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Sample records for model yielded good

  1. Food for thought: pretty good multispecies yield

    DEFF Research Database (Denmark)

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

    2017-01-01

    MSY principles for marine fisheries management reflect a focus on obtaining continued high catches to provide food and livelihoods for humanity, while not compromising ecosystems. However, maintaining healthy stocks to provide the maximum sustainable yield on a single-species basis does not ensure...... good multidimensional yield to accommodate situations where the yield from a stock affects the ecosystem, economic and social benefits, or sustainability. We demonstrate in a European example that PGMY is a practical concept. As PGMY provides a safe operating space for management that adheres...

  2. Goods Transport Modelling, Vol 1

    DEFF Research Database (Denmark)

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

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

  3. modelling relationship between rainfall variability and yields

    African Journals Online (AJOL)

    yield models should be used for planning and forecasting the yield of millet and sorghum in the study area. Key words: modelling, rainfall, yields, millet, sorghum. INTRODUCTION. Meteorological variables, such as rainfall parameters, temperature, sunshine hours, relative humidity, and wind velocity and soil moisture are.

  4. Learners' Epistemic Criteria for Good Scientific Models

    Science.gov (United States)

    Pluta, William J.; Chinn, Clark A.; Duncan, Ravit Golan

    2011-01-01

    Epistemic criteria are the standards used to evaluate scientific products (e.g., models, evidence, arguments). In this study, we analyzed epistemic criteria for good models generated by 324 middle-school students. After evaluating a range of scientific models, but before extensive instruction or experience with model-based reasoning practices,…

  5. Conceptual Models Core to Good Design

    CERN Document Server

    Johnson, Jeff

    2011-01-01

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

  6. System Model of Daily Sediment Yield

    Science.gov (United States)

    Sharma, T. C.; Dickinson, W. T.

    1980-06-01

    Input-output systems concepts have been applied to the modeling of daily runoff-sediment yield of the Thames River in southern Ontario, Canada. Spectral and correlation techniques have been used to construct a parsimonious model of daily sediment yields. It is shown that a linear discrete dynamic model is possible in terms of the log-transformed daily runoff and sediment yield sequences. The fluvial system of the Thames River watershed exhibits a weak memory on a daily basis, and the noise component corrupting the watershed fluvial system resembles a white noise process.

  7. 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.

  8. Commentary: models of academic-clinical partnerships: goods, better, best.

    Science.gov (United States)

    Pardes, Herbert; Pincus, Harold Alan

    2010-08-01

    Elsewhere in this issue, Ovseiko and colleagues discuss organizational models for emerging academic health science centers (AHSCs) in England. In this commentary, the authors consider the advantages, or "goods," to organizing educational, clinical, and research missions within the AHSC model. Cultivating relationships among the three central missions of academic medicine yields good results for clinicians, trainees, patients, researchers, and communities, but it can also inspire all stakeholders to strive for better results. After outlining some of these benefits of current AHSC models, like those common in the United States, the authors discuss how close collaboration between U.S. and U.K. AHSC leaders could foster sharing of best practices and ultimately lead to better performance at AHSCs-emerging and established-in both nations. Providing excellent health care begins with developing the best organizational models for AHSCs, and identifying and pursuing such models should be a top priority.

  9. Modeling the effects of ozone on soybean growth and yield.

    Science.gov (United States)

    Kobayashi, K; Miller, J E; Flagler, R B; Heck, W W

    1990-01-01

    A simple mechanistic model was developed based on an existing growth model in order to address the mechanisms of the effects of ozone on growth and yield of soybean [Glycine max. (L.) Merr. 'Davis'] and interacting effects of other environmental stresses. The model simulates daily growth of soybean plants using environmental data including shortwave radiation, temperature, precipitation, irrigation and ozone concentration. Leaf growth, dry matter accumulation, water budget, nitrogen input and seed growth linked to senescence and abscission of leaves are described in the model. The effects of ozone are modeled as reduced photosynthate production and accelerated senescence. The model was applied to the open-top chamber experiments in which soybean plants were exposed to ozone under two levels of soil moisture regimes. After calibrating the model to the growth data and seed yield, goodness-of-fit of the model was tested. The model fitted well for top dry weight in the vegetative growth phase and also at maturity. The effect of ozone on seen yield was also described satisfactorily by the model. The simulation showed apparent interaction between the effect of ozone and soil moisture stress on the seed yield. The model revealed that further work is needed concerning the effect of ozone on the senescence process and the consequences of alteration of canopy microclimate by the open-top chambers.

  10. 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.

  11. PREDICTION MODELS OF GRAIN YIELD AND CHARACTERIZATION

    Directory of Open Access Journals (Sweden)

    Narciso Ysac Avila Serrano

    2009-06-01

    Full Text Available With the objective to characterize the grain yield of five cowpea cultivars and to find linear regression models to predict it, a study was developed in La Paz, Baja California Sur, Mexico. A complete randomized blocks design was used. Simple and multivariate analyses of variance were carried out using the canonical variables to characterize the cultivars. The variables cluster per plant, pods per plant, pods per cluster, seeds weight per plant, seeds hectoliter weight, 100-seed weight, seeds length, seeds wide, seeds thickness, pods length, pods wide, pods weight, seeds per pods, and seeds weight per pods, showed significant differences (P≤ 0.05 among cultivars. Paceño and IT90K-277-2 cultivars showed the higher seeds weight per plant. The linear regression models showed correlation coefficients ≥0.92. In these models, the seeds weight per plant, pods per cluster, pods per plant, cluster per plant and pods length showed significant correlations (P≤ 0.05. In conclusion, the results showed that grain yield differ among cultivars and for its estimation, the prediction models showed determination coefficients highly dependable.

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

    Science.gov (United States)

    De Leo, Giulio A; Micheli, Fiorenza

    2015-11-05

    Marine reserves (MRs) are used worldwide as a means of conserving biodiversity and protecting depleted populations. Despite major investments in MRs, their environmental and social benefits have proven difficult to demonstrate and are still debated. Clear expectations of the possible outcomes of MR establishment are needed to guide and strengthen empirical assessments. Previous models show that reserve establishment in overcapitalized, quota-based fisheries can reduce both catch and population abundance, thereby negating fisheries and even conservation benefits. By using a stage-structured, spatially explicit stochastic model, we show that catches under quota-based fisheries that include a network of MRs can exceed maximum sustainable yield (MSY) under conventional quota management if reserves provide protection to old, large spawners that disproportionally contribute to recruitment outside the reserves. Modelling results predict that the net fishery benefit of MRs is lost when gains in fecundity of old, large individuals are small, is highest in the case of sedentary adults with high larval dispersal, and decreases with adult mobility. We also show that environmental variability may mask fishery benefits of reserve implementation and that MRs may buffer against collapse when sustainable catch quotas are exceeded owing to stock overestimation or systematic overfishing. © 2015 The Author(s).

  13. 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.

  14. Comparative Evaluation of Some Crop Yield Prediction Models ...

    African Journals Online (AJOL)

    (1982) to calibrate and test three of the existing yield prediction models using tropical cowpea yieldÐweather data. The models tested were Hanks Model (first and second versions). Stewart Model (first and second versions) and HallÐButcher Model. Three sets of cowpea yield-water use and weather data were collected.

  15. Transportation of Dangerous Goods: Turkey Model

    Directory of Open Access Journals (Sweden)

    Murat Şencan

    2017-12-01

    Full Text Available The shortcomings in the implementation of hazardous substances transport in the world and in our country lead to very serious hazards. These problems lead to life, property and very serious environmental disasters. This is not only a matter of transportation, but also of the chemistry, textile and fuel industries. This study provides information on the legislation on dangerous goods transport in Turkey. It also contains technical information on hazardous substances, following the search of the relevant literature for the province of hazardous goods.

  16. Statistical modelling and deconvolution of yield meter data

    DEFF Research Database (Denmark)

    Tøgersen, Frede Aakmann; Waagepetersen, Rasmus Plenge

    2004-01-01

    This paper considers the problem of mapping spatial variation of yield in a field using data from a yield monitoring system on a combine harvester. The unobserved yield is assumed to be a Gaussian random field and the yield monitoring system data is modelled as a convolution of the yield and an i......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 impulse response function. This results in an unusual spatial covariance structure (depending on the driving pattern of the combine harverster) for the yield monitoring system data. Parameters of the impulse response function and the spatial covariance function of the yield are estimated using maximum...

  17. Alchemy and uncertainty: What good are models?

    Science.gov (United States)

    F.L. Bunnell

    1989-01-01

    Wildlife-habitat models are increasing in abundance, diversity, and use, but symptoms of failure are evident in their application, including misuse, disuse, failure to test, and litigation. Reasons for failure often relate to the different purposes managers and researchers have for using the models to predict and to aid understanding. This paper examines these two...

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

    CERN Multimedia

    Johnson, G

    2002-01-01

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

  19. Comparative Evaluation of Some Crop Yield Prediction Models ...

    African Journals Online (AJOL)

    A computer program was adopted from the work of Hill et al. (1982) to calibrate and test three of the existing yield prediction models using tropical cowpea yieldÐweather data. The models tested were Hanks Model (first and second versions). Stewart Model (first and second versions) and HallÐButcher Model. Three sets of ...

  20. Validation of crop weather models for crop assessment arid yield ...

    African Journals Online (AJOL)

    IRSIS and CRPSM models were used in this study to see how closely they could predict grain yields for selected stations in Tanzania. Input for the models comprised of weather, crop and soil data collected from five selected stations. Simulation results show that IRSIS model tends to over predict grain yields of maize, ...

  1. 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).

  2. 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.

  3. Large-area dry bean yield prediction modeling in Mexico

    Science.gov (United States)

    Given the importance of dry bean in Mexico, crop yield predictions before harvest are valuable for authorities of the agricultural sector, in order to define support for producers. The aim of this study was to develop an empirical model to estimate the yield of dry bean at the regional level prior t...

  4. 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 thickne...... and distribution were varied between SCC types. The results indicate that yield stress of SCC may be predicted using the model.......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...

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

    Energy Technology Data Exchange (ETDEWEB)

    Hewett, J.L. [Stanford Univ., CA (United States)

    1994-12-01

    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 for the parameters in some cases.

  6. Basic model of quality and good practices in neonatal radiography

    International Nuclear Information System (INIS)

    Dias, Janine H.; Goulart, Juliana M.; Lykawka, Rochelle; Bacelar, Alexandre

    2016-01-01

    Neonatal chest radiographs were evaluated and 3 variables were analyzed: collimation, positioning and presence of artifacts. This study is a pilot for develop a model of good practices in radiology, which is in development phase. The index of analyzed radiographs considered inadequate is expressive and it shows the need for a model that may be part of an optimization program to medical exposures. (author)

  7. Fabrication of fluorographene nanosheets with high yield and good quality based on supercritical fluid-phase exfoliation

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Qi; Ji, Yan; Zhang, Danying; Shi, Jia [Nanjing University of Science and Technology, Key Laboratory of Soft Chemistry and Functional Materials, College of Chemical Engineering (China); Xiao, Yinghong, E-mail: yhxiao@njnu.edu.cn [Nanjing Normal University, Jiangsu Collaborative Innovation Center of Biomedical Functional Materials, College of Chemistry and Materials Science (China); Che, Jianfei, E-mail: xiaoche@mail.njust.edu.cn [Nanjing University of Science and Technology, Key Laboratory of Soft Chemistry and Functional Materials, College of Chemical Engineering (China)

    2016-07-15

    This article presents a novel and simple method of supercritical fluid-phase exfoliation to fabricate fluorographene (FG) nanosheets with high yield and good quality. After soaking with supercritical CO{sub 2} and glycol at 10 MPa and 50 °C for 24 h, fluoride graphite powder was exfoliated by the intercalated CO{sub 2} and glycol molecules during an abrupt depressurization step. Here, supercritical CO{sub 2} acted as a penetrant and glycol acted as a “molecular wedge” to exfoliate fluoride graphite very well. The properties of FG nanosheets were detected by TEM, AFM, UV spectra, FTIR, XPS, Raman spectra, and XRD, which show the possibility of producing thickness-controlled FG nanosheets by varying numbers of supercritical CO{sub 2} process and the high yield of pure FG nanosheets of 32 wt%, four times higher than that of the sample treated only by the traditional method of sonication. Its simplicity, high productivity, low cost, and short processing time make this technique suitable for large-scale manufacturing of FG nanosheets.

  8. 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.

  9. NEUROBIOLOGY OF ECONOMIC CHOICE: A GOOD-BASED MODEL

    Science.gov (United States)

    Padoa-Schioppa, Camillo

    2012-01-01

    Traditionally the object of economic theory and experimental psychology, economic choice recently became a lively research focus in systems neuroscience. Here I summarize the emerging results and I propose a unifying model of how economic choice might function at the neural level. Economic choice entails comparing options that vary on multiple dimensions. Hence, while choosing, individuals integrate different determinants into a subjective value; decisions are then made by comparing values. According to the good-based model, the values of different goods are computed independently of one another, which implies transitivity. Values are not learned as such, but rather computed at the time of choice. Most importantly, values are compared within the space of goods, independent of the sensori-motor contingencies of choice. Evidence from neurophysiology, imaging and lesion studies indicates that abstract representations of value exist in the orbitofrontal and ventromedial prefrontal cortices. The computation and comparison of values may thus take place within these regions. PMID:21456961

  10. Global evaluation of a semiempirical model for yield anomalies and application to within-season yield forecasting.

    Science.gov (United States)

    Schauberger, Bernhard; Gornott, Christoph; Wechsung, Frank

    2017-11-01

    Quantifying the influence of weather on yield variability is decisive for agricultural management under current and future climate anomalies. We extended an existing semiempirical modeling scheme that allows for such quantification. Yield anomalies, measured as interannual differences, were modeled for maize, soybeans, and wheat in the United States and 32 other main producer countries. We used two yield data sets, one derived from reported yields and the other from a global yield data set deduced from remote sensing. We assessed the capacity of the model to forecast yields within the growing season. In the United States, our model can explain at least two-thirds (63%-81%) of observed yield anomalies. Its out-of-sample performance (34%-55%) suggests a robust yield projection capacity when applied to unknown weather. Out-of-sample performance is lower when using remote sensing-derived yield data. The share of weather-driven yield fluctuation varies spatially, and estimated coefficients agree with expectations. Globally, the explained variance in yield anomalies based on the remote sensing data set is similar to the United States (71%-84%). But the out-of-sample performance is lower (15%-42%). The performance discrepancy is likely due to shortcomings of the remote sensing yield data as it diminishes when using reported yield anomalies instead. Our model allows for robust forecasting of yields up to 2 months before harvest for several main producer countries. An additional experiment suggests moderate yield losses under mean warming, assuming no major changes in temperature extremes. We conclude that our model can detect weather influences on yield anomalies and project yields with unknown weather. It requires only monthly input data and has a low computational demand. Its within-season yield forecasting capacity provides a basis for practical applications like local adaptation planning. Our study underlines high-quality yield monitoring and statistics as critical

  11. 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.

  12. 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

  13. Model Democracy: Are All Climate Models Equally Good?

    Science.gov (United States)

    Shukla, J.

    2008-05-01

    We compare the ability of IPCC climate models to simulate present climate and their sensitivity to increased greenhouse gases. We find that models with higher fidelity in simulating the present climate produce higher values of global warming due to increased greenhouse gases. We also compare the forecast skill of dynamical seasonal prediction by coupled ocean-atmosphere models and their ability to simulate observed climate. Although all the current generation of coupled models have large error in simulating observed climate, yet the models with higher fidelity have higher skill. We conclude that there is a significant relationship between model fidelity and model sensitivity, and therefore, the IPCC assessments should not accept the concept of model democracy. We further conjecture that inaccuracy of climate models is the most dominant obstacle in both realizing the potential predictability of climate variations, and in providing reliable information on regional climate change. We make some proposals for the future pathways to improve the fidelity of climate models, and to harvest the realizable predictability.

  14. ACCOUNTING MODELS FOR OUTWARD PROCESSING TRANSACTIONS OF GOODS

    Directory of Open Access Journals (Sweden)

    Lucia PALIU-POPA

    2010-09-01

    Full Text Available In modern international trade, a significant expansion is experienced by commercial operations, also including goods outward processing transactions. The motivations for expanding these international economic affairs, which take place in a complex legal framework, consist of: capitalization of the production capacity for some partners, of the brand for others, leading to a significant commercial profit and thus increasing the currency contribution, without excluding the high and complex nature of risks, both in trading and extra-trading. Starting from the content of processing transactions of goods, as part of combined commercial operations and after clarifying the tax matters which affect the entry in the accounts, we shall present models for reflecting in the accounting of an entity established in Romania the operations of outward processing of goods, if the provider of such operations belongs to the extra-Community or Community area

  15. 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.

  16. 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.

  17. Selling Digital Music: Business Models for Public Goods

    OpenAIRE

    Jens Leth Hougaard; Mich Tvede

    2009-01-01

    This paper considers the market for digital music. We claim that the combination of the MP3 format and peer-to-peer networks has made music non-excludable and this feature is essential for the understanding of the economics of the music market. We study optimal business models for selling non-excludable goods and show that despite promising theoretical results, adding just a slight uncertainty about the number of customers has significant negative implications for profitability. Indeed, as th...

  18. Simultaneous growth and yield models for Eucalyptus grandis (Hill ...

    African Journals Online (AJOL)

    Simultaneous stand-level growth and yield models for Eucalyptus grandis in Zimbabwe were developed from Correlated Curve Trend (CCT) and Nelder wheel experiments replicated on five different sites. Nonlinear three-stage least squares method was used to simultaneously fit prediction and projection equations for ...

  19. 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)

  20. Growth and yield models for Eucalyptus grandis grown in Swaziland ...

    African Journals Online (AJOL)

    The aim of this study was to develop a stand-level growth and yield model for short-rotationEucalyptus grandis grown for pulp wood production at Piggs Peak in Swaziland. The data were derived from a Nelder 1a spacing trial established with E. grandis clonal cuttings in 1998 and terminated in 2005. Planting density ...

  1. Local yield stress statistics in model amorphous solids

    Science.gov (United States)

    Barbot, Armand; Lerbinger, Matthias; Hernandez-Garcia, Anier; García-García, Reinaldo; Falk, Michael L.; Vandembroucq, Damien; Patinet, Sylvain

    2018-03-01

    We develop and extend a method presented by Patinet, Vandembroucq, and Falk [Phys. Rev. Lett. 117, 045501 (2016), 10.1103/PhysRevLett.117.045501] to compute the local yield stresses at the atomic scale in model two-dimensional Lennard-Jones glasses produced via differing quench protocols. This technique allows us to sample the plastic rearrangements in a nonperturbative manner for different loading directions on a well-controlled length scale. Plastic activity upon shearing correlates strongly with the locations of low yield stresses in the quenched states. This correlation is higher in more structurally relaxed systems. The distribution of local yield stresses is also shown to strongly depend on the quench protocol: the more relaxed the glass, the higher the local plastic thresholds. Analysis of the magnitude of local plastic relaxations reveals that stress drops follow exponential distributions, justifying the hypothesis of an average characteristic amplitude often conjectured in mesoscopic or continuum models. The amplitude of the local plastic rearrangements increases on average with the yield stress, regardless of the system preparation. The local yield stress varies with the shear orientation tested and strongly correlates with the plastic rearrangement locations when the system is sheared correspondingly. It is thus argued that plastic rearrangements are the consequence of shear transformation zones encoded in the glass structure that possess weak slip planes along different orientations. Finally, we justify the length scale employed in this work and extract the yield threshold statistics as a function of the size of the probing zones. This method makes it possible to derive physically grounded models of plasticity for amorphous materials by directly revealing the relevant details of the shear transformation zones that mediate this process.

  2. Preparation of New 2,3-Diphenylpropenoic Acid Esters – Good Yields Even for the More Hindered Z Isomers

    Directory of Open Access Journals (Sweden)

    István Pálinkó

    2004-03-01

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

  3. 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.

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

    DEFF Research Database (Denmark)

    Murgoci, Agatha

    2013-01-01

    We price vulnerable derivatives -- i.e. derivatives where the counterparty may default. These are basically the derivatives traded on the over-the-counter (OTC) markets. Default is modeled in a structural framework. The technique employed for pricing is good deal bounds (GDBs). The method imposes...... can be obtained. We provide a link between the objective probability measure and the range of potential risk-neutral measures, which has an intuitive economic meaning. We also provide tight pricing bounds for European calls and show how to extend the call formula to pricing other financial products...

  5. MODELLING CHALLENGES TO FORECAST URBAN GOODS DEMAND FOR RAIL

    Directory of Open Access Journals (Sweden)

    Antonio COMI

    2015-12-01

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

  6. Predictive models of prolonged mechanical ventilation yield moderate accuracy.

    Science.gov (United States)

    Figueroa-Casas, Juan B; Dwivedi, Alok K; Connery, Sean M; Quansah, Raphael; Ellerbrook, Lowell; Galvis, Juan

    2015-06-01

    To develop a model to predict prolonged mechanical ventilation within 48 hours of its initiation. In 282 general intensive care unit patients, multiple variables from the first 2 days on mechanical ventilation and their total ventilation duration were prospectively collected. Three models accounting for early deaths were developed using different analyses: (a) multinomial logistic regression to predict duration > 7 days vs duration ≤ 7 days alive vs duration ≤ 7 days death; (b) binary logistic regression to predict duration > 7 days for the entire cohort and for survivors only, separately; and (c) Cox regression to predict time to being free of mechanical ventilation alive. Positive end-expiratory pressure, postoperative state (negatively), and Sequential Organ Failure Assessment score were independently associated with prolonged mechanical ventilation. The multinomial regression model yielded an accuracy (95% confidence interval) of 60% (53%-64%). The binary regression models yielded accuracies of 67% (61%-72%) and 69% (63%-75%) for the entire cohort and for survivors, respectively. The Cox regression model showed an equivalent to area under the curve of 0.67 (0.62-0.71). Different predictive models of prolonged mechanical ventilation in general intensive care unit patients achieve a moderate level of overall accuracy, likely insufficient to assist in clinical decisions. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. 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...... at different temperatures (60 °C, 70 °C, 80 °C) and pH (1.5, 2.3, 3.1) values....

  8. 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)

  9. Reflexion on linear regression trip production modelling method for ensuring good model quality

    Science.gov (United States)

    Suprayitno, Hitapriya; Ratnasari, Vita

    2017-11-01

    Transport Modelling is important. For certain cases, the conventional model still has to be used, in which having a good trip production model is capital. A good model can only be obtained from a good sample. Two of the basic principles of a good sampling is having a sample capable to represent the population characteristics and capable to produce an acceptable error at a certain confidence level. It seems that this principle is not yet quite understood and used in trip production modeling. Therefore, investigating the Trip Production Modelling practice in Indonesia and try to formulate a better modeling method for ensuring the Model Quality is necessary. This research result is presented as follows. Statistics knows a method to calculate span of prediction value at a certain confidence level for linear regression, which is called Confidence Interval of Predicted Value. The common modeling practice uses R2 as the principal quality measure, the sampling practice varies and not always conform to the sampling principles. An experiment indicates that small sample is already capable to give excellent R2 value and sample composition can significantly change the model. Hence, good R2 value, in fact, does not always mean good model quality. These lead to three basic ideas for ensuring good model quality, i.e. reformulating quality measure, calculation procedure, and sampling method. A quality measure is defined as having a good R2 value and a good Confidence Interval of Predicted Value. Calculation procedure must incorporate statistical calculation method and appropriate statistical tests needed. A good sampling method must incorporate random well distributed stratified sampling with a certain minimum number of samples. These three ideas need to be more developed and tested.

  10. Model for the integrated network? Rehabilitation makes a good candidate.

    Science.gov (United States)

    Fowler, F J; Baum, C S

    1995-01-01

    Rehabilitation is a good model for an integrated delivery network (IDN). Because it is an integral part of the treatment plans of a diverse group of medical specialties, rehab often plays a pivotal role in patients' recovery. Since its focus is on functional outcomes, rehab is compatible with a capitated payment system. In addition, rehab entered the managed care arena before other "product lines," so rehab providers have experience with diverse reimbursement conditions. And although rehab encompasses all levels of care, it is not too large to function as a model for a full-scale IDN. There are four key stages in the development of a rehab IDN: A strong leader with a clear vision organizes a working committee composed of the key leaders of each entity involved in rehab: hospitals, nursing homes, home health, and others. The committee begins to design the proposed network. Though the committee may study other IDNs, its focus is on its own organization's needs and objectives. A master plan addressing systems gaps and opportunities throughout the IDN is drawn up. Integral to the plan is a schedule according to which each of the network's components will be integrated. The master plan is implemented. The working committee determines the IDN's final structure and names the members of the management team.

  11. Yield Stress Model for Molten Composition B-3

    Science.gov (United States)

    Davis, Stephen; Zerkle, David

    2017-06-01

    Composition B-3 (Comp B-3) is a melt-castable explosive composed of 60/40 wt% RDX/TNT (hexahydro-1,3,5-trinitro-1,3,5-triazine/2,4,6-trinitrotoluene). During casting operations thermal conditions are controlled which along with the low melting point of TNT and the insensitivity of the mixture to external stimuli leading to safe use. Outside these standard operating conditions a more rigorous model of Comp B-3 rheological properties is necessary to model thermal transport as Comp B-3 evolves from quiescent solid through vaporization/decomposition upon heating. One particular rheological phenomena of interest is Bingham plasticity, where a material behaves as a quiescent solid unless a sufficient load is applied, resulting in fluid flow. In this study falling ball viscometer data is used to model the change in Bingham plastic yield stresses as a function of RDX particle volume fraction; a function of temperature. Results show the yield stress of Comp B-3 (τy) follows the expression τy = B ϕ -ϕc N , where Φ and Φc are the volume fraction of RDX and a critical volume fraction, respectively and B and N are experimentally evaluated constants.

  12. Modeling of the Strain Rate Dependency of Polycarbonate’s Yield Stress: Evaluation of Four Constitutive Equations

    OpenAIRE

    Abdullah A. Al-Juaid; Ramzi Othman

    2016-01-01

    The main focus of this paper is in evaluating four constitutive relations which model the strain rate dependency of polymers yield stress. Namely, the two-term power-law, the Ree-Eyring, the cooperative, and the newly modified-Eyring equations are used to fit tensile and compression yield stresses of polycarbonate, which are obtained from the literature. The four equations give good agreement with the experimental data. Despite using only three material constants, the modified-Eyring equation...

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

    Science.gov (United States)

    Houck-Loomis, Tiffany

    2012-09-01

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

  14. Assessing disease stress and modeling yield losses in alfalfa

    Science.gov (United States)

    Guan, Jie

    weight, percentage reflectance (810 nm), and green leaf area index (GLAI). Percentage reflectance (810 nm) assessments had a stronger relationship with dry weight and green leaf area index than percentage defoliation assessments. Our research conclusively demonstrates that percentage reflectance measurements can be used to nondestructively assess green leaf area index which is a direct measure of plant health and an indirect measure of productivity. This research conclusively demonstrates that remote sensing is superior to visual assessment method to assess alfalfa stress and to model yield and GLAI in the alfalfa foliar disease pathosystem.

  15. Application of Bayesian Model Selection for Metal Yield Models using ALEGRA and Dakota.

    Energy Technology Data Exchange (ETDEWEB)

    Portone, Teresa; Niederhaus, John Henry; Sanchez, Jason James; Swiler, Laura Painton

    2018-02-01

    This report introduces the concepts of Bayesian model selection, which provides a systematic means of calibrating and selecting an optimal model to represent a phenomenon. This has many potential applications, including for comparing constitutive models. The ideas described herein are applied to a model selection problem between different yield models for hardened steel under extreme loading conditions.

  16. ExEP yield modeling tool and validation test results

    Science.gov (United States)

    Morgan, Rhonda; Turmon, Michael; Delacroix, Christian; Savransky, Dmitry; Garrett, Daniel; Lowrance, Patrick; Liu, Xiang Cate; Nunez, Paul

    2017-09-01

    EXOSIMS is an open-source simulation tool for parametric modeling of the detection yield and characterization of exoplanets. EXOSIMS has been adopted by the Exoplanet Exploration Programs Standards Definition and Evaluation Team (ExSDET) as a common mechanism for comparison of exoplanet mission concept studies. To ensure trustworthiness of the tool, we developed a validation test plan that leverages the Python-language unit-test framework, utilizes integration tests for selected module interactions, and performs end-to-end crossvalidation with other yield tools. This paper presents the test methods and results, with the physics-based tests such as photometry and integration time calculation treated in detail and the functional tests treated summarily. The test case utilized a 4m unobscured telescope with an idealized coronagraph and an exoplanet population from the IPAC radial velocity (RV) exoplanet catalog. The known RV planets were set at quadrature to allow deterministic validation of the calculation of physical parameters, such as working angle, photon counts and integration time. The observing keepout region was tested by generating plots and movies of the targets and the keepout zone over a year. Although the keepout integration test required the interpretation of a user, the test revealed problems in the L2 halo orbit and the parameterization of keepout applied to some solar system bodies, which the development team was able to address. The validation testing of EXOSIMS was performed iteratively with the developers of EXOSIMS and resulted in a more robust, stable, and trustworthy tool that the exoplanet community can use to simulate exoplanet direct-detection missions from probe class, to WFIRST, up to large mission concepts such as HabEx and LUVOIR.

  17. GOVERNMENTS’ DEBTS AND PUBLIC GOODS IN A MULTI-COUNTRY GROWTH MODEL WITH TRADABLE AND NON-TRADABLE GOODS

    Directory of Open Access Journals (Sweden)

    Wei-Bin Zhang

    2017-04-01

    Full Text Available This study deals with dynamic relationships between global growth, trade, economic structural change, and government’s debts. Government debts are seldom theoretically modelled in the literature of global economic growth theory. We introduce governments’ debts and endogenous public good supplies into a general dynamic equilibrium growth model with multiple countries and free trades between countries. The model is developed by integrating the Solow-Uzawa growth model, the Oniki–Uzawa trade model, and Diamond’s growth model with government’s debt within a comprehensive framework. The model synthesizes these well-known economic models with Zhang’s utility function to determine household behavior. It is built for any number of national economies. Each national economy consists of one tradable, one non-tradable and one public sector. The model describes a dynamic interdependence between wealth accumulation, and division of labor, governments’ debts, national debts, and wealth and capital distribution under perfect competition. We demonstrate that the dynamics of the -country world economy can be described by  differential equations. We simulate the model, demonstrating the existence of an equilibrium point, and showing instability of the equilibrium point. We also demonstrate how changes in some parameters affect short-run global economic development and the equilibrium point. Our comparative dynamic analyses provided some important insights into interactions between global economic growth, resource distributions, economic structures, and governments’ debts.

  18. What should a 'good' model of the NPP operator contain

    International Nuclear Information System (INIS)

    Bainbridge, L.

    1986-01-01

    Much of human factors design is done without reference to models. A 'scientific' cognitive model contains multi-level goal-oriented top-down processing, in which behaviour choice depends on working memory, mental and environmental constraints, and expected results. Simpler models are more practical for supporting 0 behaviour, or predicting performance limits. Many types of reason make numerical predictions of cognitive behaviour non trivial

  19. 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.

  20. Flexible competing risks regression modeling and goodness-of-fit

    DEFF Research Database (Denmark)

    Scheike, Thomas; Zhang, Mei-Jie

    2008-01-01

    In this paper we consider different approaches for estimation and assessment of covariate effects for the cumulative incidence curve in the competing risks model. The classic approach is to model all cause-specific hazards and then estimate the cumulative incidence curve based on these cause......-specific hazards. Another recent approach is to directly model the cumulative incidence by a proportional model (Fine and Gray, J Am Stat Assoc 94:496-509, 1999), and then obtain direct estimates of how covariates influences the cumulative incidence curve. We consider a simple and flexible class of regression...

  1. Assessing sediment yield in Kalaya gauged watershed (Northern Morocco using GIS and SWAT model

    Directory of Open Access Journals (Sweden)

    Hamza Briak

    2016-09-01

    Full Text Available An efficient design for erosion-control structures of any watershed in the world is entrusted with the delicate forecasting of sediment yields. These outlook yields are usually inferred by extrapolations from past observations. Because runoff, as the transporting vehicle, is more closely correlated with sediment yields than any other variable. So, calibration as well as validation of process-based hydrological models are two major processes while estimating the sediment yield in watershed. The actual survey is fulfilled with the aim of developing a trustworthy hydrologic model simulating stream flow discharge and sediment concentration with least uncertainty among the parameters picked out for calibration so as to verify the effect of the scenarios on the spatial distribution of sediment yield (sediments transported from sub-basins to the main channel during the step of time. Soil and Water Assessment Tool (SWAT, version 2012 model integrated with Geographic Information System (GIS, version 10.1 was used to simulate the stream flow and sediment concentration of Kalaya catchment situated in north of Morocco for the period from 1971 to 1993. Model calibration and validation were performed for monthly time periods using Sequential Uncertainty Fitting 2 (SUFI-2, version 2 within SWAT-CUP using 16 parameters. Our calibration outputs for monthly simulation for the period from 1976 to 1984 showed a good model performance for flow rates with NSE and PBIAS values of 0.76 and −11.80, respectively; also a good model performance for sediment concentration with NSE and PBIAS values of 0.69 and 7.12, respectively. Nonetheless, during validation period (1985–1993 for monthly time step, the NSE and PBIAS values were 0.67 and −14.44, respectively for flow rates and these statistical values were 0.70 and 15.51, respectively for sediment concentration; which also means a good model performance for both. Following calibration, the inclusive effect of each

  2. Modeling good research practices--overview: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--1.

    Science.gov (United States)

    Caro, J Jaime; Briggs, Andrew H; Siebert, Uwe; Kuntz, Karen M

    2012-01-01

    Models--mathematical frameworks that facilitate estimation of the consequences of health care decisions--have become essential tools for health technology assessment. Evolution of the methods since the first ISPOR Modeling Task Force reported in 2003 has led to a new Task Force, jointly convened with the Society for Medical Decision Making, and this series of seven articles presents the updated recommendations for best practices in conceptualizing models; implementing state-transition approaches, discrete event simulations, or dynamic transmission models; and dealing with uncertainty and validating and reporting models transparently. This overview article introduces the work of the Task Force, provides all the recommendations, and discusses some quandaries that require further elucidation. The audience for these articles includes those who build models, stakeholders who utilize their results, and, indeed, anyone concerned with the use of models to support decision making. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  3. Modeling good research practices--overview: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-1.

    Science.gov (United States)

    Caro, J Jaime; Briggs, Andrew H; Siebert, Uwe; Kuntz, Karen M

    2012-01-01

    Models-mathematical frameworks that facilitate estimation of the consequences of health care decisions-have become essential tools for health technology assessment. Evolution of the methods since the first ISPOR modeling task force reported in 2003 has led to a new task force, jointly convened with the Society for Medical Decision Making, and this series of seven papers presents the updated recommendations for best practices in conceptualizing models; implementing state-transition approaches, discrete event simulations, or dynamic transmission models; dealing with uncertainty; and validating and reporting models transparently. This overview introduces the work of the task force, provides all the recommendations, and discusses some quandaries that require further elucidation. The audience for these papers includes those who build models, stakeholders who utilize their results, and, indeed, anyone concerned with the use of models to support decision making.

  4. 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)

  5. Good Governance : negotiated settlemens for FCPA violations as a model

    NARCIS (Netherlands)

    Abiola Makinwa

    2013-01-01

    De versnippering van de internationale samenleving vermindert de kans op een overkoepelend model van global governance. Meer waarschijnlijk is het ontstaan van bepaalde processen van bestuur die zich ontwikkelen als reactie op specifieke mondiale vraagstukken. Dit artikel beschrijft het proces van

  6. Goodness-of-fit tests in mixed models

    KAUST Repository

    Claeskens, Gerda

    2009-05-12

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

  7. Modelling and water yield assessment of Lake Sibhayi | Smithers ...

    African Journals Online (AJOL)

    A yield analysis of simulated results with historical developments in the catchment for the 65-year period of observed climate record was undertaken using both a fixed minimum allowable lake level or a maximum drop from a reference lake level as criteria for system failure. Results from simulating lake levels using the ...

  8. Primary and Secondary Yield Losses Caused by Pests and Diseases: Assessment and Modeling in Coffee.

    Directory of Open Access Journals (Sweden)

    Rolando Cerda

    Full Text Available The assessment of crop yield losses is needed for the improvement of production systems that contribute to the incomes of rural families and food security worldwide. However, efforts to quantify yield losses and identify their causes are still limited, especially for perennial crops. Our objectives were to quantify primary yield losses (incurred in the current year of production and secondary yield losses (resulting from negative impacts of the previous year of coffee due to pests and diseases, and to identify the most important predictors of coffee yields and yield losses. We established an experimental coffee parcel with full-sun exposure that consisted of six treatments, which were defined as different sequences of pesticide applications. The trial lasted three years (2013-2015 and yield components, dead productive branches, and foliar pests and diseases were assessed as predictors of yield. First, we calculated yield losses by comparing actual yields of specific treatments with the estimated attainable yield obtained in plots which always had chemical protection. Second, we used structural equation modeling to identify the most important predictors. Results showed that pests and diseases led to high primary yield losses (26% and even higher secondary yield losses (38%. We identified the fruiting nodes and the dead productive branches as the most important and useful predictors of yields and yield losses. These predictors could be added in existing mechanistic models of coffee, or can be used to develop new linear mixed models to estimate yield losses. Estimated yield losses can then be related to production factors to identify corrective actions that farmers can implement to reduce losses. The experimental and modeling approaches of this study could also be applied in other perennial crops to assess yield losses.

  9. Investment Frictions and the Relative Price of Investment Goods in an Open Economy Model

    OpenAIRE

    Parantap Basu; Christoph Thoenissen

    2007-01-01

    Is the relative price of investment goods a good proxy for investment frictions? We analyze investment frictions in an open economy, flexible price, two-country model and show that when the relative price of investment goods is endogenously determined in such a model, the relative price of investment can actually rise in response to a reduction in investment frictions. Only when the model is driven by TFP shocks do we observe a data congruent negative correlation between investment and the re...

  10. Dynamics in a nonlinear Keynesian good market model

    International Nuclear Information System (INIS)

    Naimzada, Ahmad; Pireddu, Marina

    2014-01-01

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

  11. Dynamics in a nonlinear Keynesian good market model

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-03-15

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

  12. Goodness-of-fit test for proportional subdistribution hazards model.

    Science.gov (United States)

    Zhou, Bingqing; Fine, Jason; Laird, Glen

    2013-09-30

    This paper concerns using modified weighted Schoenfeld residuals to test the proportionality of subdistribution hazards for the Fine-Gray model, similar to the tests proposed by Grambsch and Therneau for independently censored data. We develop a score test for the time-varying coefficients based on the modified Schoenfeld residuals derived assuming a certain form of non-proportionality. The methods perform well in simulations and a real data analysis of breast cancer data, where the treatment effect exhibits non-proportional hazards. Copyright © 2013 John Wiley & Sons, Ltd.

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

    NARCIS (Netherlands)

    Wijnhoven, Alphonsus B.J.M.

    2002-01-01

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

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

    Science.gov (United States)

    Diamond, Joshua M

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Joshua M. Diamond

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  17. Growth and yield models for Eucalyptus grandis grown in Swaziland ...

    African Journals Online (AJOL)

    Functions were fitted to describe stand density, dominant height and basal area development over time. The functions performed well when scrutinised for their goodness of fit. They were also found to be consistent with forest growth theory when their logical behaviour was tested over the range of planting densities.

  18. 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.

  19. 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

  20. WFIRST: Integrated Coronagraph Design and Scientific Yield Modeling

    Science.gov (United States)

    Eldorado Riggs, A. J.; Nemati, Bijan; Gersh-Range, Jessica; Kasdin, Jeremy; Balasubramanian, Kunjithapatham; Krist, John; Ruane, Garreth; Sidick, Erkin

    2018-01-01

    The WFIRST Coronagraph Instrument (CGI) will be the first instrument to directly image cool gas giant exoplanets. To achieve its scientific goals of exoplanet imaging, exoplanet characterization, and circumstellar debris disk imaging, the CGI will carry both the shaped pupil coronagraph and hybrid Lyot coronagraph. Ongoing design work is focused on increasing the expected scientific yield by improving coronagraph performance (e.g., throughput or starlight suppression), robustness to observatory dynamics, and robustness to polarization aberrations. We present the design methodology, updated designs, and the evaluation process for choosing the designs with the highest scientific returns.

  1. 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.

  2. Modeling the yield potential of dryland canola under current and future climates in California

    Science.gov (United States)

    George, N.; Kaffka, S.; Beeck, C.; Bucaram, S.; Zhang, J.

    2012-12-01

    -adapted canola varieties can be justified, and the potential value of a California canola industry both now and in the future. Winter annual crops like canola use rainfall in a Mediterranean climate like California more efficiently than spring or summer crops. Our results suggest that under current production costs and seed prices, dry farmed canola will have good potential in certain areas of the California. Canola yields decline with annual winter precipitation, however economically viable yields are still achieved at relatively precipitation levels (200 mm). Results from simulation, combined with related economic modeling (reported elsewhere) suggest that canola will be viable in a variety of production systems in the northern Sacramento Valley and some coastal locations, even under drier future climate scenarios. The in-field evaluation of Australian canola varieties should contribute to maintain or improving resource use efficiency and farm profitability.

  3. Biomass yield and modeling of logging residues of Terminalia ...

    African Journals Online (AJOL)

    The use of Dbh as an independent variable in the prediction of models for estimating the biomass residues of the tree species was adjudged best because it performed well. The validation results showed that the selected models satisfied the assumptions of regression analysis. The practical implication of the models is that ...

  4. Using hardness to model yield and tensile strength

    Energy Technology Data Exchange (ETDEWEB)

    Hawk, Jeffrey A.; Dogan, Omer N.; Schrems, Karol K.

    2005-02-01

    The current direction in hardness research is towards smaller and smaller loads as nano-scale materials are developed. There remains, however, a need to investigate the mechanical behavior of complex alloys for severe environment service. In many instances this entails casting large ingots and making numerous tensile samples as the bounds of the operating environment are explored. It is possible to gain an understanding of the tensile strength of these alloys using room and elevated temperature hardness in conjunction with selected tensile tests. The approach outlined here has its roots in the work done by Tabor for metals and low alloy and carbon steels. This research seeks to extend the work to elevated temperatures for multi-phase, complex alloys. A review of the approach will be given after which the experimental data will be examined. In particular, the yield stress and tensile strength will be compared to their corresponding hardness based values.

  5. Regression models for estimating charcoal yield in a Eucalyptus ...

    African Journals Online (AJOL)

    ... dbh2H, and the product of dbh and merchantable height [(dbh)MH] as independent variables. Results of residual analysis showed that the models satisfied all the assumptions of regression analysis. Keywords: Models, charcoal production, biomass, Eucalyptus, arid, anergy, allometric. Bowen Journal of Agriculture Vol.

  6. Model prediction of maize yield responses to climate change in ...

    African Journals Online (AJOL)

    Observed data of the last three decades (1971 to 2000) from several climatological stations in north-eastern Zimbabwe and outputs from several global climate models were used. The downscaled model simulations consistently predicted a warming of between 1 and 2 ºC above the baseline period (1971-2000) at most of ...

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

    Directory of Open Access Journals (Sweden)

    M. N. Chan

    2009-08-01

    Full Text Available Laboratory chamber data serve as the basis for constraining models of secondary organic aerosol (SOA formation. Current models fall into three categories: empirical two-product (Odum, product-specific, and volatility basis set. The product-specific and volatility basis set models are applied here 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 most likely hindered by lack of explicit inclusion of particle-phase accretion compounds. While prospects for identification of the majority of SOA products for major volatile organic compounds (VOCs classes remain promising, for the near future empirical product or volatility basis set models remain the approaches of choice.

  8. 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.

  9. 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.

  10. Operational semi-physical spectral-spatial wheat yield model development

    Science.gov (United States)

    Tripathy, R.; Chaudhary, K. N.; Nigam, R.; Manjunath, K. R.; Chauhan, P.; Ray, S. S.; Parihar, J. S.

    2014-11-01

    Spectral yield models based on Vegetation Index (VI) and the mechanistic crop simulation models are being widely used for crop yield prediction. However, past experience has shown that the empirical nature of the VI based models and the intensive data requirement of the complex mechanistic models has limited their use for regional and spatial crop yield prediction especially for operational use. The present study was aimed at development of an intermediate method based on the use of remote sensing and the physiological concepts such as the photo-synthetically active solar radiation (PAR) and the fraction of PAR absorbed by the crop (fAPAR) in Monteith's radiation use efficiency based equation (Monteith, 1977) for operational wheat yield forecasting by the Department of Agriculture (DoA). Net Primary Product (NPP) has been computed using the Monteith model and stress has been applied to convert the potential NPP to actual NPP. Wheat grain yield has been computed using the actual NPP and Harvest index. Kalpana-VHRR insolation has been used for deriving the PAR. Maximum radiation use efficiency has been collected from literature and wheat crop mask was derived at MNCFC, New Delhi using RS2-AWiFS data. Water stress has been derived from the Land Surface Water Index (LSWI) which has been derived periodically from the MODIS surface reflectance data (NIR and SWIR1). Temperature stress has been derived from the interpolated daily mean temperature. Results indicated that this model underestimated the yield by 3.45 % as compared to the reported yield at state level and hence can be used to predict wheat yield at state level. This study will be able to provide the spatial wheat yield map, as well as the district-wise and state level aggregated wheat yield forecast. It is possible to operationalize this remote sensing based modified Monteith's efficiency model for future yield forecasting with around 0.15 t ha-1 RMSE at state level.

  11. Applicability of multiple yield model to earthquake response analysis for foundation rock of large-scale structure

    International Nuclear Information System (INIS)

    Yoshinaka, Ryunoshin; Iwata, Naoki; Sasaki, Takeshi

    2012-01-01

    The authors are analyzed the large-scale structure build on the discontinuous rock foundation by earthquake response analysis with non-linear FEM considering the rock joint system using the actual earthquake record. The earthquake response analysis was performed by equivalent continuum finite element method as Multiple Yield Model (MYM) introducing cyclic loading elastic-plastic deformation characteristics of rock joints, and the analytical results were compared with the observed earthquake response. As a result, adequate modeling of discontinuities and appropriate setting of mechanical properties of rock and discontinuities give the good results corresponding with the observations. We confirmed the applicability of MYM to earthquake response. (author)

  12. Evolution of the Relative Price of Goods and Services in a Neoclassical Model of Capital Accumulation

    OpenAIRE

    Vladimir Klyuev

    2005-01-01

    The paper provides an explanation for the secular increase in the price of services relative to that of manufactured goods that relies on capital accumulation rather than on an exogenous total factor productivity growth differential. The key assumptions of the two-sector, intertemporal optimizing model are relatively high capital intensity in the production of goods and limited cross-border capital mobility, allowing the interest rate to vary. With plausible parameterization, the model also p...

  13. A Model for Quantifying Sources of Variation in Test-day Milk Yield ...

    African Journals Online (AJOL)

    A cow's test-day milk yield is influenced by several systematic environmental effects, which have to be removed when estimating the genetic potential of an animal. The present study quantified the variation due to test date and month of test in test-day lactation yield records using full and reduced models. The data consisted ...

  14. System dynamics approach for modeling of sugar beet yield considering the effects of climatic variables.

    Science.gov (United States)

    Pervin, Lia; Islam, Md Saiful

    2015-02-01

    The aim of this study was to develop a system dynamics model for computation of yields and to investigate the dependency of yields on some major climatic parameters, i.e. temperature and rainfall, for Beta vulgaris subsp. (sugar beet crops) under future climate change scenarios. A system dynamics model was developed which takes account of the effects of rainfall and temperature on sugar beet yields under limited irrigation conditions. A relationship was also developed between the seasonal evapotranspiration and seasonal growing degree days for sugar beet crops. The proposed model was set to run for the present time period of 1993-2012 and for the future period 2013-2040 for Lethbridge region (Alberta, Canada). The model provides sugar beet yields on a yearly basis which are comparable to the present field data. It was found that the future average yield will be increased at about 14% with respect to the present average yield. The proposed model can help to improve the understanding of soil water conditions and irrigation water requirements of an area under certain climatic conditions and can be used for future prediction of yields for any crops in any region (with the required information to be provided). The developed system dynamics model can be used as a supporting tool for decision making, for improvement of agricultural management practice of any region. © 2014 Society of Chemical Industry.

  15. Modeling of the Strain Rate Dependency of Polycarbonate’s Yield Stress: Evaluation of Four Constitutive Equations

    Directory of Open Access Journals (Sweden)

    Abdullah A. Al-Juaid

    2016-01-01

    Full Text Available The main focus of this paper is in evaluating four constitutive relations which model the strain rate dependency of polymers yield stress. Namely, the two-term power-law, the Ree-Eyring, the cooperative, and the newly modified-Eyring equations are used to fit tensile and compression yield stresses of polycarbonate, which are obtained from the literature. The four equations give good agreement with the experimental data. Despite using only three material constants, the modified-Eyring equation, which considers a strain rate-dependent activation volume, gives slightly worse fit than the three other equations. The two-term power-law and the cooperative equation predict a progressive increase in the strain rate sensitivity of the yield stress. Oppositely, the Ree-Eyring and the modified-Eyring equations show a clear transition between the low and high strain rate ranges. Namely, they predict a linear dependency of the yield stress in terms of the strain rate at the low strain rate range. Crossing a threshold strain rate, the yield stress sensitivity sharply increases as the strain rate increases. Hence, two different behaviors were observed though the four equations fit well the experimental data. More experimental data, mainly at the intermediate strain rate range, are needed to conclude which, of the two behaviors, is more appropriate for polymers.

  16. An analytical model of nonproportional scintillator light yield in terms of recombination rates

    International Nuclear Information System (INIS)

    Bizarri, G.; Moses, W. W.; Singh, J.; Vasil'ev, A. N.; Williams, R. T.

    2009-01-01

    Analytical expressions for the local light yield as a function of the local deposited energy (-dE/dx) and total scintillation yield integrated over the track of an electron of initial energy E are derived from radiative and/or nonradiative rates of first through third order in density of electronic excitations. The model is formulated in terms of rate constants, some of which can be determined independently from time-resolved spectroscopy and others estimated from measured light yield efficiency as a constraint assumed to apply in each kinetic order. The rates and parameters are used in the theory to calculate scintillation yield versus primary electron energy for comparison to published experimental results on four scintillators. Influence of the track radius on the yield is also discussed. Results are found to be qualitatively consistent with the observed scintillation light yield. The theory can be applied to any scintillator if the rates of the radiative and nonradiative processes are known

  17. 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.

  18. [Climate change impacts on yield of Cordyceps sinensis and research on yield prediction model of C. sinensis].

    Science.gov (United States)

    Zhu, Shou-Dong; Huang, Lu-Qi; Guo, Lan-Ping; Ma, Xing-Tian; Hao, Qing-Xiu; Le, Zhi-Yong; Zhang, Xiao-Bo; Yang, Guang; Zhang, Yan; Chen, Mei-Lan

    2017-04-01

    Cordyceps sinensis is a Chinese unique precious herbal material, its genuine producing areas covering Naqu, Changdu in Qinghai Tibet Plateau, Yushu in Qinghai province and other regions. In recent 10 years, C. sinensis resources is decreasing as a result of the blindly and excessively perennial dug. How to rationally protect, develop and utilize of the valuable resources of C. sinensis has been referred to an important field of research on C. sinensis. The ecological environment and climate change trend of Qinghai Tibet plateau happens prior to other regions, which means that the distribution and evolution of C. sinensis are more obvious and intense than those of the other populations. Based on RS (remote sensing)/GIS(geographic information system) technology, this paper utilized the relationship between the snowline elevation, the average temperature, precipitation and sunshine hours in harvest period (April and may) of C. sinensis and the actual production of C. sinensis to establish a weighted geometric mean model. The model's prediction accuracy can reach 82.16% at least in forecasting C. sinensis year yield in Naqu area in every early June. This study can provide basic datum and information for supporting the C. sinensis industry healthful, sustainable development. Copyright© by the Chinese Pharmaceutical Association.

  19. 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.

  20. Diverse Data Sets Can Yield Reliable Information through Mechanistic Modeling: Salicylic Acid Clearance

    Science.gov (United States)

    Raymond, G. M.; Bassingthwaighte, J. B.

    2016-01-01

    This is a practical example of a powerful research strategy: putting together data from studies covering a diversity of conditions can yield a scientifically sound grasp of the phenomenon when the individual observations failed to provide definitive understanding. The rationale is that defining a realistic, quantitative, explanatory hypothesis for the whole set of studies, brings about a “consilience” of the often competing hypotheses considered for individual data sets. An internally consistent conjecture linking multiple data sets simultaneously provides stronger evidence on the characteristics of a system than does analysis of individual data sets limited to narrow ranges of conditions. Our example examines three very different data sets on the clearance of salicylic acid from humans: a high concentration set from aspirin overdoses; a set with medium concentrations from a research study on the influences of the route of administration and of sex on the clearance kinetics, and a set on low dose aspirin for cardiovascular health. Three models were tested: (1) a first order reaction, (2) a Michaelis-Menten (M-M) approach, and (3) an enzyme kinetic model with forward and backward reactions. The reaction rates found from model 1 were distinctly different for the three data sets, having no commonality. The M-M model 2 fitted each of the three data sets but gave a reliable estimates of the Michaelis constant only for the medium level data (Km = 24±5.4 mg/L); analyzing the three data sets together with model 2 gave Km = 18±2.6 mg/L. (Estimating parameters using larger numbers of data points in an optimization increases the degrees of freedom, constraining the range of the estimates). Using the enzyme kinetic model (3) increased the number of free parameters but nevertheless improved the goodness of fit to the combined data sets, giving tighter constraints, and a lower estimated Km = 14.6±2.9 mg/L, demonstrating that fitting diverse data sets with a single model

  1. Diverse Data Sets Can Yield Reliable Information through Mechanistic Modeling: Salicylic Acid Clearance.

    Science.gov (United States)

    Raymond, G M; Bassingthwaighte, J B

    This is a practical example of a powerful research strategy: putting together data from studies covering a diversity of conditions can yield a scientifically sound grasp of the phenomenon when the individual observations failed to provide definitive understanding. The rationale is that defining a realistic, quantitative, explanatory hypothesis for the whole set of studies, brings about a "consilience" of the often competing hypotheses considered for individual data sets. An internally consistent conjecture linking multiple data sets simultaneously provides stronger evidence on the characteristics of a system than does analysis of individual data sets limited to narrow ranges of conditions. Our example examines three very different data sets on the clearance of salicylic acid from humans: a high concentration set from aspirin overdoses; a set with medium concentrations from a research study on the influences of the route of administration and of sex on the clearance kinetics, and a set on low dose aspirin for cardiovascular health. Three models were tested: (1) a first order reaction, (2) a Michaelis-Menten (M-M) approach, and (3) an enzyme kinetic model with forward and backward reactions. The reaction rates found from model 1 were distinctly different for the three data sets, having no commonality. The M-M model 2 fitted each of the three data sets but gave a reliable estimates of the Michaelis constant only for the medium level data (K m = 24±5.4 mg/L); analyzing the three data sets together with model 2 gave K m = 18±2.6 mg/L. (Estimating parameters using larger numbers of data points in an optimization increases the degrees of freedom, constraining the range of the estimates). Using the enzyme kinetic model (3) increased the number of free parameters but nevertheless improved the goodness of fit to the combined data sets, giving tighter constraints, and a lower estimated K m = 14.6±2.9 mg/L, demonstrating that fitting diverse data sets with a single model

  2. Modeling long-term yield trends of Miscanthusxgiganteus using experimental data from across Europe

    DEFF Research Database (Denmark)

    Lesur, Claire; Jeuffroy, Marie-Hélène; Makowski, David

    2013-01-01

    . 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...... and the ceiling phases and (ii) to determine whether M. giganteus ceiling phase is followed by a decline phase where yields decrease across years. Data were analyzed through comparisons between a set of statistical growth models. The model that best fitted the experimental data included a decline phase...

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

    Science.gov (United States)

    Andrews, Benjamin J.

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

  4. 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.

  5. Residuals and the Residual-Based Statistic for Testing Goodness of Fit of Structural Equation Models

    Science.gov (United States)

    Foldnes, Njal; Foss, Tron; Olsson, Ulf Henning

    2012-01-01

    The residuals obtained from fitting a structural equation model are crucial ingredients in obtaining chi-square goodness-of-fit statistics for the model. The authors present a didactic discussion of the residuals, obtaining a geometrical interpretation by recognizing the residuals as the result of oblique projections. This sheds light on the…

  6. Modeling survival, yield, volume partitioning and their response to thinning for longleaf pine plantations

    Science.gov (United States)

    Carlos A. Gonzalez-Benecke; Salvador A. Gezan; Daniel J. Leduc; Timothy A. Martin; Wendell P. Cropper Jr; Lisa J Samuelson

    2012-01-01

    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 H

  7. Modelling of seed yield and its components in tall fescue ( Festuca ...

    African Journals Online (AJOL)

    Ridge regression analysis was used to derive a steady algorithmic model that related Z to the five components; Y1 to Y5. This model can estimate Z precisely from the values of these components. Furthermore, an approach based on the exponents of the algorithmic model could be applied to the selection for high seed yield ...

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

    International Nuclear Information System (INIS)

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

    2005-01-01

    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

  9. 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.

  10. Classifying Multi-Model Wheat Yield Impact Response Surfaces Showing Sensitivity to Temperature and Precipitation Change

    Science.gov (United States)

    Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R.; Bindi, Marco; Hoffmann, Holger; Palosuo, Taru; Ruiz-Ramos, Margarita; Tao, Fulu; Trnka, Miroslav; Acutis, Marco; hide

    2017-01-01

    Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (minus 2 to plus 9 degrees Centigrade) and precipitation (minus 50 to plus 50 percent). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the

  11. Comparison of HSPF and SWAT models performance for runoff and sediment yield prediction.

    Science.gov (United States)

    Im, Sangjun; Brannan, Kevin M; Mostaghimi, Saied; Kim, Sang Min

    2007-09-01

    A watershed model can be used to better understand the relationship between land use activities and hydrologic/water quality processes that occur within a watershed. The physically based, distributed parameter model (SWAT) and a conceptual, lumped parameter model (HSPF), were selected and their performance were compared in simulating runoff and sediment yields from the Polecat Creek watershed in Virginia, which is 12,048 ha in size. A monitoring project was conducted in Polecat Creek watershed during the period of October 1994 to June 2000. The observed data (stream flow and sediment yield) from the monitoring project was used in the calibration/validations of the models. The period of September 1996 to June 2000 was used for the calibration and October 1994 to December 1995 was used for the validation of the models. The outputs from the models were compared to the observed data at several sub-watershed outlets and at the watershed outlet of the Polecat Creek watershed. The results indicated that both models were generally able to simulate stream flow and sediment yields well during both the calibration/validation periods. For annual and monthly loads, HSPF simulated hydrologic and sediment yield more accurately than SWAT at all monitoring sites within the watershed. The results of this study indicate that both the SWAT and HSPF watershed models performed sufficiently well in the simulation of stream flow and sediment yield with HSPF performing moderately better than SWAT for simulation time-steps greater than a month.

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

    KAUST Repository

    Ma, Yanyuan

    2010-09-14

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

  13. Structural Equation Model as a Tool to Assess the Relationship Between Grain Yield Per Plant and Yield Components in Doubled Haploid Spring Barley Lines (Hordeum vulgare L.

    Directory of Open Access Journals (Sweden)

    Mańkowski Dariusz R.

    2016-06-01

    Full Text Available The aim of this study was to describe and characterize the relationships between yielding factors and grain yield per doubled haploid (DH plant of spring barley as well as relation between yield components and duration of each stage of plant development. To describe these relations structure equation modeling was used. The study included plants of doubled haploid spring barley lines (Hordeum vulgare L. derived from two-rowed form of Scarlett cultivar. The SAS® system was used to analyze the model of relationships between grain yield per plant and yield components. Our results indicate that the number of spikes per plant and grain yield per spike had a direct and decisive influence on the grain yield of the investigated DH plants of spring barley. Based on the path model analysis it was found that the most important factor determining grain yield per DH plants of spring barley was the number of spikes per plant and the duration of tillering and shooting stages.

  14. GOODNESS-OF-FIT TEST FOR THE ACCELERATED FAILURE TIME MODEL BASED ON MARTINGALE RESIDUALS

    Czech Academy of Sciences Publication Activity Database

    Novák, Petr

    2013-01-01

    Roč. 49, č. 1 (2013), s. 40-59 ISSN 0023-5954 R&D Projects: GA MŠk(CZ) 1M06047 Grant - others:GA MŠk(CZ) SVV 261315/2011 Keywords : accelerated failure time model * survival analysis * goodness-of-fit Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.563, year: 2013 http://library.utia.cas.cz/separaty/2013/SI/novak-goodness-of-fit test for the aft model based on martingale residuals.pdf

  15. 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.

  16. Analysis of yield of retinal imaging in a rural diabetes eye care model

    Directory of Open Access Journals (Sweden)

    Padmaja Kumari Rani

    2018-01-01

    Full Text Available Purpose: The aim of this study is to analyze the yield of retinal images obtained in a rural diabetes eye care model. Methods: An analysis of a sample of nonmydriatic fundus photography (NMFP of posterior segment ophthalmic images, obtained by an indigenous equipment (3 nethra-Forus Royal, was done in a district-wide rural diabetic retinopathy (DR screening program; a trained optometrist did the initial image grading. DR and diabetic macular edema (DME were classified based on international DR and DME severity scale. The agreement between the optometrist and retina specialist was very good (κ = 0.932; standard error = 0.030; 95% confidence interval = 0.874–0.991. Results: Posterior segment images of 2000 eyes of 1000 people with diabetes mellitus (DM were graded. The mean age of the participants was 55.7 ± 11.5 standard deviation years. Nearly 42% of the screened participants (n = 420/1000 needed referral. The most common referable posterior segment abnormality was DR (8.2%. The proportion of people with any form of DR was seen in 110/1225 eyes, and sight-threatening DR was seen in 35/1225 eyes. About 62% of posterior segment images were gradable. The reasons for ungradable posterior segment images (34% were small pupil, unfocused/partially available field of images, and cataract. Conclusion: A NMFP model was able to detect referable posterior segment abnormalities in a rural diabetes eye care program. Reasons found for ungradability of images in the present study can be addressed while designing future DR screening programs in the rural areas.

  17. The Architecture of the Statistical Modeling Concerning the Consumer Prices Indexes for Food Goods, Non-Food Goods and Services, in Romania

    Directory of Open Access Journals (Sweden)

    Gabriela OPAIT

    2014-08-01

    Full Text Available This paper reflects the econometric modeling between 2000-2013, in Romania, concerning the Consumer Prices Index for food goods, the Consumer Prices Index for non-food goods and the Consumer Prices Index for services, through by means of the „Least Squares Method”. The Consumer Prices Index (CPI reflects the change of price concerning the basket of goods that it is supposed to be purchased by a urban consumers in terms of the expenses incurred by a typical household.

  18. A meteorologically-driven yield reduction model for spring and winter wheat

    Science.gov (United States)

    Ravet, F. W.; Cremins, W. J.; Taylor, T. W.; Ashburn, P.; Smika, D.; Aaronson, A. (Principal Investigator)

    1983-01-01

    A yield reduction model for spring and winter wheat was developed for large-area crop condition assessment. Reductions are expressed in percentage from a base yield and are calculated on a daily basis. The algorithm contains two integral components: a two-layer soil water budget model and a crop calendar routine. Yield reductions associated with hot, dry winds (Sukhovey) and soil moisture stress are determined. Input variables include evapotranspiration, maximum temperature and precipitation; subsequently crop-stage, available water holding percentage and stress duration are evaluated. No specific base yield is required and may be selected by the user; however, it may be generally characterized as the maximum likely to be produced commercially at a location.

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

    OpenAIRE

    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

    2015-01-01

    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 in...

  20. 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.

  1. 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.

  2. 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)

  3. 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.

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

    OpenAIRE

    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 ...

  5. 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......Satellite-based techniques that provide temporally and spatially continuous information over vegetated surfaces have become increasingly important in monitoring the global agriculture yield. In this study, we examine the performance of a light use efficiency model (EC-LUE) for simulating the gross...... 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...

  6. 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.

  7. 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.

  8. PEMILIHAN MODEL ORGANISASI DAN TERWUJUDNYA PRINSIP-PRINSIP GOOD CORPORATE GOVERNANCE

    Directory of Open Access Journals (Sweden)

    Aries Susanty

    2012-02-01

    Full Text Available Ketidakmampuan penerapan prinsip good corporate governance (GSC didemonstrasikan dalam survei dengan konstrain yang diklasifikasikan dalam 3 konstrain yaitu konstrain internal, konstrain eksternal dan konstrain yang berasal dari struktur pemilik. Konstrain internal meliputi komitmen pemimpin dan pekerja, tingkat pemahaman prinsip GCG oleh pemimpin dan pekerja, keefektifan sistem kontrol internal dan formality trap (implementasi CG hanya untuk memenuhi regulasi. Konstrain internal yang disebutkan berkaitan dengan fungsi internal perusahaan. Sebagai sebuah organisasi bisnis, korporasi tidak mampu mencapai tujuan menerapkan GCG dengan sukses bila tidak didukung elemen internal organisasi. Untuk membentuk fungsi internal diperlukan diagnosa korporasi dengan model organisasi. Dalam hal ini, penulis menggunakan beberapa kriteria untuk memilih model yang paling tepat dari 10 model yang ada. Dari beberapa kriteria dapat disimpulkan bahwa Adaptasi Pascal merupakan model yang paling tepat. Model ini dapat menggambarkan hubungan antara kondisi tiap elemen organisasi dengan kesuksesan implementasi prinsip GCG. Kata kunci: Prinsip Good Corporate Governance, model organisasi             The inability to implement the principles of good corporate governance (GCG as demonstrated in the surveys is due to a number of constraints which can be classified into three; namely internal constraints, external constraints, and constraints coming from the structure of ownership. Internal constraints cover the commitment of leaders and workers, the level of understanding of GCG principles from leaders and workers, good example from leaders, the corporate culture supporting the implementation of GCG principles, effectiveness of internal control system, and formality trap (implementing CG only to meet regulations. The issues in the internal constraints mentioned are related to the internal  functions of the company. As a business organization, corporation is unable

  9. 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...... is included in the state vector. This amounts to an augmented dynamic factor model in which the factors (level, slope, and curvature of the yield curve) are supervised for the macroeconomic forecast target. In other words, the factors are informed about the dynamics of the forecast objective. The factor...... loadings have the Nelson and Siegel (1987) structure and we consider one forecast target at a time. We compare the forecasting performance of our specification to benchmark models such as principal components regression, partial least squares, and ARMA(p,q) processes. We use the yield curve data from G...

  10. Determining the Threshold Value of Basil Yield Reduction and Evaluation of Water Uptake Models under Salinity Stress Condition

    Directory of Open Access Journals (Sweden)

    M. Sarai Tabrizi

    2016-10-01

    by calculating statistical indices such as maximum error (ME, normalized root mean square error (nRMSE, modeling efficiency (EF, and coefficient of residual mass (CRM. At the end of the experiment, dry matter yield at the different treatments was measured and relative yield was calculated by dividing dry matter yield of treatments on dry matter yield at no stress treatment (control treatment. Leaching requirement in experimental treatments was calculated by Ayarset al., (2012 equation. Results and Discussion: The results indicated that Basil threshold value based on soil salinity was 2.25 dSm-1 with the yield reduction of 7.2% per dSm-1. The mathematical model of van Genuchten and Hoffman (1984 had a higher precision than other models in simulating Basil yield reduction function based on saturated soil extract salinity. The overall observations revealed that van Genuchten and Hoffman (1984, Steppuhnet al., (2005 and Homaeeet al., (2002 models were accurate for simulating Basil root water uptake and yield response to saturated soil extract salinity. Considering the presented results, it seems that among math-empirical models for salinity stress conditions, model of van Genuchten and Hoffman (1984 is more accurate than Maas and Hoffman (1977, Dirksen and Augustijn (1988 and Homaeeet al., (2002a models. The works of Green et al., (2006 and Skaggs et al., (2006 came to the same conclusion. Our work indicated that mostly statistical models have lower precision than math-empirical models. Steppuhn et al., (2005a reported that statistical models had the higher accuracy than math-empirical model of Maas and Hoffman (1977 and among statistical models, the modified Weibull model had the best fit on measured data which is in good agreement with the results of this study. Conclusion: The goals of this research were to evaluate Basil response to saturated soil extract salinity, to estimate threshold value of Basil crop coefficients, to obtain yield reduction gradient, and also to

  11. MODELING OF YIELD AND QUALITY OF TABLE ROOT CROPS WITH THE USE OF DIFFERENT AGROTECHNICAL METHODS

    Directory of Open Access Journals (Sweden)

    S. M. Nadezhkin

    2017-01-01

    Full Text Available The effects of different fertilizer rates, irrigation, sowing rate for carrot and red beet were studied in the field condition in food-hills zone of Chechen Republic. The use of N40-80P40-80K40-80 caused the increase in yield from 22.8 to 30.8-33.2 t/ha or by 35-46%, when cultivating a carrot crop. Under irrigation the yield increases by 30-33%. Application of N40P40K40 and maintenance of soil moisture at 70% of moisture rate provoked the improvement in value, market and biochemical characteristics of roots; where the increased contents of dry matter, total sugar and vitamins were observed. The mathematical modeling for the process of yielding abilities and root quality in carrot and red beet showed that highest productivity can be achieved on chernozem soil at Central Pre-Caucasus zone when the level of mineral plant nutrition was N40-60P40-60K40-60. The further increment in fertilizer doses does not bring an improvement to yields and leads to decrease in quality of yields. The increased level of antecedent soil water moisture 70-75% of moisture rates does not raise the yield, on the contrary decreasing at the same time the root quality. The use of mathematical modeling enables to rationally define the fertilizer rates depending on application of irrigation and sowing rates in cultivation of carrot and red beet.

  12. A Modified Strip-Yield-Saturation-Induction Model Solution for Cracked Piezoelectromagnetic Plate

    Directory of Open Access Journals (Sweden)

    R. R. Bhargava

    2014-01-01

    Full Text Available A strip-yield-saturation-induction model is proposed for an impermeable crack embedded in piezoelectromagnetic plate. The developed slide-yield, saturation, and induction zones are arrested by distributing, respectively, mechanical, electrical, and magnetic loads over their rims. Two cases are considered: when saturation zone exceeds induction zone and vice-versa. It is assumed that developed slide-yield zone is the smallest because of the brittle nature of piezoelectromagnetic material. Fourier integral transform technique is employed to obtain the solution. Closed form analytic expressions are derived for developed zones lengths, crack sliding displacement, crack opening potential drop, crack opening induction drop, and energy release rate. Case study presented for BaTiO3–CoFe2O4 shows that crack arrest is possible under small-scale mechanical, electrical, and magnetic yielding.

  13. Statistics-based model for prediction of chemical biosynthesis yield from Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Leonard Effendi

    2011-06-01

    Full Text Available Abstract Background The robustness of Saccharomyces cerevisiae in facilitating industrial-scale production of ethanol extends its utilization as a platform to synthesize other metabolites. Metabolic engineering strategies, typically via pathway overexpression and deletion, continue to play a key role for optimizing the conversion efficiency of substrates into the desired products. However, chemical production titer or yield remains difficult to predict based on reaction stoichiometry and mass balance. We sampled a large space of data of chemical production from S. cerevisiae, and developed a statistics-based model to calculate production yield using input variables that represent the number of enzymatic steps in the key biosynthetic pathway of interest, metabolic modifications, cultivation modes, nutrition and oxygen availability. Results Based on the production data of about 40 chemicals produced from S. cerevisiae, metabolic engineering methods, nutrient supplementation, and fermentation conditions described therein, we generated mathematical models with numerical and categorical variables to predict production yield. Statistically, the models showed that: 1. Chemical production from central metabolic precursors decreased exponentially with increasing number of enzymatic steps for biosynthesis (>30% loss of yield per enzymatic step, P-value = 0; 2. Categorical variables of gene overexpression and knockout improved product yield by 2~4 folds (P-value Saccharomyces cerevisiae has historically evolved for robust alcohol fermentation. Conclusions We generated simple mathematical models for first-order approximation of chemical production yield from S. cerevisiae. These linear models provide empirical insights to the effects of strain engineering and cultivation conditions toward biosynthetic efficiency. These models may not only provide guidelines for metabolic engineers to synthesize desired products, but also be useful to compare the

  14. 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...... Carlo simulations with SHIELD-HIT10A reasonably matched the most abundant PET isotopes 11C and 15O. We observed an ion-energy (i.e., depth) dependence of the agreement between SHIELD-HIT10A and measurement. Improved modeling requires more accurate measurements of cross-section values....

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

    Directory of Open Access Journals (Sweden)

    Naji Zuhair Alsarhi

    2015-12-01

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

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

    DEFF Research Database (Denmark)

    Rasmussen, Kourosh Marjani; Poulsen, Rolf

    Dynamic stochastic programming (DSP) provides an intuitive framework for modelling of financial portfolio choice problems where market frictions are present and dynamic re--balancing has a significant effect on initial decisions. The application of these models in practice, however, is limited by...... of yield curves. Such trees may then be used to represent the underlying uncertainty in DSP models of fixed income risk and portfolio management....

  17. Remote Sensing Protocols for Parameterizing an Individual, Tree-Based, Forest Growth and Yield Model

    Science.gov (United States)

    2014-09-01

    Penelope Morgan. 2006. “Regression Modeling and Mapping of Coniferous Forest Basal Area and Tree Density from Discrete- Return LIDAR and... Basal Area Relationships of Open-Grown Southern Pines for Modeling Competition and Growth.” Canadian Journal of of Forest Research 22: 341–347... Forest Growth and Yield Model Co ns tr uc tio n En gi ne er in g R es ea rc h La bo ra to ry Scott A. Tweddale, Patrick J. Guertin, and

  18. Winter wheat yield estimation of remote sensing research based on WOFOST crop model and leaf area index assimilation

    Science.gov (United States)

    Chen, Yanling; Gong, Adu; Li, Jing; Wang, Jingmei

    2017-04-01

    Accurate crop growth monitoring and yield predictive information are significant to improve the sustainable development of agriculture and ensure the security of national food. Remote sensing observation and crop growth simulation models are two new technologies, which have highly potential applications in crop growth monitoring and yield forecasting in recent years. However, both of them have limitations in mechanism or regional application respectively. Remote sensing information can not reveal crop growth and development, inner mechanism of yield formation and the affection of environmental meteorological conditions. Crop growth simulation models have difficulties in obtaining data and parameterization from single-point to regional application. In order to make good use of the advantages of these two technologies, the coupling technique of remote sensing information and crop growth simulation models has been studied. Filtering and optimizing model parameters are key to yield estimation by remote sensing and crop model based on regional crop assimilation. Winter wheat of GaoCheng was selected as the experiment object in this paper. And then the essential data was collected, such as biochemical data and farmland environmental data and meteorological data about several critical growing periods. Meanwhile, the image of environmental mitigation small satellite HJ-CCD was obtained. In this paper, research work and major conclusions are as follows. (1) Seven vegetation indexes were selected to retrieve LAI, and then linear regression model was built up between each of these indexes and the measured LAI. The result shows that the accuracy of EVI model was the highest (R2=0.964 at anthesis stage and R2=0.920 at filling stage). Thus, EVI as the most optimal vegetation index to predict LAI in this paper. (2) EFAST method was adopted in this paper to conduct the sensitive analysis to the 26 initial parameters of the WOFOST model and then a sensitivity index was constructed

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

    Science.gov (United States)

    Overman, Allen R; Scholtz, Richard V

    2011-01-31

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

    Directory of Open Access Journals (Sweden)

    Allen R Overman

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

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

    Directory of Open Access Journals (Sweden)

    W. O. Nyang’au

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Robert Muha

    2004-09-01

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

  3. Recommendations on the transport of dangerous goods. Model regulations. 11. revised ed.

    International Nuclear Information System (INIS)

    1999-01-01

    The Recommendations on the Transport of Dangerous Goods are addressed to governments and to the international organizations concerned with the regulation of the transport of dangerous goods. They have been prepared by the United Nations Economic and Social Council's Committee of Experts on the Transport of Dangerous Goods, and they were first published in 1956 (ST/ECA/43-E/CN.2/170). Pursuant to Resolution 645 G (XXIII) of 26 April 1957 of the Economic and Social Council and subsequent resolutions, they have been regularly amended and updated at succeeding sessions of the Committee of Experts. At its eighteenth session (28 November-7 December 1994), the Committee of Experts considered that reformatting the Recommendations on the Transport of Dangerous Goods into Model Regulations that could be directly integrated into all modal national and international regulations would enhance harmonization, facilitate regular up-dating of all legal instruments concerned, and result in overall considerable resource savings for the Governments of the Member States, the United Nations, the specialized agencies and other international organizations. At its nineteenth session (2-10 December 1996), the Committee adopted a first version of the Model Regulations on the Transport of Dangerous Goods, which was annexed to the tenth revised edition of the Recommendations on the Transport of Dangerous Goods. At its twentieth session (7-16 December 1998), the Committee adopted various amendments to the Model Regulations and new provisions including, in particular, packing instructions for individual substances and articles and additional provisions for the transport of radioactive material. The additional provisions concerning the transport of radioactive material were developed in close cooperation with the International Atomic Energy Agency (IAEA) and are based on the 1996 Edition of the IAEA Regulations for the Safe Transport of Radioactive Material which have been reformatted so as to be

  4. Modelling production-consumption flows of goods in Europe: the trade model within Transtools3

    DEFF Research Database (Denmark)

    de Jong, Gerard; Tanner, Reto; Rich, Jeppe

    2017-01-01

    The paper presents a new model for trade flows in Europe that is integrated with a logistics model for transport chain choice through Logsum variables. Logsums measures accessibility across an entire multi-modal logistical chain, and are calculated from a logistics model that has been estimated...... on disaggregated micro data and then used as an input variable in the trade model. Using Logsums in a trade model is new in applied large-scale freight models, where previous models have simply relied on the distance (e.g. crow-fly) between zones. This linkage of accessibility to the trade model makes it possible...... such a complex model can be estimated and considers the choice of mathematical formulation and the link between the trade model and logistics model. In the outcomes for the tolling scenario we decompose the total effects into effects from the trade model and effects from the logistics model....

  5. TOURISM, TRADE, EXTERNALITIES, AND PUBLIC GOODS IN A THREE-SECTOR GROWTH MODEL

    Directory of Open Access Journals (Sweden)

    Wei-Bin Zhang

    2015-06-01

    Full Text Available The purpose of this study is to introduce tourism, externalities, and public goods to a small-open growth with endogenous wealth and public goods supply. We develop the model on the basis of the Solow-Uzawa growth model, the neoclassical neoclassical growth theory with externalities, and ideas from tourism economics. The economy consists of three – service, industrial, and public - sectors. The production side is based on the traditional growth theories, while the household behavior is described by an alternative utility function proposed by Zhang. We introduce endogenous land distribution between housing and supply of services. The industrial and service sectors are perfectly competitive subject to the government’s taxation. The public sector is financially supported by the government. We introduce taxes not only on producers, but also on consumers’ incomes from wage, land, and interest of wealth, consumption of goods and services, and housing. We simulate the motion of the national economy and show the existence of a unique stable equilibrium. We carry out comparative dynamic analysis with regard to the rate of interest in the global market, the total productivity of the service sector, tax rate on the service sector, tax rate on consumption of services, human capital, the propensity to consume services, and the impact of public services on the productivity of the industrial sector. The comparative dynamic analysis provides some important insights into the complexity of open economies with endogenous wealth, public goods, and externalities.

  6. Climate driven crop planting date in the ACME Land Model (ALM): Impacts on productivity and yield

    Science.gov (United States)

    Drewniak, B.

    2017-12-01

    Climate is one of the key drivers of crop suitability and productivity in a region. The influence of climate and weather on the growing season determine the amount of time crops spend in each growth phase, which in turn impacts productivity and, more importantly, yields. Planting date can have a strong influence on yields with earlier planting generally resulting in higher yields, a sensitivity that is also present in some crop models. Furthermore, planting date is already changing and may continue, especially if longer growing seasons caused by future climate change drive early (or late) planting decisions. Crop models need an accurate method to predict plant date to allow these models to: 1) capture changes in crop management to adapt to climate change, 2) accurately model the timing of crop phenology, and 3) improve crop simulated influences on carbon, nutrient, energy, and water cycles. Previous studies have used climate as a predictor for planting date. Climate as a plant date predictor has more advantages than fixed plant dates. For example, crop expansion and other changes in land use (e.g., due to changing temperature conditions), can be accommodated without additional model inputs. As such, a new methodology to implement a predictive planting date based on climate inputs is added to the Accelerated Climate Model for Energy (ACME) Land Model (ALM). The model considers two main sources of climate data important for planting: precipitation and temperature. This method expands the current temperature threshold planting trigger and improves the estimated plant date in ALM. Furthermore, the precipitation metric for planting, which synchronizes the crop growing season with the wettest months, allows tropical crops to be introduced to the model. This presentation will demonstrate how the improved model enhances the ability of ALM to capture planting date compared with observations. More importantly, the impact of changing the planting date and introducing tropical

  7. 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.

  8. Milk yield persistency in Brazilian Gyr cattle based on a random regression model.

    Science.gov (United States)

    Pereira, R J; Verneque, R S; Lopes, P S; Santana, M L; Lagrotta, M R; Torres, R A; Vercesi Filho, A E; Machado, M A

    2012-06-15

    With the objective of evaluating measures of milk yield persistency, 27,000 test-day milk yield records from 3362 first lactations of Brazilian Gyr cows that calved between 1990 and 2007 were analyzed with a random regression model. Random, additive genetic and permanent environmental effects were modeled using Legendre polynomials of order 4 and 5, respectively. Residual variance was modeled using five classes. The average lactation curve was modeled using a fourth-order Legendre polynomial. Heritability estimates for measures of persistency ranged from 0.10 to 0.25. Genetic correlations between measures of persistency and 305-day milk yield (Y305) ranged from -0.52 to 0.03. At high selection intensities for persistency measures and Y305, few animals were selected in common. As the selection intensity for the two traits decreased, a higher percentage of animals were selected in common. The average predicted breeding values for Y305 according to year of birth of the cows had a substantial annual genetic gain. In contrast, no improvement in the average persistency breeding value was observed. We conclude that selection for total milk yield during lactation does not identify bulls or cows that are genetically superior in terms of milk yield persistency. A measure of persistency represented by the sum of deviations of estimated breeding value for days 31 to 280 in relation to estimated breeding value for day 30 should be preferred in genetic evaluations of this trait in the Gyr breed, since this measure showed a medium heritability and a genetic correlation with 305-day milk yield close to zero. In addition, this measure is more adequate at the time of peak lactation, which occurs between days 25 and 30 after calving in this breed.

  9. Evaluating accuracy of DSSAT model for soybean yield estimation using satellite weather data

    Science.gov (United States)

    Ovando, Gustavo; Sayago, Silvina; Bocco, Mónica

    2018-04-01

    Crop models allow simulating the development and yield of the crops, to represent and to evaluate the influence of multiple factors. The DSSAT cropping system model is one of the most widely used and contains CROPGRO module for soybean. This crop has a great importance for many southern countries of Latin America and for Argentina. Solar radiation and rainfall are necessary variables as inputs for crop models; however these data are not as readily available. The satellital products from Clouds and Earth's Radiant Energy System (CERES) and Tropic Rainfall Measurement Mission (TRMM) provide continuous spatial and temporal information of solar radiation and precipitation, respectively. This study evaluates and quantifies the uncertainty in estimating soybean yield using a DSSAT model, when recorded weather data are replaced with CERES and TRMM ones. Different percentages of data replacements, soybean maturity groups and planting dates are considered, for 2006-2016 period in Oliveros (Argentina). Results show that CERES and TRMM products can be used for soybean yield estimation with DSSAT considering that: percentage of data replacement, campaign, planting date and maturity group, determine the amounts and trends of yield errors. Replacements with CERES data up to 30% result in %RMSE lower than 10% in 87% of the cases; while the replacement with TRMM data presents the best statisticals in campaigns with high yields. Simulations based entirely on CERES solar radiation give better results than those with TRMM. In general, similar percentages of replacement show better performance in the estimation of soybean yield for solar radiation than the replacement of precipitation values.

  10. Soil Erosion and Sediment Yield Modelling in the Pra River Basin of ...

    African Journals Online (AJOL)

    Parameters of the model were formatted as raster layers and multiplied using the raster calculator module in ArcGIS to produce a soil erosion map. The concept of sediment delivery ratio (SDR) was used to determine the annual sediment yield of the catchment by integrating a raster SDR layer with that of the soil erosion ...

  11. Development of Models for Predicting the Yield and Quality of Soymilk

    African Journals Online (AJOL)

    Models were developed to predict the yield and quality of soymilk, one of soybean products. The quality characteristics investigated were total solids, protein content and fat content. The processing parameters considered were Amount of water added during grinding per Kg of dry seed, AW; Blanching time, BT and Heating ...

  12. Crop growth modelling and crop yield forecasting using satellite derived meteorological inputs

    NARCIS (Netherlands)

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

    2006-01-01

    One of the key challenges for operational crop monitoring and yield forecasting using crop models is to find spatially representative meteorological input data. Currently, weather inputs are often interpolated from low density networks of weather stations or derived from output from coarse (0.5

  13. 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...

  14. Soil Erosion and Sediment Yield Modelling in the Pra River Basin of ...

    African Journals Online (AJOL)

    kusimi

    are applicable at catchment scale; event based; and continuous models of spatially and temporally distribution (i.e., 2D) (e.g., Amore et al., 2004; Fistikoglu ..... the integration of RUSLE into GIS give a vivid spatial dimension in soil erosion and sediment yield in the Pra Basin. Given the elements and processes prevailing in ...

  15. 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,

  16. 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

  17. Attribute Selection Impact on Linear and Nonlinear Regression Models for Crop Yield Prediction

    Directory of Open Access Journals (Sweden)

    Alberto Gonzalez-Sanchez

    2014-01-01

    Full Text Available Efficient cropping requires yield estimation for each involved crop, where data-driven models are commonly applied. In recent years, some data-driven modeling technique comparisons have been made, looking for the best model to yield prediction. However, attributes are usually selected based on expertise assessment or in dimensionality reduction algorithms. A fairer comparison should include the best subset of features for each regression technique; an evaluation including several crops is preferred. This paper evaluates the most common data-driven modeling techniques applied to yield prediction, using a complete method to define the best attribute subset for each model. Multiple linear regression, stepwise linear regression, M5′ regression trees, and artificial neural networks (ANN were ranked. The models were built using real data of eight crops sowed in an irrigation module of Mexico. To validate the models, three accuracy metrics were used: the root relative square error (RRSE, relative mean absolute error (RMAE, and correlation factor (R. The results show that ANNs are more consistent in the best attribute subset composition between the learning and the training stages, obtaining the lowest average RRSE (86.04%, lowest average RMAE (8.75%, and the highest average correlation factor (0.63.

  18. Goodness-of-fit test in a multivariate errors-in-variables model $AX=B$

    OpenAIRE

    Kukush, Alexander; Tsaregorodtsev, Yaroslav

    2016-01-01

    We consider a multivariable functional errors-in-variables model $AX\\approx B$, where the data matrices $A$ and $B$ are observed with errors, and a matrix parameter $X$ is to be estimated. A goodness-of-fit test is constructed based on the total least squares estimator. The proposed test is asymptotically chi-squared under null hypothesis. The power of the test under local alternatives is discussed.

  19. A goods characteristics model of the hedonic ageing equation: evidence from a French marriage bureau

    OpenAIRE

    Sam Cameron; Nicolas Vaillant

    2005-01-01

    The present paper adopts a modelling perspective derived from goods characteristics analysis [Lancaster (1971)] and the general ideas of transactions costs. This is implemented in estimated equations, which feature the age of partner sought as the dependent variable and own age and various other personal characteristics, and characteristics desired in a partner, as the right-hand side variables. The results show a very strong relationship between age and desired partner age. More interestingl...

  20. 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

  1. Getting water right: A case study in water yield modelling based on precipitation data.

    Science.gov (United States)

    Pessacg, Natalia; Flaherty, Silvia; Brandizi, Laura; Solman, Silvina; Pascual, Miguel

    2015-12-15

    Water yield is a key ecosystem service in river basins and especially in dry regions around the World. In this study we carry out a modelling analysis of water yields in the Chubut River basin, located in one of the driest districts of Patagonia, Argentina. We focus on the uncertainty around precipitation data, a driver of paramount importance for water yield. The objectives of this study are to: i) explore the spatial and numeric differences among six widely used global precipitation datasets for this region, ii) test them against data from independent ground stations, and iii) explore the effects of precipitation data uncertainty on simulations of water yield. The simulations were performed using the ecosystem services model InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) with each of the six different precipitation datasets as input. Our results show marked differences among datasets for the Chubut watershed region, both in the magnitude of precipitations and their spatial arrangement. Five of the precipitation databases overestimate the precipitation over the basin by 50% or more, particularly over the more humid western range. Meanwhile, the remaining dataset (Tropical Rainfall Measuring Mission - TRMM), based on satellite measurements, adjusts well to the observed rainfall in different stations throughout the watershed and provides a better representation of the precipitation gradient characteristic of the rain shadow of the Andes. The observed differences among datasets in the representation of the rainfall gradient translate into large differences in water yield simulations. Errors in precipitation of +30% (-30%) amplify to water yield errors ranging from 50 to 150% (-45 to -60%) in some sub-basins. These results highlight the importance of assessing uncertainties in main input data when quantifying and mapping ecosystem services with biophysical models and cautions about the undisputed use of global environmental datasets. Copyright

  2. Simulating the potential yield and yield gaps of sugar beet due to water and nitrogen limitations in Khorasan province using SUCROS model

    Directory of Open Access Journals (Sweden)

    R Deihimfard

    2015-12-01

    Full Text Available Introduction Crop productivity is highly constrained by water and nitrogen limitations in many areas of the world (Kalra et al., 2007. Therefore, there is a need to investigate more on nitrogen and water management to achieve higher production as well as quality. Irrigated sugar beet in the cropping systems of Khorasan province in northeastern of Iran accounts for about 34% of the land area under sugar beet production (~115,000 ha with an average yield of around 36 t.ha-1 (Anonymous, 2009. However, there is a huge yield gap (the difference between potential and water and nitrogen-limited yield mainly due to biotic and abiotic factors causing major reduction in farmers’ yield. Accordingly, yield gap analysis should be carried out to reduce the yield reduction and reach the farmer’s yield to the potential yield. The current study aimed to simulate potential yield as well as yield gap related to water and nitrogen shortage in the major sugar beet-growing areas of Khorasan province of Iran. Materials and methods This study was carried out in 6 locations across Khorasan province, which is located in the northeast of Iran. Long term weather data for 1986 to 2009 were obtained from Iran Meteorological Organization for 6 selected locations. The weather data included daily sunshine hours (h, daily maximum and minimum temperatures (◦C, and daily rainfall (mm. Daily solar radiation was estimated using the Goudriaan (1993 method. The validated SUCROSBEET model (Deihimfard, 2011; Deihimfard et al., 2011 was then used to estimate potential, water and nitrogen-limited yield and yield gap of sugar beet for 6 selected locations across the Khorasan province in the northeast of Iran. This model simulates the impacts of weather, genotype and management factors on crop growth and development, soil water and nitrogen balance on a daily basis and finally it predicts crop yield. The model requires input data, including local weather and soil conditions, cultivar

  3. Water deficit effects on maize yields modeled under current and greenhouse climates

    International Nuclear Information System (INIS)

    Muchow, R.C.; Sinclair, T.R.

    1991-01-01

    The availability of water imposes one of the major limits on rainfed maize (Zea mays L.) productivity. This analysis was undertaken in an attempt to quantify the effects of limited water on maize growth and yield by extending a simple, mechanistic model in which temperature regulates crop development and intercepted solar radiation is used to calculate crop biomass accumulation. A soil water budget was incorporated into the model by accounting for inputs from rainfall and irrigation, and water use by soil evaporation and crop transpiration. The response functions of leaf area development and crop gas exchange to the soil water budget were developed from experimental studies. The model was used to interpret a range of field experiments using observed daily values of temperature, solar radiation, and rainfall or irrigation, where water deficits of varying durations developed at different stages of growth. The relative simplicity of the model and its robustness in simulating maize yields under a range of water-availability conditions allows the model to be readily used for studies of crop performance under alternate conditions. One such study, presented here, was a yield assessment for rainfed maize under possible greenhouse climates where temperature and atmospheric CO 2 concentration were increased. An increase in temperature combined with decreased rainfall lowered grain yield, although the increase in crop water use efficiency associated with elevated CO 2 concentration ameliorated the response to the greenhouse climate. Grain yields for the greenhouse climates as compared to current conditions increased, or decreased only slightly, except when the greenhouse climate was assumed to result in severly decreased rainfall

  4. Modelling spatial and temporal variations of annual suspended sediment yields from small agricultural catchments.

    Science.gov (United States)

    Rymszewicz, A; Bruen, M; O'Sullivan, J J; Turner, J N; Lawler, D M; Harrington, J R; Conroy, E; Kelly-Quinn, M

    2018-04-01

    Estimates of sediment yield are important for ecological and geomorphological assessment of fluvial systems and for assessment of soil erosion within a catchment. Many regulatory frameworks, such as the Convention for the Protection of the Marine Environment of the North-East Atlantic, derived from the Oslo and Paris Commissions (OSPAR) require reporting of annual sediment fluxes. While they may be measured in large rivers, sediment flux is rarely measured in smaller rivers. Measurements of sediment transport at a national scale can be also challenging and therefore, sediment yield models are often utilised by water resource managers for the predictions of sediment yields in the ungauged catchments. Regression based models, calibrated to field measurements, can offer an advantage over complex and computational models due to their simplicity, easy access to input data and due to the additional insights into factors controlling sediment export in the study sites. While traditionally calibrated to long-term average values of sediment yields such predictions cannot represent temporal variations. This study addresses this issue in a novel way by taking account of the variation from year to year in hydrological variables in the developed models (using annual mean runoff, annual mean flow, flows exceeded in five percentage of the time (Q5) and seasonal rainfall estimated separately for each year of observations). Other parameters included in the models represent spatial differences influenced by factors such as soil properties (% poorly drained soils and % peaty soils), land-use (% pasture or % arable lands), channel slope (S1085) and drainage network properties (drainage density). Catchment descriptors together with year-specific hydrological variables can explain both spatial differences and inter-annual variability of suspended sediment yields. The methodology is demonstrated by deriving equations from Irish data-sets (compiled in this study) with the best model

  5. 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.

  6. 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.

  7. 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 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.

  8. Gene therapy approaches for lysosomal storage disorders, a good model for the treatment of mendelian diseases.

    Science.gov (United States)

    Tomanin, Rosella; Zanetti, Alessandra; Zaccariotto, Eva; D'Avanzo, Francesca; Bellettato, Cinzia M; Scarpa, Maurizio

    2012-07-01

    This review describes the different gene therapy technologies applied to approach lysosomal storage disorders, monogenic conditions, with known genetic and biochemical defects, for many of which animal models are available. Both viral and nonviral procedures are described, underlying the specific needs that the treatment of genetic disorders requires. Lysosomal storage disorders represent a good model of study of gene therapeutic procedures that are, or could be, relevant to the treatment of several other mendelian diseases. © 2012 The Author(s)/Acta Paediatrica © 2012 Foundation Acta Paediatrica.

  9. 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.

  10. Sustainable stemwood yield in relation to the nitrogen balance of forest plantations: a model analysis.

    Science.gov (United States)

    Dewar, Roderick C.; McMurtrie, Ross E.

    1996-01-01

    We used an existing analytical model of stemwood growth in relation to nitrogen supply, which we describe in an accompanying paper, to examine the long-term effects of harvesting and fire on tree growth. Our analysis takes into account the balance between nitrogen additions from deposition, fixation, and fertilizer applications, and nitrogen losses from stemwood harvesting, regeneration burning, leaching and gaseous emissions. Using a plausible set of parameter values for Eucalyptus, we conclude that nitrogen loss through fire is the main factor limiting sustainable yield, defined as the maximum mean annual stemwood volume increment obtained in the steady state, if management practices are continued indefinitely. The sustainable yield is 30 m(3) ha(-1) year(-1) with harvesting only, 15 m(3) ha(-1) year(-1) with harvesting and regeneration burning, and 13 m(3) ha(-1) year(-1) with harvesting, fire, leaching and gaseous emissions combined. Our approach uses a simple graphical analysis that provides a useful framework for examining the factors affecting sustainable yield. The graphical analysis is also useful for extending the application of the present model to the effects of climate change on sustainable yield, or for interpreting the behavior of other models of sustainable forest growth.

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

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Jensen, Anders Vestergaard

    2004-01-01

    This paper concerns the assessment and modelling of so-called logistics and goods effects (LG-effects) as part of a wider economic analysis by use of the developed CLG-DSS model. The results presented are based an on-going study, Task 9 about evaluation modelling and decision support systems (DSS...... companies are taking account of logistics and transport by setting up, among other things, specific departments to improve their handling. Some aspects in the transport sector concerning goods movement and consequences have not so far got the attention they deserve. In CLG Task 9 four LG-effects have been...... The aim of this paper is to present these four LG-effects with a special emphasis on a possible way of modelling these and interpreting their importance. The calculations are carried out by using the CLG-DSS model and case studies concerning the fixed links across the Great Belt and Øresund...

  12. A model independent determination of the B{yields}X{sub s}{gamma} decay rate

    Energy Technology Data Exchange (ETDEWEB)

    Bernlochner, Florian U. [Victoria Univ., BC (Canada); Lacker, Heiko [Humboldt-Universitaet, Berlin (Germany); Ligeti, Zoltan [California Univ., Berkeley, CA (United States). Ernest Orlando Lawrence Berkeley National Laboratory; Stewart, Iain W. [Massachusetts Institute of Technology, Cambridge, MA (United States). Center for Theoretical Physics; Tackmann, Frank J.; Tackmann, Kerstin [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

    2013-03-15

    The goal of the SIMBA collaboration is to provide a global fit to the available measurements of inclusive B{yields}X{sub s}{gamma} and B{yields}X{sub u}l{nu} decays. By performing a global fit one is able to simultaneously determine the relevant normalizations, i.e. the total B{yields}X{sub s}{gamma} rate and the CKM-matrix element vertical stroke Vub vertical stroke, together with the required hadronic parameters, most importantly the b-quark mass and the b-quark distribution function in the B-meson, called the shape function. In this talk, the current status on the model-independent determination of the shape function and vertical stroke C{sub 7}{sup incl}V{sub tb}V{sub ts}{sup *} vertical stroke, which parametrizes the total B{yields}X{sub s}{gamma} rate, from a global fit to the available B{yields}X{sub s}{gamma} measurements from Babar and Belle is presented. In particular, the theoretical uncertainties originating from variations of the different factorization scales are evaluated.

  13. Impact of parameter representation in gas-particle partitioning on aerosol yield model prediction

    Science.gov (United States)

    Kelly, Janya L.

    A kinetic box model is used to highlight the importance of parameter representation in predicting the formation of secondary organic aerosol (SOA) from the photo-oxidation of toluene through a subset of the University of Leeds Master Chemical Mechanism (MCM) version 3.1, and a kinetically based gas-particle partitioning approach. The model provides a prediction of the total aerosol yield and a tentative speciation of aerosols initialized from experimental data from York University's indoor smog chamber. A series of model sensitivity experiments were performed to study the relative importance of different parameters in SOA formation, with emphasis on vapour pressure, accommodation coefficient and NOx conditions. Early sensitivity experiments indicate vapour pressure to be a critical parameter in the partitioning and final aerosol yield. Current estimation methods are highly sensitive to boiling point temperature and can lead to the propagation of errors in the model. Of concern is the estimation of vapour pressure for compounds containing organic nitrates (major contributors to the aerosol speciation in this study). Results indicate that approximately +/- 80% error can be expected in the final aerosol mass from errors in the boiling point temperature and vapour pressure estimation methods, and, that for most experiments, this error alone cannot account for a general under prediction in the aerosol mass. Current experimental conditions dictate a very high initial NOx environment and a much higher final aerosol yield compared to other smog chamber studies, leading to the question of whether the model results arise from unique experimental conditions (relative to other chambers), from using different pathways in MCMv3.1 leading to different aerosol speciation (from the high NOx conditions), or from the physical representation of partitioning in the model. Results show that the choice of isopropyl nitrite as the hydroxyl radical oxidation source may be contributing to

  14. Modelling a duopoly market of the day-to-day goods

    Directory of Open Access Journals (Sweden)

    Sherstennykov Yuriy V.

    2013-03-01

    Full Text Available Management of competitiveness of a production enterprise is directly connected with issues of formation of competitive strategies, which requires a thorough analysis of those components of the enterprise activity, which could become the basis of formation and strengthening of stable competitive advantages. The existing models do not take into account the market infrastructure and, that is why, not quite suitable for being used in the practical activity of a firm in a competitive market. The article develops dynamic models of quantitative and pricing duopolies, which describe activity of firms, which deal with production, storing and selling day-to-day goods. The models allow taking into account interdependence of the current state of the market and current production facilities of enterprises. The proposed models give a possibility of a purposeful selection of strategic behaviour of duopolists. The conducted analysis of strategies of competitive firms revealed significant influence of market characteristics upon results of economic activity of firms.

  15. Models for predicting water use and crop yields - A Cuban experience

    International Nuclear Information System (INIS)

    Ruiz, M.E.; Utset, A.

    2004-01-01

    Modelling has come into agriculture because of several reasons: 1) More comprehension about the processes that take place at the soil water atmosphere continuum SWAC, 2) Specialists from different fields come to work together, 3) Different and more efficient codes for obtaining the solutions of complex equations were introduced, 4) Amazing development of hardware and supporting softwares, 5) Large data banks coming from a lot of years of experimental laboratory and field work (mainly at the developed countries) and 6) Desires to put together as much SWAC processes as possible to get a better comprehension of such a complex system. Here we briefly present some of the results obtained in Cuba using simulation model SWACROP for estimating water use and yields in potato and model SWAP for sugar cane yields. The relationship between estimated and measured soil moisture contents for two different irrigation treatments for potato in a Rhodic Ferralsol is shown. Simulated values matched better the measured values for the higher water level. Estimated and measured potato yields are shown. A determination coefficient of 0.69 was obtained for a 95 % of confidence limit. Although this value could be considered somewhat low, it should be remembered that the soil hydraulic properties used for the simulation were taken from the results of Ruiz and Utset (1992) for this kind of soil, but not determined at the same location where potato yields were measured. Moreover, all the data considering the different irrigation treatments were considered. For sugar cane, a calibration was made for a Rhodic Ferralsol. Later the model was tested for another location. The data of crop yields, seeding dates corresponding to three different soils were used for comparing with simulation results. The SWAP simulations agree with the measured data. However, when averaged values for the input parameters are used in the model, a determination coefficient between simulated and measured output was only 0

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

    Energy Technology Data Exchange (ETDEWEB)

    Andrews, Brett H. [PITT PACC, Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260 (United States); Weinberg, David H.; Schönrich, Ralph; Johnson, Jennifer A., E-mail: andrewsb@pitt.edu [Department of Astronomy, The Ohio State University, 140 West 18th Avenue, Columbus, OH 43210 (United States)

    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. Coping among individuals with multiple sclerosis: Evaluating a goodness-of-fit model.

    Science.gov (United States)

    Roubinov, Danielle S; Turner, Aaron P; Williams, Rhonda M

    2015-05-01

    Multiple sclerosis (MS) is a chronic illness involving both controllable and uncontrollable stressors. The goodness-of-fit hypothesis posits that managing stressors effectively requires the use of different coping approaches in the face of controllable and uncontrollable stressors. To test the applicability of the goodness-of-fit model in a sample of adults with MS, we evaluated the ratio of 2 types of coping (an active problem-solving approach and an emotion-based meaning-focused approach) as a moderator of the relations between stress uncontrollability and mental health outcomes. Participants were veterans with MS (N = 90) receiving medical services through the Veterans Health Administration who completed telephone-based interviews. Regression analyses tested the interaction of stress uncontrollability and the problem- and meaning-focused coping ratio on anxious and depressive symptoms. Significant interactions were probed at 1 SD above the mean of coping (use of predominantly problem-focused coping) and 1 SD below the mean of coping (use of predominantly meaning-focused coping). Findings largely supported the goodness-of-fit hypothesis. Anxiety and depressive symptoms were elevated when participants used more problem-focused strategies relative to meaning-focused strategies in the face of perceived uncontrollable stress. Conversely, symptoms of anxiety and depression were lower when uncontrollable stress was met with predominantly meaning-focused coping; however, the relations did not reach statistical significance. The impact of uncontrollable stressors on mental health outcomes for individuals with MS may vary depending on the degree to which problem-focused versus meaning-focused coping strategies are employed, lending support to the goodness-of-fit model. (c) 2015 APA, all rights reserved).

  18. Development of a comprehensive watershed model applied to study stream yield under drought conditions

    Science.gov (United States)

    Perkins, S.P.; Sophocleous, M.

    1999-01-01

    We developed a model code to simulate a watershed's hydrology and the hydraulic response of an interconnected stream-aquifer system, and applied the model code to the Lower Republican River Basin in Kansas. The model code links two well-known computer programs: MODFLOW (modular 3-D flow model), which simulates ground water flow and stream-aquifer interaction; and SWAT (soil water assessment tool), a soil water budget simulator for an agricultural watershed. SWAT represents a basin as a collection of subbasins in terms of soil, land use, and weather data, and simulates each subbasin on a daily basis to determine runoff, percolation, evaporation, irrigation, pond seepages and crop growth. Because SWAT applies a lumped hydrologic model to each subbasin, spatial heterogeneities with respect to factors such as soil type and land use are not resolved geographically, but can instead be represented statistically. For the Republican River Basin model, each combination of six soil types and three land uses, referred to as a hydrologic response unit (HRU), was simulated with a separate execution of SWAT. A spatially weighted average was then taken over these results for each hydrologic flux and time step by a separate program, SWBAVG. We wrote a package for MOD-FLOW to associate each subbasin with a subset of aquifer grid cells and stream reaches, and to distribute the hydrologic fluxes given for each subbasin by SWAT and SWBAVG over MODFLOW's stream-aquifer grid to represent tributary flow, surface and ground water diversions, ground water recharge, and evapotranspiration from ground water. The Lower Republican River Basin model was calibrated with respect to measured ground water levels, streamflow, and reported irrigation water use. The model was used to examine the relative contributions of stream yield components and the impact on stream yield and base flow of administrative measures to restrict irrigation water use during droughts. Model results indicate that tributary

  19. Models and tests of optimal density and maximal yield for crop plants.

    Science.gov (United States)

    Deng, Jianming; Ran, Jinzhi; Wang, Zhiqiang; Fan, Zhexuan; Wang, Genxuan; Ji, Mingfei; Liu, Jing; Wang, Yun; Liu, Jianquan; Brown, James H

    2012-09-25

    We introduce a theoretical framework that predicts the optimum planting density and maximal yield for an annual crop plant. Two critical parameters determine the trajectory of plant growth and the optimal density, N(opt), where canopies of growing plants just come into contact, and competition: (i) maximal size at maturity, M(max), which differs among varieties due to artificial selection for different usable products; and (ii) intrinsic growth rate, g, which may vary with variety and environmental conditions. The model predicts (i) when planting density is less than N(opt), all plants of a crop mature at the same maximal size, M(max), and biomass yield per area increases linearly with density; and (ii) when planting density is greater than N(opt), size at maturity and yield decrease with -4/3 and -1/3 powers of density, respectively. Field data from China show that most annual crops, regardless of variety and life form, exhibit similar scaling relations, with maximal size at maturity, M(max), accounting for most of the variation in optimal density, maximal yield, and energy use per area. Crops provide elegantly simple empirical model systems to study basic processes that determine the performance of plants in agricultural and less managed ecosystems.

  20. Estimation of effects of photosynthesis response functions on rice yields and seasonal variation of CO2 fixation using a photosynthesis-sterility type of crop yield model

    International Nuclear Information System (INIS)

    Kaneko, D.; Moriwaki, Y.

    2008-01-01

    This study presents a crop production model improvement: the previously adopted Michaelis-Menten (MM) type photosynthesis response function (fsub(rad-MM)) was replaced with a Prioul-Chartier (PC) type function (fsub(rad-PC)). The authors' analysis reflects concerns regarding the background effect of global warming, under simultaneous conditions of high air temperature and strong solar radiation. The MM type function fsub(rad-MM) can give excessive values leading to an overestimate of photosynthesis rate (PSN) and grain yield for paddy-rice. The MM model is applicable to many plants whose (PSN) increases concomitant with increased insolation: wheat, maize, soybean, etc. For paddy rice, the PSN apparently shows a maximum PSN. This paper proves that the MM model overestimated the PSN for paddy rice for sufficient solar radiation: the PSN using the PC model yields 10% lower values. However, the unit crop production index (CPIsub(U)) is almost independent of the MM and PC models because of respective standardization of both PSN and crop production index using average PSNsub(0) and CPIsub(0). The authors improved the estimation method using a photosynthesis-and-sterility based crop situation index (CSIsub(E)) to produce a crop yield index (CYIsub(E)), which is used to estimate rice yields in place of the crop situation index (CSI); the CSI gives a percentage of rice yields compared to normal annual production. The model calculates PSN including biomass effects, low-temperature sterility, and high-temperature injury by incorporating insolation, effective air temperature, the normalized difference vegetation index (NDVI), and effects of temperature on photosynthesis. Based on routine observation data, the method enables automated crop-production monitoring in remote regions without special observations. This method can quantify grain production early to raise an alarm in Southeast Asian countries, which must confront climate fluctuation through this era of global

  1. 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

  2. A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

    Science.gov (United States)

    Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

    2018-04-01

    In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

  3. Testing the goodness of fit of selected infiltration models on soils with different land use histories

    International Nuclear Information System (INIS)

    Mbagwu, J.S.C.

    1993-10-01

    Six infiltration models, some obtained by reformulating the fitting parameters of the classical Kostiakov (1932) and Philip (1957) equations, were investigated for their ability to describe water infiltration into highly permeable sandy soils from the Nsukka plains of SE Nigeria. The models were Kostiakov, Modified Kostiakov (A), Modified Kostiakov (B), Philip, Modified Philip (A) and Modified Philip (B). Infiltration data were obtained from double ring infiltrometers on field plots established on a Knadic Paleustult (Nkpologu series) to investigate the effects of land use on soil properties and maize yield. The treatments were; (i) tilled-mulched (TM), (ii) tilled-unmulched (TU), (iii) untilled-mulched (UM), (iv) untilled-unmulched (UU) and (v) continuous pasture (CP). Cumulative infiltration was highest on the TM and lowest on the CP plots. All estimated model parameters obtained by the best fit of measured data differed significantly among the treatments. Based on the magnitude of R 2 values, the Kostiakov, Modified Kostiakov (A), Philip and Modified Philip (A) models provided best predictions of cumulative infiltration as a function of time. Comparing experimental with model-predicted cumulative infiltration showed, however, that on all treatments the values predicted by the classical Kostiakov, Philip and Modified Philip (A) models deviated most from experimental data. The other models produced values that agreed very well with measured data. Considering the eases of determining the fitting parameters it is proposed that on soils with high infiltration rates, either Modified Kostiakov model (I = Kt a + Ict) or Modified Philip model (I St 1/2 + Ict), (where I is cumulative infiltration, K, the time coefficient, t, time elapsed, 'a' the time exponent, Ic the equilibrium infiltration rate and S, the soil water sorptivity), be used for routine characterization of the infiltration process. (author). 33 refs, 3 figs 6 tabs

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Ali William Canaza-Cayo

    2015-10-01

    Full Text Available 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.

  6. Simulating and Predicting Cereal Crop Yields in Ethiopia: Model Calibration and Verification

    Science.gov (United States)

    Yang, M.; Wang, G.; Ahmed, K. F.; Eggen, M.; Adugna, B.; Anagnostou, E. N.

    2017-12-01

    Agriculture in developing countries are extremely vulnerable to climate variability and changes. In East Africa, most people live in the rural areas with outdated agriculture techniques and infrastructure. Smallholder agriculture continues to play a key role in this area, and the rate of irrigation is among the lowest of the world. As a result, seasonal and inter-annual weather patterns play an important role in the spatiotemporal variability of crop yields. This study investigates how various climate variables (e.g., temperature, precipitation, sunshine) and agricultural practice (e.g., fertilization, irrigation, planting date) influence cereal crop yields using a process-based model (DSSAT) and statistical analysis, and focuses on the Blue Nile Basin of Ethiopia. The DSSAT model is driven with meteorological forcing from the ECMWF's latest reanalysis product that cover the past 35 years; the statistical model will be developed by linking the same meteorological reanalysis data with harvest data at the woreda level from the Ethiopian national dataset. Results from this study will set the stage for the development of a seasonal prediction system for weather and crop yields in Ethiopia, which will serve multiple sectors in coping with the agricultural impact of climate variability.

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

    Science.gov (United States)

    Ashraf, M Irfan; Meng, Fan-Rui; Bourque, Charles P-A; MacLean, David A

    2015-01-01

    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 technology

  8. 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

  9. Critical-point model to estimate yield loss caused by Asian soybean rust

    Directory of Open Access Journals (Sweden)

    Anderson Luiz Durante Danelli

    2015-12-01

    Full Text Available ABSTRACTA model to estimate yield loss caused by Asian soybean rust (ASR (Phakopsora pachyrhizi was developed by collecting data from field experiments during the growing seasons 2009/10 and 2010/11, in Passo Fundo, RS. The disease intensity gradient, evaluated in the phenological stages R5.3, R5.4 and R5.5 based on leaflet incidence (LI and number of uredinium and lesions/cm2, was generated by applying azoxystrobin 60 g a.i/ha + cyproconazole 24 g a.i/ha + 0.5% of the adjuvant Nimbus. The first application occurred when LI = 25% and the remaining ones at 10, 15, 20 and 25-day intervals. Harvest occurred at physiological maturity and was followed by grain drying and cleaning. Regression analysis between the grain yield and the disease intensity assessment criteria generated 56 linear equations of the yield loss function. The greatest loss was observed in the earliest growth stage, and yield loss coefficients ranged from 3.41 to 9.02 kg/ha for each 1% LI for leaflet incidence, from 13.34 to 127.4 kg/ha/1 lesion/cm2 for lesion density and from 5.53 to 110.0 kg/ha/1 uredinium/cm2 for uredinium density.

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

    French, V. (Principal Investigator)

    1982-01-01

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

  12. Influence of Different Yield Loci on Failure Prediction with Damage Models

    Science.gov (United States)

    Heibel, S.; Nester, W.; Clausmeyer, T.; Tekkaya, A. E.

    2017-09-01

    Advanced high strength steels are widely used in the automotive industry to simultaneously improve crash performance and reduce the car body weight. A drawback of these multiphase steels is their sensitivity to damage effects and thus the reduction of ductility. For that reason the Forming Limit Curve is only partially suitable for this class of steels. An improvement in failure prediction can be obtained by using damage mechanics. The objective of this paper is to comparatively review the phenomenological damage model GISSMO and the Enhanced Lemaitre Damage Model. GISSMO is combined with three different yield loci, namely von Mises, Hill48 and Barlat2000 to investigate the influence of the choice of the plasticity description on damage modelling. The Enhanced Lemaitre Model is used with Hill48. An inverse parameter identification strategy for a DP1000 based on stress-strain curves and optical strain measurements of shear, uniaxial, notch and (equi-)biaxial tension tests is applied to calibrate the models. A strong dependency of fracture strains on the choice of yield locus can be observed. The identified models are validated on a cross-die cup showing ductile fracture with slight necking.

  13. A Global Data Analysis for Representing Sediment and Particulate Organic Carbon Yield in Earth System Models

    Energy Technology Data Exchange (ETDEWEB)

    Tan, Zeli [Pacific Northwest National Laboratory, Richland WA USA; Leung, L. Ruby [Pacific Northwest National Laboratory, Richland WA USA; Li, Hongyi [Montana State University, Bozeman MT USA; Tesfa, Teklu [Pacific Northwest National Laboratory, Richland WA USA; Vanmaercke, Matthias [Département de Géographie, Université de Liège, Liege Belgium; Poesen, Jean [Department of Earth and Environmental Sciences, Division of Geography, KU Leuven, Leuven Belgium; Zhang, Xuesong [Pacific Northwest National Laboratory, Richland WA USA; Lu, Hui [Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing China; Hartmann, Jens [Institute for Geology, Center for Earth System Research and Sustainability, Universität Hamburg, Hamburg Germany

    2017-12-01

    Although sediment yield (SY) from water erosion is ubiquitous and its environmental consequences are well recognized, its impacts on the global carbon cycle remain largely uncertain. This knowledge gap is partly due to the lack of soil erosion modeling in Earth System Models (ESMs), which are important tools used to understand the global carbon cycle and explore its changes. This study analyzed sediment and particulate organic carbon yield (CY) data from 1081 and 38 small catchments (0.1-200 km27 ), respectively, in different environments across the globe. Using multiple statistical analysis techniques, we explored environmental factors and hydrological processes important for SY and CY modeling in ESMs. Our results show clear correlations of high SY with traditional agriculture, seismicity and heavy storms, as well as strong correlations between SY and annual peak runoff. These highlight the potential limitation of SY models that represent only interrill and rill erosion because shallow overland flow and rill flow have limited transport capacity due to their hydraulic geometry to produce high SY. Further, our results suggest that SY modeling in ESMs should be implemented at the event scale to produce the catastrophic mass transport during episodic events. Several environmental factors such as seismicity and land management that are often not considered in current catchment-scale SY models can be important in controlling global SY. Our analyses show that SY is likely the primary control on CY in small catchments and a statistically significant empirical relationship is established to calculate SY and CY jointly in ESMs.

  14. A Global Data Analysis for Representing Sediment and Particulate Organic Carbon Yield in Earth System Models

    Science.gov (United States)

    Tan, Zeli; Leung, L. Ruby; Li, Hongyi; Tesfa, Teklu; Vanmaercke, Matthias; Poesen, Jean; Zhang, Xuesong; Lu, Hui; Hartmann, Jens

    2017-12-01

    Although sediment yield (SY) from water erosion is ubiquitous and its environmental consequences are well recognized, its impacts on the global carbon cycle remain largely uncertain. This knowledge gap is partly due to the lack of soil erosion modeling in Earth System Models (ESMs), which are important tools used to understand the global carbon cycle and explore its changes. This study analyzed sediment and particulate organic carbon yield (CY) data from 1,081 and 38 small catchments (0.1-200 km2), respectively, in different environments across the globe. Using multiple statistical analysis techniques, we explored environmental factors and hydrological processes important for SY and CY modeling in ESMs. Our results show clear correlations of high SY with traditional agriculture, seismicity and heavy storms, as well as strong correlations between SY and annual peak runoff. These highlight the potential limitation of SY models that represent only interrill and rill erosion because shallow overland flow and rill flow have limited transport capacity due to their hydraulic geometry to produce high SY. Further, our results suggest that SY modeling in ESMs should be implemented at the event scale to produce the catastrophic mass transport during episodic events. Several environmental factors such as seismicity and land management that are often not considered in current catchment-scale SY models can be important in controlling global SY. Our analyses show that SY is likely the primary control on CY in small catchments and a statistically significant empirical relationship is established to calculate SY and CY jointly in ESMs.

  15. Evaluation of Precipitation Indices for Global Crop Modeling and Definition of Drought Response Function to Yields

    Science.gov (United States)

    Kaneko, D.

    2017-12-01

    Climate change initiates abnormal meteorological disasters. Drought causes climate instability, thus producing poor harvests because of low rates of photosynthesis and sterile pollination. This research evaluates drought indices regarding precipitation and includes this data in global geophysical crop models that concern with evaporation, stomata opening, advection-effects from sea surface temperature anomalies, photosynthesis, carbon partitioning, crop yields, and crop production. Standard precipitation index (SPI) is a useful tool because of related variable not used in the stomata model. However, SPI is not an adequate tool for drought in irrigated fields. Contrary to expectations, the global comparisons of spatial characteristics between stomata opening/evapotranspiration and SPI for monitoring continental crop extremes produced serious defects and obvious differences between evapotranspiration and the small stomata-opening phenomena. The reason for this is that SPI does not include surface air temperature in its analysis. The Penman equation (Epen) describes potential evaporation better than SPI for recent hot droughts caused by climate change. However, the distribution of precipitation is a necessary condition for crop monitoring because it affirms the trend of the dry results computed by crop models. Consequently, the author uses global precipitation data observed by microwave passive sensors on TRMM and GCOM-W satellites. This remote sensing data conveniently supplies spatial distributions of global and seasonal precipitation. The author has designed a model to measure the effects of drought on crop yield and the degree of stomata closure related to the photosynthesis rate. To determine yield effects, the drought injury function is defined by integrating stomata closure during the two seasons from flowering to pollination. The stomata, defined by ratio between Epen and Eac, reflect the effects of drought and irrigation. Stomata-closure model includes the

  16. A simple model for yield prediction of rice based on vegetation index derived from satellite and AMeDAS data during ripening period

    International Nuclear Information System (INIS)

    Wakiyama, Y.; Inoue, K.; Nakazono, K.

    2003-01-01

    The present study was conducted to show a simple model for rice yield predicting by using a vegetation index (NDVI) derived from satellite and meteorological data. In a field experiment, the relationship between the vegetation index and radiation absorbed by the rice canopy was investigated from transplanting to maturity. Their correlation held. This result revealed that the vegetation index could be used as a measure of absorptance of solar radiation by rice canopy. NDVI multiplied by solar radiation (SR) every day was accumulated (Σ(SR·NDVI)) from the field experiment. Σ(SR·NDVI) was plotted against above ground dry matter. It was obvious that they had a strong relationship. Rice yield largely depends on solar radiation and air temperature during the ripening period. Air temperature affects dry matter production. Relationships between Y SR -1 (Y: rice yield, SR: solar radiation) and mean air temperature were investigated from meteorological data and statistical data on rice yield. There was an optimum air temperature, 21.3°C, for ripening. When it was near 21.3°C in the ripening period, the rice yield was higher. We proposed a simple model for yield prediction of rice based on these results. The model is composed with SR·NDVI and the optimum air temperature. Vegetation index was derived from 3 years, LANDSAT TM data in Toyama, Ishikawa, Fukui and Nagano prefectures at heading. The meteorological data was used from AMeDAS data. The model was described as follows: Y = 0.728 SR·NDVI−2.04(T−21.3) 2 + 282 (r 2 = 0.65, n = 43) where Y is rice yield (kg 10a -1 ), SR is solar radiation (MJ m -2 ) during the ripening period (from 10 days before heading to 30 days after heading), T is mean air temperature (°C) during the ripening period. RMSE was 33.7kg 10a -1 . The model revealed good precision. (author)

  17. Geographical information system based model of land suitability for good yield of rice in prachuap khiri khan province, thailand

    International Nuclear Information System (INIS)

    Hussain, W.; Sohaib, O.

    2012-01-01

    Correct assessment of land is a major issue in agricultural sector to use possible capability of any land, to raise cultivation and production of rice. Geographical Information System (GIS) provides broad techniques for suitable land classifications. This study is GIS based on land suitability analysis for rice farming in Prachuap Khiri Khan Province, Thailand, where the main livelihood of people is rice farming. This analysis was conducted considering the relationship of rice production with various data layers of elevation, slope, soil pH, rainfall, fertilizer use and land use. ArcView GIS 3.2 software is used to consider each layer according to related data to weight every coefficient, ranking techniques are used. It was based on determining correlation of rice production and these variables. This analysis showed a positive correlation with these variables in varying degrees depending on the magnitude and quality of these factors. By combining both data layers of GIS and weighted linear combination, various suitable lands have been developed for cultivation of rice. Integrated suitable assessment map and current land were compared to find suitable land in Prachuap Khiri Khan Province of Thailand. As a result of this comparison, we get a land which is suitable for optimum utilization for rice production in Prachuap Khiri Khan Province. (author)

  18. Aspects of modeling regarding the contribution of nitrogen to the formation of grape yields

    Science.gov (United States)

    Blidariu, Cosmin; Boldea, Marius; Sala, Florin

    2013-10-01

    The research focused on determining the influence of organic fertilization equivalent to 150, 200 and 250 kg ha-1 nitrogen, on the productivity indices that participate in the formation of the grape yield: grape berry weight, number of grape berries, rachis weight. Quality indices of grapes were also analyzed: structure index, berry index, as well as yield quality, through dry matter. The distribution analysis of the experimental data revealed that production increase dy/dx increases dramatically with the total fertilizer dose (x + x0), it being proportional to the saturation deficit (a-y), where a is the biologically maximum yield (asymptote). Constants a, b and x0 for each parameter were determined by confrontation with the experimental data, through the least square method, and they were used in modeling the contribution of nitrogen to the formation of grape yields. Although the equivalent quantity of nitrogen in the soil is 150 units, its use is different in the proposed model, depending on the parameter under study. When the focus is on grape berry weight, the enhancement of this parameter is at the level of 97 units, whereas the enhancement of dry matter is 300 units. Analysis of the experimental data revealed that productive parameters are in positive correlation with different intensity levels. Regression analysis, Stuart, A., 1987, facilitated prediction models for the productive characters under study, with high to very high degree of certainty ((Gb = f(Nb):r2 = 0.880;p<0.01;Gs = f(NrB):r2 = 0.852;p<0.01).

  19. 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

    Potato production ranks fourth in the world after rice, wheat, and maize and it is highly sensitive to water stress. It is thus very important to implement irrigation management strategies to minimize the effects of water stress under different climate conditions. The use of modelling tools...... 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...

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

    Directory of Open Access Journals (Sweden)

    Alireza Karbasivar

    2014-11-01

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

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

    Science.gov (United States)

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

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

  2. Towards Better Simulation of US Maize Yield Responses to Climate in the Community Earth System Model

    Science.gov (United States)

    Peng, B.; Guan, K.; Chen, M.; Lawrence, D. M.; Jin, Z.; Bernacchi, C.; Ainsworth, E. A.; DeLucia, E. H.; Lombardozzi, D. L.; Lu, Y.

    2017-12-01

    Global food security is undergoing continuing pressure from increased population and climate change despites the potential advancement in breeding and management technologies. Earth system models (ESMs) are essential tools to study the impacts of historical and future climate on regional and global food production, as well as to assess the effectiveness of possible adaptations and their potential feedback to climate. Here we developed an improved maize representation within the Community Earth System Model (CESM) by combining the strengths of both the Community Land Model version 4.5 (CLM4.5) and the Agricultural Production Systems sIMulator (APSIM) models. Specifically, we modified the maize planting scheme, incorporated the phenology scheme adopted from the APSIM model, added a new carbon allocation scheme into CLM4.5, and improved the estimation of canopy structure parameters including leaf area index (LAI) and canopy height. Unique features of the new model (CLM-APSIM) include more detailed phenology stages, an explicit implementation of the impacts of various abiotic environmental stresses (including nitrogen, water, temperature and heat stresses) on maize phenology and carbon allocation, as well as an explicit simulation of grain number and grain size. We conducted a regional simulation of this new model over the US Corn Belt during 1990 to 2010. The simulated maize yield as well as its responses to climate (growing season mean temperature and precipitation) are benchmarked with data from UADA NASS statistics. Our results show that the CLM-APSIM model outperforms the CLM4.5 in simulating county-level maize yield production and reproduces more realistic yield responses to climate variations than CLM4.5. However, some critical processes (such as crop failure due to frost and inundation and suboptimal growth condition due to biotic stresses) are still missing in both CLM-APSIM and CLM4.5, making the simulated yield responses to climate slightly deviate from the

  3. An improved public goods game model with reputation effect on the spatial lattices

    International Nuclear Information System (INIS)

    Zhou, Tianwei; Ding, Shuai; Fan, Wenjuan; Wang, Hao

    2016-01-01

    Highlights: • The reputation effect is added into the spatial public goods game model. • The individual utility is calculated as a combination of payoff and reputation. • The individual reputation will be adaptively modified as the system evolves. • The larger the reputation factor, the higher the cooperation level. - Abstract: How to model the evolution of cooperation within the population is an important and interdisciplinary issue across the academia. In this paper, we propose an improved public goods game model with reputation effect on spatial lattices to investigate the evolution of cooperation regarding the allocation of public resources. In our model, we modify the individual utility or fitness as a product of the present payoff and reputation-related power function, and strategy update adopts a Fermi-like probability function during the game evolution. Meanwhile, for an interaction between a pair of partners, the reputation of a cooperative agent will be accrued beyond two units, but the defective player will decrease his reputation by one unit. Extensive Monte Carlo numerical simulations indicate the introduction of reputation will foster the formation of cooperative clusters, and greatly enhance the level of public cooperation on the spatial lattices. The larger reputation factor leads to the higher cooperation level since the reputation effect will be enormously embedded into the utility evaluation under this scenario. The current results are vastly beneficial to understand the persistence and emergence of cooperation among many natural, social and synthetic systems, and also provide some useful suggestions to devise the feasible social governance measures and modes for the public resources or affairs.

  4. Updated stomatal flux and flux-effect models for wheat for quantifying effects of ozone on grain yield, grain mass and protein yield.

    Science.gov (United States)

    Grünhage, Ludger; Pleijel, Håkan; Mills, Gina; Bender, Jürgen; Danielsson, Helena; Lehmann, Yvonne; Castell, Jean-Francois; Bethenod, Olivier

    2012-06-01

    Field measurements and open-top chamber experiments using nine current European winter wheat cultivars provided a data set that was used to revise and improve the parameterisation of a stomatal conductance model for wheat, including a revised value for maximum stomatal conductance and new functions for phenology and soil moisture. For the calculation of stomatal conductance for ozone a diffusivity ratio between O(3) and H(2)O in air of 0.663 was applied, based on a critical review of the literature. By applying the improved parameterisation for stomatal conductance, new flux-effect relationships for grain yield, grain mass and protein yield were developed for use in ozone risk assessments including effects on food security. An example of application of the flux model at the local scale in Germany shows that negative effects of ozone on wheat grain yield were likely each year and on protein yield in most years since the mid 1980s. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. Association between Empirically Estimated Monsoon Dynamics and Other Weather Factors and Historical Tea Yields in China: Results from a Yield Response Model

    Directory of Open Access Journals (Sweden)

    Rebecca Boehm

    2016-04-01

    Full Text Available Farmers in China’s tea-growing regions report that monsoon dynamics and other weather factors are changing and that this is affecting tea harvest decisions. To assess the effect of climate change on tea production in China, this study uses historical weather and production data from 1980 to 2011 to construct a yield response model that estimates the partial effect of weather factors on tea yields in China, with a specific focus on East Asian Monsoon dynamics. Tea (Camellia sinensis (L. Kunze has not been studied using these methods even though it is an important crop for human nutrition and the economic well-being of rural communities in many countries. Previous studies have approximated the monsoon period using historical average onset and retreat dates, which we believe limits our understanding of how changing monsoon patterns affect crop productivity. In our analysis, we instead estimate the monsoon season across China’s tea growing regions empirically by identifying the unknown breakpoints in the year-by-province cumulative precipitation. We find that a 1% increase in the monsoon retreat date is associated with 0.481%–0.535% reduction in tea yield. In the previous year, we also find that a 1% increase in the date of the monsoon retreat is associated with a 0.604% decrease in tea yields. For precipitation, we find that a 1% increase in average daily precipitation occurring during the monsoon period is associated with a 0.184%–0.262% reduction in tea yields. In addition, our models show that 1% increase in the average daily monsoon precipitation from the previous growing season is associated with 0.258%–0.327% decline in yields. We also find that a 1% decrease in solar radiation in the previous growing season is associated with 0.554%-0.864% decrease in tea yields. These findings suggest the need for adaptive management and harvesting strategies given climate change projections and the known negative association between excess

  6. Good teacher, good tutor

    Directory of Open Access Journals (Sweden)

    Couto LB

    2016-07-01

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

  7. A toy model for the yield of a tamped fission bomb

    Science.gov (United States)

    Reed, B. Cameron

    2018-02-01

    A simple expression is developed for estimating the yield of a tamped fission bomb, that is, a basic nuclear weapon comprising a fissile core jacketed by a surrounding neutron-reflecting tamper. This expression is based on modeling the nuclear chain reaction as a geometric progression in combination with a previously published expression for the threshold-criticality condition for such a core. The derivation is especially straightforward, as it requires no knowledge of diffusion theory and should be accessible to students of both physics and policy. The calculation can be set up as a single page spreadsheet. Application to the Little Boy and Fat Man bombs of World War II gives results in reasonable accord with published yield estimates for these weapons.

  8. Planting data and wheat yield models. [Kansas, South Dakota, and U.S.S.R.

    Science.gov (United States)

    Feyerherm, A. M. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. A variable date starter model for spring wheat depending on temperature was more precise than a fixed date model. The same conclusions for fall-planted wheat were not reached. If the largest and smallest of eight temperatures were used to estimate daily maximum and minimum temperatures; respectively, a 1-4 F bias would be introduced into these extremes. For Kansas, a reduction of 0.5 bushels/acre in the root-mean-square-error between model and SRS yields was achieved by a six fold increase (7 to 42) in the density of weather stations. An additional reduction of 0.3 b/A was achieved by incorporating losses due to rusts in the model.

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

    Directory of Open Access Journals (Sweden)

    S. Mirzaee

    2016-02-01

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

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

    Directory of Open Access Journals (Sweden)

    D. K. Henze

    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

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

    Science.gov (United States)

    Henze, D. K.; Seinfeld, J. H.; Ng, N. L.; Kroll, J. H.; Fu, T.-M.; Jacob, D. J.; Heald, C. L.

    2008-05-01

    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 production of anthropogenic SOA still exist beyond those accounted

  13. A mathematical framework for yield (vs. rate) optimization in constraint-based modeling and applications in metabolic engineering.

    Science.gov (United States)

    Klamt, Steffen; Müller, Stefan; Regensburger, Georg; Zanghellini, Jürgen

    2018-02-07

    The optimization of metabolic rates (as linear objective functions) represents the methodical core of flux-balance analysis techniques which have become a standard tool for the study of genome-scale metabolic models. Besides (growth and synthesis) rates, metabolic yields are key parameters for the characterization of biochemical transformation processes, especially in the context of biotechnological applications. However, yields are ratios of rates, and hence the optimization of yields (as nonlinear objective functions) under arbitrary linear constraints is not possible with current flux-balance analysis techniques. Despite the fundamental importance of yields in constraint-based modeling, a comprehensive mathematical framework for yield optimization is still missing. We present a mathematical theory that allows one to systematically compute and analyze yield-optimal solutions of metabolic models under arbitrary linear constraints. In particular, we formulate yield optimization as a linear-fractional program. For practical computations, we transform the linear-fractional yield optimization problem to a (higher-dimensional) linear problem. Its solutions determine the solutions of the original problem and can be used to predict yield-optimal flux distributions in genome-scale metabolic models. For the theoretical analysis, we consider the linear-fractional problem directly. Most importantly, we show that the yield-optimal solution set (like the rate-optimal solution set) is determined by (yield-optimal) elementary flux vectors of the underlying metabolic model. However, yield- and rate-optimal solutions may differ from each other, and hence optimal (biomass or product) yields are not necessarily obtained at solutions with optimal (growth or synthesis) rates. Moreover, we discuss phase planes/production envelopes and yield spaces, in particular, we prove that yield spaces are convex and provide algorithms for their computation. We illustrate our findings by a small

  14. 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.

  15. A Study of Estimating Winter Wheat Yields by Using Satellite Data Assimilation with Crop Growth Model

    Science.gov (United States)

    Kuwata, K.

    2013-12-01

    Accurate information of crop yield is important for production planning in agriculture. Crop growth model is a effective tool to comprehend crop growth situation. Accordingly, we use the MOSIS data for two types of utilization to provide necessary information for DSSAT. The objective of this study is developing a method of estimating winter wheat yield without adequate information of the field. The first use is estimation of solar radiation, which is required as input data into DSSAT. Since MODIS is observing the earth everyday, solar radiation can be estimated in a region where a climate observation system is not developed. The second use is data assimilation that provides appropriate parameter of cultivation management to DSSAT. MODIS LAI and Dry Matter Production (DMP) estimated from MODIS GPP are assimilated into DSSAT. Before developing data assimilation, we have accomplished sensitivity analysis of DSSAT. As the result of the analysis, we found that planting date and amount of applied fertilizer have correlated strongly with LAI and Dry Matter (DM) for specific growth period. Based on the result, we estimated winter wheat yield by assimilating MODIS LAI and DMP observed during the specific period. In contrast, previous study estimated crop yield by assimilating satellite data observed for the whole growth period. Three different assimilation schemes were tested to verify the accuracy of our method. Our results showed that the estimated winter wheat yield agreed very well with the Japanese agricultural experiment station data. Among different assimilating scenarios, the best result was obtained when MODIS LAI and DMP observed for specific growth period; the Root Square Mean Error (RMSE) was 406.52 kg ha2. The distribution map of full year incident PAR in Asia. Estimated Winter Wheat Yield in Japan In the case 1, detail information gathered by experiment reports.In the case 2, all management parameters are determined by reference to cultivation manuals.In the

  16. Recent changes in county-level corn yield variability in the United States from observations and crop models

    Energy Technology Data Exchange (ETDEWEB)

    Leng, Guoyong

    2017-12-01

    The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota, Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated

  17. Recent changes in county-level corn yield variability in the United States from observations and crop models.

    Science.gov (United States)

    Leng, Guoyong

    2017-12-31

    The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota, Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated

  18. 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.

  19. Safety Assessment of Dangerous Goods Transport Enterprise Based on the Relative Entropy Aggregation in Group Decision Making Model

    Directory of Open Access Journals (Sweden)

    Jun Wu

    2014-01-01

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

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

    Science.gov (United States)

    Wu, Jun; Li, Chengbing; Huo, Yueying

    2014-01-01

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

  1. Trade potential of climate smart goods of Vietnam: An application of gravity model

    Directory of Open Access Journals (Sweden)

    Trung Van Vu

    2016-01-01

    Full Text Available This paper examines the trade potential of climate smart goods (CSG of Vietnam. In particular, the study employs gravity model with panel data for bilateral trade between Vietnam and its 45 partners from 2002 to 2013 with an objective of identifying the determinants explaining Vietnam's trade of climate smart products. The estimation results reveal that economic size, market size, distance, real exchange rate, border, and the quality of infrastructure of both Vietnam and its trading partners play a major role in bilateral trade of CSG. Additionally, the paper applies the method using speed of convergence and the estimated gravity equation to answer whether Vietnam has fully realized the potential trade of CSG. Accordingly, Vietnam has strong opportunity for trade expansion with 19 out of 45 countries in the scope of this paper.

  2. 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

    reflects the fact that in different stages of lactation, CM gives rise to different yield-loss patterns or postulates just one type of yield-loss pattern irrespective of when, during lactation, CM occurs. A dynamic and stochastic simulation model, SimHerd, was used to study the effects of CM in a herd...... a single yield-loss pattern irrespective of when, during the lactation period, the cow develops CM - was compared with a new modelling strategy in which CM was assumed to affect production differently depending on its lactational timing. The effect of the choice of reference level when estimating yield...

  3. Sustainable stemwood yield in relation to the nitrogen balance of forest plantations: a model analysis

    Energy Technology Data Exchange (ETDEWEB)

    Dewar, R. C.; McMurtrie, R. E. [New South Wales Univ., Sydney, NSW (Australia)

    1996-01-01

    An existing analytical model of stemwood growth in relation to nitrogen supply was used to examine the long-term effects of harvesting and fire on tree growth. Balance between nitrogen additions from a variety of sources, such as from deposition, fixation and fertilizer applications, and nitrogen losses from harvesting, regeneration burning, leaching and gaseous emissions, have been considered. Using a hypothetical set of parameters for Eucalyptus, it was concluded that nitrogen loss through fire is the main factor limiting sustainable yield. The analysis technique and the model can also be applied to a simulation of the effects of climate change, or to verifying results of sustainable forest growth obtained by using other models. 24 refs., 5 figs.

  4. 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 CO 2 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 CO 2 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. © 2016 John Wiley & Sons Ltd.

  5. Adapting SWAT hillslope erosion model to predict sediment concentrations and yields in large Basins.

    Science.gov (United States)

    Vigiak, Olga; Malagó, Anna; Bouraoui, Fayçal; Vanmaercke, Matthias; Poesen, Jean

    2015-12-15

    The Soil and Water Assessment Tool (SWAT) is used worldwide for water quality assessment and planning. This paper aimed to assess and adapt SWAT hillslope sediment yield model (Modified Universal Soil Loss Equation, MUSLE) for applications in large basins, i.e. when spatial data is coarse and model units are large; and to develop a robust sediment calibration method for large regions. The Upper Danube Basin (132,000km(2)) was used as case study representative of large European Basins. The MUSLE was modified to reduce sensitivity of sediment yields to the Hydrologic Response Unit (HRU) size, and to identify appropriate algorithms for estimating hillslope length (L) and slope-length factor (LS). HRUs gross erosion was broadly calibrated against plot data and soil erosion map estimates. Next, mean annual SWAT suspended sediment concentrations (SSC, mg/L) were calibrated and validated against SSC data at 55 gauging stations (622 station-years). SWAT annual specific sediment yields in subbasin reaches (RSSY, t/km(2)/year) were compared to yields measured at 33 gauging stations (87station-years). The best SWAT configuration combined a MUSLE equation modified by the introduction of a threshold area of 0.01km(2) where L and LS were estimated with flow accumulation algorithms. For this configuration, the SSC residual interquartile was less than +/-15mg/L both for the calibration (1995-2004) and the validation (2005-2009) periods. The mean SSC percent bias for 1995-2009 was 24%. RSSY residual interquartile was within +/-10t/km(2)/year, with a mean RSSY percent bias of 12%. Residuals showed no bias with respect to drainage area, slope, or spatial distribution. The use of multiple data types at multiple sites enabled robust simulation of sediment concentrations and yields of the region. The MUSLE modifications are recommended for use in large basins. Based on SWAT simulations, we present a sediment budget for the Upper Danube Basin. Copyright © 2015. Published by Elsevier B.V.

  6. 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.

  7. 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.

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

    Science.gov (United States)

    González-Cabaleiro, Rebeca; Lema, Juan M; Rodríguez, Jorge

    2015-01-01

    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.

  9. 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

  10. Study on the Method of Grass Yield Model in the Source Region of Three Rivers with Multivariate Data

    International Nuclear Information System (INIS)

    You, Haoyan; Luo, Chengfeng; Liu, Zhengjun; Wang, Jiao

    2014-01-01

    This paper uses remote sensing and GIS technology to analyse the Source Region of Three Rivers (SRTR) to establish a grass yield estimation model during 2010 with remote sensing data, meteorological data, grassland type data and ground measured data. Analysis of the correlation between ground measured data, vegetation index based HJ-1A/B satellite data, meteorological data and grassland type data were used to establish the grass yield model. The grass yield model was studied by several statistical methods, such as multiple linear regression and Geographically Weighted Regression (GWR). The model's precision was validated. Finally, the best model to estimate the grass yield of Maduo County in SRTR was contrasted with the TM degraded grassland interpretation image of Maduo County from 2009. The result shows that: (1) Comparing with the multiple linear regression model, the GWR model gave a much better fitting result with the quality of fit increasing significantly from less than 0.3 to more than 0.8; (2) The most sensitive factors affecting the grass yield in SRTR were precipitation from May to August and drought index from May to August. From calculation of the five vegetation indices, MSAVI fitted the best; (3) The Maduo County grass yield estimated by the optimal model was consistent with the TM degraded grassland interpretation image, the spatial distribution of grass yield in Maduo County for 2010 showed a ''high south and low north'' pattern

  11. 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.)

  12. 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.

  13. 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.

  14. Development of yield prediction models in the maize crop using spectral data for precisión agriculture applications

    OpenAIRE

    Rueda Ayala, Victor Patricio

    2015-01-01

    Yield estimation for the maize crop (Zea mays L.) is required in Ecuador for decision making on imports and commercialization. In the literature many yield predictive models have been developed for different crops, but they need to be adapted to the local conditions. In this study, machine learning techniques and statistical tools such as simple, logistic and polynomial regression were applied in order to develop yield predictive algorithms. Spectral information was gathered from ...

  15. Evaluation of simulated corn yields and associated uncertainty in different climate zones of China using Daycent Model

    Science.gov (United States)

    Fu, A.; Xue, Y.

    2017-12-01

    Corn is one of most important agricultural production in China. Research on the simulation of corn yields and the impacts of climate change and agricultural management practices on corn yields is important in maintaining the stable corn production. After climatic data including daily temperature, precipitation, solar radiation, relative humidity, and wind speed from 1948 to 2010, soil properties, observed corn yields, and farmland management information were collected, corn yields grown in humidity and hot environment (Sichuang province) and cold and dry environment (Hebei province) in China in the past 63 years were simulated by Daycent, and the results was evaluated based on published yield record. The relationship between regional climate change, global warming and corn yield were analyzed, the uncertainties of simulation derived from agricultural management practices by changing fertilization levels, land fertilizer maintenance and tillage methods were reported. The results showed that: (1) Daycent model is capable to simulate corn yields under the different climatic background in China. (2) When studying the relationship between regional climate change and corn yields, it has been found that observed and simulated corn yields increased along with total regional climate change. (3) When studying the relationship between the global warming and corn yields, It was discovered that newly-simulated corn yields after removing the global warming trend of original temperature data were lower than before.

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

    Science.gov (United States)

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

    2016-05-01

    Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) . © 2015 John Wiley & Sons Ltd/London School of Economics.

  17. "Grey nomads" in Australia: are they a good model for successful aging and health?

    Science.gov (United States)

    Higgs, Paul F D; Quirk, Frances

    2007-10-01

    Lifestyle factors have been identified as being very important in determining health in later life. Nutrition, exercise, and social environment all interact to promote, or to limit, opportunities for an active and healthy post-working life. Not only are rates of chronic illness and disability reduced through the promotion of healthy lifestyles, but also quality of life is maintained through the compression of morbidity. Governments in Australia, as in the European Union and North America, have highlighted the importance of behavioral change in health promotion strategies with the aim of having an impact on the health-related lifestyles of their populations. This paper examines the example of a group of older Australians, the "grey nomads," who may present opportunities for examining health-related lifestyle changes. The term grey nomad refers to a portion of the older population in Australia who choose to use their later years and retirement as opportunities for travel and leisure, mainly within the confines of the Australian continent. As such, they are similar to groups in North America, such as the "snow birds," who travel to the southern United States to escape the colder winters of more northerly latitudes. Similar seasonal migrations occur from Northern to Southern Europe. What all share in common is an active culture/lifestyle of attempting to "age successfully." Grey nomads also participate in the creation of what can be termed postmodern communities, where they and other regular travelers may develop a sense of community feeling with others who are also regularly returning to the same spot year after year. Social support is highly predictive of health outcomes and such mobile communities may prove a positive factor in promoting good health. In this paper we examine whether the "grey nomads" represent a good model for improving health-related lifestyles in later life.

  18. Aggregation of polymer-grafted nanoparticles in good solvents: A hierarchical modeling method

    Science.gov (United States)

    Cheng, Lisheng; Cao, Dapeng

    2011-09-01

    Brownian dynamics simulations are carried out to study the aggregation behavior of polymer-grafted nanoparticles (NPs) in good solvents by using the coarse-grained model derived from the all-atom force field, according to the hierarchical modeling strategy, and here PEG-grafted gold nanoparticles (GNPs) were taken as an example. Generally, grafting PEG to the surface of GNPs is to protect them from aggregation in the solution. However, our results reveal that PEG-grafted GNPs may also aggregate when concentration increases. Our simulations indicate that there exists a critical aggregating concentration (CAC), beyond which the PEG-grafted GNPs will aggregate. We further check the effects of grafting density and the length of grafted chains on the aggregation behavior of the grafted GNPs, and find that there exists an optimized length of grafted chain, at which the system has the maximal CAC. Furthermore, the aggregate size of self-assembled mesostructures formed by the grafted GNPs increases with the concentration. Interestingly, it is observed that the aggregation favors to form linear gold nanowires rather than compact gold nanoclusters, and the corresponding mechanism is also addressed. It is expected that this work would provide useful information for the fabrication of metal nanowires and the surface modification of metal nanoparticles.

  19. Crop Yield Predictions - High Resolution Statistical Model for Intra-season Forecasts Applied to Corn in the US

    Science.gov (United States)

    Cai, Y.

    2017-12-01

    Accurately forecasting crop yields has broad implications for economic trading, food production monitoring, and global food security. However, the variation of environmental variables presents challenges to model yields accurately, especially when the lack of highly accurate measurements creates difficulties in creating models that can succeed across space and time. In 2016, we developed a sequence of machine-learning based models forecasting end-of-season corn yields for the US at both the county and national levels. We combined machine learning algorithms in a hierarchical way, and used an understanding of physiological processes in temporal feature selection, to achieve high precision in our intra-season forecasts, including in very anomalous seasons. During the live run, we predicted the national corn yield within 1.40% of the final USDA number as early as August. In the backtesting of the 2000-2015 period, our model predicts national yield within 2.69% of the actual yield on average already by mid-August. At the county level, our model predicts 77% of the variation in final yield using data through the beginning of August and improves to 80% by the beginning of October, with the percentage of counties predicted within 10% of the average yield increasing from 68% to 73%. Further, the lowest errors are in the most significant producing regions, resulting in very high precision national-level forecasts. In addition, we identify the changes of important variables throughout the season, specifically early-season land surface temperature, and mid-season land surface temperature and vegetation index. For the 2017 season, we feed 2016 data to the training set, together with additional geospatial data sources, aiming to make the current model even more precise. We will show how our 2017 US corn yield forecasts converges in time, which factors affect the yield the most, as well as present our plans for 2018 model adjustments.

  20. A Remote Sensing Based Forage Biomass Yield Inversion Model of Alpine-cold Meadow during Grass-withering Period in Sanjiangyuan Area

    International Nuclear Information System (INIS)

    Song, Weize; Jia, Haifeng; Liang, Shidong; Wang, Zheng; Liu, Shujie; Hao, Lizhuang; Chai, Shatuo

    2014-01-01

    Estimating forage biomass yield remotely from space is still challenging nowadays. Field experiments were conducted and ground measurements correlated to remote sensing data to estimate the forage biomass yield of Alpine-cold meadow grassland during the grass and grass-withering period in Sanjiangyuan area in Yushu county. Both Shapiro-Wilk and Kolmogorov-Smirnov two-tailed tests showed that the field training samples are normally distributed, the Spearman coefficient indicated that the parametric correlation analysis had significant differences. The optimal regression models were developed based on the Landsat Thematic Mapper Normalized Difference Vegetation Index (TM-NDVI) and the forage biomass field data during the grass and the grass-withering periods, respectively. Then an integration model was used to predict forage biomass yield of alpine-cold meadow in the grass-withering period. The model showed good prediction accuracy and reliability. It was found that this approach can not only estimate forage yield in large scale efficiently but also overcome the seasonal limitation of remote sensing inversion. This technique can provides valuable guidance to animal husbandry to resource more efficiently in winter

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

    Science.gov (United States)

    Bourne, Paul A

    2009-07-01

    In recent times, the World Health Organization has increasing drawn attention to the pivotal role of social conditions in determining health status. The non-biological factors produced inequalities in health and need to be considered in health development. In spite of this, extensive review of health Caribbean revealed that no study has examined health status over the life course of Jamaicans. With the value of research in public health, this study is timely and will add value to understand the elderly, middle age and young adults in Jamaica. The aim of this study is to develop models that can be used to examine (or evaluate) health of Jamaicans, elderly, middle age and young adults. The current study used data from a cross-sectional survey which was conducted between July and October 2002. Stratified random probability sampling technique was used to collect the data from 25,018 respondents across the island. The non-response rate for the survey was 29.7% with 20.5% who did not respond to particular questions, 9.0% did not participated in the survey and another 0.2% was rejected due to data cleaning. Logistic regression analyses were used to model health status of Jamaicans, young adults, middle age adults and elderly. The predictive power of the model was tested using Omnibus Test of Model and Hosmer and Lemeshow (24) was used to examine goodness of fit of the model. The correlation matrix was examined in order to ascertain whether autocorrelation (or multi-collinearity) existed between variables. Using logistic regression analysis, eleven variables emerged as statistically significant predictors of current good health Status of Jamaicans (p<0.05). The factors are retirement income (95%CI=0.487-0.958), logged medical expenditure (95% Confidence Interval, CI =0.907-0.993), marital status (Separated or widowed or divorced: 95%CI=0.309-0.464; married: 95%CI=0.495-0.667; Never married), health insurance (95%CI=0.029-0.046), area of residence (other towns:, 95%CI=1

  2. Limited-information goodness-of-fit testing of hierarchical item factor models.

    Science.gov (United States)

    Cai, Li; Hansen, Mark

    2013-05-01

    In applications of item response theory, assessment of model fit is a critical issue. Recently, limited-information goodness-of-fit testing has received increased attention in the psychometrics literature. In contrast to full-information test statistics such as Pearson's X(2) or the likelihood ratio G(2) , these limited-information tests utilize lower-order marginal tables rather than the full contingency table. A notable example is Maydeu-Olivares and colleagues'M2 family of statistics based on univariate and bivariate margins. When the contingency table is sparse, tests based on M2 retain better Type I error rate control than the full-information tests and can be more powerful. While in principle the M2 statistic can be extended to test hierarchical multidimensional item factor models (e.g., bifactor and testlet models), the computation is non-trivial. To obtain M2 , a researcher often has to obtain (many thousands of) marginal probabilities, derivatives, and weights. Each of these must be approximated with high-dimensional numerical integration. We propose a dimension reduction method that can take advantage of the hierarchical factor structure so that the integrals can be approximated far more efficiently. We also propose a new test statistic that can be substantially better calibrated and more powerful than the original M2 statistic when the test is long and the items are polytomous. We use simulations to demonstrate the performance of our new methods and illustrate their effectiveness with applications to real data. © 2012 The British Psychological Society.

  3. Assessments of Future Maize Yield Potential Changes in the Korean Peninsula Using Multiple Crop Models

    Science.gov (United States)

    Kim, S. H.; Lim, C. H.; Kim, J.; Lee, W. K.; Kafatos, M.

    2016-12-01

    The Korean Peninsula has unique agricultural environment due to the differences of political and socio-economical system between Republic of Korea (SK, hereafter) and Democratic Peoples' Republic of Korea (NK, hereafter). NK has been suffering lack of food supplies caused by natural disasters, land degradation and political failure. The neighboring developed country SK has better agricultural system but very low food self-sufficiency rate. 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 utilized multiple process-based crop models, having ability of regional scale assessment, to evaluate maize Yp and assess the model uncertainties -EPIC, GEPIC, DSSAT, and APSIM model that has capability of regional scale expansion (apsimRegions). First we evaluated each crop model for 3 years from 2012 to 2014 using reanalysis data (RDAPS; Regional Data Assimilation and Prediction System produced by Korea Meteorological Agency) and observed yield data. Each model performances were compared over the different regions in the Korean Peninsula having different local climate characteristics. To quantify of the major influence of at each climate variables, we also conducted sensitivity test using 20 years of climatology in historical period from 1981 to 2000. Lastly, the multi-crop model ensemble analysis was performed for future period from 2031 to 2050. The required weather variables projected for mid-century were employed from COordinated Regional climate Downscaling EXperiment (CORDEX) East Asia. The high-resolution climate data were obtained from multiple regional climate models (RCM) driven by multiple climate scenarios projected from multiple global climate models (GCMs) in conjunction with multiple greenhouse gas

  4. Estimation of maize yield by using a process-based model and remote sensing data in the Northeast China Plain

    Science.gov (United States)

    Yao, Fengmei; Tang, Yanjing; Wang, Peijuan; Zhang, Jiahua

    Climate change significantly impact on agriculture in recent year, the accurate estimation of crop yield is of great importance for the food security. In this study, a process-based mechanism model was modified to estimate yield of C4 crop by modifying the carbon metabolic pathway in the photosynthesis sub-module of the RS-P-YEC (Remote-Sensing-Photosynthesis-Yield estimation for Crops) model. The yield was calculated by multiplying net primary productivity (NPP) and the harvest index (HI) derived from the ratio of grain to stalk yield. The modified RS-P-YEC model was used to simulate maize yield in the Northeast China Plain during the period 2002-2011. The 111 statistical data of maize yield from study area was used to validate the simulated results at county-level. The results showed that the Pearson correlation coefficient (R) was 0.827 (p yield and the statistical data, and the root mean square error (RMSE) was 712 kg/ha with a relative error (RE) of 9.3%. From 2002 to 2011, the yield of maize planting zone in the Northeast China Plain was increasing with smaller coefficient of variation (CV). The spatial pattern of simulated maize yield was consistent with the actual distribution in the Northeast China Plain, with an increasing trend from the northeast to the southwest. Hence the results demonstrated that the modified process-based model coupled with remote sensing data was suitable for yield prediction of maize in the Northeast China Plain at the spatial scale.

  5. Nuclear reaction rate uncertainties and astrophysical modeling: Carbon yields from low-mass giants

    International Nuclear Information System (INIS)

    Herwig, Falk; Austin, Sam M.; Lattanzio, John C.

    2006-01-01

    Calculations that demonstrate the influence of three key nuclear reaction rates on the evolution of asymptotic giant branch stars have been carried out. We study the case of a star with an initial mass of 2 M · and a metallicity of Z=0.01, somewhat less than the solar metallicity. The dredge-up of nuclear processed material from the interior of the star and the yield predictions for carbon are sensitive to the rate of the 14 N(p,γ) 15 O and triple-α reactions. These reactions dominate the H- and He-burning shells of stars in this late evolutionary phase. Published uncertainty estimates for each of these two rates propagated through stellar evolution calculations cause uncertainties in carbon enrichment and yield predictions of about a factor of 2. The other important He-burning reaction, 12 C(α,γ) 16 O, although associated with the largest uncertainty in our study, does not have a significant influence on the abundance evolution compared with other modeling uncertainties. This finding remains valid when the entire evolution from the main sequence to the tip of the asymptotic giant branch is considered. We discuss the experimental sources of the rate uncertainties addressed here and give some outlooks for future work

  6. Mixed models for selection of Jatropha progenies with high adaptability and yield stability in Brazilian regions.

    Science.gov (United States)

    Teodoro, P E; Bhering, L L; Costa, R D; Rocha, R B; Laviola, B G

    2016-08-19

    The aim of this study was to estimate genetic parameters via mixed models and simultaneously to select Jatropha progenies grown in three regions of Brazil that meet high adaptability and stability. From a previous phenotypic selection, three progeny tests were installed in 2008 in the municipalities of Planaltina-DF (Midwest), Nova Porteirinha-MG (Southeast), and Pelotas-RS (South). We evaluated 18 families of half-sib in a randomized block design with three replications. Genetic parameters were estimated using restricted maximum likelihood/best linear unbiased prediction. Selection was based on the harmonic mean of the relative performance of genetic values method in three strategies considering: 1) performance in each environment (with interaction effect); 2) performance in each environment (with interaction effect); and 3) simultaneous selection for grain yield, stability and adaptability. Accuracy obtained (91%) reveals excellent experimental quality and consequently safety and credibility in the selection of superior progenies for grain yield. The gain with the selection of the best five progenies was more than 20%, regardless of the selection strategy. Thus, based on the three selection strategies used in this study, the progenies 4, 11, and 3 (selected in all environments and the mean environment and by adaptability and phenotypic stability methods) are the most suitable for growing in the three regions evaluated.

  7. 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.

  8. 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. PMID:26010900

  9. Comparison of the performances of the CS model coil and the Good Joint SULTAN sample

    International Nuclear Information System (INIS)

    Wesche, Rainer; Herzog, Robert; Bruzzone, Pierluigi

    2008-01-01

    The relevance of short sample measurements in SULTAN for the prediction of the performance of the coils of the International Thermonuclear Experimental Reactor (ITER) is assessed using the case of the Nb 3 Sn high-field central solenoid model coil (CSMC) conductor, for which both coil performance and short sample SULTAN results (Good Joint (GJ) sample) are available. A least-squares fit procedure, based on a uniform current distribution among the strands and the Durham scaling relations for the field, temperature and strain dependences of the strand J c provides a thermal strain of -0.294% and a degradation factor of approximately 60% for the GJ sample. In the calculation of the voltage along Layer 1A of the CSMC the hoop stress and the variation of the magnetic field in the conductor cross-section were taken into account. The temperature profile, used in the calculations, is based on published temperature profiles and empirical relations between helium inlet and outlet temperatures. A comparison with the GJ results indicates that short sample measurements in SULTAN provide a conservative estimate of the coil performance

  10. Anthropogenic factors as an element of uncertainty in hydrological modelling of water yield with SWAT

    Directory of Open Access Journals (Sweden)

    R. Corobov

    2016-05-01

    Full Text Available In 2014 the SWAT (Soil and Water Assessment Tool model was used as a basis for follow-up investigations of Moldova’s small rivers potential flow. The first step of the study included the validation of SWAT for local conditions. As an experimental area, the Cogilnic River watershed was selected. Interim steps included the watershed delineation aimed to identify the subwatersheds and the Hydrological Response Units (small entities with the same characteristics of hydrologic soil type, land use and slopes. To address these tasks, the land cover, soil and slope layers, based on the Digital Elevation Model, were integrated in the SWAT environment. These thematic layers, alongside with long-term information on local monthly maximum and minimum temperatures and precipitation, enabled reflecting the differences in hydrological conditions and defining the watershed runoff. However, the validation of the modelling outputs, carried out through comparison of a simulated water yield from the studied watershed with actual Cogilnic streamflow measures, observed in 2010-2012, showed a great discrepancy between these parameters caused by anthropogenic loading on this small river. Thus, a ‘classical’ SWAT modelling needs to account for real environmental conditions and water use in the study area.

  11. Assimilation of Remotely Sensed Soil Moisture Profiles into a Crop Modeling Framework for Reliable Yield Estimations

    Science.gov (United States)

    Mishra, V.; Cruise, J.; Mecikalski, J. R.

    2017-12-01

    Much effort has been expended recently on the assimilation of remotely sensed soil moisture into operational land surface models (LSM). These efforts have normally been focused on the use of data derived from the microwave bands and results have often shown that improvements to model simulations have been limited due to the fact that microwave signals only penetrate the top 2-5 cm of the soil surface. It is possible that model simulations could be further improved through the introduction of geostationary satellite thermal infrared (TIR) based root zone soil moisture in addition to the microwave deduced surface estimates. In this study, root zone soil moisture estimates from the TIR based Atmospheric Land Exchange Inverse (ALEXI) model were merged with NASA Soil Moisture Active Passive (SMAP) based surface estimates through the application of informational entropy. Entropy can be used to characterize the movement of moisture within the vadose zone and accounts for both advection and diffusion processes. The Principle of Maximum Entropy (POME) can be used to derive complete soil moisture profiles and, fortuitously, only requires a surface boundary condition as well as the overall mean moisture content of the soil column. A lower boundary can be considered a soil parameter or obtained from the LSM itself. In this study, SMAP provided the surface boundary while ALEXI supplied the mean and the entropy integral was used to tie the two together and produce the vertical profile. However, prior to the merging, the coarse resolution (9 km) SMAP data were downscaled to the finer resolution (4.7 km) ALEXI grid. The disaggregation scheme followed the Soil Evaporative Efficiency approach and again, all necessary inputs were available from the TIR model. The profiles were then assimilated into a standard agricultural crop model (Decision Support System for Agrotechnology, DSSAT) via the ensemble Kalman Filter. The study was conducted over the Southeastern United States for the

  12. 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.

  13. 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

  14. Global sensitivity analysis of a local water balance model predicting evaporation, water yield and drought

    Science.gov (United States)

    Speich, Matthias; Zappa, Massimiliano; Lischke, Heike

    2017-04-01

    Evaporation and transpiration affect both catchment water yield and the growing conditions for vegetation. They are driven by climate, but also depend on vegetation, soil and land surface properties. In hydrological and land surface models, these properties may be included as constant parameters, or as state variables. Often, little is known about the effect of these variables on model outputs. In the present study, the effect of surface properties on evaporation was assessed in a global sensitivity analysis. To this effect, we developed a simple local water balance model combining state-of-the-art process formulations for evaporation, transpiration and soil water balance. The model is vertically one-dimensional, and the relative simplicity of its process formulations makes it suitable for integration in a spatially distributed model at regional scale. The main model outputs are annual total evaporation (TE, i.e. the sum of transpiration, soil evaporation and interception), and a drought index (DI), which is based on the ratio of actual and potential transpiration. This index represents the growing conditions for forest trees. The sensitivity analysis was conducted in two steps. First, a screening analysis was applied to identify unimportant parameters out of an initial set of 19 parameters. In a second step, a statistical meta-model was applied to a sample of 800 model runs, in which the values of the important parameters were varied. Parameter effect and interactions were analyzed with effects plots. The model was driven with forcing data from ten meteorological stations in Switzerland, representing a wide range of precipitation regimes across a strong temperature gradient. Of the 19 original parameters, eight were identified as important in the screening analysis. Both steps highlighted the importance of Plant Available Water Capacity (AWC) and Leaf Area Index (LAI). However, their effect varies greatly across stations. For example, while a transition from a

  15. Data assimilation of MODIS and TM observations into CERES-Maize model to estimate regional maize yield

    Science.gov (United States)

    Jin, Huaan; Wang, Jindi; Bo, Yanchen; Chen, Guifen; Xue, Huazhu

    2010-08-01

    Accurate and real-time estimation of crop yield over large areas is critical for many applications such as crop management, and agricultural management decision-making. This study presents a scheme to assimilate multi-temporal MODIS and Landsat TM reflectance data into the CERES-Maize crop growth model which is coupled with the radiative transfer model SAIL for maize yield estimation. We extract the directional reflectance data of MODIS subpixels corresponding to pure maize conditions with the objective to increase time series observations at the TM scale. The variables to be assimilated were chosen by conducting the sensitivity analysis on the coupled model. The SCE-UA algorithm was applied to determine the optimal set of these sensitive variables. Finally the maize yields maps were produced at TM scale with the coupled assimilation model. The proposed scheme was applied over Yushu County located in Jilin province of Northeast China and validated by using field yield measurement dataset during the maize growing season in 2007. The measurement data include the species of planting maize, soil type and fertility, field observed leaf, canopy and soil reflectance data etc. Furthermore, yield data were gained in specially designed experimental campaigns. The validation results indicate that the yield estimation scheme using multiple remote sensing data assimilation is very promising. The accuracy of TM yield map produced by adding time series MODIS subpixel information was improved comparing with that only using TM data.

  16. 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

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

    Science.gov (United States)

    Newbigging, Karen; McKeown, Mick; French, Beverley

    2011-01-01

    Abstract Background  Advocacy has a critical role to play in addressing concerns about access to appropriate mental health care and treatment for African and Caribbean men. Aim  To investigate good practice principles and organizational models for mental health advocacy provision for African and Caribbean men. Study design  The study consisted of: (i) A systematic literature review. Bibliographic and internet searching was undertaken from 1994 to 2006. The inclusion criteria related to mental health, advocacy provision for African and Caribbean men. (ii) Four focus groups with African and Caribbean men to explore needs for and experiences of mental health advocacy. (iii) An investigation into current advocacy provision through a survey of advocacy provision in England, Wales and Northern Ireland. (iv) Twenty‐two qualitative stakeholder interviews to investigate the operation of mental health advocacy for this client group. The study was undertaken in partnership with two service user‐led organizations and an African Caribbean mental health service. Results  Primary research in this area is scant. Mainstream mental health advocacy services are often poor at providing appropriate services. Services developed by the Black Community and voluntary sector are grounded in different conceptualizations of advocacy and sharper understanding of the needs of African and Caribbean men. The lack of sustainable funding for these organizations is a major barrier to the development of high‐quality advocacy for this group, reflecting a lack of understanding about their distinctive role. Conclusions  The commissioning and provision of mental health advocacy needs to recognize the distinct experiences of African and Caribbean men and develop capacity in the range of organizations to ensure equitable access. PMID:21645185

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

    Science.gov (United States)

    Newbigging, Karen; McKeown, Mick; French, Beverley

    2013-03-01

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

  19. Estimation of Winter Wheat Yield with the Assimilation of FY-3 MERSI Data into the WOFOST Crop Growth Model

    Science.gov (United States)

    Xu, Wenbo; Fan, Jinlong

    2014-11-01

    Taking the winter wheat planting area Taihang piedmont as object of the study, and based on WOFST model and FY Satellite 250m-resolution MERSI data, this article launched the assimilation yield estimation study on winter wheat. Firstly, MERSI-LAI data is inversed from the measured biophysics data and MERSI data of winter wheat in growing season within the study area; next, WOFOST model sensitivity analysis was developed and conduct assimilation yield estimation through MERSI-LAI built by SCE algorithm and the minimum cost function of model simulation LAI; finally, conduct comparison validation between the estimation results and MODIS-LAI assimilation yield estimation results as well as the statistical data. The conclusion has been drawn that the estimation accuracy based on FY-3 MERSI data assimilation is higher than that based on MODIS data assimilation, with the RMES being reduced by 750.20kg/ha, and the yield being closer to the statistics.

  20. Crop yield and CO2 fixation monitoring over Asia by a photosynthetic-sterility model comparing with MODIS and carbon amounts in grain yields

    Science.gov (United States)

    Kaneko, Daijiro; Yang, Peng; Kumakura, Toshiro

    2009-08-01

    The authors have developed a photosynthesis crop model for grain production under the background of climate change and Asian economic growth in developing countries. This paper presents an application of the model to grain fields of paddy rice, winter wheat, and maize in China and Southeast Asia. The carbon hydrate in grains has the same chemical formula as that of cellulose in grain vegetation. The partitioning of carbon in grain plants can validate fixation amounts of computed carbon using a satellite-based photosynthesis model. The model estimates the photosynthesis fixation of rice reasonably in Japan and China. Results were validated through examination of carbon in grains, but the model tends to underestimate results for winter wheat and maize. This study also provides daily distributions of the PSN, which is the CO2 fixation in Asian areas combined with a land-cover distribution classified from MODIS data, NDVI from SPOT VEGETATION, and meteorological re-analysis data by European Centre for Medium-Range Forecasts (ECMWF). The mean CO2 and carbon fixation rates in paddy areas were 25.92 (t CO2/ha) and 5.28 (t/ha) in Japan, respectively. The method is based on routine observation data, enabling automated monitoring of crop yields.

  1. Basic model of quality and good practices in neonatal radiography; Modelo basico de qualidade e boas praticas em radiografia neonatal

    Energy Technology Data Exchange (ETDEWEB)

    Dias, Janine H.; Goulart, Juliana M.; Lykawka, Rochelle; Bacelar, Alexandre [Hospital de Clinicas de Porto Alegre (HCPA), Porto Alegre, RS (Brazil)

    2016-07-01

    Neonatal chest radiographs were evaluated and 3 variables were analyzed: collimation, positioning and presence of artifacts. This study is a pilot for develop a model of good practices in radiology, which is in development phase. The index of analyzed radiographs considered inadequate is expressive and it shows the need for a model that may be part of an optimization program to medical exposures. (author)

  2. A Spatially Distributed Conceptual Model for Estimating Suspended Sediment Yield in Alpine catchments

    Science.gov (United States)

    Costa, Anna; Molnar, Peter; Anghileri, Daniela

    2017-04-01

    Suspended sediment is associated with nutrient and contaminant transport in water courses. Estimating suspended sediment load is relevant for water-quality assessment, recreational activities, reservoir sedimentation issues, and ecological habitat assessment. Suspended sediment concentration (SSC) along channels is usually reproduced by suspended sediment rating curves, which relate SSC to discharge with a power law equation. Large uncertainty characterizes rating curves based only on discharge, because sediment supply is not explicitly accounted for. The aim of this work is to develop a source-oriented formulation of suspended sediment dynamics and to estimate suspended sediment yield at the outlet of a large Alpine catchment (upper Rhône basin, Switzerland). We propose a novel modelling approach for suspended sediment which accounts for sediment supply by taking into account the variety of sediment sources in an Alpine environment, i.e. the spatial location of sediment sources (e.g. distance from the outlet and lithology) and the different processes of sediment production and transport (e.g. by rainfall, overland flow, snowmelt). Four main sediment sources, typical of Alpine environments, are included in our model: glacial erosion, hillslope erosion, channel erosion and erosion by mass wasting processes. The predictive model is based on gridded datasets of precipitation and air temperature which drive spatially distributed degree-day models to simulate snowmelt and ice-melt, and determine erosive rainfall. A mass balance at the grid scale determines daily runoff. Each cell belongs to a different sediment source (e.g. hillslope, channel, glacier cell). The amount of sediment entrained and transported in suspension is simulated through non-linear functions of runoff, specific for sediment production and transport processes occurring at the grid scale (e.g. rainfall erosion, snowmelt-driven overland flow). Erodibility factors identify different lithological units

  3. Forecasting the yield curve - Forecast performance of the dynamic Nelson-Siegel model from 1971 to 2008

    OpenAIRE

    Molenaars, Tomas K.; Reinerink, Nick H.; Hemminga, Marcus A.

    2013-01-01

    We define a parameter representing the relative forecast performance to compare forecasting results of different methods. By using this parameter, we analyze the performance of the dynamic Nelson-Siegel model and, for comparison, the first order autoregressive (AR(1)) model applied to a set of US bond yield data that covers a time span from November 1971 to December 2008. As a reference, we take the random walk model applied to the yield data. Our findings indicate that none of the models can...

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

    Science.gov (United States)

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

    2012-01-01

    How to design highly reputable and hot-selling products is an essential issue in product design. Whether consumers choose a product depends largely on their perception of the product image. A consumer-oriented design approach presented in this paper helps product designers incorporate consumers' perceptions of product forms in the design process. The consumer-oriented design approach uses quantification theory type I, grey prediction (the linear modeling technique), and neural networks (the nonlinear modeling technique) to determine the optimal form combination of product design for matching a given product image. An experimental study based on the concept of Kansei Engineering is conducted to collect numerical data for examining the relationship between consumers' perception of product image and product form elements of personal digital assistants (PDAs). The result of performance comparison shows that the QTTI model is good enough to help product designers determine the optimal form combination of product design. Although the PDA form design is used as a case study, the approach is applicable to other consumer products with various design elements and product images. The approach provides an effective mechanism for facilitating the consumer-oriented product design process. PMID:23258961

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

    Directory of Open Access Journals (Sweden)

    Yang-Cheng Lin

    2012-01-01

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

  6. Modeling of yield and environmental impact categories in tea processing units based on artificial neural networks.

    Science.gov (United States)

    Khanali, Majid; Mobli, Hossein; Hosseinzadeh-Bandbafha, Homa

    2017-12-01

    In this study, an artificial neural network (ANN) model was developed for predicting the yield and life cycle environmental impacts based on energy inputs required in processing of black tea, green tea, and oolong tea in Guilan province of Iran. A life cycle assessment (LCA) approach was used to investigate the environmental impact categories of processed tea based on the cradle to gate approach, i.e., from production of input materials using raw materials to the gate of tea processing units, i.e., packaged tea. Thus, all the tea processing operations such as withering, rolling, fermentation, drying, and packaging were considered in the analysis. The initial data were obtained from tea processing units while the required data about the background system was extracted from the EcoInvent 2.2 database. LCA results indicated that diesel fuel and corrugated paper box used in drying and packaging operations, respectively, were the main hotspots. Black tea processing unit caused the highest pollution among the three processing units. Three feed-forward back-propagation ANN models based on Levenberg-Marquardt training algorithm with two hidden layers accompanied by sigmoid activation functions and a linear transfer function in output layer, were applied for three types of processed tea. The neural networks were developed based on energy equivalents of eight different input parameters (energy equivalents of fresh tea leaves, human labor, diesel fuel, electricity, adhesive, carton, corrugated paper box, and transportation) and 11 output parameters (yield, global warming, abiotic depletion, acidification, eutrophication, ozone layer depletion, human toxicity, freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, terrestrial ecotoxicity, and photochemical oxidation). The results showed that the developed ANN models with R 2 values in the range of 0.878 to 0.990 had excellent performance in predicting all the output variables based on inputs. Energy consumption for

  7. European-wide simulations of croplands using an improved terrestrial biosphere model: 2. Interannual yields and anomalous CO2 fluxes in 2003

    Science.gov (United States)

    Smith, P. C.; Ciais, P.; Peylin, P.; de Noblet-Ducoudré, N.; Viovy, N.; Meurdesoif, Y.; Bondeau, A.

    2010-12-01

    Aiming at producing improved estimates of carbon source/sink spatial and interannual patterns across Europe (35% croplands), this work uses the ORCHIDEE-STICS terrestrial biosphere model including a more realistic representation of croplands, described in part 1 (Smith et al., 2010). Crop yield is derived from annual Net Primary Productivity and compared with wheat and grain maize harvest data for five European countries. Over a 34 year period, the best correlation coefficient obtained between observed and simulated yield time series is for irrigated maize in Italy (R = 0.73). In the data as well as in the model, 1976 and 2003 appear as climate anomalies causing a ≈40% yield drop in the most affected regions. Simulated interannual yield anomalies and the spatial pattern of the yield drop in 2003 are found to be more realistic than the results from ORCHIDEE with no representation of croplands. The simulated 2003 anomalous carbon source from European ecosystems to the atmosphere due to the 2003 summer heat wave is in good agreement with atmospheric inversions (0.20GtC, from May to October). The anomaly is twice too large in the ORCHIDEE alone simulation, owing to the unrealistically high exposure of herbaceous plants to the extreme summer conditions. The mechanisms linking abnormally high summer temperatures, the crop productivity drop, and significant carbon source from European ecosystems in 2003 are discussed. Overall, this study highlights the importance of accounting for the specific phenologies of crops sown both in winter and in spring and for irrigation applied to summer crops in regional/global models of the terrestrial carbon cycle.

  8. The Load Capacity Model and Experimental Tests of a New Yielding Steel Prop

    Directory of Open Access Journals (Sweden)

    Yanlong Chen

    2017-01-01

    Full Text Available As the mining depth increases year by year, the deformation and failure of deep roadway become more and more serious, and new support equipment with high supporting force and yieldable character is quite necessary for mining safety. In this research, a new yielding steel prop with high stable load capacity was introduced, which features sustaining large deformation in the field. Based on principle stress method and elastic-plastic theory, a mathematical model of load capacity was proposed for the new prop. The results show that the stable load capacity of the prop increases linearly with the increase of the effective number of the steel balls. Meanwhile, the stable load capacity of the prop increases initially and decreases afterwards with the increase of the radius of the steel ball. Under the fixed radius of the steel ball, the stable load capacity will increase with the decrease of the gap between the inner tube and the outer tube. The stable load capacity of the prop calculated using the theoretical model quantitatively agrees with that of the experimental tests, with only an error within 5%.

  9. Investigation of Water Dynamics and the Effect of Evapotranspiration on Grain Yield of Rainfed Wheat and Barley under a Mediterranean Environment: A Modelling Approach.

    Science.gov (United States)

    Zhang, Kefeng; Bosch-Serra, Angela D; Boixadera, Jaume; Thompson, Andrew J

    2015-01-01

    Agro-hydrological models have increasingly become useful and powerful tools in optimizing water and fertilizer application, and in studying the environmental consequences. Accurate prediction of water dynamics in such models is essential for models to produce reasonable results. In this study, detailed simulations were performed for water dynamics of rainfed winter wheat and barley grown under a Mediterranean climate over a 10-year period. The model employed (Yang et al., 2009. J. Hydrol., 370, 177-190) uses easily available agronomic data, and takes into consideration of all key soil and plant processes in controlling water dynamics in the soil-crop system, including the dynamics of root growth. The water requirement for crop growth was calculated according to the FAO56, and the soil hydraulic properties were estimated using peto-transfer functions (PTFs) based on soil physical properties and soil organic matter content. Results show that the simulated values of soil water content at the depths of 15, 45 and 75 cm agreed with the measurements well with the root of the mean squared errors of 0.027 cm(3) cm(-3) and the model agreement index of 0.875. The simulated seasonal evapotranspiration (ET) ranged from 208 to 388 mm, and grain yield was found to correlate with the simulated seasonal ET in a linear manner within the studied ET range. The simulated rates of grain yield increase were 17.3 and 23.7 kg ha(-l) for every mm of water evapotranspired for wheat and barley, respectively. The good agreement of soil water content between measurement and simulation and the simulated relationships between grain yield and seasonal ET supported by the data in the literature indicates that the model performed well in modelling water dynamics for the studied soil-crop system, and therefore has the potential to be applied reliably and widely in precision agriculture. Finally, a two-staged approach using inverse modelling techniques to further improve model performance was

  10. Fit of different functions to the individual deviations in random regression test day models for milk yield in dairy cattle

    Directory of Open Access Journals (Sweden)

    L.R. Schaeffer

    2010-04-01

    Full Text Available The shape of individual deviations of milk yield for dairy cattle from the fixed part of a random regression test day model (RRTDM was investigated. Data were 53,217 TD records for milk yield of 6,229 first lactation Canadian Holsteins in Ontario. Data were fitted with a model that included the fixed effects of herd-testdate, DIM interval nested within age and season of calving. Residuals of the model were then fitted with the following functions: Ali and Schaeffer 5 parameter model, fourth-order Legendre Polynomials, and cubic spline with three, four or five knots. Result confirm the great variability of shape that can be found when individual lactation are modeled. Cubic splines gave better fitting pe4rformances although together with a marked tendency to yield aberrant estimates at the edge of the lactation trajectory.

  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. 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)

  13. 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

    2017-11-01

    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.

  14. Yield strengths of flows on the earth, Mars, and moon. [application of Bingham plastic model to lava flows

    Science.gov (United States)

    Moore, H. J.; Arthur, D. W. G.; Schaber, G. G.

    1978-01-01

    Dimensions of flows on the earth, Mars, and moon and their topographic gradients obtained from remote measurements are used to calculate yield strengths with a view to explore the validity of the Bingham plastic model and determine whether there is a relation between yield strengths and silica contents. Other factors are considered such as the vagaries of natural phenomena that might contribute to erroneous interpretations and measurements. Comparison of yield strengths of Martian and lunar flows with terrestrial flows suggests that the Martian and lunar flows are more akin to terrestrial basalts than they are to terrestrial andesites, trachytes, and rhyolites.

  15. Exploring the performance of the SEDD model to predict sediment yield in eucalyptus plantations. Long-term results from an experimental catchment in Southern Italy

    Science.gov (United States)

    Porto, P.; Cogliandro, V.; Callegari, G.

    2018-01-01

    In this paper, long-term sediment yield data, collected in a small (1.38 ha) Calabrian catchment (W2), reafforested with eucalyptus trees (Eucalyptus occidentalis Engl.) are used to validate the performance of the SEdiment Delivery Distributed Model (SEDD) in areas with high erosion rates. At first step, the SEDD model was calibrated using field data collected in previous field campaigns undertaken during the period 1978-1994. This first phase allowed the model calibration parameter β to be calculated using direct measurements of rainfall, runoff, and sediment output. The model was then validated in its calibrated form for an independent period (2006-2016) for which new measurements of rainfall, runoff and sediment output are also available. The analysis, carried out at event and annual scale showed good agreement between measured and predicted values of sediment yield and suggested that the SEDD model can be seen as an appropriate means of evaluating erosion risk associated with manmade plantations in marginal areas. Further work is however required to test the performance of the SEDD model as a prediction tool in different geomorphic contexts.

  16. Spatial Rice Yield Estimation Based on MODIS and Sentinel-1 SAR Data and ORYZA Crop Growth Model

    Directory of Open Access Journals (Sweden)

    Tri D. Setiyono

    2018-02-01

    Full Text Available Crop insurance is a viable solution to reduce the vulnerability of smallholder farmers to risks from pest and disease outbreaks, extreme weather events, and market shocks that threaten their household food and income security. In developing and emerging countries, the implementation of area yield-based insurance, the form of crop insurance preferred by clients and industry, is constrained by the limited availability of detailed historical yield records. Remote-sensing technology can help to fill this gap by providing an unbiased and replicable source of the needed data. This study is dedicated to demonstrating and validating the methodology of remote sensing and crop growth model-based rice yield estimation with the intention of historical yield data generation for application in crop insurance. The developed system combines MODIS and SAR-based remote-sensing data to generate spatially explicit inputs for rice using a crop growth model. MODIS reflectance data were used to generate multitemporal LAI maps using the inverted Radiative Transfer Model (RTM. SAR data were used to generate rice area maps using MAPScape-RICE to mask LAI map products for further processing, including smoothing with logistic function and running yield simulation using the ORYZA crop growth model facilitated by the Rice Yield Estimation System (Rice-YES. Results from this study indicate that the approach of assimilating MODIS and SAR data into a crop growth model can generate well-adjusted yield estimates that adequately describe spatial yield distribution in the study area while reliably replicating official yield data with root mean square error, RMSE, of 0.30 and 0.46 t ha−1 (normalized root mean square error, NRMSE of 5% and 8% for the 2016 spring and summer seasons, respectively, in the Red River Delta of Vietnam, as evaluated at district level aggregation. The information from remote-sensing technology was also useful for identifying geographic locations with

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

    African Journals Online (AJOL)

    ozcan_eren

    The accurate measurement or prediction of milk yield is essential to their economy (Fernandez et al., 2007). ... economic predictions, and in medical diagnoses. ..... Jadhav, R.G., Vaıdya, M.S. & Toro, V.A., 1998. Prediction of first lactation milk yield based on part lactation performance in crossbred cows. J. Bombay Vet. Coll.

  18. Formative Assessment and Self-Regulated Learning: A Model and Seven Principles of Good Feedback Practice

    Science.gov (United States)

    Nicol, David J.; Macfarlane-Dick, Debra

    2006-01-01

    The research on formative assessment and feedback is reinterpreted to show how these processes can help students take control of their own learning, i.e. become self-regulated learners. This reformulation is used to identify seven principles of good feedback practice that support self-regulation. A key argument is that students are already…

  19. Asymptotic distribution for goodness-of-fit statistics in a sequence of multinomial models

    Czech Academy of Sciences Publication Activity Database

    Vajda, Igor; Gyorfi, L.

    2002-01-01

    Roč. 56, č. 1 (2002), s. 57-67 ISSN 0167-7152 R&D Projects: GA AV ČR IAA1075101 Institutional research plan: CEZ:AV0Z1075907 Keywords : goodness-of-fit statistics * disparity statistics * goodnes-of-fit tests Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.364, year: 2002

  20. Determining the Threshold Value of Basil Yield Reduction and Evaluation of Water Uptake Models under Salinity Stress Condition

    OpenAIRE

    M. Sarai Tabrizi; H. Babazadeh; M. Homaee; F. Kaveh Kaveh; M. Parsinejad

    2016-01-01

    Introduction: Several mathematical models are being used for assessing the plant response to the salinity of the root zone. The salinity of the soil and water resources is a major challenge for agricultural sector in Iran. Several mathematical models have been developed for plant responses to the salinity stress. However, these models are often applicable in particular conditions. The objectives of this study were to evaluate the threshold value of Basil yield reduction, modeling Basil respon...

  1. Analyzing and modelling the effect of long-term fertilizer management on crop yield and soil organic carbon in China.

    Science.gov (United States)

    Zhang, Jie; Balkovič, Juraj; Azevedo, Ligia B; Skalský, Rastislav; Bouwman, Alexander F; Xu, Guang; Wang, Jinzhou; Xu, Minggang; Yu, Chaoqing

    2018-06-15

    This study analyzes the influence of various fertilizer management practices on crop yield and soil organic carbon (SOC) based on the long-term field observations and modelling. Data covering 11 years from 8 long-term field trials were included, representing a range of typical soil, climate, and agro-ecosystems in China. The process-based model EPIC (Environmental Policy Integrated Climate model) was used to simulate the response of crop yield and SOC to various fertilization regimes. The results showed that the yield and SOC under additional manure application treatment were the highest while the yield under control treatment was the lowest (30%-50% of NPK yield) at all sites. The SOC in northern sites appeared more dynamic than that in southern sites. The variance partitioning analysis (VPA) showed more variance of crop yield could be explained by the fertilization factor (42%), including synthetic nitrogen (N), phosphorus (P), potassium (K) fertilizers, and fertilizer NPK combined with manure. The interactive influence of soil (total N, P, K, and available N, P, K) and climate factors (mean annual temperature and precipitation) determine the largest part of the SOC variance (32%). EPIC performs well in simulating both the dynamics of crop yield (NRMSE = 32% and 31% for yield calibration and validation) and SOC (NRMSE = 13% and 19% for SOC calibration and validation) under diverse fertilization practices in China. EPIC can assist in predicting the impacts of different fertilization regimes on crop growth and soil carbon dynamics, and contribute to the optimization of fertilizer management for different areas in China. Copyright © 2018. Published by Elsevier B.V.

  2. Yield responses of crops to changes in environment and management practices: Model sensitivity analysis. II. Rice, wheat, and potato

    Science.gov (United States)

    Terjung, W. H.; Hayes, J. T.; O'Rourke, P. A.; Todhunter, P. E.

    1984-12-01

    This paper is a continuation of our prior examination of yield responses of maize (Terjung et al., 1984b). The analysis of the response of the model YIELD to changes in a variety of basic environmental and decision-making inputs was continued for paddy rice, winter wheat, and early potato. As before, temperature, solar radiation, and relative humidity regimes were analyzed during a growing season along with different water application strategies, irrigation frequencies, soil types, and wind regimes. Among the results, yield decreased on the average by 4.9% (rice) and 6.0% (wheat) per 1‡ (C) increase in air temperature. A 1% change in solar radiation resulted in an average of 1% (wheat) and 0.4% (rice) change in yield. Analogous changes in relative humidity caused yield changes of about 0.8% and nothing for wheat and rice, respectively. For all crops, the relationship between irrigation frequency and yield increase was near-linear for large irrigation intervals. This linearity vanished under high frequency waterings. With respect to irrigation amounts, 1 mm/ha of applied water was related, on the average, to 75 (potato), 19 (grain corn), 8 (rice), and 6 kg/ha (wheat) of harvestable yield.

  3. 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.

  4. Prediction of winter wheat high yield from remote sensing based model: application in United States and Ukraine

    Science.gov (United States)

    Franch, B.; Vermote, E.; Roger, J. C.; Skakun, S.; Becker-Reshef, I.; Justice, C. O.

    2017-12-01

    Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. In Becker-Reshef et al. (2010) and Franch et al. (2015) we developed an empirical generalized model for forecasting winter wheat yield. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season and the Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data. These methods were applied to MODIS CMG data in Ukraine, the US and China with errors around 10%. However, the NDVI is saturated for yield values higher than 4 MT/ha. As a consequence, the model had to be re-calibrated in each country and the validation of the national yields showed low correlation coefficients. In this study we present a new model based on the extrapolation of the pure wheat signal (100% of wheat within the pixel) from MODIS data at 1km resolution and using the Difference Vegetation Index (DVI). The model has been applied to monitor the national yield of winter wheat in the United States and Ukraine from 2001 to 2016.

  5. Using the Good Way Model to Work Positively with Adults and Youth with Intellectual Difficulties and Sexually Abusive Behaviour

    Science.gov (United States)

    West, Bill

    2007-01-01

    The Good Way model is being used increasingly in New Zealand and Australia in both community-based and residential programmes for the treatment of adolescents and adults with intellectual difficulties who have sexually abusive behaviour. It is also being used with children and, in adapted forms, with mainstream adolescents and people of indigenous…

  6. Identifying critical nitrogen application rate for maize yield and nitrate leaching in a Haplic Luvisol soil using the DNDC model.

    Science.gov (United States)

    Zhang, Yitao; Wang, Hongyuan; Liu, Shen; Lei, Qiuliang; Liu, Jian; He, Jianqiang; Zhai, Limei; Ren, Tianzhi; Liu, Hongbin

    2015-05-01

    Identification of critical nitrogen (N) application rate can provide management supports for ensuring grain yield and reducing amount of nitrate leaching to ground water. A five-year (2008-2012) field lysimeter (1 m × 2 m × 1.2 m) experiment with three N treatments (0, 180 and 240 kg Nha(-1)) was conducted to quantify maize yields and amount of nitrate leaching from a Haplic Luvisol soil in the North China Plain. The experimental data were used to calibrate and validate the process-based model of Denitrification-Decomposition (DNDC). After this, the model was used to simulate maize yield production and amount of nitrate leaching under a series of N application rates and to identify critical N application rate based on acceptable yield and amount of nitrate leaching for this cropping system. The results of model calibration and validation indicated that the model could correctly simulate maize yield and amount of nitrate leaching, with satisfactory values of RMSE-observation standard deviation ratio, model efficiency and determination coefficient. The model simulations confirmed the measurements that N application increased maize yield compared with the control, but the high N rate (240 kg Nha(-1)) did not produce more yield than the low one (120 kg Nha(-1)), and that the amount of nitrate leaching increased with increasing N application rate. The simulation results suggested that the optimal N application rate was in a range between 150 and 240 kg ha(-1), which would keep the amount of nitrate leaching below 18.4 kg NO₃(-)-Nha(-1) and meanwhile maintain acceptable maize yield above 9410 kg ha(-1). Furthermore, 180 kg Nha(-1) produced the highest yields (9837 kg ha(-1)) and comparatively lower amount of nitrate leaching (10.0 kg NO₃(-)-Nha(-1)). This study will provide a valuable reference for determining optimal N application rate (or range) in other crop systems and regions in China. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Drought mitigation in perennial crops by fertilization and adjustments of regional yield models for future climate variability

    Science.gov (United States)

    Kantola, I. B.; Blanc-Betes, E.; Gomez-Casanovas, N.; Masters, M. D.; Bernacchi, C.; DeLucia, E. H.

    2017-12-01

    Increased variability and intensity of precipitation in the Midwest agricultural belt due to climate change is a major concern. The success of perennial bioenergy crops in replacing maize for bioethanol production is dependent on sustained yields that exceed maize, and the marketing of perennial crops often emphasizes the resilience of perennial agriculture to climate stressors. Land conversion from maize for bioethanol to Miscanthus x giganteus (miscanthus) increases yields and annual evapotranspiration rates (ET). However, establishment of miscanthus also increases biome water use efficiency (the ratio between net ecosystem productivity after harvest and ET), due to greater belowground biomass in miscanthus than in maize or soybean. In 2012, a widespread drought reduced the yield of 5-year-old miscanthus plots in central Illinois by 36% compared to the previous two years. Eddy covariance data indicated continued soil water deficit during the hydrologically-normal growing season in 2013 and miscanthus yield failed to rebound as expected, lagging behind pre-drought yields by an average of 53% over the next three years. In early 2014, nitrogen fertilizer was applied to half of mature (7-year-old) miscanthus plots in an effort to improve yields. In plots with annual post-emergence application of 60 kg ha-1 of urea, peak biomass was 29% greater than unfertilized miscanthus in 2014, and 113% greater in 2015, achieving statistically similar yields to the pre-drought average. Regional-scale models of perennial crop productivity use 30-year climate averages that are inadequate for predicting long-term effects of short-term extremes on perennial crops. Modeled predictions of perennial crop productivity incorporating repeated extreme weather events, observed crop response, and the use of management practices to mitigate water deficit demonstrate divergent effects on predicted yields.

  8. What is the Best Model Specification and Earth Observation Product for Predicting Regional Grain Yields in Food Insecure Countries?

    Science.gov (United States)

    Davenport, F., IV; Harrison, L.; Shukla, S.; Husak, G. J.; Funk, C. C.

    2017-12-01

    We evaluate the predictive accuracy of an ensemble of empirical model specifications that use earth observation data to predict sub-national grain yields in Mexico and East Africa. Products that are actively used for seasonal drought monitoring are tested as yield predictors. Our research is driven by the fact that East Africa is a region where decisions regarding agricultural production are critical to preventing the loss of economic livelihoods and human life. Regional grain yield forecasts can be used to anticipate availability and prices of key staples, which can turn can inform decisions about targeting humanitarian response such as food aid. Our objective is to identify-for a given region, grain, and time year- what type of model and/or earth observation can most accurately predict end of season yields. We fit a set of models to county level panel data from Mexico, Kenya, Sudan, South Sudan, and Somalia. We then examine out of sample predicative accuracy using various linear and non-linear models that incorporate spatial and time varying coefficients. We compare accuracy within and across models that use predictor variables from remotely sensed measures of precipitation, temperature, soil moisture, and other land surface processes. We also examine at what point in the season a given model or product is most useful for determining predictive accuracy. Finally we compare predictive accuracy across a variety of agricultural regimes including high intensity irrigated commercial agricultural and rain fed subsistence level farms.

  9. 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

  10. Estimation of genetic parameters for test-day milk yield in Holstein cows using a random regression model

    Directory of Open Access Journals (Sweden)

    Jaime Araujo Cobuci

    2005-03-01

    Full Text Available Test-day milk yield records of 11,023 first-parity Holstein cows were used to estimate genetic parameters for milk yield during different lactation periods. (Covariance components were estimated using two random regression models, RRM1 and RRM2, and the restricted maximum likelihood method, compared by the likelihood ratio test. Additive genetic variances determined by RRM1 and additive genetic and permanent environmental variances estimated by RRM2 were described, using the Wilmink function. Residual variance was constant throughout lactation for the two models. The heritability estimates obtained by RRM1 (0.34 to 0.56 were higher than those obtained by RRM2 (0.15 to 0.31. Due to the high heritability estimates for milk yield throughout lactation and the negative genetic correlation between test-day yields during different lactation periods, the RRM1 model did not fit the data. Overall, genetic correlations between individual test days tended to decrease at the extremes of the lactation trajectory, showing values close to unity for adjacent test days. The inclusion of random regression coefficients to describe permanent environmental effects led to a more precise estimation of genetic and non-genetic effects that influence milk yield.

  11. The Case of a Giffen Good: Reply.

    Science.gov (United States)

    Spiegel, Uriel

    1997-01-01

    Reexamines Spiegel's analysis of the Giffen phenomenon, a utility function that yields an inferior good with an upward-sloping demand curve and incorporates Christian Weber's criticism into the model. Disagrees with Weber on some points but agrees that as income decreases the likelihood of the Giffen product decreases. (MJP)

  12. Impacts of climate change on peanut yield in China simulated by CMIP5 multi-model ensemble projections

    Science.gov (United States)

    Xu, Hanqing; Tian, Zhan; Zhong, Honglin; Fan, Dongli; Shi, Runhe; Niu, Yilong; He, Xiaogang; Chen, Maosi

    2017-09-01

    Peanut is one of the major edible vegetable oil crops in China, whose growth and yield are very sensitive to climate change. In addition, agriculture climate resources are expected to be redistributed under climate change, which will further influence the growth, development, cropping patterns, distribution and production of peanut. In this study, we used the DSSAT-Peanut model to examine the climate change impacts on peanut production, oil industry and oil food security in China. This model is first calibrated using site observations including 31 years' (1981-2011) climate, soil and agronomy data. This calibrated model is then employed to simulate the future peanut yield based on 20 climate scenarios from 5 Global Circulation Models (GCMs) developed by the InterSectoral Impact Model Intercomparison Project (ISIMIP) driven by 4 Representative Concentration Pathways (RCPs). Results indicate that the irrigated peanut yield will decrease 2.6% under the RCP 2.6 scenario, 9.9% under the RCP 4.5 scenario and 29% under the RCP 8.5 scenario, respectively. Similarly, the rain-fed peanut yield will also decrease, with a 2.5% reduction under the RCP 2.6 scenario, 11.5% reduction under the RCP 4.5 scenario and 30% reduction under the RCP 8.5 scenario, respectively.

  13. 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, p<0.01 and SOC with R2=0.70, d=0.86, EF=0.59, and p<0.01. EPIC can well simulate soil available P moderately and capture the temporal changes in soil P reservoirs. Both of Crop yields and soil available were found more sensitive to the fertilizer P rates in humid than drought year and soil available P is closely linked to concentrated rainfall. This study concludes that EPIC model has great potential to simulate the P cycle in croplands in China and can explore the optimum management practices.

  14. 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

  15. 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.)

  16. How good is the Prevent model for estimating the health benefits of prevention?

    DEFF Research Database (Denmark)

    Brønnum-Hansen, Henrik

    1999-01-01

    Prevent is a public health model for estimating the effect on mortality of changes in exposure to risk factors. When the model is tested by simulating a development that has already taken place, the results may differ considerably from the actual situation. The purpose of this study is to test...... the Prevent model by applying it to a synthetic cohort in which the development is unaffected by concealed factors....

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

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus

    2006-01-01

    The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...... distribution of the simulated random effects coincides with the assumed random effects distribution. In practice, the specified model depends on some unknown parameter which is replaced by an estimate. We obtain a correction for this by deriving the asymptotic distribution of the empirical distribution...

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

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus Plenge

    The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...... distribution of the simulated random effects coincides with the assumed random effects distribution. In practice the specified model depends on some unknown parameter which is replaced by an estimate. We obtain a correction for this by deriving the asymptotic distribution of the empirical distribution function...

  19. How good is the Prevent model for estimating the health benefits of prevention?

    DEFF Research Database (Denmark)

    Brønnum-Hansen, Henrik

    1999-01-01

    Prevent is a public health model for estimating the effect on mortality of changes in exposure to risk factors. When the model is tested by simulating a development that has already taken place, the results may differ considerably from the actual situation. The purpose of this study is to test...

  20. Every good regulator of a system must be a model of that system

    Directory of Open Access Journals (Sweden)

    Pieter Eykhoff

    1994-07-01

    Full Text Available A model for the process under control - do or don't we really need it? Some elementary philosophical considerations confirming such a need, are well supported by examples of various 'optimal' control schemes. How does this affirmation influence the requirements to identification and the implemcntation of control using such a model?

  1. Preserving the Public Good: Presenting an Organizational Model for the Changing Future of Higher Education

    Science.gov (United States)

    Garcia, Stephanie Parra

    2011-01-01

    Institutions of higher education face financial pressure to become self-sustaining (Gumport, 2001; 2000). This rapidly growing economic demand is negatively affecting the social mission of higher education (Kezar, 2004). Scholars suggest the implementation of a new model of higher education, one that blends a for-profit model with the traditional…

  2. A Production Efficiency Model-Based Method for Satellite Estimates of Corn and Soybean Yields in the Midwestern US

    Directory of Open Access Journals (Sweden)

    Andrew E. Suyker

    2013-11-01

    Full Text Available Remote sensing techniques that provide synoptic and repetitive observations over large geographic areas have become increasingly important in studying the role of agriculture in global carbon cycles. However, it is still challenging to model crop yields based on remotely sensed data due to the variation in radiation use efficiency (RUE across crop types and the effects of spatial heterogeneity. In this paper, we propose a production efficiency model-based method to estimate corn and soybean yields with MODerate Resolution Imaging Spectroradiometer (MODIS data by explicitly handling the following two issues: (1 field-measured RUE values for corn and soybean are applied to relatively pure pixels instead of the biome-wide RUE value prescribed in the MODIS vegetation productivity product (MOD17; and (2 contributions to productivity from vegetation other than crops in mixed pixels are deducted at the level of MODIS resolution. Our estimated yields statistically correlate with the national survey data for rainfed counties in the Midwestern US with low errors for both corn (R2 = 0.77; RMSE = 0.89 MT/ha and soybeans (R2 = 0.66; RMSE = 0.38 MT/ha. Because the proposed algorithm does not require any retrospective analysis that constructs empirical relationships between the reported yields and remotely sensed data, it could monitor crop yields over large areas.

  3. Multitrait, random regression, or simple repeatability model in high-throughput phenotyping data improve genomic prediction for wheat grain yield

    Science.gov (United States)

    High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat (Triticum aestivum L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect s...

  4. Simulation of spring barley yield in different climatic zones of Northern and Central Europe. A comparison of nine crop models

    Czech Academy of Sciences Publication Activity Database

    Rötter, R.P.; Palosuo, T.; Kersebaum, K. C.; Angulo, C.; Bindi, M.; Ewert, F.; Ferrise, R.; Hlavinka, P.; Moriondo, M.; Nendel, C.; Olesen, J. E.; Patil, R. H.; Ruget, F.; Takáč, J.; Trnka, Miroslav

    2012-01-01

    Roč. 133, July 2012 (2012), s. 23-36 ISSN 0378-4290 R&D Projects: GA MŠk(CZ) ED1.1.00/02.0073 Institutional research plan: CEZ:AV0Z60870520 Keywords : Climate * Crop growth simulation * Model comparison * Spring barley * Yield variability * Uncertainty Subject RIV: EH - Ecology, Behaviour Impact factor: 2.474, year: 2012

  5. 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 availabl...

  6. 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...

  7. Theories of learning: models of good practice for evidence-based information skills teaching.

    Science.gov (United States)

    Spring, Hannah

    2010-12-01

    This feature considers models of teaching and learning and how these can be used to support evidence based practice. © 2010 The authors. Health Information and Libraries Journal © 2010 Health Libraries Group.

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

    OpenAIRE

    Diamond, Joshua M.

    2016-01-01

    The conserved nature of sleep in Drosophila has allowed the fruit fly to emerge in the last decade as a powerful model organism in which to study sleep. Recent sleep studies in Drosophila have focused on the discovery and characterization of hyposomnolent mutants. One common feature of these animals is a change in sleep architecture: sleep bout count tends to be greater, and sleep bout length lower, in hyposomnolent mutants. I propose a mathematical model, produced by least-squares nonlinear ...

  9. 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.

  10. Development of growth and yield models for southern hardwoods: site index determinations

    Science.gov (United States)

    John Paul McTague; Daniel J. Robison; David O' Loughlin; Joseph Roise; Robert Kellison

    2006-01-01

    Growth and yield data from across 13 southern States, collected from 1967 to 2004 from fully-stocked even-aged southern hardwood forests on a variety of site types, was used to calculate site index curves. These derived curves provide an efficient means to evaluate the productivity-age relation which varies across many sites. These curves were derived for mixed-species...

  11. Modeling osmotic salinity effects on yield characteristics of substrate-grown greenhouse crops

    NARCIS (Netherlands)

    Sonneveld, C.; Bos, van den A.L.; Voogt, W.

    2004-01-01

    In a series of experiments with different osmotic potentials in the root environment, various vegetables, and ornamentals were grown in a substrate system. The osmotic potential was varied by addition of nutrients. Yield characteristics of the crop were related to the osmotic potential of the

  12. Crop Yields and Climate Change to the Year 2000. Volume 2: Climate Model and Technical Appendixes.

    Science.gov (United States)

    1988-01-01

    it encounters the relatively flat region where yields are less sensitive to fluctuations of annual temperature and precipitation than they are in...the others are transpacific in nature (e.g., a negative correlation between the precipitation affec- ting wheat in Argentina and Australia). Hayes

  13. 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

  14. Modelling of seed yield and its components in tall fescue (Festuca ...

    African Journals Online (AJOL)

    AJL

    2011-10-03

    Oct 3, 2011 ... number spikelet -1 (Y4), seed weight (Y5), and the seed yield (Z) of tall fescue were determined in field experiments from 2003 to .... the time of fertilisation (X1), the quantity of irrigation (X2), the amount of N applied (X3), the ...... certain agronomical traits in soybean [Glycine max (L.) Merr.]. Afr. J. Biotechnol.

  15. Design of an integrated forward and reverse logistics network optimi-zation model for commercial goods management

    Directory of Open Access Journals (Sweden)

    Eva Ponce-Cueto

    2015-01-01

    Full Text Available In this study, an optimization model is formulated for designing an integrated forward and reverse logistics network in the consumer goods industry. The resultant model is a mixed-integer linear programming model (MILP. Its purpose is to minimize the total costs of the closed-loop supply chain network. It is important to note that the design of the logistics network may involve a trade-off between the total costs and the optimality in commercial goods management. The model comprises a discrete set as potential locations of unlimited capacity warehouses and fixed locations of customers’ zones. It provides decisions related to the facility location and customers’ requirements satisfaction, all of this related with the inventory and shipment decisions of the supply chain. Finally, an application of this model is illustrated by a real-life case in the food and drinks industry. We can conclude that this model can significantly help companies to make decisions about problems associated with logistics network design.

  16. The Effects of Mixing, Reaction Rates, and Stoichiometry on Yield for Mixing Sensitive Reactions—Part I: Model Development

    Directory of Open Access Journals (Sweden)

    Syed Imran A. Shah

    2012-01-01

    Full Text Available There are two classes of mixing sensitive reactions: competitive-consecutive and competitive-parallel. The yield of desired product from these coupled reactions depends on how fast the reactants are brought together. Recent experimental results have suggested that the mixing effect may depend strongly on the stoichiometry of the reactions. To investigate this, a 1D, dimensionless, reaction-diffusion model at the micromixing scale was developed. Assuming constant mass concentration and mass diffusivities, systems of PDE's were derived on a mass fraction basis for both types of reactions. Two dimensionless reaction rate ratios and a single general Damköhler number emerged from the analysis. The resulting dimensionless equations were used to investigate the effects of mixing, reaction rate ratio, and reaction stoichiometry. As expected, decreasing either the striation thickness or the dimensionless rate ratio maximizes yield, the reaction stoichiometry has a considerable effect on yield, and all three variables interact strongly.

  17. Low apparent quantum yield in Arctic plants suggests that terrestrial biosphere models will over estimate carbon assimilation at high latitudes

    Science.gov (United States)

    Rogers, A.; Serbin, S.; Ely, K.; Wullschleger, S.

    2017-12-01

    Estimates of Gross Primary Productivity (GPP) by terrestrial biosphere models (TBMs) rely on accurate model representation of photosynthesis. In the Arctic, TBM uncertainty over GPP is the dominant driver of an uncertain Arctic carbon cycle. Previously we have shown that TBMs underestimate light saturated photosynthesis due to poor model representation of maximum carboxylation capacity and maximum electron transport. Here we extend this work to investigate model representation of the response of photosynthesis to irradiance. TBMs use an empirical relationship, typically a non-rectangular hyperbola, to estimate potential electron transport rate from incident irradiance. The key model inputs used to parameterize this formulation are; absorptance, quantum yield, and a curvature factor. TBMs show a high divergence in the response of photosynthesis to irradiance driven in part by variation in these parameters. In addition, most existing measurements used to parameterize TBMs have been made within a narrow temperature range (20-30°C) and the scarcity of data collected at low temperature has been highlighted as an important driver of model uncertainty at high latitudes. To address this issue we measured photosynthetic light response curves at 5 and 15°C and the leaf optical properties of six species growing on the Barrow Environmental Observatory, Barrow, Alaska. We determined leaf absorbtance, the convexity term, and apparent quantum yield. Our key finding was that measured apparent quantum yield was lower than model estimates, particularly at 5°C. Our results show that TBMs that rely on relatively high theoretical estimates of apparent quantum yield will likely overestimate carbon assimilation at low temperature and low irradiance.

  18. Mechanical responses, texture evolution, and yield loci of extruded AZ31 magnesium alloy under various loading conditions: Experiment and modeling

    Science.gov (United States)

    Kabirian, Farhoud

    Mechanical responses and texture evolution of extruded AZ31 Mg are measured under uniaxial (tension-compression) and multiaxial (free-end torsion) loadings. Compression loading is carried out in three different directions at temperature and strain rate ranges of 77-423 K and 10-4 -3000 s -1, respectively. Texture evolution at different intermediate strains reveals that crystal reorientation is exhausted at smaller strains with increase in strain rate while increase in temperature retards twinning. In addition to the well-known tension-compression yield asymmetry, a strong anisotropy in strain hardening response is observed. Strain hardening during the compression experiment is intensified with decreasing and increasing temperature and strain rate, respectively. This complex behavior is explained through understanding the roles of deformation mechanisms using the Visco-Plastic Self Consistent (VPSC) model. In order to calibrate the VPSC model's constants as accurate as possible, a vast number of mechanical responses including stress-strain curves in tension, compression in three directions, and free-end torsion, texture evolution at different strains, lateral strains of compression samples, twin volume fraction, and axial strain during the torsion experiment. Modeling results show that depending on the number of measurements used for calibration, roles of different mechanisms in plastic deformation change significantly. In addition, a precise definition of yield is established for the extruded AZ31magnesium alloy after it is subjected to different loading conditions (uniaxial to multiaxial) at four different plastic strains. The yield response is measured in ?-? space. Several yield criteria are studied to predict yield response of extruded AZ31. This study proposes an asymmetrical fourth-order polynomial yield function. Material constants in this model can be directly calculated using mechanical measurements. Convexity of the proposed model is discussed, and

  19. From humanitarianism to good governance? Reflections on a Danish-Ethiopian aid model

    DEFF Research Database (Denmark)

    Wilson, Fiona

    The report reflects on what people engaged in development research and practice mean by 'aid models'. Illustrating the argument is the history of an NGO alliance between Ethiopia and Denmark over the last 10 years. The report argues that 'northern' NGOs are often guilty of imposing new concepts...... and languages of development aid on their southern counterparts and that this has deleterious effects....

  20. Substandard model? At last, a good reason to opt for a sexier theory of particle physics

    CERN Multimedia

    Cho, A

    2001-01-01

    According to experimenters at Brookhaven, a tiny discrepancy in the magnetism of the muon may signal a crack in the Standard Model. The deviation could be the first piece of hard evidence for a more complete theory called supersymmetry (1 page).

  1. An Application of Structural Equation Modeling for Developing Good Teaching Characteristics Ontology

    Science.gov (United States)

    Phiakoksong, Somjin; Niwattanakul, Suphakit; Angskun, Thara

    2013-01-01

    Ontology is a knowledge representation technique which aims to make knowledge explicit by defining the core concepts and their relationships. The Structural Equation Modeling (SEM) is a statistical technique which aims to explore the core factors from empirical data and estimates the relationship between these factors. This article presents an…

  2. Long-term culture of organotypic multicellular glioma spheroids: a good culture model for studying gliomas

    NARCIS (Netherlands)

    Kaaijk, P.; Troost, D.; Das, P. K.; Leenstra, S.; Bosch, D. A.

    1995-01-01

    Gliomas, as well as other solid tumours, contain tumour stroma composed of connective tissue, macrophages, capillaries and other non-cellular constituents. Therefore, a homogeneous culture of tumour cells alone, as is often used as a culture model for gliomas, is not ideal to study all aspects of

  3. TEACHING AND LEARNING WITH TECHNOLOGY: A THEORETICAL MODEL FOR GOOD EDUCATIONAL PRACTICES WITH ICT

    Directory of Open Access Journals (Sweden)

    Jesús Valverde Berrocoso

    2010-02-01

    Full Text Available This article aims to define a theoretical explanatory framework for the integration of information technologies and communication technologies (ICT in education from the perspective of teacher education. The initial and continuing training of teachers is characterized by a tendency towards "essentialisation" of technology and generation of users who do not usually think about educational uses of technology in their own contexts. Our research on the integration of ICT in the classroom has allowed us to observe the lack of connection between the personal and professional use of teachers of these technological tools, as well as the need for training is geared towards developing skills and knowledge to examine, in a critical manner, the educational implications of these new teaching aids. This article is based on the proposed Koehler & Mishra (2005, 2006, 2007 and 2008 called TPCK (Technological Pedagogical Content Knowledge which is based on the construct of PCK Shulman (1987 to which is added the concept of "Technology" (T to those of "Pedagogy" (P and "Curriculum Content" (C. Connections and dynamic interactions between these three key components leading to different components to be considered in understanding the processes of integration of ICT in schools. Good educational practices with ICT are multidimensional and complex actions that require (1 understand the representation and formulation of concepts and procedures for their understanding through ICT, (2 develop constructivist teaching strategies that use ICT for teaching content curriculum, (3 know the difficulties in learning concepts and how ICT can help overcome them, and (4 knowing the students' prior knowledge and the epistemology of the curriculum to understand how ICT can be used to build on pre-existing knowledge and develop new epistemologies. These skills clearly go beyond the isolation that has an expert in a curriculum (teacher of a discipline, an expert in IT (engineer, or an

  4. 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)

  5. Kinetic modeling of solid yields formation in the fast pyrolysis of mahogany wood

    Science.gov (United States)

    Wijayanti, W.; Sasongko, M. N.

    2016-03-01

    There have been many research of biomass pyrolysis not only in heat transfer point of view but also in chemical reaction point of view. In the present study, the rate of reaction (kinetic rate) formation of solid yield was calculated by varying the pyrolysis temperature that gives a chance of 250 °C, 350 °C, 450 °C, 500 °C, 600 °C, 700 °C, until 800°C with heating rate around 700 °C/hour. The heating rate used was the fast pyrolysis in which the heating rate for heating furnaces takes place quickly. Pyrolysis was accomplished by direct pyrolysis process in which each process was conducted at the certain pyrolysis temperature variation that took over 3 hours. Biomass used was mahogany wood, while the inert gas used to hold in order to avoid combustion was nitrogen gas. The decreasing of solid yields formation obtained was used to calculate the kinetic rate of the pyrolysis process. It was calculated by using the similar Arrhenius equation that considering the temperature changes during the process and the decreasing mass of solid yield formation occurred. The kinetic rate results showed the decomposition of biomass occurs tended in two stages, namely a stage of water evaporation and degradation of biomass solid yield coal followed by a stage of constant formation. The decomposition is expressed by the magnitude of the rate of reaction at 25˚C-517˚C temperature range with a reaction rate constant k1 = 2151.67 exp (-2141/Tp). While at pyrolysis temperatures above 517˚C, the reaction rate constant is expressed with k2 = 32.20 exp (-127.8 / Tp).

  6. Good practice models for public workplace health promotion projects in Austria: promoting mental health.

    Science.gov (United States)

    Burkert, Nathalie T; Muckenhuber, Johanna; Großschädl, Franziska; Sprenger, Martin; Rohrauer-Näf, Gerlinde; Ropin, Klaus; Martinel, Evelyn; Dorner, Thomas

    2014-04-01

    Promoting mental health is a central public health issue since the Jakarta statement in 1997. In Austria, the nationwide organisation for health promotion is the 'Fonds Gesundes Österreich' (FGÖ), which has been established in 1998. The FGÖ funds and supports workplace health promotion projects; therefore, it co-operates with the Austrian Network on Workplace Health Promotion. In 2011, among others, two Austrian companies were honoured as best practice models for promoting mental health in the project 'Work. In tune with life. Move Europe'. One of their central key success factors are the provision of equal opportunities, engagement, their focus on overall health as well as the implementation of behavioural and environmental preventive measures. Since mental health problems in the population are still rising, public health promotion projects which orientate on the best practice models have to be established in Austria.

  7. Why Enforcing its UNCAC Commitments Would be Good for Russia: A Computable General Equilibrium Model

    Directory of Open Access Journals (Sweden)

    Michael P. BARRY

    2010-05-01

    Full Text Available Russia has ratified the UN Convention Against Corruption but has not successfully enforced it. This paper uses updated GTAP data to reconstruct a computable general equilibrium (CGE model to quantify the macroeconomic effects of corruption in Russia. Corruption is found to cost the Russian economy billions of dollars a year. A conclusion of the paper is that implementing and enforcing the UNCAC would be of significant economic benefit to Russia and its people.

  8. Computational modelling suggests good, bad and ugly roles of glycosaminoglycans in arterial wall mechanics and mechanobiology

    Science.gov (United States)

    Roccabianca, S.; Bellini, C.; Humphrey, J. D.

    2014-01-01

    The medial layer of large arteries contains aggregates of the glycosaminoglycan hyaluronan and the proteoglycan versican. It is increasingly thought that these aggregates play important mechanical and mechanobiological roles despite constituting only a small fraction of the normal arterial wall. In this paper, we offer a new hypothesis that normal aggregates of hyaluronan and versican pressurize the intralamellar spaces, and thereby put into tension the radial elastic fibres that connect the smooth muscle cells to the elastic laminae, which would facilitate mechanosensing. This hypothesis is supported by novel computational simulations using two complementary models, a mechanistically based finite-element mixture model and a phenomenologically motivated continuum hyperelastic model. That is, the simulations suggest that normal aggregates of glycosaminoglycans/proteoglycans within the arterial media may play equally important roles in supporting (i.e. a structural role) and sensing (i.e. an instructional role) mechanical loads. Additional simulations suggest further, however, that abnormal increases in these aggregates, either distributed or localized, may over-pressurize the intralamellar units. We submit that these situations could lead to compromised mechanosensing, anoikis and/or reduced structural integrity, each of which represent fundamental aspects of arterial pathologies seen, for example, in hypertension, ageing and thoracic aortic aneurysms and dissections. PMID:24920112

  9. 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.

  10. Investigation of Water Dynamics and the Effect of Evapotranspiration on Grain Yield of Rainfed Wheat and Barley under a Mediterranean Environment: A Modelling Approach.

    Directory of Open Access Journals (Sweden)

    Kefeng Zhang

    Full Text Available Agro-hydrological models have increasingly become useful and powerful tools in optimizing water and fertilizer application, and in studying the environmental consequences. Accurate prediction of water dynamics in such models is essential for models to produce reasonable results. In this study, detailed simulations were performed for water dynamics of rainfed winter wheat and barley grown under a Mediterranean climate over a 10-year period. The model employed (Yang et al., 2009. J. Hydrol., 370, 177-190 uses easily available agronomic data, and takes into consideration of all key soil and plant processes in controlling water dynamics in the soil-crop system, including the dynamics of root growth. The water requirement for crop growth was calculated according to the FAO56, and the soil hydraulic properties were estimated using peto-transfer functions (PTFs based on soil physical properties and soil organic matter content. Results show that the simulated values of soil water content at the depths of 15, 45 and 75 cm agreed with the measurements well with the root of the mean squared errors of 0.027 cm(3 cm(-3 and the model agreement index of 0.875. The simulated seasonal evapotranspiration (ET ranged from 208 to 388 mm, and grain yield was found to correlate with the simulated seasonal ET in a linear manner within the studied ET range. The simulated rates of grain yield increase were 17.3 and 23.7 kg ha(-l for every mm of water evapotranspired for wheat and barley, respectively. The good agreement of soil water content between measurement and simulation and the simulated relationships between grain yield and seasonal ET supported by the data in the literature indicates that the model performed well in modelling water dynamics for the studied soil-crop system, and therefore has the potential to be applied reliably and widely in precision agriculture. Finally, a two-staged approach using inverse modelling techniques to further improve model

  11. Using ORYZA2000 to model cold rice yield response to climate change in the Heilongjiang province, China

    Directory of Open Access Journals (Sweden)

    Jingting Zhang

    2015-08-01

    Full Text Available 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

  12. Keep Up the Good Work! Age-Moderated Mediation Model on Intention to Retire.

    Science.gov (United States)

    Dordoni, Paola; Van der Heijden, Beatrice; Peters, Pascale; Kraus-Hoogeveen, Sascha; Argentero, Piergiorgio

    2017-01-01

    In European nations, the aging of the workforce is a major issue which is increasingly addressed both in national and organizational policies in order to sustain older workers' employability and to encourage longer working lives. Particularly older workers' employability can be viewed an important issue as this has the potential to motivate them for their work and change their intention to retire. Based on lifespan development theories and Van der Heijden's 'employability enhancement model', this paper develops and tests an age-moderated mediation model (which refers to the processes that we want to test in this model), linking older workers' (55 years old and over) perceptions of job support for learning (job-related factor) and perceptions of negative age stereotypes on productivity (organizational factor), on the one hand, and their intention to retire, on the other hand, via their participation in employability enhancing activities, being the mediator in our model. A total of 2,082 workers aged 55 years and above were included in the analyses. Results revealed that the two proposed relationships between the predictors and intention to retire were mediated by participation in employability enhancing activities, reflecting two mechanisms through which work context affects intention to retire (namely 'a gain spiral and a loss spiral'). Multi-Group SEM analyses, distinguishing between two age groups (55-60 and 61-65 years old), revealed different paths for the two distinguished groups of older workers. Employability mediated the relationship between perceptions of job support for learning and intention to retire in both age groups, whereas it only mediated the relationship between perceptions of negative age stereotypes and intention to retire in the 55-60 group. From our empirical study, we may conclude that employability is an important factor in the light of older workers' intention to retire. In order to motivate this category of workers to participate in

  13. 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....

  14. Equity yields

    NARCIS (Netherlands)

    Vrugt, E.; van Binsbergen, J.H.; Koijen, R.S.J.; Hueskes, W.

    2013-01-01

    We study a new data set of dividend futures with maturities up to ten years across three world regions: the US, Europe, and Japan. We use these asset prices to construct equity yields, analogous to bond yields. We decompose the equity yields to obtain a term structure of expected dividend growth

  15. When It’s Good to Feel Bad: An Evolutionary Model of Guilt and Apology

    Directory of Open Access Journals (Sweden)

    Sarita Rosenstock

    2018-03-01

    Full Text Available We use techniques from evolutionary game theory to analyze the conditions under which guilt can provide individual fitness benefits, and so evolve. In particular, we focus on the benefits of guilty apology. We consider models where actors err in an iterated prisoner’s dilemma and have the option to apologize. Guilt either improves the trustworthiness of apology or imposes a cost on actors who apologize. We analyze the stability and likelihood of evolution of such a “guilt-prone” strategy against cooperators, defectors, grim triggers, and individuals who offer fake apologies, but continue to defect. We find that in evolutionary models guilty apology is more likely to evolve in cases where actors interact repeatedly over long periods of time, where the costs of apology are low or moderate, and where guilt is hard to fake. Researchers interested in naturalized ethics, and emotion researchers, can employ these results to assess the plausibility of fuller accounts of the evolution of guilt.

  16. Comparison of parametric, orthogonal, and spline functions to model individual lactation curves for milk yield in Canadian Holsteins

    Directory of Open Access Journals (Sweden)

    Corrado Dimauro

    2010-11-01

    Full Text Available Test day records for milk yield of 57,390 first lactation Canadian Holsteins were analyzed with a linear model that included the fixed effects of herd-test date and days in milk (DIM interval nested within age and calving season. Residuals from this model were analyzed as a new variable and fitted with a five parameter model, fourth-order Legendre polynomials, with linear, quadratic and cubic spline models with three knots. The fit of the models was rather poor, with about 30-40% of the curves showing an adjusted R-square lower than 0.20 across all models. Results underline a great difficulty in modelling individual deviations around the mean curve for milk yield. However, the Ali and Schaeffer (5 parameter model and the fourth-order Legendre polynomials were able to detect two basic shapes of individual deviations among the mean curve. Quadratic and, especially, cubic spline functions had better fitting performances but a poor predictive ability due to their great flexibility that results in an abrupt change of the estimated curve when data are missing. Parametric and orthogonal polynomials seem to be robust and affordable under this standpoint.

  17. Improving Spring Maize Yield Estimation at Field Scale by Assimilating Time-Series HJ-1 CCD Data into the WOFOST Model Using a New Method with Fast Algorithms

    OpenAIRE

    Zhiqiang Cheng; Jihua Meng; Yiming Wang

    2016-01-01

    Field crop yield prediction is crucial to grain storage, agricultural field management, and national agricultural decision-making. Currently, crop models are widely used for crop yield prediction. However, they are hampered by the uncertainty or similarity of input parameters when extrapolated to field scale. Data assimilation methods that combine crop models and remote sensing are the most effective methods for field yield estimation. In this study, the World Food Studies (WOFOST) model is u...

  18. Keep Up the Good Work! Age-Moderated Mediation Model on Intention to Retire

    Directory of Open Access Journals (Sweden)

    Paola Dordoni

    2017-10-01

    Full Text Available In European nations, the aging of the workforce is a major issue which is increasingly addressed both in national and organizational policies in order to sustain older workers' employability and to encourage longer working lives. Particularly older workers' employability can be viewed an important issue as this has the potential to motivate them for their work and change their intention to retire. Based on lifespan development theories and Van der Heijden's ‘employability enhancement model’, this paper develops and tests an age-moderated mediation model (which refers to the processes that we want to test in this model, linking older workers' (55 years old and over perceptions of job support for learning (job-related factor and perceptions of negative age stereotypes on productivity (organizational factor, on the one hand, and their intention to retire, on the other hand, via their participation in employability enhancing activities, being the mediator in our model. A total of 2,082 workers aged 55 years and above were included in the analyses. Results revealed that the two proposed relationships between the predictors and intention to retire were mediated by participation in employability enhancing activities, reflecting two mechanisms through which work context affects intention to retire (namely ‘a gain spiral and a loss spiral’. Multi-Group SEM analyses, distinguishing between two age groups (55–60 and 61–65 years old, revealed different paths for the two distinguished groups of older workers. Employability mediated the relationship between perceptions of job support for learning and intention to retire in both age groups, whereas it only mediated the relationship between perceptions of negative age stereotypes and intention to retire in the 55–60 group. From our empirical study, we may conclude that employability is an important factor in the light of older workers' intention to retire. In order to motivate this category of

  19. Documenting good practices: scaling up the youth friendly health service model in Colombia.

    Science.gov (United States)

    Huaynoca, Silvia; Svanemyr, Joar; Chandra-Mouli, Venkatraman C; Moreno Lopez, Diva Jeaneth

    2015-09-18

    Young people make up for 24.5 % of Latin America's population. Inadequate supply of specific and timely sexual and reproductive health (SRH) services and sexuality education for young people increases their risk of sexual and reproductive ill health. Colombia is one of the few countries in Latin America that has implemented and scaled up specific and differentiated health and SRH services-termed as its Youth Friendly Health Services (YFHS) Model. To provide a systematic description of the crucial factors that facilitated and hindered the scale up process of the YFHS Model in Colombia. A comprehensive literature search on SRH services for young people and national efforts to improve their quality of care in Colombia and neighbouring countries was carried out along with interviews with a selection of key stakeholders. The information gathered was analysed using the World Health Organization-ExpandNet framework (WHO-ExpandNet). In 7 years (2007-2013) of the implementation of the YFHS Model in Colombia more than 800 clinics nationally have been made youth friendly. By 2013, 536 municipalities in 32 departments had YFHS, resulting in coverage of 52 % of municipalities offering YHFS. The analysis using the WHO-ExpandNet framework identified five elements that enabled the scale up process: Clear policies and implementation guidelines on YFHS, clear attributes of the user organization and resource team, establishment and implementation of an inter-sectoral and interagency strategy, identification of and support to stakeholders and advocates of YFHS, and solid monitoring and evaluation. The elements that limited or slowed down the scale up effort were: Insufficient number of health personnel trained in youth health and SRH, a high turnover of health personnel, a decentralized health security system, inadequate supply of financial and human resources, and negative perceptions among community members about providing SRH information and services to young people. Colombia

  20. Limited-information goodness-of-fit testing of item response theory models for sparse 2 tables.

    Science.gov (United States)

    Cai, Li; Maydeu-Olivares, Albert; Coffman, Donna L; Thissen, David

    2006-05-01

    Bartholomew and Leung proposed a limited-information goodness-of-fit test statistic (Y) for models fitted to sparse 2(P ) contingency tables. The null distribution of Y was approximated using a chi-squared distribution by matching moments. The moments were derived under the assumption that the model parameters were known in advance and it was conjectured that the approximation would also be appropriate when the parameters were to be estimated. Using maximum likelihood estimation of the two-parameter logistic item response theory model, we show that the effect of parameter estimation on the distribution of Y is too large to be ignored. Consequently, we derive the asymptotic moments of Y for maximum likelihood estimation. We show using a simulation study that when the null distribution of Y is approximated using moments that take into account the effect of estimation, Y becomes a very useful statistic to assess the overall goodness of fit of models fitted to sparse 2(P) tables.

  1. Defining ‘good health’

    OpenAIRE

    Erdman, Susan E

    2016-01-01

    We all want to live a long life with ‘good health’. But what does that really mean? Clinicians often define ‘good health’ as the absence of disease. Indeed, modern biomedical research focuses on finding remedies for specific ailments, that, when absent, will yieldgood health’.

  2. Theoretical modeling of yields for proton-induced reactions on natural and enriched molybdenum targets

    Energy Technology Data Exchange (ETDEWEB)

    Celler, A; Hou, X [University of British Columbia, Vancouver, BC, Canada, (Canada); Benard, F; Ruth, T, E-mail: aceller@physics.ubc.ca, E-mail: xinchi@phas.ubc.ca, E-mail: fbenard@bccrc.ca, E-mail: truth@triumf.ca [BC Cancer Agency, Vancouver, BC (Canada)

    2011-09-07

    Recent acute shortage of medical radioisotopes prompted investigations into alternative methods of production and the use of a cyclotron and {sup 100}Mo(p,2n){sup 99m}Tc reaction has been considered. In this context, the production yields of {sup 99m}Tc and various other radioactive and stable isotopes which will be created in the process have to be investigated, as these may affect the diagnostic outcome and radiation dosimetry in human studies. Reaction conditions (beam and target characteristics, and irradiation and cooling times) need to be optimized in order to maximize the amount of {sup 99m}Tc and minimize impurities. Although ultimately careful experimental verification of these conditions must be performed, theoretical calculations can provide the initial guidance allowing for extensive investigations at little cost. We report the results of theoretically determined reaction yields for {sup 99m}Tc and other radioactive isotopes created when natural and enriched molybdenum targets are irradiated by protons. The cross-section calculations were performed using a computer program EMPIRE for the proton energy range 6-30 MeV. A computer graphical user interface for automatic calculation of production yields taking into account various reaction channels leading to the same final product has been created. The proposed approach allows us to theoretically estimate the amount of {sup 99m}Tc and its ratio relative to {sup 99g}Tc and other radioisotopes which must be considered reaction contaminants, potentially contributing to additional patient dose in diagnostic studies.

  3. Utilization of the cropgro-soybean model to estimate yield loss caused by Asian rust in cultivars with different cycle

    Directory of Open Access Journals (Sweden)

    Rafael de Ávila Rodrigues

    2012-01-01

    Full Text Available In recent years, crop models have increasingly been used to simulate agricultural features. The DSSAT (Decision Support System for Agrotechnology Transfer is an important tool in modeling growth; however, one of its limitations is related to the unaccounted-for effect of diseases. Therefore, the goals of this study were to calibrate and validate the CSM CROPGRO-Soybean for the soybean cultivars M-SOY 6101 and MG/BR 46 (Conquista, analyze the performance and the effect of Asian soybean rust on these cultivars under the environmental conditions of Viçosa, Minas Gerais, Brazil. The experimental data for the evaluation, testing, and adjustment of the genetic coefficients for the cultivars, M-SOY 6101 and MG/BR 46 (Conquista, were obtained during the 2006/2007, 2007/2008 and 2009/2010 growing seasons. GLUE (Generalized Likelihood Uncertainty Estimation was used for the estimation of the genetic coefficients, and pedotransfer functions have been utilized to estimate the physical characteristics of the soil. For all of the sowing dates, the early season cultivar, M-SOY 6101, exhibited a lower variance in yield, which represents more stability with regard to the interannual climate variability, i.e., the farmers who use this cultivar will have in 50% of the crop years analyzed, a higher yield than a late-season cultivar. The MG/BR 46 (Conquista cultivar demonstrated a greater probability of obtaining higher yield in years with favorable weather conditions. However, in the presence of the Asian soybean rust, yield is heavily affected. The early cultivar, M-SOY 6101, showed a lower risk of being affected by the rust and consequently exhibited less yield loss considering the scenario D90 (condensation on the leaf surface occurs when the relative humidity is greater than or equal to 90%, for a sowing date of November 14.

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

    Czech Academy of Sciences Publication Activity Database

    Pirttioja, N. K.; Carter, T. R.; Fronzek, S.; Bindi, M.; Hoffmann, H. D.; Palosuo, T.; Ruiz-Ramos, M.; Tao, F.; Trnka, Miroslav; Acutis, M.; Asseng, S.; Baranowski, P.; Basso, B.; Bodin, P.; Buis, S.; Cammarano, D.; Deligios, P.; Destain, M. F.; Dumont, B.; Ewert, F.; Ferrise, R.; Francois, L.; Gaiser, T.; Hlavinka, Petr; Jacquemin, I.; Kersebaum, K. C.; Kollas, C.; Krzyszczak, J.; Lorite, I. J.; Minet, J.; Minquez, M. I.; Montesino, M.; Moriondo, M.; Müller, C.; Nendel, C.; Öztürk, I.; Perego, A.; Rodriguez, A.; Ruane, A. C.; Ruget, F.; Sanna, M.; Semenov, M. A.; Slawinski, C.; Stratonovitch, P.; Supit, I.; Waha, K.; Wang, E.; Wu, L.; Zhao, Z.; Rötter, R. P.

    2015-01-01

    Roč. 65, č. 31 (2015), s. 87-105 ISSN 0936-577X R&D Projects: GA MZe QJ1310123; GA MŠk(CZ) LD13030 Grant - others:German Federal Ministries of Education and Research, and Food and Agriculture(DE) 2812ERA115 Institutional support: RVO:67179843 Keywords : climate * crop model * impact response surface * IRS * sensitivity analysis * wheat * yield Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.690, year: 2015

  5. Radiation utilization efficiency, nitrogen uptake and modeling crop growth and yield of rainfed rice under different nitrogen rates

    International Nuclear Information System (INIS)

    Gouranga, Kar; Ashwani Kumar; Mohapatra, Sucharita

    2014-01-01

    Optimum utilization of photosynthetically active radiation (PAR) along with proper nitrogen (N) management for sustainable rice production is still a promising management recommendation for sustainable rainfed rice cultivation in eastern India. The objective of this investigation was to study radiation utilization efficiency (RUE), N uptake and modeling growth and productivity of wet/rainy season rice (cv. Lalat and Gayatri) under 0, 50, 90, 120 and 150 kg ha -1 N application. Results showed that N rates significantly affected plant biomass, leaf area index (LAI), biological yield (straw and grain yield) and N uptake for both the varieties. The intercepted photosynthetically active radiation (IPAR) and spectral reflectance based vegetation indices (IR/R, NDVI) were also different between two varieties and among N rates. Higher rate of N increased the RUE significantly; averaged over years and varieties, mean values of RUE were 1.35, 1.70, 2.01, 2.15 and 2.17 g MJ -1 under 0, 50, 90, 120 and 150 kg N ha -1 , respectively. Though crop growth, yield, N uptake and RUE were higher at 150 kg N ha -1 but the results were at par with 120 kg N ha -1 . Agronomic N use efficiency (ANUE) was also low at 150 kg N ha -1 . The DSSAT v 4.5 model was applied to simulate crop growth, yield and phenology of the crop under different N rates. Model performance was found to be poor at low N rates (0, 50 kg N ha -1 ), but the model performed fairly well at higher N rates (90 kg ha -1 and above). (author)

  6. A Comparison of Crop Yields Using El Nino and Non-El Nino Climatological Data in a Crop Model

    Science.gov (United States)

    1990-01-01

    CERES- Maize ..... 65 Appendix F: Palmer Drought Severity Index (PDSI). 76 Appendix G: Yearly Corn Yield Averages for the U. S. and the Five Midwestern...model for predicting corn ( Zea mays L.) performance in the tropics. Ph.D. diss. University of Hawaii, Honolulu. Skaggs, R.H., and D.G. Baker. 1985...predicting corn ( Zea mays L.) performance in the tropics. Ph.D. diss. University of Hawaii, Honolulu. Skaggs, R.H., and D.G. Baker. 1985. Fluctuations

  7. 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

  8. SELECTION VIA MIXED MODELS IN SEGREGATING GUAVA FAMILIES BASED ON YIELD AND QUALITY TRAITS

    Directory of Open Access Journals (Sweden)

    SILVANA SILVA RED QUINTAL

    Full Text Available ABSTRACT Aiming at the generation of new guava varieties with superior attributes, we conducted this study adopting the REML/BLUP procedure at individual level. Seventeen segregating guava families were evaluated in a randomized-block design with two replicates and 12 plants per plot. Families were obtained after controlled biparental pollination. The studied individuals showed high genotypic variance for fruit weight (FW, total yield (YLD, and ascorbic acid content (AAC. The heritability coefficients of the mean of progenies led to high progeny-selection accuracy for pulp yield (PY, soluble solids content (SSC, in addition to FW, YLD, and AAC; moderate accuracy for fruit acidity (FA and SSC/FA ratio; and low accuracy for mesocarp thickness (MT and pH. Selection among families (h2mp indicated the highest values for FW, PY, YLD, SSC, and AAC, revealing that, for the present study, this practice would be effective, since these traits allowed for the highest selection accuracy values among families. As for the ranking of individuals, families originating from crosses UENF 1835 × UENF 1834, UENF 1831 × UENF 1832, and UENF 1831 × UENF 3739 stood out, occupying the first positions for most traits.

  9. A GIS-based model of potential groundwater yield zonation for a sandstone aquifer in the Juye Coalfield, Shangdong, China

    Science.gov (United States)

    Yin, Huiyong; Shi, Yongli; Niu, Huigong; Xie, Daolei; Wei, Jiuchuan; Lefticariu, Liliana; Xu, Shuanxiang

    2018-02-01

    Resolving the potential groundwater yield zonation of sandstone aquifers occurring at depths of several hundred meters has been an important and challenging objective of the hydrogeological research focused on preventing flood hazards in coal mines. Using accessible geological exploration data we put forward a method of predicting the spatial distribution of groundwater storage potential in sandstone aquifers from Permian-age coal deposits in Juye Coalfield, Shangdong, China. A Geological, Tectonic and Lithological Composition Index (GTLCI) model was created using the following parameters: sandstone depth and thickness, faults length density (FaLD), faults density (FaD), fault frequency density (FaFD), fault scale density (FaSD), variation coefficient of the slope (VCS) of the coal seam, intensity index of folds in horizontal direction (IIFoH), and lithological composition index (LCI). Each of these factors was subsequently divided into 5 classes. The analytic hierarchy process (AHP) and trapezoidal fuzzy number (TFN) method was applied to calculate the weight of the conditioning factor and their respective sub-classes. Groundwater yield potential contour map, which was initially constructed using the GTLCI values revealed four groundwater abundance zones. The map was further refined by taking into account hydrogeologic data collected during mining activities. The GTLCI model predictive success rate of 80% was explained by the limited number of boreholes available for validation. It is considered that the GTLCI model is effective at predicting zonation of groundwater yield in the sandstone aquifers from Permian- age coal deposits in Juye Coalfield, China.

  10. Multiple linear regression and artificial neural networks for delta-endotoxin and protease yields modelling of Bacillus thuringiensis.

    Science.gov (United States)

    Ennouri, Karim; Ben Ayed, Rayda; Triki, Mohamed Ali; Ottaviani, Ennio; Mazzarello, Maura; Hertelli, Fathi; Zouari, Nabil

    2017-07-01

    The aim of the present work was to develop a model that supplies accurate predictions of the yields of delta-endotoxins and proteases produced by B. thuringiensis var. kurstaki HD-1. Using available medium ingredients as variables, a mathematical method, based on Plackett-Burman design (PB), was employed to analyze and compare data generated by the Bootstrap method and processed by multiple linear regressions (MLR) and artificial neural networks (ANN) including multilayer perceptron (MLP) and radial basis function (RBF) models. The predictive ability of these models was evaluated by comparison of output data through the determination of coefficient (R 2 ) and mean square error (MSE) values. The results demonstrate that the prediction of the yields of delta-endotoxin and protease was more accurate by ANN technique (87 and 89% for delta-endotoxin and protease determination coefficients, respectively) when compared with MLR method (73.1 and 77.2% for delta-endotoxin and protease determination coefficients, respectively), suggesting that the proposed ANNs, especially MLP, is a suitable new approach for determining yields of bacterial products that allow us to make more appropriate predictions in a shorter time and with less engineering effort.

  11. 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.

  12. The structure of personality of a good teacher from students perspective according to the Big-Five model

    Directory of Open Access Journals (Sweden)

    Genc Lajoš

    2014-01-01

    Full Text Available This paper deals with the identification of desirable personality characteristics of teachers from students perspective in the Big-Five Model of personality from a phenomenological approach. The description of personality of a good teacher was obtained from students of the University of Novi Sad (n=443. The Big Five Inventory (BFI was applied with the instruction to respond to claims as a good teacher would answer. The students’ estimates indicate that a good teacher is expected to have lower emotional instability, but more pronounced extroversion, openness to experience, cooperativeness (pleasantness and consciousness with regard to referent values in general population. For the domain of neuroticism, the difference is either small or medium in size, for cooperativeness of a medium size, and for extroversion, consciousness and openness to experience the difference is large. The gender of students does not influence their expectations. Methodological dilemmas in this area of research and implications of the results for the selection and professional development of teachers are discussed. [Projekat Ministarstva nauke Republike Srbije, br. 179010 i br. 47020

  13. Spatially distinct response of rice yield to autonomous adaptation under the CMIP5 multi-model projections

    Science.gov (United States)

    Shin, Yonghee; Lee, Eun-Jeong; Im, Eun-Soon; Jung, Il-Won

    2017-02-01

    Rice ( Oryza sativa L.) is a very important staple crop, as it feeds more than half of the world's population. Numerous studies have focused on the negative impacts of climate change on rice production. However, there is little debate on which region of the world is more vulnerable to climate change and how adaptation to this change can mitigate the negative impacts on rice production. We investigated the impacts of climate change on rice yield, based on simulations combining a global crop model, M-GAZE, and Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model projections. Our focus was the impact of mitigating emission forcings (representative concentration pathway RCP 4.5 vs. RCP 8.5) and autonomous adaptation (i.e., changing crop variety and planting date) on rice yield. In general, our results showed that climate change due to anthropogenic warming leads to a significant reduction in rice yield. However, autonomous adaptation provides the potential to reduce the negative impact of global warming on rice yields in a spatially distinct manner. The adaptation was less beneficial for countries located at a low latitude (e.g., Cambodia, Thailand, Brazil) compared to mid-latitude countries (e.g., USA, China, Pakistan), as regional climates at the lower latitudes are already near the upper temperature thresholds for acceptable rice growth. These findings suggest that the socioeconomic effects from rice production in lowlatitude countries can be highly vulnerable to anthropogenic global warming. Therefore, these countries need to be accountable to develop transformative adaptation strategies, such as adopting (or developing) heat-tolerant varieties, and/or improve irrigation systems and fertilizer use efficiency.

  14. A phenomenological molecular model for yielding and brittle-ductile transition of polymer glasses.

    Science.gov (United States)

    Wang, Shi-Qing; Cheng, Shiwang; Lin, Panpan; Li, Xiaoxiao

    2014-09-07

    This work formulates, at a molecular level, a phenomenological theoretical description of the brittle-ductile transition (BDT) in tensile extension, exhibited by all polymeric glasses of high molecular weight (MW). The starting point is our perception of a polymer glass (under large deformation) as a structural hybrid, consisting of a primary structure due to the van der Waals bonding and a chain network whose junctions are made of pairs of hairpins and function like chemical crosslinks due to the intermolecular uncrossability. During extension, load-bearing strands (LBSs) emerge between the junctions in the affinely strained chain network. Above the BDT, i.e., at "warmer" temperatures where the glass is less vitreous, the influence of the chain network reaches out everywhere by activating all segments populated transversely between LBSs, starting from those adjacent to LBSs. It is the chain network that drives the primary structure to undergo yielding and plastic flow. Below the BDT, the glassy state is too vitreous to yield before the chain network suffers a structural breakdown. Thus, brittle failure becomes inevitable. For any given polymer glass of high MW, there is one temperature TBD or a very narrow range of temperature where the yielding of the glass barely takes place as the chain network also reaches the point of a structural failure. This is the point of the BDT. A theoretical analysis of the available experimental data reveals that (a) chain pullout occurs at the BDT when the chain tension builds up to reach a critical value f(cp) during tensile extension; (b) the limiting value of f(cp), extrapolated to far below the glass transition temperature T(g), is of a universal magnitude around 0.2-0.3 nN, for all eight polymers examined in this work; (c) pressurization, which is known [K. Matsushige, S. V. Radcliffe, and E. Baer, J. Appl. Polym. Sci. 20, 1853 (1976)] to make brittle polystyrene (PS) and poly(methyl methacrylate) (PMMA) ductile at room

  15. Good Faith

    DEFF Research Database (Denmark)

    Fomcenco, Alex

    2017-01-01

    This article outlines the current state of law in Canada in respect to good faith in contratial relations. The topic is highly relevant due to expected growth in the numbers of contracts concluded between European and Canadian enterprises in the wake of adoption of the Comprehensive Economic...

  16. a deterministic model for predicting water yield from two different watersheds

    Directory of Open Access Journals (Sweden)

    Putu Sudira

    2013-07-01

    The final test of the adequacy of the model lay in a comparison of observed and simulated runoff The comparison showed that the observed and simulated runoff values are not significantly different. This was based on the results obtained from statistical measures to test the model. The model did a better simulation in the smaller watershed (Pogung-Code sub watershed than in the larger one (Pulo-Opak sub watershed.

  17. Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling

    Directory of Open Access Journals (Sweden)

    Piotr Tompalski

    2018-02-01

    Full Text Available The increasing availability of highly detailed three-dimensional remotely-sensed data depicting forests, including airborne laser scanning (ALS and digital aerial photogrammetric (DAP approaches, provides a means for improving stand dynamics information. The availability of data from ALS and DAP has stimulated attempts to link these datasets with conventional forestry growth and yield models. In this study, we demonstrated an approach whereby two three-dimensional point cloud datasets (one from ALS and one from DAP, acquired over the same forest stands, at two points in time (circa 2008 and 2015, were used to derive forest inventory information. The area-based approach (ABA was used to predict top height (H, basal area (BA, total volume (V, and stem density (N for Time 1 and Time 2 (T1, T2. We assigned individual yield curves to 20 × 20 m grid cells for two scenarios. The first scenario used T1 estimates only (approach 1, single date, while the second scenario combined T1 and T2 estimates (approach 2, multi-date. Yield curves were matched by comparing the predicted cell-level attributes with a yield curve template database generated using an existing growth simulator. Results indicated that the yield curves using the multi-date data of approach 2 were matched with slightly higher accuracy; however, projections derived using approach 1 and 2 were not significantly different. The accuracy of curve matching was dependent on the ABA prediction error. The relative root mean squared error of curve matching in approach 2 for H, BA, V, and N, was 18.4, 11.5, 25.6, and 27.53% for observed (plot data, and 13.2, 44.6, 50.4 and 112.3% for predicted data, respectively. The approach presented in this study provides additional detail on sub-stand level growth projections that enhances the information available to inform long-term, sustainable forest planning and management.

  18. 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.

  19. 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

  20. 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

  1. A new model of dependence of secondary electron emission yield on primary electron energy for application to polymers

    Energy Technology Data Exchange (ETDEWEB)

    Cazaux, J [LASSI/UTAP, Faculte des Sciences, BP1039, 51687 Reims Cedex 2 (France)

    2005-07-21

    A new analytical model for the secondary electron (SE) emission yield, {delta}, is applied to polymers. It involves a parameter k, k = z{sub C}/R, between the most probable energy dissipation depth, z{sub C}, of primary electrons (PE) and their range R, where k ranges from 0.5 and 0.45 for low-density, low atomic-weight materials. Reduced yield curves (RYC), {delta}/{delta}{sub (max)} versus E{sup 0}/E{sup 0}{sub (max)}, and normal yield curves, {delta} versus E{sup 0}, obtained from published experimental data on a wide variety of polymers (polystyrene, PET, polyimide; Kapton; PTFE; Teflon, PMMA, nylon, polyurethane) are compared with the calculated change of {delta} with PE energy, E{sup 0}. In contrast to the use of the conventional constant loss model where the best fit requires an empirical change in the exponent 'n' in the power law expression of the PE range, R versus E{sup 0}, the present approach is based on the usual choice for n, n = 1.35, and on a choice for k governed by physical arguments. This physical basis then enables one to predict the RYC of other polymers. Finally, values of the SE escape probability and SE attenuation length are estimated for the polymers of interest and a new mechanism is suggested for the contrast reversal in scanning electron microscopy.

  2. A new model of dependence of secondary electron emission yield on primary electron energy for application to polymers

    International Nuclear Information System (INIS)

    Cazaux, J

    2005-01-01

    A new analytical model for the secondary electron (SE) emission yield, δ, is applied to polymers. It involves a parameter k, k = z C /R, between the most probable energy dissipation depth, z C , of primary electrons (PE) and their range R, where k ranges from 0.5 and 0.45 for low-density, low atomic-weight materials. Reduced yield curves (RYC), δ/δ (max) versus E 0 /E 0 (max) , and normal yield curves, δ versus E 0 , obtained from published experimental data on a wide variety of polymers (polystyrene, PET, polyimide; Kapton; PTFE; Teflon, PMMA, nylon, polyurethane) are compared with the calculated change of δ with PE energy, E 0 . In contrast to the use of the conventional constant loss model where the best fit requires an empirical change in the exponent 'n' in the power law expression of the PE range, R versus E 0 , the present approach is based on the usual choice for n, n = 1.35, and on a choice for k governed by physical arguments. This physical basis then enables one to predict the RYC of other polymers. Finally, values of the SE escape probability and SE attenuation length are estimated for the polymers of interest and a new mechanism is suggested for the contrast reversal in scanning electron microscopy

  3. 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.

  4. Evaluation of root water uptake in the ISBA-A-gs land surface model using agricultural yield statistics over France

    Science.gov (United States)

    Canal, N.; Calvet, J.-C.; Decharme, B.; Carrer, D.; Lafont, S.; Pigeon, G.

    2014-12-01

    The simulation of root water uptake in land surface models is affected by large uncertainties. The difficulty in mapping soil depth and in describing the capacity of plants to develop a rooting system is a major obstacle to the simulation of the terrestrial water cycle and to the representation of the impacts of drought. In this study, long time series of agricultural statistics are used to evaluate and constrain root water uptake models. The inter-annual variability of cereal grain yield and permanent grassland dry matter yield is simulated over France 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 two-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 départements, for a range of rooting depths. The number of départements 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 neutral impact of the most refined versions of the model is found with respect to the simplified soil hydrology scheme. This shows that efforts should be made in future studies to reduce other sources of uncertainty, e.g. by using a more detailed soil and root density profile description together with satellite vegetation products. It is found that modelling additional subroot-zone base flow soil layers does not improve (and may even degrade) the representation of the inter-annual variability of the vegetation above-ground biomass. These results are

  5. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change

    NARCIS (Netherlands)

    Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R.; Bindi, Marco; Hoffmann, Holger; Palosuo, Taru; Ruiz-Ramos, Margarita; Tao, Fulu; Trnka, Miroslav; Acutis, Marco; Asseng, Senthold; Baranowski, Piotr; Basso, Bruno; Bodin, Per; Buis, Samuel; Cammarano, Davide; Deligios, Paola; Destain, Marie France; Dumont, Benjamin; Ewert, Frank; Ferrise, Roberto; François, Louis; Gaiser, Thomas; Hlavinka, Petr; Jacquemin, Ingrid; Kersebaum, Kurt Christian; Kollas, Chris; Krzyszczak, Jaromir; Lorite, Ignacio J.; Minet, Julien; Minguez, M.I.; Montesino, Manuel; Moriondo, Marco; Müller, Christoph; Nendel, Claas; Öztürk, Isik; Perego, Alessia; Rodríguez, Alfredo; Ruane, Alex C.; Ruget, Françoise; Sanna, Mattia; Semenov, Mikhail A.; Slawinski, Cezary; Stratonovitch, Pierre; Supit, Iwan; Waha, Katharina; Wang, Enli; Wu, Lianhai; Zhao, Zhigan; Rötter, Reimund P.

    2018-01-01

    Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in

  6. Defensive Egotism and Bullying: Gender Differences Yield Qualified Support for the Compensation Model of Aggression

    Science.gov (United States)

    Nail, Paul R.; Simon, Joan B.; Bihm, Elson M.; Beasley, William Howard

    2016-01-01

    According to the compensation model of aggression (Staub, 1989), some people bully to defend against their own feelings of weakness and vulnerability. Classmates and teachers rated a sample of American sixth graders in terms of trait: defensiveness (i.e., defensive egotism), self-esteem, bullying, and related behaviors. Consistent with the model,…

  7. Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change

    Czech Academy of Sciences Publication Activity Database

    Fronzek, S.; Pirttioja, N. K.; Carter, T. R.; Bindi, M.; Hoffmann, H.; Palosuo, T.; Ruiz-Ramos, M.; Tao, F.; Trnka, Miroslav; Acutis, M.; Asseng, S.; Baranowski, P.; Basso, B.; Bodin, P.; Buis, S.; Cammarano, D.; Deligios, P.; Destain, M. F.; Dumont, B.; Ewert, F.; Ferrise, R.; Francois, L.; Gaiser, T.; Hlavinka, Petr; Jacquemin, I.; Kersebaum, K. C.; Kollas, C.; Krzyszczak, J.; Lorite, I. J.; Minet, J.; Ines Minguez, M.; Montesino, M.; Moriondo, M.; Mueller, C.; Nendel, C.; Öztürk, I.; Perego, A.; Rodriguez, A.; Ruane, A. C.; Ruget, F.; Sanna, M.; Semenov, M. A.; Slawinski, C.; Stratonovitch, P.; Supit, I.; Waha, K.; Wang, E.; Wu, L.; Zhao, Z.; Rötter, R.

    2018-01-01

    Roč. 159, jan (2018), s. 209-224 ISSN 0308-521X Keywords : climate-change * crop models * probabilistic assessment * simulating impacts * british catchments * uncertainty * europe * productivity * calibration * adaptation * Classification * Climate change * Crop model * Ensemble * Sensitivity analysis * Wheat Impact factor: 2.571, year: 2016

  8. ANN-based sediment yield models for Vamsadhara river basin (India)

    African Journals Online (AJOL)

    High numbers of iterations adopted for model development were found to reduce the value of the objective function, but with model's over-learning and that is reflected? Unclear what is meant by an increase and decrease of the performance in calibration and cross-validation, respectively. The generalised pattern- learned ...

  9. Uncertainty modelling and analysis of environmental systems: a river sediment yield example

    NARCIS (Netherlands)

    Keesman, K.J.; Koskela, J.; Guillaume, J.H.; Norton, J.P.; Croke, B.; Jakeman, A.

    2011-01-01

    Abstract: Throughout the last decades uncertainty analysis has become an essential part of environmental model building (e.g. Beck 1987; Refsgaard et al., 2007). The objective of the paper is to introduce stochastic and setmembership uncertainty modelling concepts, which basically differ in the

  10. Work, Health, Music: The enduring Rusyn model of a good life amid changing socioeconomic contexts of progress

    Directory of Open Access Journals (Sweden)

    K. M. Cantin

    2013-11-01

    Full Text Available Rusyns in Eastern and Central Europe have experience with two predominant models of “progress”: the Soviet-style communist and the neoliberal.  Proponents of each system promised to better the lives of all but did not take into account what “better” meant to local populations, including Rusyns.  Increasingly, European governmental and nongovernmental organizations are redefining notions of progress and development to accord with values of sustainability and a capability approach (CA to well-being.  Giovanola (2005 and Robeyns (2005 have argued that scholars of the CA need to better develop concepts of “personhood” and “human flourishing”, and to better explain the importance of social group membership and norms to living a valued life.  The emerging anthropological focus on well-being, emphasizing culturally specific definitions of what happiness and a good life mean, can provide these conceptualizations.  As a case in point, I use freelist and interview data obtained from residents in the Prešov Region of Slovakia and the Zakarpattia Oblast of Ukraine along with Rusyn cultural narratives drawn from poems, folktales, plays, songs, interviews, and speeches to identify prevalent models of “personhood” and “a good life”. I discuss how these narratives intersect and diverge with discourses of happiness and progress along with the implications for Rusyns' ability to flourish. 

  11. Numerical experiments on plasma focus for soft x-ray yield scaling laws derivation using Lee model

    International Nuclear Information System (INIS)

    Akel, M.

    2012-09-01

    The required plasma parameters of krypton and xenon at different temperatures were calculated, the x-ray emission properties of plasmas were studied, and based on the corona model the suitable temperature range for generating H-like and He-like ions (therefore soft x-ray emissions) of different gases plasma were found. The code is applied to characterize the plasma focus in different plasma focus devices, and for optimizing the nitrogen, oxygen, neon, argon, krypton and xenon soft x-ray yields based on bank, tubes and operating parameters. It is found that the soft x-ray yield increases with changing pressure until it reaches the maximum value for each plasma focus device. Keeping the bank parameters, operational voltage unchanged but systematically changing other parameters, numerical experiments were performed finding the optimum combination of P o , Z o and 'a' for the maximum soft x-ray yield. Thus we expect to increase the soft x-ray yield of plasma focus device several-fold from its present typical operation; without changing the capacitor bank, merely by changing the electrode configuration and the operating pressure. The Lee model code was also used to run numerical experiments on plasma focus devices for optimizing soft x-ray yield with reducing L o , varying L o and 'a' to get engineering designs with maximum soft x-ray yield for these devices at different experimental conditions and gases. Numerical experiments showed the influence of the gas used in plasma focus and its properties on soft x-ray emission and its properties and then on its applications. Scaling laws for soft x-ray of nitrogen, oxygen, neon, argon, krypton and xenon plasma focus, in terms of energy, peak discharge current and focus pinch current were found. Radiative cooling effects are studied indicating that radiative collapse may be observed for heavy noble gases (Ar, Kr, Xe) for pinch currents even below 100 kA. The results show that the line radiation emission and tube voltages have

  12. A Model of Equilibrium Conditions of Roof Rock Mass Giving Consideration to the Yielding Capacity of Powered Supports

    Science.gov (United States)

    Jaszczuk, Marek; Pawlikowski, Arkadiusz

    2017-12-01

    The work presents the model of interactions between the powered roof support units and the rock mass, while giving consideration to the yielding capacity of the supports - a value used for the analysis of equilibrium conditions of roof rock mass strata in geological and mining conditions of a given longwall. In the model, the roof rock mass is kept in equilibrium by: support units, the seam, goafs, and caving rocks (Fig. 1). In the assumed model of external load on the powered roof support units it is a new development - in relation to the model applied in selection of supports based on the allowable deflection of roof theory - that the load bearing capacity is dependent on the increment of the inclination of the roof rock mass and on the properties of the working medium, while giving consideration to the air pockets in the hydraulic systems, the load of the caving rocks on the caving shield, introducing the RA support value of the roof rock mass by the coal seam as a closed-form expression and while giving consideration to the additional support provided by the rocks of the goaf as a horizontal component R01H of the goaf reaction. To determine the roof maintenance conditions it is necessary to know the characteristics linking the yielding capacity of the support units with the heading convergence, which may be measured as the inclination angle of the roof rock mass. In worldwide mining, Ground Reaction Curves are used, which allow to determine the required yielding capacity of support units based on the relation between the load exerted on the unit and the convergence of the heading ensuring the equilibrium of the roof rock mass. (Figs. 4 and 8). The equilibrium of the roof rock mass in given conditions is determined at the displacement of the rock mass by the α angle, which impacts the following values: yielding capacity of units FN, vertical component of goaf reaction R01V and the horizontal component of goaf reaction R01H. In the model of load on the support

  13. Goodness-of-fit test of the stratified mark-specific proportional hazards model with continuous mark.

    Science.gov (United States)

    Sun, Yanqing; Li, Mei; Gilbert, Peter B

    2016-01-01

    Motivated by the need to assess HIV vaccine efficacy, previous studies proposed an extension of the discrete competing risks proportional hazards model, in which the cause of failure is replaced by a continuous mark only observed at the failure time. However the model assumptions may fail in several ways, and no diagnostic testing procedure for this situation has been proposed. A goodness-of-fit test procedure for the stratified mark-specific proportional hazards model in which the regression parameters depend nonparametrically on the mark and the baseline hazards depends nonparametrically on both time and the mark is proposed. The test statistics are constructed based on the weighted cumulative mark-specific martingale residuals. The critical values of the proposed test statistics are approximated using the Gaussian multiplier method. The performance of the proposed tests are examined extensively in simulations for a variety of the models under the null hypothesis and under different types of alternative models. An analysis of the 'Step' HIV vaccine efficacy trial using the proposed method is presented. The analysis suggests that the HIV vaccine candidate may increase susceptibility to HIV acquisition.

  14. YIELD INDICATORS

    African Journals Online (AJOL)

    International Institute of Tropical Agriculture, East and Southern Africa, Centre, P.O. Box 7878,. Kampala, Uganda. Makerere ... would have great potential in terms of human nutrition. Storage root yield , the ... Inter-relationships among traits and path analysis for yield components of cassava. 604 collected included plant ...

  15. 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.

  16. Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve

    Directory of Open Access Journals (Sweden)

    Lorenčič Eva

    2016-06-01

    Full Text Available Understanding the relationship between interest rates and term to maturity of securities is a prerequisite for developing financial theory and evaluating whether it holds up in the real world; therefore, such an understanding lies at the heart of monetary and financial economics. Accurately fitting the term structure of interest rates is the backbone of a smoothly functioning financial market, which is why the testing of various models for estimating and predicting the term structure of interest rates is an important topic in finance that has received considerable attention for many decades. In this paper, we empirically contrast the performance of cubic splines and the Nelson-Siegel model by estimating the zero-coupon yields of Austrian government bonds. The main conclusion that can be drawn from the results of the calculations is that the Nelson-Siegel model outperforms cubic splines at the short end of the yield curve (up to 2 years, whereas for medium-term maturities (2 to 10 years the fitting performance of both models is comparable.

  17. Validation of AquaCrop Model for Simulation of Winter Wheat Yield and Water Use Efficiency under Simultaneous Salinity and Water Stress

    Directory of Open Access Journals (Sweden)

    M. Mohammadi

    2016-02-01

    simulation of soil salinity. In general, the model accuracy for simulation yield and WP was better than simulation of biomass. The d (index of agreement values were very close to one for both varieties, which means that simulated reduction in grain yield and biomass was similar to those of measured ones. In most cases the R2 values were about one, confirming a good correlation between simulated and measured values. The NRMSE values in most cases were lower than 10% which seems to be good. The CRM values were close to zero (under- and over-estimation were negligible. Based on higher WP under deficit irrigation treatments (e.g. I3 compared to full irrigation treatments (e.g. I1 and I2, it seems logical to adopt I3 treatment, especially in Birjand as a water-short region, assigning the remaining 25% to another piece of land. By such strategy, WP would be optimized at the regional scale. Conclusion: The AquaCrop was separately and simultaneously nested calibrated and validated for all salinity treatments. The model accuracy under simultaneous case was slightly lower than that for separate case. According to the results, if the model is well calibrated for minimum and maximum irrigation treatments (full irrigation and maximum deficit irrigation, it could simulate grain yield for any other irrigation treatment in between these two limits. Adopting this approach may reduce the cost of field studies for calibrating the model, since only two irrigation treatments should be conducted in the field. AquaCrop model can be a valuable tool for modelling winter wheat grain yield, WP and biomass. The simplicity of AquaCrop, as it is less data dependent, made it to be user-friendly. Nevertheless, the performance of the model has to be evaluated, validated and fine-tuned under a wider range of conditions and crops. Keywords: Biomass, Plant modeling, Sensitivity analysis

  18. A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns

    KAUST Repository

    Dao, Ngocanh

    2014-04-03

    Assessing the goodness-of-fit (GOF) for intricate parametric spatial point process models is important for many application fields. When the probability density of the statistic of the GOF test is intractable, a commonly used procedure is the Monte Carlo GOF test. Additionally, if the data comprise a single dataset, a popular version of the test plugs a parameter estimate in the hypothesized parametric model to generate data for theMonte Carlo GOF test. In this case, the test is invalid because the resulting empirical level does not reach the nominal level. In this article, we propose a method consisting of nested Monte Carlo simulations which has the following advantages: the bias of the resulting empirical level of the test is eliminated, hence the empirical levels can always reach the nominal level, and information about inhomogeneity of the data can be provided.We theoretically justify our testing procedure using Taylor expansions and demonstrate that it is correctly sized through various simulation studies. In our first data application, we discover, in agreement with Illian et al., that Phlebocarya filifolia plants near Perth, Australia, can follow a homogeneous Poisson clustered process that provides insight into the propagation mechanism of these plants. In our second data application, we find, in contrast to Diggle, that a pairwise interaction model provides a good fit to the micro-anatomy data of amacrine cells designed for analyzing the developmental growth of immature retina cells in rabbits. This article has supplementary material online. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

  19. 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.

  20. Dynamic Transmission Modeling : A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-5

    NARCIS (Netherlands)

    Pitman, Richard; Fisman, David; Zaric, Gregory S.; Postma, Maarten; Kretzschmar, Mirjam; Edmunds, John; Brisson, Marc

    2012-01-01

    The transmissible nature of communicable diseases is what sets them apart from other diseases modeled by health economists. The probability of a susceptible individual becoming infected at any one point in time (the force of infection) is related to the number of infectious individuals in the

  1. Dynamic Transmission Modeling : A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group-5

    NARCIS (Netherlands)

    Pitman, Richard; Fisman, David; Zaric, Gregory S.; Postma, Maarten; Kretzschmar, Mirjam; Edmunds, John; Brisson, Marc

    2012-01-01

    The transmissible nature of communicable diseases is what sets them apart from other diseases modeled by health economists. The probability of a susceptible individual becoming infected at any one point in time (the force of infection) is related to the number of infectious individuals in the

  2. Models to Estimate Lactation Curves of Milk Yield and Somatic Cell Count in Dairy Cows at the Herd Level for the Use in Simulations and Predictive Models

    DEFF Research Database (Denmark)

    Græsbøll, Kaare; Kirkeby, Carsten Thure; Nielsen, Søren Saxmose

    2016-01-01

    using a herd level curve allows for estimating the cow production level from first the recording in the parity, while a two-parameter model requires more recordings for a credible estimate, but may more precisely predict persistence, and given the independence of parameters, these can be easily drawn....... Furthermore, we investigated how the parameters of lactation models correlate between parities and from dam to offspring. The aim of the study was to provide simple and robust models for cow level milk yield and somatic cell count for fitting to sparse data to parameterize herd- and cow-specific simulation...... than somatic cells per milliliter. A positive correlation was found between relative levels of the total somatic cell count and the milk yield. The variation of lactation and somatic cell count curves between farms highlights the importance of a herd level approach. The one-parameter per cow model...

  3. 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

    Eleven widely used crop simulation models (APSIM, CERES, CROPSYST, COUP, DAISY, EPIC, FASSET, HERMES, MONICA, STICS and WOFOST) were tested using spring barley (Hordeum vulgare L.) data set under varying nitrogen (N) fertilizer rates from three experimental years in the boreal climate of Jokioinen...

  4. 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

  5. Improving the CROPGRO-Tomato model for predicting growth and yield to temperature

    NARCIS (Netherlands)

    Boote, K.J.; Rybak, M.R.; Scholberg, J.M.S.; Jones, J.W.

    2012-01-01

    Parameterizing crop models for more accurate response to climate factors such as temperature is important considering potential temperature increases associated with climate change, particularly for tomato (Lycopersicon esculentum Mill.), which is a heat-sensitive crop. The objective of this work

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

    African Journals Online (AJOL)

    R.W. 1997. CRPSM - Crop,growth and irrigation scheduling model. Software user manual. Biolog- ical & Irrigation Engineering Department. Utah. State University. Logan, UT 84322-4105, 204 p. Jensen. M.E. 1968. Water consumption by agricultural plants. 111: T. T. Kozlowski (Eds.), Vo1.2, Water deficits and plant growth.

  7. 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

  8. Modelling of bio-oil yield from fast pyrolysis of sawdust | Kuye ...

    African Journals Online (AJOL)

    Bio-oil has received great attention due to the environmental concerns associated with the usage of fossil fuels and the predicted inability of these fuels to cope with future increases in energy demands. In this work an existing kinetic model equation has been modified using polynomial equations in conjunction with ...

  9. Models for the transport of low energy electrons in water and the yield of hydrated electrons at early times

    International Nuclear Information System (INIS)

    Brenner, D.J.; Miller, J.H.; Ritchie, R.H.; Bichsel, H.

    1985-01-01

    An insulator model with four experimental energy bands was used to fit the optical properties of liquid water and to extend these data to non-zero momentum transfer. Inelastic mean free paths derived from this dielectric response function provided the basic information necessary to degrade high energy electrons to the subexcitation energy domain. Two approaches for the transport of subexcitation electrons were investigated. (i) Gas phase cross sections were used to degrade subexcitation electrons to thermal energy and the thermalization lengths were scaled to unit density. (ii) Thermalization lengths were estimated by age-diffusion theory with a stopping power deduced from the data on liquid water and transport cross sections derived from elastic scattering in water vapor. Theoretical ranges were compared to recent experimental results. A stochastic model was used to calculate the rapid diffusion and reaction of hydrated electrons with other radiolysis products. The sensitivity of the calculated yields to the model assumptions and comparison with experimental data are discussed

  10. Modeling future water footprint of barley production in Alberta, Canada: Implications for water use and yields to 2064.

    Science.gov (United States)

    Masud, Mohammad Badrul; McAllister, Tim; Cordeiro, Marcos R C; Faramarzi, Monireh

    2018-03-01

    Despite the perception of being one of the most agriculturally productive regions globally, crop production in Alberta, a western province of Canada, is strongly dependent on highly variable climate and water resources. We developed agro-hydrological models to assess the water footprint (WF) of barley by simulating future crop yield (Y) and consumptive water use (CWU) within the agricultural region of Alberta. The Soil and Water Assessment Tool (SWAT) was used to develop rainfed and irrigated barley Y simulation models adapted to sixty-seven and eleven counties, respectively through extensive calibration, validation, sensitivity, and uncertainty analysis. Eighteen downscaled climate projections from nine General Circulation Models (GCMs) under the Representative Concentration Pathways 2.6 and 8.5 for the 2040-2064 period were incorporated into the calibrated SWAT model. Based on the ensemble of GCMs, rainfed barley yield is projected to increase while irrigated barley is projected to remain unchanged in Alberta. Results revealed a considerable decrease (maximum 60%) in WF to 2064 relative to the simulated baseline 1985-2009 WF. Less water will also be required to produce barley in northern Alberta (rainfed barley) than southern Alberta (irrigated barley) due to reduced water consumption. The modeled WF data adjusted for water stress conditions and found a remarkable change (increase/decrease) in the irrigated counties. Overall, the research framework and the locally adapted regional model results will facilitate the development of future water policies in support of better climate adaptation strategies by providing improved WF projections. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. 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.

  12. 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.

  13. Regional crop yield forecasting using probalistic crop growth modelling and remote sensing data assimilation

    OpenAIRE

    Wit, de, A.J.W.

    2007-01-01

    Een belangrijk onderdeel van het MARS oogstvoorspellingssysteem is het zogenaamde CGMS (crop growth monitoring system). CGMS gebruikt een gewasgroeimodel om het effect van bodem, weer en teeltmaatregelen op de groei van het gewas te bepalen. Hiervoor worden relevante gegevens verzameld over Europa. Op basis van deze gegevens simuleert het model WOFOST de gewasgroei. In dit proefschrift wordt op praktische en theoretische gronden beargumenteerd dat de onzekerheid in het weer de bepalende facto...

  14. 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

  15. 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

  16. 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. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Good Manufacturing Practices (GMP) manufacturing of advanced therapy medicinal products: a novel tailored model for optimizing performance and estimating costs.

    Science.gov (United States)

    Abou-El-Enein, Mohamed; Römhild, Andy; Kaiser, Daniel; Beier, Carola; Bauer, Gerhard; Volk, Hans-Dieter; Reinke, Petra

    2013-03-01

    Advanced therapy medicinal products (ATMP) have gained considerable attention in academia due to their therapeutic potential. Good Manufacturing Practice (GMP) principles ensure the quality and sterility of manufacturing these products. We developed a model for estimating the manufacturing costs of cell therapy products and optimizing the performance of academic GMP-facilities. The "Clean-Room Technology Assessment Technique" (CTAT) was tested prospectively in the GMP facility of BCRT, Berlin, Germany, then retrospectively in the GMP facility of the University of California-Davis, California, USA. CTAT is a two-level model: level one identifies operational (core) processes and measures their fixed costs; level two identifies production (supporting) processes and measures their variable costs. The model comprises several tools to measure and optimize performance of these processes. Manufacturing costs were itemized using adjusted micro-costing system. CTAT identified GMP activities with strong correlation to the manufacturing process of cell-based products. Building best practice standards allowed for performance improvement and elimination of human errors. The model also demonstrated the unidirectional dependencies that may exist among the core GMP activities. When compared to traditional business models, the CTAT assessment resulted in a more accurate allocation of annual expenses. The estimated expenses were used to set a fee structure for both GMP facilities. A mathematical equation was also developed to provide the final product cost. CTAT can be a useful tool in estimating accurate costs for the ATMPs manufactured in an optimized GMP process. These estimates are useful when analyzing the cost-effectiveness of these novel interventions. Copyright © 2013 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

  18. Bohman-Frieze-Wormald model on the lattice, yielding a discontinuous percolation transition

    Science.gov (United States)

    Schrenk, K. J.; Felder, A.; Deflorin, S.; Araújo, N. A. M.; D'Souza, R. M.; Herrmann, H. J.

    2012-03-01

    The BFW model introduced by Bohman, Frieze, and Wormald [Random Struct. Algorithms1042-983210.1002/rsa.20038, 25, 432 (2004)], and recently investigated in the framework of discontinuous percolation by Chen and D'Souza [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.106.115701 106, 115701 (2011)], is studied on the square and simple-cubic lattices. In two and three dimensions, we find numerical evidence for a strongly discontinuous transition. In two dimensions, the clusters at the threshold are compact with a fractal surface of fractal dimension df=1.49±0.02. On the simple-cubic lattice, distinct jumps in the size of the largest cluster are observed. We proceed to analyze the tree-like version of the model, where only merging bonds are sampled, for dimension two to seven. The transition is again discontinuous in any considered dimension. Finally, the dependence of the cluster-size distribution at the threshold on the spatial dimension is also investigated.

  19. Estimates of genetic parameters for Holstein cows for test-day yield traits with a random regression cubic spline model.

    Science.gov (United States)

    DeGroot, B J; Keown, J F; Van Vleck, L D; Kachman, S D

    2007-06-30

    Genetic parameters were estimated with restricted maximum likelihood for individual test-day milk, fat, and protein yields and somatic cell scores with a random regression cubic spline model. Test-day records of Holstein cows that calved from 1994 through early 1999 were obtained from Dairy Records Management Systems in Raleigh, North Carolina, for the analysis. Estimates of heritability for individual test-days and estimates of genetic and phenotypic correlations between test-days were obtained from estimates of variances and covariances from the cubic spline analysis. Estimates were calculated of genetic parameters for the averages of the test days within each of the ten 30-day test intervals. The model included herd test-day, age at first calving, and bovine somatropin treatment as fixed factors. Cubic splines were fitted for the overall lactation curve and for random additive genetic and permanent environmental effects, with five predetermined knots or four intervals between days 0, 50, 135, 220, and 305. Estimates of heritability for lactation one ranged from 0.10 to 0.15, 0.06 to 0.10, 0.09 to 0.15, and 0.02 to 0.06 for test-day one to test-day 10 for milk, fat, and protein yields and somatic cell scores, respectively. Estimates of heritability were greater in lactations two and three. Estimates of heritability increased over the course of the lactation. Estimates of genetic and phenotypic correlations were smaller for test-days further apart.

  20. Simulation of rice yield under different irrigation and nitrogen application managements by CropSyst model

    Directory of Open Access Journals (Sweden)

    Narjes ZARE

    2015-12-01

    Full Text Available The aim of this study was the calibration and validation of CropSyst model for rice in the city of Rasht. The necessary data were extracted from a field experiment which was carried out during 2005-2007 in a split-plot design. The main plots were irrigation regimes including continuous flooding irrigation and 5-day irrigation intervals. The subplots consisted of four nitrogen levels: zero N application, 45, 60 and 75 kg N ha-1. Normalized Root Mean Squared Error (nRMSE and Residual Mass Coefficient (Crm in calibration years were 9.3 % and 0.06, respectively. In validation year, nRMSE and Crm were 9.7 % and 0.11, respectively. According to other indices to assess irrigation regimes and fertilizer levels, the most suitable treatments regarding environmental aspect were 5-day irrigation regime and 45 kg N ha-1.

  1. Science yield modeling with the Exoplanet Open-Source Imaging Mission Simulator (EXOSIMS)

    Science.gov (United States)

    Delacroix, Christian; Savransky, Dmitry; Garrett, Daniel; Lowrance, Patrick; Morgan, Rhonda

    2016-08-01

    We report on our ongoing development of EXOSIMS and mission simulation results for WFIRST. We present the interface control and the modular structure of the software, along with corresponding prototypes and class definitions for some of the software modules. More specifically, we focus on describing the main steps of our high-fidelity mission simulator EXOSIMS, i.e., the completeness, optical system and zodiacal light modules definition, the target list module filtering, and the creation of a planet population within our simulated universe module. For the latter, we introduce the integration of a recent mass-radius model from the FORECASTER software. We also provide custom modules dedicated to WFIRST using both the Hybrid Lyot Coronagraph (HLC) and the Shaped Pupil Coronagraph (SPC) for detection and characterization, respectively. In that context, we show and discuss the results of some preliminary WFIRST simulations, focusing on comparing different methods of integration time calculation, through ensembles (large numbers) of survey simulations.

  2. Bioenergy Sorghum Crop Model Predicts VPD-Limited Transpiration Traits Enhance Biomass Yield in Water-Limited Environments.

    Science.gov (United States)

    Truong, Sandra K; McCormick, Ryan F; Mullet, John E

    2017-01-01

    Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum's long duration of vegetative growth increased water capture and biomass yield by ~30% compared to short season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development

  3. Simulation of winter wheat yield and its variability in different climates of Europe: A comparison of eight crop growth models

    DEFF Research Database (Denmark)

    Palosuo, Taru; Kersebaum, Kurt Christian; Angulo, Carlos

    2011-01-01

    We compared the performance of eight widely used, easily accessible and well-documented crop growth simulation models (APES, CROPSYST, DAISY, DSSAT, FASSET, HERMES, STICS and WOFOST) for winter wheat (Triticum aestivum L.) during 49 growing seasons at eight sites in northwestern, Central and sout......We compared the performance of eight widely used, easily accessible and well-documented crop growth simulation models (APES, CROPSYST, DAISY, DSSAT, FASSET, HERMES, STICS and WOFOST) for winter wheat (Triticum aestivum L.) during 49 growing seasons at eight sites in northwestern, Central...... values were lowest (1428 and 1603 kg ha−1) and the index of agreement (0.71 and 0.74) highest. CROPSYST systematically underestimated yields (MBE – 1186 kg ha−1), whereas HERMES, STICS and WOFOST clearly overestimated them (MBE 1174, 1272 and 1213 kg ha−1, respectively). APES, DAISY, HERMES, STICS...

  4. Project on the Good Physician: Further Evidence for the Validity of a Moral Intuitionist Model of Virtuous Caring.

    Science.gov (United States)

    Leffel, G Michael; Oakes Mueller, Ross A; Ham, Sandra A; Karches, Kyle E; Curlin, Farr A; Yoon, John D

    2018-01-19

    In the Project on the Good Physician, the authors propose a moral intuitionist model of virtuous caring that places the virtues of Mindfulness, Empathic Compassion, and Generosity at the heart of medical character education. Hypothesis 1a: The virtues of Mindfulness, Empathic Compassion, and Generosity will be positively associated with one another (convergent validity). Hypothesis 1b: The virtues of Mindfulness and Empathic Compassion will explain variance in the action-related virtue of Generosity beyond that predicted by Big Five personality traits alone (discriminant validity). Hypothesis 1c: Virtuous students will experience greater well-being ("flourishing"), as measured by four indices of well-being: life meaning, life satisfaction, vocational identity, and vocational calling (predictive validity). Hypothesis 1d: Students who self-report higher levels of the virtues will be nominated by their peers for the Gold Humanism Award (predictive validity). Hypothesis 2a-2c: Neuroticism and Burnout will be positively associated with each other and inversely associated with measures of virtue and well-being. The authors used data from a 2011 nationally representative sample of U.S. medical students (n = 499) in which medical virtues (Mindfulness, Empathic Compassion, and Generosity) were measured using scales adapted from existing instruments with validity evidence. Supporting the predictive validity of the model, virtuous students were recognized by their peers to be exemplary doctors, and they were more likely to have higher ratings on measures of student well-being. Supporting the discriminant validity of the model, virtues predicted prosocial behavior (Generosity) more than personality traits alone, and students higher in the virtue of Mindfulness were less likely to be high in Neuroticism and Burnout. Data from this descriptive-correlational study offered additional support for the validity of the moral intuitionist model of virtuous caring. Applied to medical

  5. Estimation of genotype X environment interactions, in a grassbased system, for milk yield, body condition score,and body weight using random regression models

    NARCIS (Netherlands)

    Berry, D.P.; Buckley, F.; Dillon, P.; Evans, R.D.; Rath, M.; Veerkamp, R.F.

    2003-01-01

    (Co)variance components for milk yield, body condition score (BCS), body weight (BW), BCS change and BW change over different herd-year mean milk yields (HMY) and nutritional environments (concentrate feeding level, grazing severity and silage quality) were estimated using a random regression model.

  6. Simplified geometric model for the calculation of neutron yield in an accelerator of 18 MV for radiotherapy

    International Nuclear Information System (INIS)

    Paredes G, L.C.; Balcazar G, M.; Francois L, J.L.; Azorin N, J.

    2008-01-01

    The results of the neutrons yield in different components of the bolster of an accelerator Varian Clinac 2100C of 18 MV for radiotherapy are presented, which contribute to the radiation of flight of neutrons in the patient and bolster planes. For the calculation of the neutrons yield, a simplified geometric model of spherical cell for the armor-plating of the bolster with Pb and W was used. Its were considered different materials for the Bremsstrahlung production and of neutrons produced through the photonuclear reactions and of electro disintegration, in function of the initial energy of the electron. The theoretical result of the total yield of neutrons is of 1.17x10 -3 n/e, considering to the choke in position of closed, in the patient plane with a distance source-surface of 100 cm; of which 15.73% corresponds to the target, 58.72% to the primary collimator, 4.53% to the levelled filter of Fe, 4.87% to the levelled filter of Ta and 16.15% to the closed choke. For an initial energy of the electrons of 18 MeV, a half energy of the neutrons of 2 MeV was obtained. The calculated values for radiation of experimental neutrons flight are inferior to the maxima limit specified in the NCRP-102 and IEC-60601-201.Ed.2.0 reports. The absorbed dose of neutrons determined through the measurements with TLD dosemeters in the isocenter to 100 cm of the target when the choke is closed one, is approximately 3 times greater that the calculated for armor-plating of W and 1.9 times greater than an armor-plating of Pb. (Author)

  7. 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.

  8. Predicting future US water yield and ecosystem productivity by linking an ecohydrological model to WRF dynamically downscaled climate projections

    Science.gov (United States)

    Sun, S.; Sun, G.; Cohen, E.; McNulty, S. G.; Caldwell, P.; Duan, K.; Zhang, Y.

    2015-12-01

    Quantifying the potential impacts of climate change on water yield and ecosystem productivity (i.e., carbon balances) is essential to developing sound watershed restoration plans, and climate change adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) dynamically downscaled climate projections of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12 digit Hydrologic Unit Code level) in the conterminous US (CONUS), and evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or 2-digit HUCs. Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8 °C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 g C m-2 yr-1 (9 %) increase in GPP. Response to climate change was highly variable across the 82, 773 watersheds, but in general, the majority would see consistent increases in all variables evaluated. Over half of the 82 773 watersheds, mostly found in the northeast and the southern part of the southwest would have an increase in annual Q (>100 mm yr-1 or 20 %). This study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results will be useful for policy-makers and land managers in formulating appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

  9. Crop modelling as a tool to separate the influence of the soil and weather on crop yields

    Science.gov (United States)

    Mathe-Gaspar, Gabriella; Fodor, Nandor; Pokovai, Klara; Kovacs, Geza Janos

    The yield of traditional food and feed crops in a given habitat is controlled by the soil and weather conditions as the main environmental factors. In real world it is not possible to segregate the influences of the soil and the weather on the crop production. Using simulation models there are ways to analyse the effects of the changes of soil characteristics or weather elements separately. The role of different soil characteristics can be studied in a way that the first run is considered as a control, then one of the soil characteristics is changed within a realistic range while all the other soil factors and weather inputs are left original. This way all the soil characteristic and weather elements can be changed one by one or different combinations of them can be used as input series. A more practical approach is when the role of local soils and weather are compared by a series of runs applying observed weather data from different years and real soil profiles from different fields of the selected farm. The results of the simulation can be evaluated from many different aspects: biomass or yield production, vulnerability to nitrate leaching or denitrification and profitability. In this study real Hungarian soil and weather scenarios were used that are significantly different from one another. The two main crops of Hungary were used: maize and wheat plus field pea as an addition. Pea is known as a sensitive crop to weather. 4M-simulation package was used as a modelling tool. Our group at RISSAC based on CERES and CROPGRO models has developed it. The results showed that the weather differences caused more significant changes in yields then soil differences though soils could moderate the effects of the extreme weather scenarios. The measure of reactions is meaningfully different depending on the species and cultivars. Analysis of separated effects of soil and weather factors has not only theoretical and methodological importance, but useful for the practice, too

  10. Crop modelling as a tool to separate the influences of the soil and weather on crop yields

    Science.gov (United States)

    Mathe-Gaspar, G.; Fodor, N.; Pokovai, K.; Kovacs, G. J.

    2003-04-01

    The yield of traditional food and feed crops in a given habitat is controlled by the soil and weather conditions as the main environmental factors. In real world it is not possible to segregate the influences of the soil and the weather on the crop production. Using simulation models there are ways to analyse the effects of the changes of soil characteristics or weather elements separately. The role of different soil characteristics can be studied in a way that the first run is considered as a control, then one of the soil characteristics is changed within a realistic range while all the other soil factors and weather inputs are left original. This way all the soil characteristic and weather elements can be changed one by one or different combinations of them can be used as input series. A more practical approach is when the role of local soils and weather are compared by a series of runs applying observed weather data from different years and real soil profiles from different fields of the selected farm. The results of the simulation can be evaluated from many different aspects: biomass or yield production, vulnerability to nitrate leaching or denitrification and profitability. In this study real Hungarian soil and weather scenarios were used that are significantly different from one another. The two main crops of Hungary were used: maize and wheat plus field pea as an addition. Pea is known as a sensitive crop to weather. 4M-simulation package was used as a modelling tool. Our group at RISSAC based on CERES and CROPGRO models has developed it. The results showed that the weather differences caused more significant changes in yields then soil differences though soils could moderate the effects of the extreme weather scenarios. The measure of reactions is meaningfully different depending on the species and cultivars. Analysis of separated effects of soil and weather factors has not only theoretical and methodological importance, but useful for the practice, too

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

    Directory of Open Access Journals (Sweden)

    Ajay Singh

    2016-06-01

    Full Text Available 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.

  12. 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

  13. Random regression models to estimate genetic parameters for test-day milk yield in Brazilian Murrah buffaloes.

    Science.gov (United States)

    Sesana, R C; Bignardi, A B; Borquis, R R A; El Faro, L; Baldi, F; Albuquerque, L G; Tonhati, H

    2010-10-01

    The objective of this work was to estimate covariance functions for additive genetic and permanent environmental effects and, subsequently, to obtain genetic parameters for buffalo's test-day milk production using random regression models on Legendre polynomials (LPs). A total of 17 935 test-day milk yield (TDMY) from 1433 first lactations of Murrah buffaloes, calving from 1985 to 2005 and belonging to 12 herds located in São Paulo state, Brazil, were analysed. Contemporary groups (CGs) were defined by herd, year and month of milk test. Residual variances were modelled through variance functions, from second to fourth order and also by a step function with 1, 4, 6, 22 and 42 classes. The model of analyses included the fixed effect of CGs, number of milking, age of cow at calving as a covariable (linear and quadratic) and the mean trend of the population. As random effects were included the additive genetic and permanent environmental effects. The additive genetic and permanent environmental random effects were modelled by LP of days in milk from quadratic to seventh degree polynomial functions. The model with additive genetic and animal permanent environmental effects adjusted by quintic and sixth order LP, respectively, and residual variance modelled through a step function with six classes was the most adequate model to describe the covariance structure of the data. Heritability estimates decreased from 0.44 (first week) to 0.18 (fourth week). Unexpected negative genetic correlation estimates were obtained between TDMY records at first weeks with records from middle to the end of lactation, being the values varied from -0.07 (second with eighth week) to -0.34 (1st with 42nd week). TDMY heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in milking buffaloes. Copyright 2010 Blackwell Verlag GmbH.

  14. 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

  15. 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...

  16. Improving Spring Maize Yield Estimation at Field Scale by Assimilating Time-Series HJ-1 CCD Data into the WOFOST Model Using a New Method with Fast Algorithms

    Directory of Open Access Journals (Sweden)

    Zhiqiang Cheng

    2016-04-01

    Full Text Available Field crop yield prediction is crucial to grain storage, agricultural field management, and national agricultural decision-making. Currently, crop models are widely used for crop yield prediction. However, they are hampered by the uncertainty or similarity of input parameters when extrapolated to field scale. Data assimilation methods that combine crop models and remote sensing are the most effective methods for field yield estimation. In this study, the World Food Studies (WOFOST model is used to simulate the growing process of spring maize. Common assimilation methods face some difficulties due to the scarce, constant, or similar nature of the input parameters. For example, yield spatial heterogeneity simulation, coexistence of common assimilation methods and the nutrient module, and time cost are relatively important limiting factors. To address the yield simulation problems at field scale, a simple yet effective method with fast algorithms is presented for assimilating the time-series HJ-1 A/B data into the WOFOST model in order to improve the spring maize yield simulation. First, the WOFOST model is calibrated and validated to obtain the precise mean yield. Second, the time-series leaf area index (LAI is calculated from the HJ data using an empirical regression model. Third, some fast algorithms are developed to complete assimilation. Finally, several experiments are conducted in a large farmland (Hongxing to evaluate the yield simulation results. In general, the results indicate that the proposed method reliably improves spring maize yield estimation in terms of spatial heterogeneity simulation ability and prediction accuracy without affecting the simulation efficiency.

  17. A major challenge for modeling conservation-based water use reductions in aquifers supporting irrigated agriculture: The specific yield quandary

    Science.gov (United States)

    Butler, J. J., Jr.; Whittemore, D. O.; Wilson, B. B.; Bohling, G.

    2017-12-01

    Many large regional aquifers supporting irrigated agriculture are experiencing high rates of water-level decline. The primary means of moderating these rates is to reduce pumping. The key question is what percent pumping reduction will significantly impact decline rates. We have recently developed a water-balance approach to address this question for subareas (100s to 1000s km2 in size) of seasonally pumped aquifers (Butler et al., GRL, 2016). This approach also provides an estimate of specific yield (Sy), which has been difficult to estimate from field data at the scale of modeling analyses. When applied to subareas of the High Plains aquifer in Kansas, this approach reveals that the Sy estimate is much lower (as much as a factor of five or more) than expected for an unconsolidated aquifer. One explanation is that the aquifer is heterogeneous with considerable amounts of fine material, whereas field data, such as drillers' logs, are often biased towards coarser intervals. An additional explanation, which appears to have received little attention, is the impact of entrapped air. In seasonally pumped systems, water levels pass through the same aquifer intervals multiple times, giving ample opportunity for air to be entrapped. This entrapped air imbues the aquifer with a specific yield that is considerably lower than what would be expected from lithology. If unrecognized, a larger-than-actual Sy value is input into the aquifer model. This can lead to the inadvertent use of the same-year recharge assumption, which may not be appropriate for many conditions (e.g., large depths to water), and can also result in artificially low estimates of net inflow for a depleting aquifer. Moreover, failure to recognize this condition can bedevil efforts to model conservation-based water use reductions. In that case, models will leave the range of conditions for which they have been calibrated and can become more vulnerable to parameter errors. Conservation-based water use reductions

  18. 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.

  19. 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.

  20. Prone Whole-Breast Irradiation Using Three-Dimensional Conformal Radiotherapy in Women Undergoing Breast Conservation for Early Disease Yields High Rates of Excellent to Good Cosmetic Outcomes in Patients With Large and/or Pendulous Breasts

    Energy Technology Data Exchange (ETDEWEB)

    Bergom, Carmen; Kelly, Tracy; Morrow, Natalya; Wilson, J. Frank [Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI (United States); Walker, Alonzo [Department of Surgery, Medical College of Wisconsin, Milwaukee, WI (United States); Xiang Qun; Ahn, Kwang Woo [Division of Biostatistics, Medical College of Wisconsin, Milwaukee, WI (United States); White, Julia, E-mail: jwhite@mcw.edu [Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI (United States)

    2012-07-01

    Purpose: To report our institution's experience using prone positioning for three-dimensional conformal radiotherapy (3D-CRT) to deliver post-lumpectomy whole breast irradiation (WBI) in a cohort of women with large and/or pendulous breasts, to determine the rate of acute and late toxicities and, more specifically, cosmetic outcomes. We hypothesized that using 3D-CRT for WBI in the prone position would reduce or eliminate patient and breast size as negative prognostic indicators for toxicities associated with WBI. Methods and Materials: From 1998 to 2006, 110 cases were treated with prone WBI using 3D-CRT. The lumpectomy, breast target volumes, heart, and lung were contoured on all computed tomography scans. A dose of 45-50 Gy was prescribed to the breast volume using standard fractionation schemes. The planning goals were {>=}95% of prescription to 95% of the breast volume, and 100% of boost dose to 95% of lumpectomy planning target volume. Toxicities and cosmesis were prospectively scored using the Common Terminology Criteria for Adverse Effects Version 3.0 and the Harvard Scale. The median follow-up was 40 months. Results: The median body mass index (BMI) was 33.6 kg/m{sup 2}, and median breast volume was 1396 cm{sup 3}. The worst toxicity encountered during radiation was Grade 3 dermatitis in 5% of our patient population. Moist desquamation occurred in 16% of patients, with only 2% of patients with moist desquamation outside the inframammary/axillary folds. Eleven percent of patients had Grade {>=}2 late toxicities, including Grade 3 induration/fibrosis in 2%. Excellent to good cosmesis was achieved in 89%. Higher BMI was associated with moist desquamation and breast pain, but BMI and breast volume did not impact fibrosis or excellent to good cosmesis. Conclusion: In patients with higher BMI and/or large-pendulous breasts, delivering prone WBI using 3D-CRT results in favorable toxicity profiles and high excellent to good cosmesis rates. Higher BMI was

  1. Doing Good

    DEFF Research Database (Denmark)

    Jørgensen, Frances; Sluhan, Anne

    2015-01-01

    In this paper, we investigate how corporate philanthropy serves as a mechanism for building organizational commitment. Although much research has reported on the potential benefits of philanthropy and highlighted its impact on organizational commitment, reports are lacking on how philanthropic...... activities can be implemented to actively influence organizational commitment. We address this gap through a longitudinal qualitative study in a Danish family-owned firm, where we model how initiation of and participation in philanthropic activities encourages organizational commitment through...... an organizational identification process. Theoretically, we contribute to the literature by providing an in-depth processual perspective on how engagement in philanthropic activities facilitates value alignment between employees and their organization, and therein fosters organizational commitment. Practically...

  2. Modelling predicts that tolerance to drought during reproductive development will be required for high yield potential and stability of wheat in Europe

    Science.gov (United States)

    Semenov, Mikhail A.; Stratonovitch, Pierre; Paul, Matthew J.

    2017-04-01

    Short periods of extreme weather, such as a spell of high temperature or drought during a sensitive stage of development, could result in substantial yield losses due to reduction in grain number and grain size. In a modelling study (Stratonovitch & Semenov 2015), heat tolerance around flowering in wheat was identified as a key trait for increased yield potential in Europe under climate change. Ji et all (Ji et al. 2010) demonstrated cultivar specific responses of yield to drought stress around flowering in wheat. They hypothesised that carbohydrate supply to anthers may be the key in maintaining pollen fertility and grain number in wheat. It was shown in (Nuccio et al. 2015) that genetically modified varieties of maize that increase the concentration of sucrose in ear spikelets, performed better under non-drought and drought conditions in field experiments. The objective of this modelling study was to assess potential benefits of tolerance to drought during reproductive development for wheat yield potential and yield stability across Europe. We used the Sirius wheat model to optimise wheat ideotypes for 2050 (HadGEM2, RCP8.5) climate scenarios at selected European sites. Eight cultivar parameters were optimised to maximise mean yields, including parameters controlling phenology, canopy growth and water limitation. At those sites where water could be limited, ideotypes sensitive to drought produced substantially lower mean yields and higher yield variability compare with tolerant ideotypes. Therefore, tolerance to drought during reproductive development is likely to be required for wheat cultivars optimised for the future climate in Europe in order to achieve high yield potential and yield stability.

  3. Customs control of goods

    Directory of Open Access Journals (Sweden)

    Mentor Gashi

    2015-11-01

    Full Text Available Customs control, is regulated by law in different countries. Different countries define through the law, the control of goods.. Main purpose of this paper is to analyze two types of customs controls, and their effect in reducing avoidance of duty or tax evasion which may be caused by the import of goods of certain companies. For this reason we researched which model is implemented in developing countries and what results were reached through questionnaires. In this sense the next research question, consists in defining the moment of customs control pre or post-clearance control of goods.

  4. 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.

  5. Selecting a dynamic simulation modeling method for health care delivery research-part 2: report of the ISPOR Dynamic Simulation Modeling Emerging Good Practices Task Force.

    Science.gov (United States)

    Marshall, Deborah A; Burgos-Liz, Lina; IJzerman, Maarten J; Crown, William; Padula, William V; Wong, Peter K; Pasupathy, Kalyan S; Higashi, Mitchell K; Osgood, Nathaniel D

    2015-03-01

    In a previous report, the ISPOR Task Force on Dynamic Simulation Modeling Applications in Health Care Delivery Research Emerging Good Practices introduced the fundamentals of dynamic simulation modeling and identified the types of health care delivery problems for which dynamic simulation modeling can be used more effectively than other modeling methods. The hierarchical relationship between the health care delivery system, providers, patients, and other stakeholders exhibits a level of complexity that ought to be captured using dynamic simulation modeling methods. As a tool to help researchers decide whether dynamic simulation modeling is an appropriate method for modeling the effects of an intervention on a health care system, we presented the System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence (SIMULATE) checklist consisting of eight elements. This report builds on the previous work, systematically comparing each of the three most commonly used dynamic simulation modeling methods-system dynamics, discrete-event simulation, and agent-based modeling. We review criteria for selecting the most suitable method depending on 1) the purpose-type of problem and research questions being investigated, 2) the object-scope of the model, and 3) the method to model the object to achieve the purpose. Finally, we provide guidance for emerging good practices for dynamic simulation modeling in the health sector, covering all aspects, from the engagement of decision makers in the model design through model maintenance and upkeep. We conclude by providing some recommendations about the application of these methods to add value to informed decision making, with an emphasis on stakeholder engagement, starting with the problem definition. Finally, we identify areas in which further methodological development will likely occur given the growing "volume, velocity and variety" and availability of "big data" to provide empirical evidence and techniques

  6. 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.

  7. 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.)

  8. Genome sequence and plasmid transformation of the model high-yield bacterial cellulose producer Gluconacetobacter hansenii ATCC 53582.

    Science.gov (United States)

    Florea, Michael; Reeve, Benjamin; Abbott, James; Freemont, Paul S; Ellis, Tom

    2016-03-24

    Bacterial cellulose is a strong, highly pure form of cellulose that is used in a range of applications in industry, consumer goods and medicine. Gluconacetobacter hansenii ATCC 53582 is one of the highest reported bacterial cellulose producing strains and has been used as a model organism in numerous studies of bacterial cellulose production and studies aiming to increased cellulose productivity. Here we present a high-quality draft genome sequence for G. hansenii ATCC 53582 and find that in addition to the previously described cellulose synthase operon, ATCC 53582 contains two additional cellulose synthase operons and several previously undescribed genes associated with cellulose production. In parallel, we also develop optimized protocols and identify plasmid backbones suitable for transformation of ATCC 53582, albeit with low efficiencies. Together, these results provide important information for further studies into cellulose synthesis and for future studies aiming to genetically engineer G. hansenii ATCC 53582 for increased cellulose productivity.

  9. Good manufacturing practice

    International Nuclear Information System (INIS)

    Schlyer, D.J.

    2001-01-01

    In this presentation author deals with the Implementation of good manufacturing practice for radiopharmaceuticals. The presentation is divided into next parts: Batch size; Expiration date; QC Testing; Environmental concerns; Personnel aspects; Radiation concerns; Theoretical yields; Sterilizing filters; Control and reconciliation of materials and components; Product strength; In process sampling and testing; Holding and distribution; Drug product inspection; Buildings and facilities; Renovations at BNL for GMP; Aseptic processing and sterility assurance; Process validation and control; Quality control and drug product stability; Documentation and other GMP topics; Building design considerations; Equipment; and Summary

  10. Brazilian Soybean Yields and Yield Gaps Vary with Farm Size

    Science.gov (United States)

    Jeffries, G. R.; Cohn, A.; Griffin, T. S.; Bragança, A.

    2017-12-01

    Understanding the farm size-specific characteristics of crop yields and yield gaps may help to improve yields by enabling better targeting of technical assistance and agricultural development programs. Linking remote sensing-based yield estimates with property boundaries provides a novel view of the relationship between farm size and yield structure (yield magnitude, gaps, and stability over time). A growing literature documents variations in yield gaps, but largely ignores the role of farm size as a factor shaping yield structure. Research on the inverse farm size-productivity relationship (IR) theory - that small farms are more productive than large ones all else equal - has documented that yield magnitude may vary by farm size, but has not considered other yield structure characteristics. We examined farm size - yield structure relationships for soybeans in Brazil for years 2001-2015. Using out-of-sample soybean yield predictions from a statistical model, we documented 1) gaps between the 95th percentile of attained yields and mean yields within counties and individual fields, and 2) yield stability defined as the standard deviation of time-detrended yields at given locations. We found a direct relationship between soy yields and farm size at the national level, while the strength and the sign of the relationship varied by region. Soybean yield gaps were found to be inversely related to farm size metrics, even when yields were only compared to farms of similar size. The relationship between farm size and yield stability was nonlinear, with mid-sized farms having the most stable yields. The work suggests that farm size is an important factor in understanding yield structure and that opportunities for improving soy yields in Brazil are greatest among smaller farms.

  11. Methodological model for economic and accounting valuation of environmental goods and services –EGS- in the municipality of Miraflores Boyacá

    Directory of Open Access Journals (Sweden)

    Claudia Marcela Camargo-López

    2013-12-01

    Full Text Available This paper addresses the theoretical and conceptual bases related to economic valuation of environmental goods and services for designing of a methodological model, as well as approaches for categorization, identification and classification of such goods in the municipality of Miraflores. We apply the valuation "Cascade El Ombligo" in such a way to allow making decisions on a project of creation of a natural park in this water reserve.

  12. The Good Way Model: A Strengths-Based Approach for Working with Young People, Especially Those with Intellectual Difficulties, Who Have Sexually Abusive Behaviour

    Science.gov (United States)

    Ayland, Lesley; West, Bill

    2006-01-01

    The Good Way model was originally developed for working with youth with intellectual difficulties who have sexually abused and is also now being used with adults with intellectual disabilities and non-disabled adolescents. The model is practical and has been developed to address the need for a common, coherent narrative with which clients and…

  13. Random regression test day models to estimate genetic parameters for milk yield and milk components in Philippine dairy buffaloes.

    Science.gov (United States)

    Flores, E B; van der Werf, J

    2015-08-01

    Heritabilities and genetic correlations for milk production traits were estimated from first-parity test day records on 1022 Philippine dairy buffalo cows. Traits analysed included milk (MY), fat (FY) and protein (PY) yields, and fat (Fat%) and protein (Prot%) concentrations. Varying orders of Legendre polynomials (Leg(m)) as well as the Wilmink function (Wil) were used in random regression models. These various models were compared based on log likelihood, Akaike's information criterion, Bayesian information criterion and genetic variance estimates. Six residual variance classes were sufficient for MY, FY, PY and Fat%, while seven residual classes for Prot%. Multivariate analysis gave higher estimates of genetic variance and heritability compared with univariate analysis for all traits. Heritability estimates ranged from 0.25 to 0.44, 0.13 to 0.31 and 0.21 to 0.36 for MY, FY and PY, respectively. Wilmink's function was the better fitting function for additive genetic effects for all traits. It was also the preferred function for permanent environment effects for Fat% and Prot%, but for MY, FY and PY, the Legm was the appropriate function. Genetic correlations of MY with FY and PY were high and they were moderately negative with Fat% and Prot%. To prevent deterioration in Fat% and Prot% and improve milk quality, more weight should be applied to milk component traits. © 2015 Blackwell Verlag GmbH.

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

    Energy Technology Data Exchange (ETDEWEB)

    Čufar, Aljaž, E-mail: aljaz.cufar@ijs.si [Reactor Physics Department, Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Batistoni, Paola [ENEA, Department of Fusion and Nuclear Safety Technology, I-00044 Frascati, Rome (Italy); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Conroy, Sean [Uppsala University, Department of Physics and Astronomy, PO Box 516, SE-75120 Uppsala (Sweden); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Ghani, Zamir [Culham Centre for Fusion Energy, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Lengar, Igor [Reactor Physics Department, Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Milocco, Alberto; Packer, Lee [Culham Centre for Fusion Energy, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Pillon, Mario [ENEA, Department of Fusion and Nuclear Safety Technology, I-00044 Frascati, Rome (Italy); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Popovichev, Sergey [Culham Centre for Fusion Energy, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Snoj, Luka [Reactor Physics Department, Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); EUROfusion Consortium, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom)

    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.

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

    Science.gov (United States)

    Parker, Sarah M; Serre, Thomas

    2015-01-01

    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 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 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. 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.

  17. 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; JET Contributors

    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.

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    Canaway Rachel

    2010-12-01

    Full Text Available Abstract Background The co-occurrence of mental illness and substance use problems (referred to as "comorbidity" in this paper is common, and is often reported by service providers as the expectation rather than the exception. Despite this, many different treatment service models are being used in the alcohol and other drugs (AOD and mental health (MH sectors to treat this complex client group. While there is abundant literature in the area of comorbidity treatment, no agreed overarching framework to describe the range of service delivery models is apparent internationally or at the national level. The aims of the current research were to identify and describe elements of good practice in current service models of treatment of comorbidity in Australia. The focus of the research was on models of service delivery. The research did not aim to measure the client outcomes achieved by individual treatment services, but sought to identify elements of good practice in services. Methods Australian treatment services were identified to take part in the study through a process of expert consultation. The intent was to look for similarities in the delivery models being implemented across a diverse set of services that were perceived to be providing good quality treatment for people with comorbidity problems. Results A survey was designed based on a concept map of service delivery devised from a literature review. Seventeen Australian treatment services participated in the survey, which explored the context in which services operate, inputs such as organisational philosophy and service structure, policies and procedures that guide the way in which treatment is delivered by the service, practices that reflect the way treatment is provided to clients, and client impacts. Conclusions The treatment of people with comorbidity of mental health and substance use disorders presents complex problems that require strong but flexible service models. While the treatment

  20. 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.

  1. Causes of variation among rice models in yield response to CO2 examined with Free-Air CO2 Enrichment and growth chamber experiments.

    Science.gov (United States)

    Hasegawa, Toshihiro; Li, Tao; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Baker, Jeffrey; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fugice, Job; Fumoto, Tamon; Gaydon, Donald; Kumar, Soora Naresh; Lafarge, Tanguy; Marcaida Iii, Manuel; Masutomi, Yuji; Nakagawa, Hiroshi; Oriol, Philippe; Ruget, Françoise; Singh, Upendra; Tang, Liang; Tao, Fulu; Wakatsuki, Hitomi; Wallach, Daniel; Wang, Yulong; Wilson, Lloyd Ted; Yang, Lianxin; Yang, Yubin; Yoshida, Hiroe; Zhang, Zhao; Zhu, Jianguo

    2017-11-01

    The CO 2 fertilization effect is a major source of uncertainty in crop models for future yield forecasts, but coordinated efforts to determine the mechanisms of this uncertainty have been lacking. Here, we studied causes of uncertainty among 16 crop models in predicting rice yield in response to elevated [CO 2 ] (E-[CO 2 ]) by comparison to free-air CO 2 enrichment (FACE) and chamber experiments. The model ensemble reproduced the experimental results well. However, yield prediction in response to E-[CO 2 ] varied significantly among the rice models. The variation was not random: models that overestimated at one experiment simulated greater yield enhancements at the others. The variation was not associated with model structure or magnitude of photosynthetic response to E-[CO 2 ] but was significantly associated with the predictions of leaf area. This suggests that modelled secondary effects of E-[CO 2 ] on morphological development, primarily leaf area, are the sources of model uncertainty. Rice morphological development is conservative to carbon acquisition. Uncertainty will be reduced by incorporating this conservative nature of the morphological response to E-[CO 2 ] into the models. Nitrogen levels, particularly under limited situations, make the prediction more uncertain. Improving models to account for [CO 2 ] × N interactions is necessary to better evaluate management practices under climate change.

  2. Genetic analysis of coagulation properties, curd firming modeling, milk yield, composition, and acidity in Sarda dairy sheep.

    Science.gov (United States)

    Bittante, G; Cipolat-Gotet, C; Pazzola, M; Dettori, M L; Vacca, G M; Cecchinato, A

    2017-01-01

    Sheep milk is an important source of food, especially in Mediterranean countries, and is used in large part for cheese production. Milk technological traits are important for the sheep dairy industry, but research is lacking into the genetic variation of such traits. Therefore the aim of this study was to estimate the heritability of traditional milk coagulation properties and curd firmness modeled on time t (CF t ) parameters, and their genetic relationships with test-day milk yield, composition (fat, protein, and casein content), and acidity in Sarda dairy sheep. Milk samples from 1,121 Sarda ewes from 23 flocks were analyzed for 5 traditional coagulation properties by lactodynamographic tests conducted for up to 60min: rennet coagulation time (min), curd-firming time (k 20 , min), and 3measures of curd firmness (a 30 , a 45 , and a 60 , mm). The 240 curd firmness observations (1 every 15 s) from each milk sample were recorded, and 4 parameters for each individual sample equation were estimated: rennet coagulation time estimated from the equation (RCT eq ), the asymptotic potential curd firmness (CF P ), the curd firming instant rate constant (k CF ), and the syneresis instant rate constant (k SR ). Two other derived traits were also calculated (CF max , the maximum curd firmness value; and t max , the attainment time). Multivariate analyses using Bayesian methodology were performed to estimate the genetic relationships of milk coagulation properties and CF t with the other traits; statistical inference was based on the marginal posterior distributions of the parameters of concern. The marginal posterior distribution of heritability estimates of milk yield (0.16±0.07) and composition (0.21±0.11 to 0.28±0.10) of Sarda ewes was similar to those often obtained for bovine species. The heritability of rennet coagulation time as a single point trait was also similar to that frequently obtained for cow milk (0.19±0.09), whereas the same trait calculated as an

  3. Modeling the effects of ultrasound power and reactor dimension on the biodiesel production yield: Comparison of prediction abilities between response surface methodology (RSM) and adaptive neuro-fuzzy inference system (ANFIS)

    International Nuclear Information System (INIS)

    Mostafaei, Mostafa; Javadikia, Hossein; Naderloo, Leila

    2016-01-01

    Biodiesel is as an alternative petro-diesel fuel produced from the renewable resources. The use of novel technologies such as ultrasound technology for biodiesel production intensifies the reaction and reduces the process cost. The present study is aimed to evaluate and compare the prediction and simulating efficiency of the response surface methodology (RSM) and adaptive Neuro-fuzzy inference system (ANFIS) approaches for modeling the transesterification yield achieved in ultrasonic reactor. The influence of independent variables (reactor diameter, liquid height and ultrasound intensity) on the conversion of fatty acid methyl esters (FAME) was investigated by Box-Behnken design of RSM and two ANFIS approaches (hybrid and back-propagation optimization methods). All models were compared statistically based on the training and validation data set by the coefficient of determination (R2), root mean squares error (RMSE), mean absolute percentage error (MAPE), mean absolute error (MAE) and mean relative percent deviation (MRPD). The calculated R2 for RSM and two ANFIS models were 0.9669, 0.9812 and 0.9808, respectively. All models indicated good predictions, however, the ANFIS models were more precise compared to the RSM model, which proves that the ANFIS is a powerful tool for modeling and optimizing FAME production in ultrasound reactor. - Highlights: • The ultrasound assisted FAME conversion was modelled using RSM and ANFIS approaches. • The scatter diagrams indicate the models accurately predicted the reaction yield. • The ANFIS model (hybrid) has higher R 2 (0.9812) compared to the RSM model. • The predicted deviations and residual values are relatively small for ANFIS model. • ANFIS model was more accurate for predicting ultrasound assisted FAME conversion.

  4. Accelerating the domestication of a bioenergy crop: identifying and modelling morphological targets for sustainable yield increase in Miscanthus.

    Science.gov (United States)

    Robson, Paul; Jensen, Elaine; Hawkins, Sarah; White, Simon R; Kenobi, Kim; Clifton-Brown, John; Donnison, Iain; Farrar, Kerrie

    2013-11-01

    To accelerate domestication of Miscanthus, an important energy crop, 244 replicated genotypes, including two different species and their hybrids, were analysed for morphological traits and biomass yield over three growing seasons following an establishment phase of 2 years in the largest Miscanthus diversity trial described to date. Stem and leaf traits were selected that contributed both directly and indirectly to total harvested biomass yield, and there was variation in all traits measured. Morphological diversity within the population was correlated with dry matter yield (DMY) both as individual traits and in combination, in order to determine the respective contributions of the traits to biomass accumulation and to identify breeding targets for yield improvement. Predictive morphometric analysis was possible at year 3 within Miscanthus sinensis genotypes but not between M. sinensis, Miscanthus sacchariflorus, and interspecific hybrids. Yield is a complex trait, and no single simple trait explained more than 33% of DMY, which varied from 1 to 5297 g among genotypes within this trial. Associating simple traits increased the power of the morphological data to predict yield to 60%. Trait variety, in combination, enabled multiple ideotypes, thereby increasing the potential diversity of the crop for multiple growth locations and end uses. Both triploids and interspecific hybrids produced the highest mature yields, indicating that there is significant heterosis to be exploited within Miscanthus that might be overlooked in early selection screens within years 1-3. The potential for optimizing biomass yield by selecting on the basis of morphology is discussed.

  5. Analysis of strengthening in AA6111 during the early stages of aging: Atom probe tomography and yield stress modelling

    International Nuclear Information System (INIS)

    Marceau, R.K.W.; Vaucorbeil, A. de; Sha, G.; Ringer, S.P.; Poole, W.J.

    2013-01-01

    In this work, a series of aging treatments has been conducted on AA6111 alloy samples for various times at ambient temperature (so-called natural aging) and at temperatures between 60 and 180 °C (artificially aged). The time at artificial ageing was chosen such that samples with approximately the same yield stress were produced. The microstructures of these alloy samples have been carefully characterized using atom probe tomography together with advanced cluster-finding techniques in order to obtain quantitative information about the changes in distribution of both the solute clusters and early-stage precipitates that are formed. The size distribution of clusters has been mapped onto the glide plane and then the stress necessary for a dislocation to pass through the range of obstacles has been estimated using an areal glide model where the dislocation–obstacle interaction strength has been assumed to be related to the obstacle size on the glide plane. It is demonstrated that the contribution of cluster strengthening during artificial aging at higher temperatures is dominated by the high number density of small clusters (Guinier radius <1 nm), whereas the situation during room temperature natural aging is more complex

  6. Visual Basic Growth-and-Yield Models With A Merchandising Optimizer For Planted Slash and Loblolly Pine in the West Gulf Region

    Science.gov (United States)

    R.L. Busby; S.J. Chang; P.R. Pasala; J.C.G. Goelz

    2004-01-01

    We developed two growth-and-yield models for thinned and unthinned plantations of slash pine (Pinus elliottii Engelm. var elliottii) and loblolly pine (P. taeda L.). The models, VB Merch-Slash and VB Merch-Lob, can be used to forecast product volumes and stand values for stands partitioned into 1-inch diameter-at...

  7. Projecting water yield and ecosystem productivity across the United States by linking an ecohydrological model to WRF dynamically downscaled climate data

    Science.gov (United States)

    Shanlei Sun; Ge Sun; Erika Cohen Mack; Steve McNulty; Peter V. Caldwell; Kai Duan; Yang Zhang

    2016-01-01

    Quantifying the potential impacts of climatechange on water yield and ecosystem productivity is essential to developing sound watershed restoration plans, andecosystem adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and StressIndex, WaSSI) with WRF (Weather Research and Forecasting Model) using dynamically downscaled...

  8. Genetic Analysis of Milk Yield Using Random Regression Test Day Model in Tehran Province Holstein Dairy Cow

    Directory of Open Access Journals (Sweden)

    A. Seyeddokht

    2012-09-01

    Full Text Available In this research a random regression test day model was used to estimate heritability values and calculation genetic correlations between test day milk records. a total of 140357 monthly test day milk records belonging to 28292 first lactation Holstein cattle(trice time a day milking distributed in 165 herd and calved from 2001 to 2010 belonging to the herds of Tehran province were used. The fixed effects of herd-year-month of calving as contemporary group and age at calving and Holstein gene percentage as covariate were fitted. Orthogonal legendre polynomial with a 4th-order was implemented to take account of genetic and environmental aspects of milk production over the course of lactation. RRM using Legendre polynomials as base functions appears to be the most adequate to describe the covariance structure of the data. The results showed that the average of heritability for the second half of lactation period was higher than that of the first half. The heritability value for the first month was lowest (0.117 and for the eighth month of the lactation was highest (0.230 compared to the other months of lactation. Because of genetic variation was increased gradually, and residual variance was high in the first months of lactation, heritabilities were different over the course of lactation. The RRMs with a higher number of parameters were more useful to describe the genetic variation of test-day milk yield throughout the lactation. In this research estimation of genetic parameters, and calculation genetic correlations were implemented by random regression test day model, therefore using this method is the exact way to take account of parameters rather than the other ways.

  9. 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.

  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. Financial Giffen Goods

    DEFF Research Database (Denmark)

    Poulsen, Rolf; Rasmussen, Kourosh Marjani

    2008-01-01

    In the basic Markowitz and Merton models, a stock’s weight in efficient portfolios goes up if its expected rate of return goes up. Put differently, there are no financial Giffen goods. By an example from mortgage choice we illustrate that for more complicated portfolio problems Giffen effects do...

  12. Good Faith and Game Theory

    DEFF Research Database (Denmark)

    Rose, Caspar

    2016-01-01

    This article shows how game theory can be applied to model good faith mathematically using an example of a classic legal dispute related to rei vindicato. The issue is whether an owner has a legal right to his good if a person has bought it in good faith by using updated probabilities. The article...

  13. Secondary electron emission yield: graphite and some aromatic hydrocarbons

    International Nuclear Information System (INIS)

    Cazaux, J

    2005-01-01

    A recent analytical model for the secondary electron emission yield, δ, is successfully applied here to graphite and some aromatic hydrocarbons (xylene, anthracene, phenanthrene and biphenyl). In contrast to the use of conventional constant loss model, this model takes a more realistic account of the in-depth generation of the secondary electrons and permits a good description of the reduced yield curves, δ/δ (max) versus E 0 /E 0 (max) , via a suitable choice of the most probable energy dissipation depth, z C , of primary electrons in these low-density, low atomic-weight materials. Physical information on escape probability and on attenuation length of secondary electrons propagating in the investigated specimens is deduced from the good fit between calculated and experimental yield curves, δ = f(E 0 )

  14. Secondary electron emission yield: graphite and some aromatic hydrocarbons

    Energy Technology Data Exchange (ETDEWEB)

    Cazaux, J [LASSI/UTAP, Faculte des Sciences, BP1039, 51687 Reims Cedex 2 (France)

    2005-07-21

    A recent analytical model for the secondary electron emission yield, {delta}, is successfully applied here to graphite and some aromatic hydrocarbons (xylene, anthracene, phenanthrene and biphenyl). In contrast to the use of conventional constant loss model, this model takes a more realistic account of the in-depth generation of the secondary electrons and permits a good description of the reduced yield curves, {delta}/{delta}{sub (max)} versus E{sup 0}/E{sup 0}{sub (max)}, via a suitable choice of the most probable energy dissipation depth, z{sub C}, of primary electrons in these low-density, low atomic-weight materials. Physical information on escape probability and on attenuation length of secondary electrons propagating in the investigated specimens is deduced from the good fit between calculated and experimental yield curves, {delta} = f(E{sup 0})

  15. Yield gains in leafy vegetables

    Science.gov (United States)

    Yield of all crops have increased during the past century through improved cultural practices and plant breeding. We reviewed gains in yield of lettuce and spinach in the U.S., principally California and Arizona. We proposed several genetic models for yield of lettuce based on the market type: whole...

  16. Public Goods, Voting, and Growth

    OpenAIRE

    Kirill Borissov; Joseph Hanna; Stephane Lambrecht

    2014-01-01

    We study a parametric politico-economic model of economic growth with productive public goods and public consumption goods. The provision of public goods is funded by a proportional tax on consumers' income. Agents are heterogeneous in their initial capital endowments, discount factors and the relative weights of public consumption in overall private utility. They vote on the shares of public goods in GDP. We propose a definition of voting equilibrium, prove the existence and provide a charac...

  17. Codes of Good Governance

    DEFF Research Database (Denmark)

    Beck Jørgensen, Torben; Sørensen, Ditte-Lene

    2013-01-01

    Good governance is a broad concept used by many international organizations to spell out how states or countries should be governed. Definitions vary, but there is a clear core of common public values, such as transparency, accountability, effectiveness, and the rule of law. It is quite likely......, however, that national views of good governance reflect different political cultures and institutional heritages. Fourteen national codes of conduct are analyzed. The findings suggest that public values converge and that they match model codes from the United Nations and the European Council as well...... as conceptions of good governance from other international organizations. While values converge, they are balanced and communicated differently, and seem to some extent to be translated into the national cultures. The set of global public values derived from this analysis include public interest, regime dignity...

  18. Assimilation of TOPEX/POSEIDON Altimeter Data into a Global Ocean Circulation Model: Are the Results Any Good?

    Science.gov (United States)

    Fukumori, I.; Fu, L. L.; Chao, Y.

    1998-01-01

    The feasibility of assimilating satellite altimetry data into a global ocean general ocean general circulation model is studied. Three years of TOPEX/POSEIDON data is analyzed using a global, three-dimensional, nonlinear primitive equation model.

  19. Good Clinical Teachers Likely to be Specialist Role Models: Results from a Multicenter Cross-Sectional Survey

    NARCIS (Netherlands)

    Lombarts, Kiki M. J. M. H.; Heineman, Maas Jan; Arah, Onyebuchi A.

    2010-01-01

    Context: Medical educational reform includes enhancing role modelling of clinical teachers. This requires faculty being aware of their role model status and performance. We developed the System for Evaluation of Teaching Qualities (SETQ) to generate individualized feedback on previously defined

  20. 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, Raveendra Hanumantagoud; Lægdsmand, Mette; Olesen, Jørgen Eivind

    2012-01-01

    Sensitivity of wheat yield and soil nitrogen (N) losses to stepwise changes in means and variances of climatic variables were determined using the FASSET model. The LARS-WG was used to generate climate scenarios using observed climate data (1961–90) from two sites in Denmark, which differed...... 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...... temperatures, caused by early maturity, with little change in variability. This, however, increased soil mineral N causing increased N losses. On sandy loam, larger temperature variability lowered grain yields and increased N losses coupled with higher variability at all the mean temperature ranges. On coarse...

  1. A Different Approach to Answering a Good Question: A Response to Hewes's Models of Communication Effects on Small Group Outcomes

    Science.gov (United States)

    Bonito, Joseph A.; Sanders, Robert E.

    2009-01-01

    This article presents the authors' response to Hewes's (1986, 1996, 2009) models of communication effects on small group outcomes. As sophisticated and thoughtful as Hewes's new model is, however, the authors take issue with it. For one, there is reason to question whether his approach is feasible. For another, his models are not founded on solid…

  2. Integrating remotely sensed leaf area index and leaf nitrogen accumulation with RiceGrow model based on particle swarm optimization algorithm for rice grain yield assessment

    Science.gov (United States)

    Wang, Hang; Zhu, Yan; Li, Wenlong; Cao, Weixing; Tian, Yongchao

    2014-01-01

    A regional rice (Oryza sativa) grain yield prediction technique was proposed by integration of ground-based and spaceborne remote sensing (RS) data with the rice growth model (RiceGrow) through a new particle swarm optimization (PSO) algorithm. Based on an initialization/parameterization strategy (calibration), two agronomic indicators, leaf area index (LAI) and leaf nitrogen accumulation (LNA) remotely sensed by field spectra and satellite images, were combined to serve as an external assimilation parameter and integrated with the RiceGrow model for inversion of three model management parameters, including sowing date, sowing rate, and nitrogen rate. Rice grain yield was then predicted by inputting these optimized parameters into the reinitialized model. PSO was used for the parameterization and regionalization of the integrated model and compared with the shuffled complex evolution-University of Arizona (SCE-UA) optimization algorithm. The test results showed that LAI together with LNA as the integrated parameter performed better than each alone for crop model parameter initialization. PSO also performed better than SCE-UA in terms of running efficiency and assimilation results, indicating that PSO is a reliable optimization method for assimilating RS information and the crop growth model. The integrated model also had improved precision for predicting rice grain yield.

  3. 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)

    Durand, Jean-Louis; Delusca, Kenel; Boote, Ken; Lizaso, Jon; Manderscheid, Remy; Weigel, Hans Johachim; Ruane, Alexander Clark; Rosenzweig, Cynthia E.; Jones, Jim; Ahuja, Laj; hide

    2017-01-01

    This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration [CO2] on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thunen Institute in Braunschweig, Germany (Manderscheid et al. 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50 percent of models within a range of plus/minus 1 Mg ha(exp. -1) around the mean. The bias of the median of the 21 models was less than 1 Mg ha(exp. -1). However under water deficit in one of the two years, the models captured only 30 percent of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase.

  4. Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

    Science.gov (United States)

    Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

    2017-09-01

    Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates

  5. Impact of urbanization on the sediment yield in tropical watershed using temporal land-use changes and a GIS-based model

    Directory of Open Access Journals (Sweden)

    Bello Al-Amin D.

    2017-09-01

    Full Text Available Abundant rainfall areas promote sediment yield at both sub-watershed and watershed scale due to soil erosion and increase siltation of river channel, but it can be curtailed through planned urbanization. The urbanization of Skudai watershed is analysed from historical and future perspective. A GIS-based model (Hydrological Simulation Programme-FORTRAN-HSPF is used to modelled sediment flow using basin-wide simulation, and the output result is utilized in evaluating sediment yield reduction due to increased urbanization by swapping multiple temporal land-use of decadent time-steps. The analysis indicates that sediment yield reduces with increase urban built-up and decrease forest and agricultural land. An estimated 12 400 tons of sediment will be reduced for every 27% increase in built-up areas under high rainfall condition and 1 490 tons at low rainfall. The sensitivity analysis of land-use classes shows that built-up, forest and barren are more sensitive to sediment yield reduction compared to wetland and agricultural land at both high and low rainfall. The result of the study suggests that increased urbanization reduced sediment yield in proportion to the rainfall condition and can be used as an alternative approach for soil conservation at watershed scale independent of climate condition.

  6. 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...

  7. Application of a crop growth model (SUCROS-87) to assess the effect of moisture on yield potential of durum wheat in Ethiopia.

    NARCIS (Netherlands)

    Simane, B.; Keulen, van H.; Stol, W.; Struik, P.C.

    1994-01-01

    A spring wheat growth model (SUCROS-87) was used to identify moisture stress periods during the growing seasons and simulate yield potentials of durum wheat (Triticum turgidum var. durum) in six durum wheat growing regions of Ethiopia. The start of the rainy season and distribution of rainfall were

  8. 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.

  9. 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.

  10. A comparative analysis of three habitat suitability models for commercial yield estimation of Tapes philippinarum in a North Adriatic coastal lagoon (Sacca di Goro, Italy).

    Science.gov (United States)

    Vincenzi, Simone; Caramori, Graziano; Rossi, Remigio; De Leo, Giulio A

    2007-01-01

    Habitat Suitability (HS) models have been extensively used by conservation planners to estimate the spatial distribution of threatened species and of species of commercial interest. In this work we compare three HS models for the estimation of commercial yield potential and the identification of suitable sites for Tapes philippinarum rearing in the Sacca di Goro lagoon (Italy) on the basis of six environmental factors. The habitat suitability index (HSI) is based on expert opinion while the habitat suitability conditional (HSC) is calibrated on observational data. The habitat suitability mixed (HSM) model is a two-part model combining expert knowledge and regression analysis: the first component of the model uses logistic regression to identify the areas in which clams are likely to be present; the second part applies the same parameter-specific suitability functions of the HSI model only in the areas previously identified as productive by the logistic component. The HS models were validated on an independent data set and estimates of potential yield of the Goro lagoon were compared. The effectiveness of the three approaches is then discussed in terms of predicted yield and identification of suitable sites for farming.

  11. Optimization model of peach production relevant to input energies – Yield function in Chaharmahal va Bakhtiari province, Iran

    International Nuclear Information System (INIS)

    Ghatrehsamani, Shirin; Ebrahimi, Rahim; Kazi, Salim Newaz; Badarudin Badry, Ahmad; Sadeghinezhad, Emad

    2016-01-01

    The aim of this study was to determine the amount of input–output energy used in peach production and to develop an optimal model of production in Chaharmahal va Bakhtiari province, Iran. Data were collected from 100 producers by administering a questionnaire in face-to-face interviews. Farms were selected based on random sampling method. Results revealed that the total energy of production is 47,951.52 MJ/ha and the highest share of energy consumption belongs to chemical fertilizers (35.37%). Consumption of direct energy was 47.4% while indirect energy was 52.6%. Also, Total energy consumption was divided into two groups; renewable and non-renewable (19.2% and 80.8% respectively). Energy use efficiency, Energy productivity, Specific energy and Net energy were calculated as 0.433, 0.228 (kg/MJ), 4.38 (MJ/kg) and −27,161.722 (MJ/ha), respectively. According to the negative sign for Net energy, if special strategy is used, energy dismiss will decrease and negative effect of some parameters could be omitted. In the present case the amount is indicating decimate of production energy. In addition, energy efficiency was not high enough. Some of the input energies were applied to machinery, chemical fertilizer, water irrigation and electricity which had significant effect on increasing production and MPP (marginal physical productivity) was determined for variables. This parameter was positive for energy groups namely; machinery, diesel fuel, chemical fertilizer, water irrigation and electricity while it was negative for other kind of energy such as chemical pesticides and human labor. Finally, there is a need to pursue a new policy to force producers to undertake energy-efficient practices to establish sustainable production systems without disrupting the natural resources. In addition, extension activities are needed to improve the efficiency of energy consumption and to sustain the natural resources. - Highlights: • Replacing non-renewable energy with renewable

  12. Water Ice Radiolytic O2, H2, and H2O2 Yields for Any Projectile Species, Energy, or Temperature: A Model for Icy Astrophysical Bodies

    Science.gov (United States)

    Teolis, B. D.; Plainaki, C.; Cassidy, T. A.; Raut, U.

    2017-10-01

    O2, H2, and H2O2 radiolysis from water ice is pervasive on icy astrophysical bodies, but the lack of a self-consistent, quantitative model of the yields of these water products versus irradiation projectile species and energy has been an obstacle to estimating the radiolytic oxidant sources to the surfaces and exospheres of these objects. A major challenge is the wide variation of O2 radiolysis yields between laboratory experiments, ranging over 4 orders of magnitude from 5 × 10-7 to 5 × 10-3 molecules/eV for different particles and energies. We revisit decades of laboratory data to solve this long-standing puzzle, finding an inverse projectile range dependence in the O2 yields, due to preferential O2 formation from an 30 Å thick oxygenated surface layer. Highly penetrating projectile ions and electrons with ranges ≳30 Å are therefore less efficient at producing O2 than slow/heavy ions and low-energy electrons (≲ 400 eV) which deposit most energy near the surface. Unlike O2, the H2O2 yields from penetrating projectiles fall within a comparatively narrow range of (0.1-6) × 10-3 molecules/eV and do not depend on range, suggesting that H2O2 forms deep in the ice uniformly along the projectile track, e.g., by reactions of OH radicals. We develop an analytical model for O2, H2, and H2O2 yields from pure water ice for electrons and singly charged ions of any mass and energy and apply the model to estimate possible O2 source rates on several icy satellites. The yields are upper limits for icy bodies on which surface impurities may be present.

  13. Income and Wealth Distribution in a Neoclassical Two-Sector Heterogeneous-Households Growth Model with Elastic Labor Supply and Consumer Durable Goods

    Directory of Open Access Journals (Sweden)

    Wei-Bin ZHANG

    2017-06-01

    Full Text Available This paper proposes a two-sector two-group growth model with elastic labor supply and consumer durable goods. We study dynamics of wealth and income distribution in a competitive economy with capital accumulation as the main engine of economic growth. The model is built on the Uzawa two-sector model. It is also influenced by the neoclassical growth theory and the post-Keynesian theory of growth and distribution. We plot the motion of the economic system and determine the economic equilibrium. We carry out comparative dynamic analysis with regard to the propensity to save and improvements in human capital and technology.

  14. Modeling Biometric Traits, Yield and Nutritional and Antioxidant Properties of Seeds of Three Soybean Cultivars Through the Application of Biostimulant Containing Seaweed and Amino Acids.

    Science.gov (United States)

    Kocira, Sławomir; Szparaga, Agnieszka; Kocira, Anna; Czerwińska, Ewa; Wójtowicz, Agnieszka; Bronowicka-Mielniczuk, Urszula; Koszel, Milan; Findura, Pavol

    2018-01-01

    In recent years, attempts have been made to use preparations that allow obtaining high and good quality yields, while reducing the application of pesticides and mineral fertilizers. These include biostimulants that are safe for the natural environment and contribute to the improvement of yield size and quality, especially after the occurrence of stressors. Their use is advisable in the case of crops sensitive to such biotic stress factors like low temperatures or drought. One of these is soybean which is a very important plant from the economic viewpoint. Field experiments were established in the years 2014-2016 in a random block design in four replicates on experimental plots of 10 m 2 . Three soybean cultivars: Annushka, Mavka, and Atlanta were planted in the third decade of April. Fylloton biostimulant was used at 0.7% or 1% concentrations as single spraying (BBCH 13-15) or double spraying (BBCH 13-15, BBCH 61) in the vegetation period. The number of seeds per 1 m 2 , seed yield, thousand seed weight, number of pods per plant, number of nodes in the main shoot, height of plants, and protein and fat contents in seeds were determined. The content of phenolic compounds, antioxidant capacity and antioxidant effect of soybean seeds were assayed as well. Foliar treatment of soybean with Fylloton stimulated the growth and yield of plants without compromising their nutritional and nutraceutical properties. The double application of the higher concentration of Fylloton was favorable for the plant height, seed number and soybean yield. Moreover, the highest number of pods was obtained after single treatment of plants with the lower biostimulant concentration. There was also a positive effect of using this biostimulant on the content and activity of some bioactive compounds, such as phenolics and flavonoids, and on the reducing power.

  15. Modeling Biometric Traits, Yield and Nutritional and Antioxidant Properties of Seeds of Three Soybean Cultivars Through the Application of Biostimulant Containing Seaweed and Amino Acids

    Directory of Open Access Journals (Sweden)

    Sławomir Kocira

    2018-03-01

    Full Text Available In recent years, attempts have been made to use preparations that allow obtaining high and good quality yields, while reducing the application of pesticides and mineral fertilizers. These include biostimulants that are safe for the natural environment and contribute to the improvement of yield size and quality, especially after the occurrence of stressors. Their use is advisable in the case of crops sensitive to such biotic stress factors like low temperatures or drought. One of these is soybean which is a very important plant from the economic viewpoint. Field experiments were established in the years 2014-2016 in a random block design in four replicates on experimental plots of 10 m2. Three soybean cultivars: Annushka, Mavka, and Atlanta were planted in the third decade of April. Fylloton biostimulant was used at 0.7% or 1% concentrations as single spraying (BBCH 13-15 or double spraying (BBCH 13-15, BBCH 61 in the vegetation period. The number of seeds per 1 m2, seed yield, thousand seed weight, number of pods per plant, number of nodes in the main shoot, height of plants, and protein and fat contents in seeds were determined. The content of phenolic compounds, antioxidant capacity and antioxidant effect of soybean seeds were assayed as well. Foliar treatment of soybean with Fylloton stimulated the growth and yield of plants without compromising their nutritional and nutraceutical properties. The double application of the higher concentration of Fylloton was favorable for the plant height, seed number and soybean yield. Moreover, the highest number of pods was obtained after single treatment of plants with the lower biostimulant concentration. There was also a positive effect of using this biostimulant on the content and activity of some bioactive compounds, such as phenolics and flavonoids, and on the reducing power.

  16. Modeling of DNA single stage splicing language via Yusof-Goode approach: One string with two rules

    Science.gov (United States)

    Lim, Wen Li; Yusof, Yuhani; Mudaber, Mohammad Hassan

    2015-02-01

    Splicing system plays a pivotal role in attempts to recombine sets of double-stranded DNA molecules when acted by restriction enzymes and ligase. Traditional method of finding the result of DNA recombination through experiment is both time and money consuming. Hence, finding the number of patterns of DNA single stage splicing language through formalism of splicing system is a way to optimize the searching process. From the biological perspective, it predicts the number of types of molecules that will exist in the system under existence of restriction enzymes and ligase. In this paper, some theorems, corollaries and examples that lead to the predictions of single stage splicing languages involving one pattern string and two rules are presented via Yusof-Goode approach.

  17. Informed Design of Educational Technology for Teaching and Learning? Towards an Evidence-Informed Model of Good Practice

    Science.gov (United States)

    Price, Linda; Kirkwood, Adrian

    2014-01-01

    The aim of this paper is to model evidence-informed design based on a selective critical analysis of research articles. The authors draw upon findings from an investigation into practitioners' use of educational technologies to synthesise and model what informs their designs. They found that practitioners' designs were often driven by implicit…

  18. The effect of high-sugar grass on predicted nitrogen excretion and milk yield simulated using a dynamic model

    NARCIS (Netherlands)

    Ellis, J.L.; Dijkstra, J.; Bannink, A.; Parsons, A.J.; Rasmussen, S.; Edwards, G.R.; Kebreab, E.; France, J.

    2011-01-01

    High-sugar grass varieties have received considerable attention for their potential to reduce nitrogen (N) excretion and increase milk yield in cattle. However, considerable variation exists in the magnitude of response in published results. The purpose of this study is to explain the variation in

  19. Yield gap analysis and assessment of climate-induced yield trends of irrigated rice in selected provinces of the Philippines

    Directory of Open Access Journals (Sweden)

    Reiner Wassmann

    2012-04-01

    Full Text Available This study describes a combined empirical/modeling approach to assess the possible impact of climate variability on rice production in the Philippines. We collated climate data of the last two decades (1985-2002 as well as yield statistics of six provinces of the Philippines, selected along a North-South gradient. Data from the climate information system of NASA were used as input parameters of the model ORYZA2000 to determine potential yields and, in the next steps, the yield gaps defined as the difference between potential and actual yields. Both simulated and actual yields of irrigated rice varied strongly between years. However, no climate-driven trends were apparent and the variability in actual yields showed no correlation with climatic parameters. The observed variation in simulated yields was attributable to seasonal variations in climate (dry/wet season and to climatic differences between provinces and agro-ecological zones. The actual yield variation between provinces was not related to differences in the climatic yield potential but rather to soil and management factors. The resulting yield gap was largest in remote and infrastructurally disfavored provinces (low external input use with a high production potential (high solar radiation and day-night temperature differences. In turn, the yield gap was lowest in central provinces with good market access but with a relatively low climatic yield potential. We conclude that neither long-term trends nor the variability of the climate can explain current rice yield trends and that agroecological, seasonal, and management effects are over-riding any possible climatic variations. On the other hand the lack of a climate-driven trend in the present situation may be superseded by ongoing climate change in the future.

  20. Informed design of educational technology for teaching and learning? Towards an evidence-informed model of good practice

    OpenAIRE

    Price, Linda; Kirkwood, Adrian

    2014-01-01

    The aim of this paper is to model evidence-informed design based on a selective critical analysis of research articles. We draw upon findings from an investigation into practitioners’ use of educational technologies to synthesise and model what informs their designs. We found that practitioners’ designs were often driven by implicit assumptions about learning. These shaped both the design of interventions and the methods sought to derive evaluations and interpret the findings. We argue that i...

  1. Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle.

    Science.gov (United States)

    Pereira, R J; Bignardi, A B; El Faro, L; Verneque, R S; Vercesi Filho, A E; Albuquerque, L G

    2013-01-01

    Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  2. Impact of the spatial resolution of climatic data and soil physical properties on regional corn yield predictions using the STICS crop model

    Science.gov (United States)

    Jégo, Guillaume; Pattey, Elizabeth; Mesbah, S. Morteza; Liu, Jiangui; Duchesne, Isabelle

    2015-09-01

    The assimilation of Earth observation (EO) data into crop models has proven to be an efficient way to improve yield prediction at a regional scale by estimating key unknown crop management practices. However, the efficiency of prediction depends on the uncertainty associated with the data provided to crop models, particularly climatic data and soil physical properties. In this study, the performance of the STICS (Simulateur mulTIdisciplinaire pour les Cultures Standard) crop model for predicting corn yield after assimilation of leaf area index derived from EO data was evaluated under different scenarios. The scenarios were designed to examine the impact of using fine-resolution soil physical properties, as well as the impact of using climatic data from either one or four weather stations across the region of interest. The results indicate that when only one weather station was used, the average annual yield by producer was predicted well (absolute error <5%), but the spatial variability lacked accuracy (root mean square error = 1.3 t ha-1). The model root mean square error for yield prediction was highly correlated with the distance between the weather stations and the fields, for distances smaller than 10 km, and reached 0.5 t ha-1 for a 5-km distance when fine-resolution soil properties were used. When four weather stations were used, no significant improvement in model performance was observed. This was because of a marginal decrease (30%) in the average distance between fields and weather stations (from 10 to 7 km). However, the yield predictions were improved by approximately 15% with fine-resolution soil properties regardless of the number of weather stations used. The impact of the uncertainty associated with the EO-derived soil textures and the impact of alterations in rainfall distribution were also evaluated. A variation of about 10% in any of the soil physical textures resulted in a change in dry yield of 0.4 t ha-1. Changes in rainfall distribution

  3. Developing a good practice model to evaluate the effectiveness of comprehensive primary health care in local communities.

    Science.gov (United States)

    Lawless, Angela; Freeman, Toby; Bentley, Michael; Baum, Fran; Jolley, Gwyn

    2014-05-15

    This paper describes the development of a model of Comprehensive Primary Health Care (CPHC) applicable to the Australian context. CPHC holds promise as an effective model of health system organization able to improve population health and increase health equity. However, there is little literature that describes and evaluates CPHC as a whole, with most evaluation focusing on specific programs. The lack of a consensus on what constitutes CPHC, and the complex and context-sensitive nature of CPHC are all barriers to evaluation. The research was undertaken in partnership with six Australian primary health care services: four state government funded and managed services, one sexual health non-government organization, and one Aboriginal community controlled health service. A draft model was crafted combining program logic and theory-based approaches, drawing on relevant literature, 68 interviews with primary health care service staff, and researcher experience. The model was then refined through an iterative process involving two to three workshops at each of the six participating primary health care services, engaging health service staff, regional health executives and central health department staff. The resultant Southgate Model of CPHC in Australia model articulates the theory of change of how and why CPHC service components and activities, based on the theory, evidence and values which underpin a CPHC approach, are likely to lead to individual and population health outcomes and increased health equity. The model captures the importance of context, the mechanisms of CPHC, and the space for action services have to work within. The process of development engendered and supported collaborative relationships between researchers and stakeholders and the product provided a description of CPHC as a whole and a framework for evaluation. The model was endorsed at a research symposium involving investigators, service staff, and key stakeholders. The development of a theory

  4. 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 <1 dB. Reasonable selection of GA's parameters is essential for stability and efficiency of rice parameter retrieval. Two rice parameters are retrieved by the proposed RCSM-GA technology with better accuracy. The rice ear length are estimated with error o