined models using data from different water regimes and each phenological stage were used to predict grain yield, and the coefficients of determination (R2 increased to 89.9% and 92.0% for anthesis and grain filling, respectively. The model generated during anthesis in MWS was the best at predicting yields when it was applied to other conditions. Comparisons against conventional reflectance indices were made, showing lower predictive abilities. It was concluded that a Ridge Regression Model using a data set based on spectral reflectance at anthesis or grain filling represents an effective method to predict grain yield in genotypes under different water regimes.

  8. Modeling Runoff and Sediments Yields and their Response to Climate Change: Case Study from the Red Sea Coast of Saudi Arabia

    Science.gov (United States)

    Alharbi, T.; Sultan, M.; Ahmed, M.; Sefry, S.; AboAbdallah, M.

    2013-12-01

    Efforts to quantify runoff and sediments yields and to assess the factors controlling their spatial and temporal distribution are often hindered by the paucity of appropriate field data. In this study, we developed and applied an integrated cost-effective approach that takes advantages of the readily available remote sensing datasets to quantify the runoff and sediments yields of the Red Sea costal watersheds, Saudi Arabia. The Soil Water Assessment Tool (SWAT) model was implemented to determine annual runoff and sediment yields, spatially delineate the factors controlling their distribution, and predict their response to climate change. SWAT is a public-domain, Geographic Information System (GIS)-based, spatially-distributed, dynamic model that can simulate watershed scale hydrology and water quality processes. The landuse-landcover GIS layer for the selected watersheds was downloaded and manually updated from the Global Land Cover 2000 (GLC 2000) datasets. Soil data was downloaded from the Harmonized World Soil Database (HWSD) and refined from 1:250,000 scale geologic maps. A 90m digital elevation model (DEM) extracted from Shuttle Radar Topography Mission (STRM) data was used to characterize the watershed boundaries in SWAT. Weather data for model simulations was downloaded from the global weather data for SWAT. Model simulations were performed for the period from 1979 to 2010 for 10 watersheds ranging in areas from 5×103 km2 to 107×103 km2. Preliminary results show an average annual precipitation, runoff, and sediments yields of 78.1 mm (8.3 ×109 m3), 24.5 mm (2.6 ×109 m3), 0.1 ton/ha, respectively for Wadi El Hamd watershed (area: 107×103 km2). Model calibration is being performed by comparing simulated stream flow discharge and sediment yields against measured values. The response of the runoff and sediments yields to the climate change is being estimated using predictions from Community Climate System Model (CCSM) outputs.

  9. A Model for Predicting the Yield Strength Difference between Pipe and Plate of Low-Carbon Microalloyed Steel

    Science.gov (United States)

    Zhang, Wenlong; Ding, Dongyan; Gu, Mingyuan

    2012-12-01

    A combination of finite-element calculation and tension-compression tests was employed to predict the yield strength difference between the pipe and plate of low-carbon microalloyed steel (LCMS) in the production of high-frequency straight bead welding pipes (HFSBWPs). The deformation process was divided into bending, flattening, and tension deformations. The bending and flattening deformations were simulated using a finite-element method in order to obtain circumferential strains at pipe wall positions along the wall thickness. These strains were the transition strains in the subsequent tension-compression-tension and compression-tension tests. The yield stresses (0.5 pct proof stresses) at the pipe wall positions were derived from the obtained stress-strain curves. The average of the obtained yield stresses was taken as the predicted yield strength of the pipes. It is found that the difference between the latter and the strength of the original steel plates is a result of the combined action of the Bauschinger effect and strain hardening caused by bending and reverse bending deformations. It is strongly dependent on the ratio of pipe wall thickness to pipe outer diameter ( T/D ratio). At low T/D ratios, the Bauschinger effect was dominant, resulting in a decreased yield strength. Strain hardening due to work hardening was dominant at higher T/D ratios, resulting in an increased yield strength. The increase in yield strength was greater at the inner pipe walls than at outer ones, indicating that strain hardening is stronger at inner pipe walls. The yield strength differences predicted with the presented approach are comparable with the values obtained from industrial productions of HFSBWPs, indicating that this approach can be used to predict the yield strength difference between pipe and plate of LCMS.

  10. Assessment of AquaCrop model in the simulation of durum wheat (Triticum aestivum L. growth and yield under different water regimes in Tadla- Morocco

    Directory of Open Access Journals (Sweden)

    Bassou BOUAZZAM

    2017-09-01

    Full Text Available Simulation models that clarify the effects of water on crop yield are useful tools for improving farm level water management and optimizing water use efficiency. In this study, AquaCrop was evaluated for Karim genotype which is the main durum winter wheat (Triticum aestivum L. practiced in Tadla. AquaCrop is based on the water-driven growth module, in that transpiration is converted into biomass through a water productivity parameter. The model was calibrated on data from a full irrigation treatment in 2014/15 and validated on other stressed and unstressed treatments including rain-fed conditions in 2014/15 and 2015/16. Results showed that the model provided excellent simulations of canopy cover, biomass and grain yield. Overall, the relationship between observed and modeled wheat grain yield for all treatments combined produced an R2 of 0.79, a mean squared error of 1.01 t ha-1 and an efficiency coefficient of 0.68. The model satisfactory predicted the trend of soil water reserve. Consequently, AquaCrop can be a valuable tool for simulating wheat grain yield in Tadla plain, particularly considering the fact that the model requires a relatively small number of input data. However, the performance of the model has to be fine-tuned under a wider range of conditions.

  11. Evaluation of the AquaCrop model for simulating yield response of winter wheat to water on the southern Loess Plateau of China.

    Science.gov (United States)

    Zhang, Wanhong; Liu, Wenzhao; Xue, Qingwu; Chen, Jie; Han, Xiaoyang

    2013-01-01

    The objective of this study was to evaluate the performance of the FAO-AquaCrop model in winter wheat in the southern Loess Plateau of China. Multi-year field experimental data from 2004 and 2011 were used to calibrate and validate the model for simulating biomass, canopy cover (CC), soil water content, and grain yield under rainfed conditions. The model performance was evaluated using root mean square error (RMSE) and Willmott index of agreement (d) as criteria. The RMSE ranged from 0.16 to 0.38 t/ha for simulating aboveground biomass, 1.87 to 4.15% for CC, 0.50 to 1.44 t/ha for grain yield, and 5.70 to 22.56 mm for soil water content. The d ranged from 0.22 to 0.89, 0.25 to 0.43, 0.36 to 0.62 and 0.95 to 0.98 for aboveground biomass, CC, soil water content and grain yield, respectively. Generally, the model performed better for simulating CC and yield than biomass and soil water content. The results further indicated that AquaCrop is capable of simulating winter wheat yield under rainfed conditions. Further improvement may be needed to capture the variation of different management practices such as fertility and irrigation levels in this region.

  12. 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

  13. 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

  14. The Promises of Biology and the Biology of Promises

    DEFF Research Database (Denmark)

    Lee, Jieun

    2015-01-01

    commitments with differently imagined futures. I argue that promises are constitutive of the stem cell biology, rather than being derivative of it. Since the biological concept of stem cells is predicated on the future that they promise, the biological life of stem cells is inextricably intertwined...... patients’ bodies in anticipation of materializing the promises of stem cell biology, they are produced as a new form of biovaluable. The promises of biology move beyond the closed circuit of scientific knowledge production, and proliferate in the speculative marketplaces of promises. Part II looks at how...... of technologized biology and biological time can appear promising with the backdrop of the imagined intransigence of social, political, and economic order in the Korean society....

  15. The Promises of Biology and the Biology of Promises

    DEFF Research Database (Denmark)

    Lee, Jieun

    2015-01-01

    commitments with differently imagined futures. I argue that promises are constitutive of the stem cell biology, rather than being derivative of it. Since the biological concept of stem cells is predicated on the future that they promise, the biological life of stem cells is inextricably intertwined...... patients’ bodies in anticipation of materializing the promises of stem cell biology, they are produced as a new form of biovaluable. The promises of biology move beyond the closed circuit of scientific knowledge production, and proliferate in the speculative marketplaces of promises. Part II looks at how...... of technologized biology and biological time can appear promising with the backdrop of the imagined intransigence of social, political, and economic order in the Korean society....

  16. Estimating Corporate Yield Curves

    OpenAIRE

    Antionio Diaz; Frank Skinner

    2001-01-01

    This paper represents the first study of retail deposit spreads of UK financial institutions using stochastic interest rate modelling and the market comparable approach. By replicating quoted fixed deposit rates using the Black Derman and Toy (1990) stochastic interest rate model, we find that the spread between fixed and variable rates of interest can be modeled (and priced) using an interest rate swap analogy. We also find that we can estimate an individual bank deposit yield curve as a spr...

  17. Simulation of Wild oat (Avena ludoviciana L. Competition on Winter Wheat (Triticum astivum Growth and Yield. I: Model Description and Validation

    Directory of Open Access Journals (Sweden)

    F Mondani

    2015-09-01

    Full Text Available Crop growth models could stimulate growth and development based on science principles and mathematical equations. They also able to evaluate effects of climate, soil, water and agronomic management practices on crop yield. In the present study, an eco-physiological simulation model developed to assess wild oat damage to winter wheat growth and yield. The general structure of this model is derived from LINTUL1 model which modified to wild oat competition against winter wheat. LINTUL1 model was developed for simulation of spring wheat potential production level. In this study, first, we added development stage (DVS and vernalization to LINTUL1 for simulation of winter wheat growth and development and then the model calibrated for potential production level. Finally, we incorporate harmful effects of wild oat to winter wheat growth and yield. Weather data used as input were average daily minimum and maximum temperature (°C and daily global radiation (MJ m-2 in Mashhad, Iran. Parameter values were derived from the literature. The model is written in Fortran Simulation Translator (FST programming language and then validated based on an experiment data. For these purposes different wild oat plant densities were arranged. The data of this experiment does not use for calibration. The results showed that this model was in general able to simulate the temporal changes in DVS of winter wheat and wild oat, total dry matter (TDM of winter wheat and wild oat and yield loss of wheat due to wild oat competition in all treatments, satisfactorily. Root mean square error (RMSE for winter wheat DVS, wild oat DVS, average winter wheat TDM, average wild oat TDM, and yield loss of winter wheat was 10.4, 14.5, 5.8, 7.6 and 7.5, respectively.

  18. Ecosystem Viable Yields

    CERN Document Server

    De Lara, Michel; Oliveros-Ramos, Ricardo; Tam, Jorge

    2011-01-01

    The World Summit on Sustainable Development (Johannesburg, 2002) encouraged the application of the ecosystem approach by 2010. However, at the same Summit, the signatory States undertook to restore and exploit their stocks at maximum sustainable yield (MSY), a concept and practice without ecosystemic dimension, since MSY is computed species by species, on the basis of a monospecific model. Acknowledging this gap, we propose a definition of "ecosystem viable yields" (EVY) as yields compatible i) with biological viability levels for all time and ii) with an ecosystem dynamics. To the difference of MSY, this notion is not based on equilibrium, but on viability theory, which offers advantages for robustness. For a generic class of multispecies models with harvesting, we provide explicit expressions for the EVY. We apply our approach to the anchovy--hake couple in the Peruvian upwelling ecosystem between the years 1971 and 1981.

  19. 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

  20. 3D classical ensemble modeling of non-sequential double ionization: the dependence of double-ionization yield on the nucleus

    Science.gov (United States)

    Haan, Stanley; Shomsky, Katherine; Danks, Nathan

    2011-05-01

    In 3D classical modeling of non-sequential double ionization, we find that plots of double ionization yield vs laser intensity show strong dependence on an adjustable nuclear softening parameter. We explore why, and uncover chaotic behavior and strong sensitivity to interaction with nucleus in recollision excitation with subsequent photoionization. This work supported by Calvin College ISRI and by NSF grant No. 0969984.

  1. Thermal spike model interpretation of sputtering yield data for Bi thin films irradiated by MeV {sup 84}Kr{sup 15+} ions

    Energy Technology Data Exchange (ETDEWEB)

    Mammeri, S. [Centre de Recherche Nucléaire d’Alger, B.P. 399, 02 Bd. Frantz Fanon, Alger-gare, Algiers (Algeria); Ouichaoui, S., E-mail: souichaoui@gmail.com [Université des Sciences et de la Technologie H. Boumediene (USTHB), Faculté de Physique, Laboratoire SNIRM, B.P. 32, El-Alia, 16111 Bab Ezzouar, Algiers (Algeria); Ammi, H. [Centre de Recherche Nucléaire d’Alger, B.P. 399, 02 Bd. Frantz Fanon, Alger-gare, Algiers (Algeria); Pineda-Vargas, C.A. [iThemba LABS, National Research Foundation, P.O. Box 722, Somerset West 7129 (South Africa); Faculty of Health and Wellness Sciences, CPUT, P.O. Box 1906, Bellville 7535 (South Africa); Dib, A. [Centre de Recherche Nucléaire d’Alger, B.P. 399, 02 Bd. Frantz Fanon, Alger-gare, Algiers (Algeria); Msimanga, M. [iThemba LABS, National Research Foundation, P. Bag 11, Wits 2050, Johannesburg (South Africa); Department of Physics, Tshwane University of Technology, P. Bag X680, Pretoria 001 (South Africa)

    2015-07-01

    A modified thermal spike model initially proposed to account for defect formation in metals within the high heavy ion energy regime is adapted for describing the sputtering of Bi thin films under MeV Kr ions. Surface temperature profiles for both the electronic and atomic subsystems have been carefully evaluated versus the radial distance and time with introducing appropriate values of the Bi target electronic stopping power for multi-charged Kr{sup 15+} heavy ions as well as different target physical proprieties like specific heats and thermal conductivities. Then, the total sputtering yields of the irradiated Bi thin films have been determined from a spatiotemporal integration of the local atomic evaporation rate. Besides, an expected non negligible contribution of elastic nuclear collisions to the Bi target sputtering yields and ion-induced surface effects has also been considered in our calculation. Finally, the latter thermal spike model allowed us to derive numerical sputtering yields in satisfactorily agreement with existing experimental data both over the low and high heavy ion energy regions, respectively, dominated by elastic nuclear collisions and inelastic electronic collisions, in particular with our data taken recently for Bi thin films irradiated by 27.5 MeV Kr{sup 15+} heavy ions. An overall consistency of our model calculation with the predictions of sputtering yield theoretical models within the target nuclear stopping power regime was also pointed out.

  2. How accurately do maize crop models simulate the interactions of atmospheric CO2 concentration levels with limited water supply on water use and yield?

    Science.gov (United States)

    This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration ([CO218 ]) on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thünen Institute in Braunschweig, Germany (Manderscheid et al. 2014). D...

  3. Ecosystem-management-based Management Models of Fast-growing and High-yield Plantation and Its Eco-economic Benefits Analysis

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The paper expounded the basic concept and principles of ecosystem management,and analyzed the state and trend of industrial plantation ecosystem management in other countries.Based on the analysis of typical case studies,the eco-economic benefits were evaluated for the management models of fast-growing and high-yield plantations.

  4. Seasonal forecasts of the SINTEX-F coupled model applied to maize yield and streamflow estimates over north-eastern South Africa

    CSIR Research Space (South Africa)

    Malherbe, J

    2014-07-01

    Full Text Available Forecasts of a Global Coupled Model for austral summer with a 1 month lead are downscaled to end-of-season maize yields and accumulated streamflow over the Limpopo Province and adjacent districts in northeastern South Africa through application...

  5. Using an Active-Optical Sensor to Develop an Optimal NDVI Dynamic Model for High-Yield Rice Production (Yangtze, China).

    Science.gov (United States)

    Liu, Xiaojun; Ferguson, Richard B; Zheng, Hengbiao; Cao, Qiang; Tian, Yongchao; Cao, Weixing; Zhu, Yan

    2017-03-24

    The successful development of an optimal canopy vegetation index dynamic model for obtaining higher yield can offer a technical approach for real-time and nondestructive diagnosis of rice (Oryza sativa L) growth and nitrogen (N) nutrition status. In this study, multiple rice cultivars and N treatments of experimental plots were carried out to obtain: normalized difference vegetation index (NDVI), leaf area index (LAI), above-ground dry matter (DM), and grain yield (GY) data. The quantitative relationships between NDVI and these growth indices (e.g., LAI, DM and GY) were analyzed, showing positive correlations. Using the normalized modeling method, an appropriate NDVI simulation model of rice was established based on the normalized NDVI (RNDVI) and relative accumulative growing degree days (RAGDD). The NDVI dynamic model for high-yield production in rice can be expressed by a double logistic model: RNDVI = ( 1 + e - 15.2829 × ( R A G D D i - 0.1944 ) ) - 1 - ( 1 + e - 11.6517 × ( R A G D D i - 1.0267 ) ) - 1 (R2 = 0.8577**), which can be used to accurately predict canopy NDVI dynamic changes during the entire growth period. Considering variation among rice cultivars, we constructed two relative NDVI (RNDVI) dynamic models for Japonica and Indica rice types, with R2 reaching 0.8764** and 0.8874**, respectively. Furthermore, independent experimental data were used to validate the RNDVI dynamic models. The results showed that during the entire growth period, the accuracy (k), precision (R2), and standard deviation of RNDVI dynamic models for the Japonica and Indica cultivars were 0.9991, 1.0170; 0.9084**, 0.8030**; and 0.0232, 0.0170, respectively. These results indicated that RNDVI dynamic models could accurately reflect crop growth and predict dynamic changes in high-yield crop populations, providing a rapid approach for monitoring rice growth status.

  6. Highly Ordered Graphene Oxide and Reduced Graphene Oxide Based Polymer Nanocomposites: Promise and Limits for Dynamic Impacts Demonstrated in Model Organic Coatings.

    Science.gov (United States)

    Schmelter, Dirk; Hintze-Bruening, Horst

    2016-06-29

    Graphene oxide (GO) dispersed in water has been combined with a mixture of aqueous polymer dispersions and melamine formaldehyde resin (MF). Stable low viscous fluids with no obvious signs of mesoscale ordering at 0.3 wt % yield transparent films with GO loadings up to one weight percent in the form of homogeneously aligned double strands, each comprising few individual layers of the carbon allotrope. While baking of the films at 160 °C results in minor thermal reduction of GO, in situ reduction with excess hydroxylamine (HA) in the presence of the polymer colloids yields stable dispersions in which amphiphilic graphene like flakes temporarily encapsulate gaseous reaction products. Depending on the parameters in the time-temperature domain, the hollow spheres may be transferred into solid material or disassemble during film formation, the latter case providing black, smooth, and transparent films with up to eight magnitudes increased electrical conductivity and an oxygen permeability 30-fold higher compared to the neat polymer matrix. In contrast, GO reduces oxygen permeability by that factor, while water permeability stays unchanged. Thermo-mechanical measurements reveal matrix stiffening by the platelets as well as by HA, the latter via modifying the MF reactivity. Excellent stone chip resistance and ballistic impact tests demonstrate efficient energy dissipation and crack deflection provided by the laminate like morphology of GO based composite. On the contrary, the same material only provides moderate substrate protection in rain erosion tests.

  7. 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)

  8. Application of a modified distributed-dynamic erosion and sediment yield model in a typical watershed of a hilly and gully region, Chinese Loess Plateau

    Science.gov (United States)

    Wu, Lei; Liu, Xia; Ma, Xiaoyi

    2016-11-01

    Soil erosion not only results in the destruction of land resources and the decline of soil fertility, but also contributes to river channel sedimentation. In order to explore the spatiotemporal evolution of erosion and sediment yield before and after returning farmland in a typical watershed of the hilly and gully region (Chinese Loess Plateau), a distributed-dynamic model of sediment yield based on the Chinese Soil Loss Equation (CSLE) was established and modified to assess the effects of hydrological factors and human activities on erosion and sediment yield between 1995 and 2013. Results indicate that (1) the modified model has the characteristics of a simple algorithm, high accuracy, wide practicability and easy expansion, and can be applied to predict erosion and sediment yield in the study area, (2) soil erosion gradations are closely related to the spatial distribution of rainfall erosivity and land use patterns, and the current soil and water conservation measures are not efficient for high rainfall intensities, and (3) the average sediment yield rate before and after model modification in the most recent 5 years (in addition to 2013) is 4574.62 and 1696.1 Mg km-2, respectively, decreasing by about 35.4 and 78.2 % when compared to the early governance (1995-1998). However, in July 2013 the once-in-a-century storm is the most important reason for maximum sediment yield. Results may provide an effective and scientific basis for soil and water conservation planning and ecological construction of the hilly and gully region, Chinese Loess Plateau.

  9. JavaScript promises essentials

    CERN Document Server

    Sarieddine, Rami

    2014-01-01

    If you are a JavaScript developer working with asynchronous operations and want to know more about promises, then this book is ideal for you. Having a detailed explanation of JavaScript promises will be perfect as your next step towards adopting this new standard and using the API in your web and JavaScript applications.

  10. Quantifying the effect of heat stress on daily milk yield and monitoring dynamic changes using an adaptive dynamic model

    NARCIS (Netherlands)

    Andre, G.; Engel, B.; Berentsen, P.B.M.; Vellinga, T.V.; Oude Lansink, A.G.J.M.

    2011-01-01

    Automation and use of robots are increasingly being used within dairy farming and result in large amounts of real time data. This information provides a base for the new management concept of precision livestock farming. From 2003 to 2006, time series of herd mean daily milk yield were collected on

  11. The Myth of Softening behavior of the Cohesive Zone Model Exact derivation of yield drop behavior of wood

    NARCIS (Netherlands)

    Van der Put, T.A.C.M.

    2015-01-01

    It is shown that the postulate of strain softening of the fracture stress is based on the error to regard the nominal stress to be the actual, ultimate stress, at the actual area of the fracture plan. Strain sof-tening called yield drop is elastic unloading of the actual elastic stress at the

  12. Sensitivity of crop yield and N losses in winter wheat to changes in mean and variability of temperature and precipitation in Denmark using the FASSET model

    DEFF Research Database (Denmark)

    Patil, Ravi; Lægdsmand, Mette; Olesen, Jørgen E;

    2012-01-01

    in climate and soil conditions. Scenarios involved changes to (i) mean temperature alone, (ii) mean and variability of temperature, (iii) winter and summer precipitation amounts and (iv) duration of dry and wet series. The model predicted lower grain yield and N uptake in response to increases in mean...... in variability. Larger temperature variability did not affect soil mineral N and N2O emissions, but increased N leaching on coarse sand. Large response in grain yield, N uptake and soil N cycling, and in their variability was predicted when summer precipitation was varied, whereas only N leaching responded...

  13. Search for the standard model Higgs boson in the decay mode H {yields} W{sup +}W{sup -} {yields} l{sup +}{nu}l{sup -}{nu} at the D0 experiment

    Energy Technology Data Exchange (ETDEWEB)

    Penning, Bjoern

    2009-09-07

    A search for for the Standard Model Higgs boson produced via the H to WW({sup *}) to l+l'- process at a center-of-mass energy of {radical}(s)=1.96 TeV with the D0 detector at the Fermilab Tevatron collider is presented. The leptonic final states contain two electrons or a muon and a hadronically decaying tau lepton. A Higgs boson particle with a mass greater than 140 GeV primarily decays into a pair of W-bosons and the leptonic decay channels of the W provide a clear signature. This channel provides the greatest sensitivity to the Higgs at the Tevatron. A data set of 4.2 fb{sup -1} is used. The analysis is combined with other Higgs boson searches, yielding a Higgs boson sensitivity to the Mass range of 160-170 GeV/c{sup 2}. (orig.)

  14. Identification of phosphorus export from low-runoff yielding areas using combined application of high frequency water quality data and MODHMS modelling.

    Science.gov (United States)

    Donn, Michael J; Barron, Olga V; Barr, Anthony D

    2012-06-01

    In basins combining flat-sandy valleys and hilly-bedrock sub-catchments, the assessment of nutrient (phosphorus) exports from low-runoff yielding environments is difficult. To overcome this issue hydrological modelling and high frequency phosphorus measurements were simultaneously employed. A coupled surface water-groundwater interaction model (MODHMS) was used to determine runoff from the low-runoff yielding part of the catchment. The modelling results indicated that the lower catchment contributed less than 10% of annual catchment discharge over a number of weeks during mid-winter. High frequency phosphorus (P) measurements showed a threefold increase in P concentration during this period in 2008, which lasted for 3 weeks. Concentration-discharge analysis suggested that the increase in P concentration was associated with runoff generation processes in the low-runoff yielding sub-catchment. It was estimated that this area contributed 32% of the annual P load though only 2% of total annual discharge in 2008. Both runoff and P contributions occurred during the period when the water table rose to the surface causing inundation. It was shown that the P concentrations in discharge from the low-runoff yielding sub-catchment were similar to those observed in the shallow groundwater layers.

  15. Estimation of rice grain yield from dual-polarization Radarsat-2 SAR data by integrating a rice canopy scattering model and a genetic algorithm

    Science.gov (United States)

    Zhang, Yuan; Yang, Bin; Liu, Xiaohui; Wang, Cuizhen

    2017-05-01

    Fast and accurate estimation of rice yield plays a role in forecasting rice productivity for ensuring regional or national food security. Microwave synthetic aperture radar (SAR) data has been proved to have a great potential for rice monitoring and parameters retrieval. In this study, a rice canopy scattering model (RCSM) was revised and then was applied to simulate the backscatter of rice canopy. The combination of RCSM and genetic algorithm (GA) was proposed for retrieving two important rice parameters relating to grain yield, ear length and ear number density, from a C-band, dual-polarization (HH and HV) Radarsat-2 SAR data. The stability of retrieved results of GA inversion was also evaluated by changing various parameter configurations. Results show that RCSM can effectively simulate backscattering coefficients of rice canopy at HH and HV mode with an error of operational yield estimation.

  16. Neural network-based crop growth model to predict processing tomato yield on a site-specific basis using remotely sensed data

    Science.gov (United States)

    Koller, Michal

    Remote sensing is one of the major data acquisition tools available to rapidly acquire soil and plant related information over a wide area for use in precision agriculture. Green canopy has very specific reflectance characteristics distinguishing it from other materials such as soil and dry vegetative matter. Reflectance values in red (R) and near infra-red (NIR) spectral bands have been widely used for calculating normalized difference vegetation index (NDVI). Many researchers have related NDVI values to plant vigor, water stress, leaf area index (LAI) and/or yield. However, vegetative indices such as NDVI are usually sensitive to background reflectance characteristics. Often soil adjusted vegetation indices (SAVI) are used to minimize the background effect. In this study we have developed a relationship between the processing tomato yield and SAVI based on the R and NIR reflectance. Eight three band (R, NIR and green) aerial images were obtained at approximately two-week intervals during the 2000 processing tomato growing season. These images were analyzed to obtain SAVI values which were in turn related to LAI using regression techniques. A tuned neural network was developed to predict daily LAI values based on the biweekly experimental LAI values derived from aerial images. The coefficients of multiple determination between the actual LAI and neural network predicted LAI values were greater than 0.96 for all 56 grid points. The LAI values were numerically integrated over the whole growing season to obtain cumulative leaf area index days (CLAID). The CLAID values predicted from the neural network correlated very well with experimentally derived CLAID values (coefficient of determination, r2 = 0.83) indicating that the neural network model simulated processing tomato growth well. A crop growth model that was capable of predicting crop yield based on neural network predicted LAI values and CIMIS weather data was developed. Although predicted yield tended to be low

  17. Random regression models to account for the effect of genotype by environment interaction due to heat stress on the milk yield of Holstein cows under tropical conditions.

    Science.gov (United States)

    Santana, Mário L; Bignardi, Annaiza Braga; Pereira, Rodrigo Junqueira; Menéndez-Buxadera, Alberto; El Faro, Lenira

    2016-02-01

    The present study had the following objectives: to compare random regression models (RRM) considering the time-dependent (days in milk, DIM) and/or temperature × humidity-dependent (THI) covariate for genetic evaluation; to identify the effect of genotype by environment interaction (G×E) due to heat stress on milk yield; and to quantify the loss of milk yield due to heat stress across lactation of cows under tropical conditions. A total of 937,771 test-day records from 3603 first lactations of Brazilian Holstein cows obtained between 2007 and 2013 were analyzed. An important reduction in milk yield due to heat stress was observed for THI values above 66 (-0.23 kg/day/THI). Three phases of milk yield loss were identified during lactation, the most damaging one at the end of lactation (-0.27 kg/day/THI). Using the most complex RRM, the additive genetic variance could be altered simultaneously as a function of both DIM and THI values. This model could be recommended for the genetic evaluation taking into account the effect of G×E. The response to selection in the comfort zone (THI ≤ 66) is expected to be higher than that obtained in the heat stress zone (THI > 66) of the animals. The genetic correlations between milk yield in the comfort and heat stress zones were less than unity at opposite extremes of the environmental gradient. Thus, the best animals for milk yield in the comfort zone are not necessarily the best in the zone of heat stress and, therefore, G×E due to heat stress should not be neglected in the genetic evaluation.

  18. 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

  19. Development of an Assimilation Scheme for the Estimation of Drought-Induced Yield Losses Based on Multi-Source Remote Sensing and the AcquaCrop Model

    Science.gov (United States)

    Silvestro, Paolo Cosmo; Casa, Raffaele; Pignatti, Stefano; Castaldi, Fabio; Yang, Hao; Yang, Guijun

    2014-11-01

    In the context of the Dragon-3 Farmland Drought project, our research deals with the development of methods for the assimilation of biophysical variables, estimated from multi-source remote sensing, into the AquaCrop model, in order to estimate the yield losses due to drought both at the farm and at the regional scale. The first part of this project was employed to refine a methodology to obtain maps of leaf area index (LAI), canopy cover (CC), fraction of adsorbed photosynthetically active radiation (FAPAR) and chlorophyll (Cab) from satellite optical data, using algorithms based on the training of artificial neural networks (ANN) on PROSAIL model simulations. In the second part, retrieved values of CC were assimilated into the AquaCrop model using the assimilation method of the Ensemble Kalman Filter to estimate grain wheat yield at the field scale.

  20. A Tracer Method for Computing Type Ia Supernova Yields: Burning Model Calibration, Reconstruction of Thickened Flames, and Verification for Planar Detonations

    CERN Document Server

    Townsley, Dean M; Timmes, F X; Calder, Alan C; Brown, Edward F

    2016-01-01

    We refine our previously introduced parameterized model for explosive carbon-oxygen fusion during thermonuclear supernovae (SN Ia) by adding corrections to post-processing of recorded Lagrangian fluid element histories to obtain more accurate isotopic yields. Deflagration and detonation products are verified for propagation in a uniform density medium. A new method is introduced for reconstructing the temperature-density history within the artificially thick model deflagration front. We obtain better than 5\\% consistency between the electron capture computed by the burning model and yields from post-processing. For detonations, we compare to a benchmark calculation of the structure of driven steady-state planar detonations performed with a large nuclear reaction network and error-controlled integration. We verify that, for steady-state planar detonations down to a density of 5x10^6 g/cc, our post processing matches the major abundances in the benchmark solution typically to better than 10% for times greater t...

  1. Soybean yield estimation by an agrometeorological model in a GIS Produtividade de soja estimada por modelo agrometeorológico num SIG

    Directory of Open Access Journals (Sweden)

    Luciana Miura Sugawara Berka

    2003-01-01

    Full Text Available Agrometeorological models interfaced with the Geographic Information System - GIS are an alternative to simulate and quantify the effect of weather spatial and temporal variability on crop yield. The objective of this work was to adapt and interface an agrometeorological model with a GIS to estimate soybean [Glycine max (L. Merr.] yield. Yield estimates were generated for 144 municipalities in the State of Paraná, Brazil, responsible for 90% of the soybean production in the State, from 1996/1997 to 2000/2001. The model uses agronomical parameters and meteorological data to calculate maximum yield which will be penalized under drought stress. Comparative analyses between the yield estimated by the model and that reported by the Paraná State Department of Agriculture (SEAB were performed using the "t" test for paired observations. For the 1996/1997 year the model overestimated yield by 10.8%, which may be attributed to the occurrence of fungal diseases not considered by the model. For 1997/1998, 1998/1999 and 1999/2000 no differences (P > 0.05 were found between the yield estimated by the model and SEAB's data. For 2000/2001 the model underestimated yield by 10.5% and the cause for this difference needs further investigation. The model interfaced with a GIS is an useful tool to monitor soybean crop during growing season to estimate crop yield.Os modelos agrometeorológicos integrados em Sistemas de Informação Geográfica - SIG são uma alternativa para simular e quantificar o efeito da variabilidade espacial e temporal do clima sobre a produtividade agrícola. O objetivo deste trabalho foi adaptar e integrar um modelo agrometeorológico num SIG para estimar a produtividade da soja [Glycine max (L. Merr.]. Foram geradas estimativas de produtividade para 144 municípios do Estado do Paraná, responsáveis por 90% da produção de soja no Estado, em cinco anos-safra no período de 1996/1997 a 2000/2001. O modelo utiliza parâmetros agronômicos e

  2. Exploring Climate Change Effects on Watershed Sediment Yield and Land Cover-Based Mitigation Measures Using Swat Model, RS and Gis: Case of Cagayan River Basin, Philippines

    Science.gov (United States)

    Principe, J. A.

    2012-07-01

    The impact of climate change in the Philippines was examined in the country's largest basin-the Cagayan River Basin-by predicting its sediment yield for a long period of time. This was done by integrating the Soil and Water Assessment Tool (SWAT) model, Remote Sensing (RS) and Geographic Information System (GIS). A set of Landsat imageries were processed to include an atmospheric correction and a filling procedure for cloud and cloud-shadow infested pixels was used to maximize each downloaded scene for a subsequent land cover classification using Maximum Likelihood classifier. The Shuttle Radar Topography Mission (SRTM)-DEM was used for the digital elevation model (DEM) requirement of the model while ArcGIS™ provided the platform for the ArcSWAT extension, for storing data and displaying spatial data. The impact of climate change was assessed by varying air surface temperature and amount of precipitation as predicted in the Intergovernmental Panel on Climate Change (IPCC) scenarios. A Nash-Sutcliff efficiency (NSE) > 0.4 and coefficient of determination (R2) > 0.5 for both the calibration and validation of the model showed that SWAT model can realistically simulate the hydrological processes in the study area. The model was then utilized for land cover change and climate change analyses and their influence on sediment yield. Results showed a significant relationship exists among the changes in the climate regime, land cover distributions and sediment yield. Finally, the study suggested land cover distribution that can potentially mitigate the serious negative effects of climate change to a regional watershed's sediment yield.

  3. EXPLORING CLIMATE CHANGE EFFECTS ON WATERSHED SEDIMENT YIELD AND LAND COVER-BASED MITIGATION MEASURES USING SWAT MODEL, RS AND GIS: CASE OF CAGAYAN RIVER BASIN, PHILIPPINES

    Directory of Open Access Journals (Sweden)

    J. A. Principe

    2012-07-01

    Full Text Available The impact of climate change in the Philippines was examined in the country's largest basin–the Cagayan River Basin–by predicting its sediment yield for a long period of time. This was done by integrating the Soil and Water Assessment Tool (SWAT model, Remote Sensing (RS and Geographic Information System (GIS. A set of Landsat imageries were processed to include an atmospheric correction and a filling procedure for cloud and cloud-shadow infested pixels was used to maximize each downloaded scene for a subsequent land cover classification using Maximum Likelihood classifier. The Shuttle Radar Topography Mission (SRTM-DEM was used for the digital elevation model (DEM requirement of the model while ArcGIS™ provided the platform for the ArcSWAT extension, for storing data and displaying spatial data. The impact of climate change was assessed by varying air surface temperature and amount of precipitation as predicted in the Intergovernmental Panel on Climate Change (IPCC scenarios. A Nash-Sutcliff efficiency (NSE > 0.4 and coefficient of determination (R2 > 0.5 for both the calibration and validation of the model showed that SWAT model can realistically simulate the hydrological processes in the study area. The model was then utilized for land cover change and climate change analyses and their influence on sediment yield. Results showed a significant relationship exists among the changes in the climate regime, land cover distributions and sediment yield. Finally, the study suggested land cover distribution that can potentially mitigate the serious negative effects of climate change to a regional watershed's sediment yield.

  4. Supersymmetric extension of Hopf maps: N = 4 {sigma}-models and the S{sup 3} {yields} S{sup 2} fibration

    Energy Technology Data Exchange (ETDEWEB)

    Carvalho, L. Faria; Toppan, F., E-mail: leofc@cbpf.b, E-mail: toppan@cbpf.b [Centro Brasileiro de Pesquisas Fisicas (CBPF), Rio de Janeiro, RJ (Brazil); Kuznetsova, Z., E-mail: zhanna.kuznetsova@ufabc.edu.b [Universidade Federal do ABC (UFABC), Santo Andre, SP (Brazil)

    2009-07-01

    We discuss four off-shell N = 4 D = 1 supersymmetry transformations, their associated one-dimensional -models and their mutual relations. They are given by I - the (4, 4){sub lin} linear 'root' supermultiplet (supersymmetric extension of R{sup 4}), II - the (3, 4, 1){sub lin} linear supermultiplet (supersymmetric extension of R3), III - the (3, 4, 1){sub nl} non-linear supermultiplet living on S{sup 3} and IV - the (2, 4, 2){sub nl} non-linear supermultiplet living on S{sup 2}. The I {yields} II map is the supersymmetric extension of the R4 {yields} R3 bilinear map, while the II {yields} IV map is the supersymmetric extension of the S{sup 3} {yields} S{sup 2} first Hopf fibration. The restrictions on the S{sup 3}, S{sup 2} spheres are expressed in terms of the stereo graphic projections. The non-linear supermultiplets, whose super transformations are local differential polynomials, are not equivalent to the linear supermultiplets with the same field content. The -models are determined in terms of an unconstrained pre potential of the target coordinates. The Uniformization Problem requires solving an inverse problem for the pre potential. The basic features of the supersymmetric extension of the second and third Hopf maps are briefly sketched. Finally, the Schur's lemma (i.e. the real, complex or quaternionic property) is extended to all minimal linear supermultiplets up to N {<=} 8. (author)

  5. Development and application of a multiple linear regression model to consider the impact of weekly waste container capacity on the yield from kerbside recycling programmes in Scotland.

    Science.gov (United States)

    Baird, Jim; Curry, Robin; Reid, Tim

    2013-03-01

    This article describes the development and application of a multiple linear regression model to identify how the key elements of waste and recycling infrastructure, namely container capacity and frequency of collection, affect the yield from municipal kerbside recycling programmes. The overall aim of the research was to gain an understanding of the factors affecting the yield from municipal kerbside recycling programmes in Scotland with an underlying objective to evaluate the efficacy of the model as a decision-support tool for informing the design of kerbside recycling programmes. The study isolates the principal kerbside collection service offered by all 32 councils across Scotland, eliminating those recycling programmes associated with flatted properties or multi-occupancies. The results of the regression analysis model have identified three principal factors which explain 80% of the variability in the average yield of the principal dry recyclate services: weekly residual waste capacity, number of materials collected and the weekly recycling capacity. The use of the model has been evaluated and recommendations made on ongoing methodological development and the use of the results in informing the design of kerbside recycling programmes. We hope that the research can provide insights for the further development of methods to optimise the design and operation of kerbside recycling programmes.

  6. A physiological and biophysical model of coppice willow (Salix spp.) production yields for the contiguous USA in current and future climate scenarios.

    Science.gov (United States)

    Wang, Dan; Jaiswal, Deepak; LeBauer, David S; Wertin, Timothy M; Bollero, Germán A; Leakey, Andrew D B; Long, Stephen P

    2015-09-01

    High-performance computing has facilitated development of biomass production models that capture the key mechanisms underlying production at high spatial and temporal resolution. Direct responses to increasing [CO2 ] and temperature are important to long-lived emerging woody bioenergy crops. Fast-growing willow (Salix spp.) within short rotation coppice (SRC) has considerable potential as a renewable biomass source, but performance over wider environmental conditions and under climate change is uncertain. We extended the bioenergy crop modeling platform, BioCro, to SRC willow by adding coppicing and C3 photosynthesis subroutines, and modifying subroutines for perennation, allocation, morphology, phenology and development. Parameterization with measurements of leaf photosynthesis, allocation and phenology gave agreement of modeled with measured yield across 23 sites in Europe and North America. Predictions for the continental USA suggest yields of ≥17 Mg ha(-1)  year(-1) in a 4 year rotation. Rising temperature decreased predicted yields, an effect partially ameliorated by rising [CO2 ]. This model, based on over 100 equations describing the physiological and biophysical mechanisms underlying production, provides a new framework for utilizing mechanism of plant responses to the environment, including future climates. As an open-source tool, it is made available here as a community resource for further application, improvement and adaptation.

  7. Stability and adaptability analysis of rice cultivars using environment-centered yield in two-way ANOVA model

    Directory of Open Access Journals (Sweden)

    D. Sumith De. Z. Abeysiriwardena

    2011-12-01

    Full Text Available Identification of rice varieties with wider adaptability and stability are the important aspects in varietal recommendation to achieve better economic benefits for farmers. Multi locational trails are conducted in different locations / seasons to test and identify the consistently performing varieties in wider environments and location specific high performing varieties. The interaction aspect of varieties with environment is complex and highly variable across locations. Thus, the identifying varieties under these circumstances are difficult for varietal recommendations. However, several methods have been proposed in the recent past with the complex computation requirements. But, the aid of statistical software and other programs capabilities ease the complexity to a large extent. In this study, we employed one of the established techniques called variance component analysis (VCA to make the varietal recommendation for wider adaptability for many varying environments and the location specific recommendations. In this method variety × environment interaction is portioned into components for individual varieties using yield deviation approach. The average effect of variety (environment centered yield deviation - Dk and the stability measure of each variety (variety interaction variance -Sk2 are used make the recommendations. The rice yield data of cultivars of three month maturity duration, cultivated across diverse environments during the 2002/03 wet–season in Sri Lanka was analyzed for making recommendations. Based on the results the variety At581 gave the highest D2ksk value with wide adaptability selected for general recommendation. Varieties Bg305 and At303 also had relatively higher Dk and thus these two can also be selected for general cultivation purpose.

  8. The In Vitro Mass-Produced Model Mycorrhizal Fungus, Rhizophagus irregularis, Significantly Increases Yields of the Globally Important Food Security Crop Cassava

    Science.gov (United States)

    Ceballos, Isabel; Ruiz, Michael; Fernández, Cristhian; Peña, Ricardo

    2013-01-01

    The arbuscular mycorrhizal symbiosis is formed between arbuscular mycorrhizal fungi (AMF) and plant roots. The fungi provide the plant with inorganic phosphate (P). The symbiosis can result in increased plant growth. Although most global food crops naturally form this symbiosis, very few studies have shown that their practical application can lead to large-scale increases in food production. Application of AMF to crops in the tropics is potentially effective for improving yields. However, a main problem of using AMF on a large-scale is producing cheap inoculum in a clean sterile carrier and sufficiently concentrated to cheaply transport. Recently, mass-produced in vitro inoculum of the model mycorrhizal fungus Rhizophagus irregularis became available, potentially making its use viable in tropical agriculture. One of the most globally important food plants in the tropics is cassava. We evaluated the effect of in vitro mass-produced R. irregularis inoculum on the yield of cassava crops at two locations in Colombia. A significant effect of R. irregularis inoculation on yield occurred at both sites. At one site, yield increases were observed irrespective of P fertilization. At the other site, inoculation with AMF and 50% of the normally applied P gave the highest yield. Despite that AMF inoculation resulted in greater food production, economic analyses revealed that AMF inoculation did not give greater return on investment than with conventional cultivation. However, the amount of AMF inoculum used was do