WorldWideScience

Sample records for model yields insights

  1. Modeling for Insights

    Energy Technology Data Exchange (ETDEWEB)

    Jacob J. Jacobson; Gretchen Matthern

    2007-04-01

    System Dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, System Dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The real power of System Dynamic modeling is gaining insights into total system behavior as time, and system parameters are adjusted and the effects are visualized in real time. System Dynamic models allow decision makers and stakeholders to explore long-term behavior and performance of complex systems, especially in the context of dynamic processes and changing scenarios without having to wait decades to obtain field data or risk failure if a poor management or design approach is used. The Idaho National Laboratory recently has been developing a System Dynamic model of the US Nuclear Fuel Cycle. The model is intended to be used to identify and understand interactions throughout the entire nuclear fuel cycle and suggest sustainable development strategies. This paper describes the basic framework of the current model and presents examples of useful insights gained from the model thus far with respect to sustainable development of nuclear power.

  2. Franchise Business Model: Theoretical Insights

    OpenAIRE

    Levickaitė, Rasa; Reimeris, Ramojus

    2010-01-01

    The article is based on literature review, theoretical insights, and deals with the topic of franchise business model. The objective of the paper is to analyse peculiarities of franchise business model and its developing conditions in Lithuania. The aim of the paper is to make an overview on franchise business model and its environment in Lithuanian business context. The overview is based on international and local theoretical insights. In terms of practical meaning, this article should be re...

  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. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Transcriptomic identification of starfish neuropeptide precursors yields new insights into neuropeptide evolution

    Science.gov (United States)

    Semmens, Dean C.; Mirabeau, Olivier; Moghul, Ismail; Pancholi, Mahesh R.; Wurm, Yannick; Elphick, Maurice R.

    2016-01-01

    Neuropeptides are evolutionarily ancient mediators of neuronal signalling in nervous systems. With recent advances in genomics/transcriptomics, an increasingly wide range of species has become accessible for molecular analysis. The deuterostomian invertebrates are of particular interest in this regard because they occupy an ‘intermediate' position in animal phylogeny, bridging the gap between the well-studied model protostomian invertebrates (e.g. Drosophila melanogaster, Caenorhabditis elegans) and the vertebrates. Here we have identified 40 neuropeptide precursors in the starfish Asterias rubens, a deuterostomian invertebrate from the phylum Echinodermata. Importantly, these include kisspeptin-type and melanin-concentrating hormone-type precursors, which are the first to be discovered in a non-chordate species. Starfish tachykinin-type, somatostatin-type, pigment-dispersing factor-type and corticotropin-releasing hormone-type precursors are the first to be discovered in the echinoderm/ambulacrarian clade of the animal kingdom. Other precursors identified include vasopressin/oxytocin-type, gonadotropin-releasing hormone-type, thyrotropin-releasing hormone-type, calcitonin-type, cholecystokinin/gastrin-type, orexin-type, luqin-type, pedal peptide/orcokinin-type, glycoprotein hormone-type, bursicon-type, relaxin-type and insulin-like growth factor-type precursors. This is the most comprehensive identification of neuropeptide precursor proteins in an echinoderm to date, yielding new insights into the evolution of neuropeptide signalling systems. Furthermore, these data provide a basis for experimental analysis of neuropeptide function in the unique context of the decentralized, pentaradial echinoderm bauplan. PMID:26865025

  9. Statistical modelling and deconvolution of yield meter data

    DEFF Research Database (Denmark)

    Tøgersen, Frede Aakmann; Waagepetersen, Rasmus Plenge

    2004-01-01

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

  10. 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 ...

  11. Does the effectiveness of the ketogenic diet in different epilepsies yield insights into its mechanisms?

    Science.gov (United States)

    Hartman, Adam L.

    2009-01-01

    Summary The ketogenic diet (KD) has been used successfully in a variety of epilepsy syndromes. This includes syndromes with multiple etiologies, including Lennox-Gastaut syndrome and infantile spasms; developmental syndromes of unknown etiology, such as Landau-Kleffner syndrome; and idiopathic epilepsies, such as myoclonic-astatic (Doose) epilepsy. It also includes syndromes where genetics play a major role, such as Dravet syndrome, tuberous sclerosis, and Rett syndrome. Study of the KD in humans and animals harboring various genetic mutations may yield insights into the diet’s mechanisms. Comparison of the diet’s effectiveness with other treatments in specific syndromes may be another useful tool for mechanistic studies. The diet’s utility in epilepsy syndromes of various etiologies and in some neurodegenerative disorders suggests it may have multiple mechanisms of action. PMID:19049588

  12. New insights in permafrost modelling

    Science.gov (United States)

    Tubini, Niccolò; Serafin, Francesco; Gruber, Stephan; Casulli, Vincenzo; Rigon, Riccardo

    2017-04-01

    Simulating freezing soil has ignored for long time in mainstream surface hydrology. However, it has indubitably a large influence on soil infiltrability and an even larger influence on the soil energy budget, and, over large spatial scales, a considerable feedback on climate. The topic is difficult because it involves concepts of disequilibrium Thermodynamics and also because, once solved the theoretical problem, integration of the resulting partial differential equations in a robust manner, is not trivial at all. In this abstract, we are presenting a new algorithm to estimate the water and energy budget in freezing soils. The first step is a derivation of a new equation for freezing soil mass budget (called generalized Richards equation) based on the freezing equals drying hypothesis (Miller 1965). The second step is the re-derivation of the energy budget. Finally there is the application of new techniques based on the double nested Newton algorithm (Casulli and Zanolli, 2010) to integrate the coupled equations. Some examples of the freezing dynamics and comparison with the Dall'Amico et al. (2011) algorithm are also shown. References Casulli, V., & Zanolli,P. (2010). A nested newton-type algorithm for finite colume methods solving Richards' equation in mixed form. SIAM J. SCI. Comput., 32(4), 2225-2273. Dall'Amico, M., Endrizzi, S., Gruber, S., & Rigon, R. (2011). A robust and energy-conserving model of freezing variably-saturated soil. The Cryosphere, 5(2), 469-484. http://doi.org/10.5194/tc-5-469-2011 Miller, R.: Phase equilibria and soil freezing, in: Permafrost: Proceedings of the Second International Conference. Washington DC: National Academy of Science-National Research Council, 287, 193-197, 1965.

  13. Mountain erosion over decades and millennia: New insights from sediment yields and cosmogenic nuclides

    Science.gov (United States)

    Callahan, R. P.; Riebe, C. S.; Ferrier, K.

    2017-12-01

    For more than two decades, cosmogenic nuclides have been used to quantify catchment-wide erosion rates averaged over tens of thousands of years. These rates have been used as baselines for comparison with sediment yields averaged over decades, leading to insights on how human activities such as deforestation and agriculture have influenced the production and delivery of sediment to streams and oceans. Here we present new data from the southern Sierra Nevada, California, where sediment yields have been measured over the last ten years using sediment trapping and gauging methods. Cosmogenic nuclides measured in stream sediment reveal erosion rates that are between 13 and 400 (average = 94) times faster than erosion rates inferred from annual accumulations in sediment traps. We show that the discrepancy can be explained by extremely low sediment trapping efficiency, which leads to bias in the short-term rates due to incomplete capture of suspended sediment. Thus the short-term rates roughly agree with the long-term rates, despite intensive timber harvesting in the study catchments over the last century. This differs from results obtained in similar forested granitic catchments of Idaho, where long-term rates are more than ten times greater than short-term rates because large, rare events do not contribute to the short-term averages. Our analysis of a global database indicates that both the magnitude and sign of differences between short- and long-term average erosion rates are difficult to predict, even when the history of land use in known.

  14. 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, ...

  15. 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.

  16. 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...

  17. 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...

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Modelling marine protected areas: insights and hurdles

    Science.gov (United States)

    Fulton, Elizabeth A.; Bax, Nicholas J.; Bustamante, Rodrigo H.; Dambacher, Jeffrey M.; Dichmont, Catherine; Dunstan, Piers K.; Hayes, Keith R.; Hobday, Alistair J.; Pitcher, Roland; Plagányi, Éva E.; Punt, André E.; Savina-Rolland, Marie; Smith, Anthony D. M.; Smith, David C.

    2015-01-01

    Models provide useful insights into conservation and resource management issues and solutions. Their use to date has highlighted conditions under which no-take marine protected areas (MPAs) may help us to achieve the goals of ecosystem-based management by reducing pressures, and where they might fail to achieve desired goals. For example, static reserve designs are unlikely to achieve desired objectives when applied to mobile species or when compromised by climate-related ecosystem restructuring and range shifts. Modelling tools allow planners to explore a range of options, such as basing MPAs on the presence of dynamic oceanic features, and to evaluate the potential future impacts of alternative interventions compared with ‘no-action’ counterfactuals, under a range of environmental and development scenarios. The modelling environment allows the analyst to test if indicators and management strategies are robust to uncertainties in how the ecosystem (and the broader human–ecosystem combination) operates, including the direct and indirect ecological effects of protection. Moreover, modelling results can be presented at multiple spatial and temporal scales, and relative to ecological, economic and social objectives. This helps to reveal potential ‘surprises', such as regime shifts, trophic cascades and bottlenecks in human responses. Using illustrative examples, this paper briefly covers the history of the use of simulation models for evaluating MPA options, and discusses their utility and limitations for informing protected area management in the marine realm. PMID:26460131

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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 ...

  9. 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)

  10. 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 ...

  11. 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.

  12. 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.

  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. Sans Studies Insight Into Improving of Yield of Block Copolymer-Stabilized Gold Nanoparticles

    Science.gov (United States)

    Ray, Debes; Aswal, V. K.

    2010-01-01

    Triblock copolymer poly(ethylene oxide)-poly(propylene oxide)-poly(ethylene oxide) (PEO-PPO-PEO) are well known as dispersion stabilizers. It has also been recently found that they can act as reducing agents along with stabilizers and these two properties of block copolymers together have provided a single-step synthesis and stabilization of gold nanoparticles at ambient temperature. We have studied the synthesis of stable gold nanoparticle solutions using block copolymer P85. Gold nanoparticles are prepared from 1 wt% aqueous solution of P85 mixed with varying concentration of HAuCl4.3H2O salt in the range 0.001 to 0.1 wt%. Surface plasmon resonance (SPR) band in UV-visible absorption spectra confirm the formation of the gold nanoparticles and the maximum yield of the nanoparticles is found to be quite low at 0.005 wt% of the salt solution. Small-angle neutron scattering (SANS) measurements in these systems suggest that a very small fraction of the block copolymers (nanoparticles and remaining form their own micelles, which probably results in the low yield. This can be explained as on an average a high block copolymer-to-gold ion ratio r0 (22) is required for 1 wt% P85 in the reduction reaction to produce gold nanoparticles. Based on this understanding, a step-addition method is used to enhance the yield of gold nanoparticles by manifold where the gold salt is added in small steps to maintain higher value of r(>r0) and therefore continuous formation of nanoparticles.

  15. Mid-Pliocene warm-period deposits in the High Arctic yield insight into camel evolution.

    Science.gov (United States)

    Rybczynski, Natalia; Gosse, John C; Harington, C Richard; Wogelius, Roy A; Hidy, Alan J; Buckley, Mike

    2013-01-01

    The mid-Pliocene was a global warm period, preceding the onset of Quaternary glaciations. Here we use cosmogenic nuclide dating to show that a fossiliferous terrestrial deposit that includes subfossil trees and the northern-most evidence of Pliocene ice wedge casts in Canada's High Arctic (Ellesmere Island, Nunavut) was deposited during the mid-Pliocene warm period. The age estimates correspond to a general maximum in high latitude mean winter season insolation, consistent with the presence of a rich, boreal-type forest. Moreover, we report that these deposits have yielded the first evidence of a High Arctic camel, identified using collagen fingerprinting of a fragmentary fossil limb bone. Camels originated in North America and dispersed to Eurasia via the Bering Isthmus, an ephemeral land bridge linking Alaska and Russia. The results suggest that the evolutionary history of modern camels can be traced back to a lineage of giant camels that was well established in a forested Arctic.

  16. 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.

  17. 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.

  18. Simulating clinical trial visits yields patient insights into study design and recruitment

    Directory of Open Access Journals (Sweden)

    Lim SS

    2017-07-01

    discussing SLE, emphasis on transportation and child care help during the visits, and concerns related to financial matters; and they placed greater importance on time commitment, understanding of potential personal benefit, trust, and confidentiality of patient data as factors for participation. Using these results, we present recommendations to improve study procedures to increase retention, recruitment, and compliance for clinical trials.Conclusion: Insights from these two studies can be applied to the development and implementation of future clinical trials to improve patient recruitment, retention, compliance, and advocacy. Keywords: systemic lupus erythematosus, lupus nephritis, clinical trial simulation, patient recruitment, patient retention

  19. 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....

  20. 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)

  1. 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.

  2. Changes in apparent molar water volume and DKP solubility yield insights on the Hofmeister effect.

    Science.gov (United States)

    Payumo, Alexander Y; Huijon, R Michael; Mansfield, Deauna D; Belk, Laurel M; Bui, Annie K; Knight, Anne E; Eggers, Daryl K

    2011-12-15

    This study examines the properties of a 4 × 2 matrix of aqueous cations and anions at concentrations up to 8.0 M. The apparent molar water volume, as calculated by subtracting the mass and volume of the ions from the corresponding solution density, was found to exceed the molar volume of ice in many concentrated electrolyte solutions, underscoring the nonideal behavior of these systems. The solvent properties of water were also analyzed by measuring the solubility of diketopiperazine (DKP) in 2.000 M salt solutions prepared from the same ion combinations. Solution rankings for DKP solubility were found to parallel the Hofmeister series for both cations and anions, whereas molar water volume concurred with the cation series only. The results are discussed within the framework of a desolvation energy model that attributes solute-specific changes in equilibria to solute-dependent changes in the free energy of bulk water.

  3. Metagenomic analysis of microbial communities yields insight into impacts of nanoparticle design

    Science.gov (United States)

    Metch, Jacob W.; Burrows, Nathan D.; Murphy, Catherine J.; Pruden, Amy; Vikesland, Peter J.

    2018-01-01

    Next-generation DNA sequencing and metagenomic analysis provide powerful tools for the environmentally friendly design of nanoparticles. Herein we demonstrate this approach using a model community of environmental microbes (that is, wastewater-activated sludge) dosed with gold nanoparticles of varying surface coatings and morphologies. Metagenomic analysis was highly sensitive in detecting the microbial community response to gold nanospheres and nanorods with either cetyltrimethylammonium bromide or polyacrylic acid surface coatings. We observed that the gold-nanoparticle morphology imposes a stronger force in shaping the microbial community structure than does the surface coating. Trends were consistent in terms of the compositions of both taxonomic and functional genes, which include antibiotic resistance genes, metal resistance genes and gene-transfer elements associated with cell stress that are relevant to public health. Given that nanoparticle morphology remained constant, the potential influence of gold dissolution was minimal. Surface coating governed the nanoparticle partitioning between the bioparticulate and aqueous phases.

  4. Crystal structures of an intrinsically active cholera toxin mutant yield insight into the toxin activation mechanism.

    Science.gov (United States)

    O'Neal, Claire J; Amaya, Edward I; Jobling, Michael G; Holmes, Randall K; Hol, Wim G J

    2004-04-06

    Cholera toxin (CT) is a heterohexameric bacterial protein toxin belonging to a larger family of A/B ADP-ribosylating toxins. Each of these toxins undergoes limited proteolysis and/or disulfide bond reduction to form the enzymatically active toxic fragment. Nicking and reduction render both CT and the closely related heat-labile enterotoxin from Escherichia coli (LT) unstable in solution, thus far preventing a full structural understanding of the conformational changes resulting from toxin activation. We present the first structural glimpse of an active CT in structures from three crystal forms of a single-site A-subunit CT variant, Y30S, which requires no activational modifications for full activity. We also redetermined the structure of the wild-type, proenzyme CT from two crystal forms, both of which exhibit (i) better geometry and (ii) a different A2 "tail" conformation than the previously determined structure [Zhang et al. (1995) J. Mol. Biol. 251, 563-573]. Differences between wild-type CT and active CTY30S are observed in A-subunit loop regions that had been previously implicated in activation by analysis of the structure of an LT A-subunit R7K variant [van den Akker et al. (1995) Biochemistry 34, 10996-11004]. The 25-36 activation loop is disordered in CTY30S, while the 47-56 active site loop displays varying degrees of order in the three CTY30S structures, suggesting that disorder in the activation loop predisposes the active site loop to a greater degree of flexibility than that found in unactivated wild-type CT. On the basis of these six new views of the CT holotoxin, we propose a model for how the activational modifications experienced by wild-type CT are communicated to the active site.

  5. High Resolution Structure of Deinococcus Bacteriophytochrome Yields New Insights into Phytochrome Architecture and Evolution

    Energy Technology Data Exchange (ETDEWEB)

    Wagner, Jeremiah R.; Zhang, Junrui; Brunzelle, Joseph S.; Vierstra, Richard D.; Forest, Katrina T. (NWU); (UW)

    2010-03-08

    Phytochromes are red/far red light photochromic photoreceptors that direct many photosensory behaviors in the bacterial, fungal, and plant kingdoms. They consist of an N-terminal domain that covalently binds a bilin chromophore and a C-terminal region that transmits the light signal, often through a histidine kinase relay. Using x-ray crystallography, we recently solved the first three-dimensional structure of a phytochrome, using the chromophore-binding domain of Deinococcus radiodurans bacterial phytochrome assembled with its chromophore, biliverdin IX{alpha}. Now, by engineering the crystallization interface, we have achieved a significantly higher resolution model. This 1.45 {angstrom} resolution structure helps identify an extensive buried surface between crystal symmetry mates that may promote dimerization in vivo. It also reveals that upon ligation of the C3{sup 2} carbon of biliverdin to Cys{sup 24}, the chromophore A-ring assumes a chiral center at C2, thus becoming 2(R),3(E)-phytochromobilin, a chemistry more similar to that proposed for the attached chromophores of cyanobacterial and plant phytochromes than previously appreciated. The evolution of bacterial phytochromes to those found in cyanobacteria and higher plants must have involved greater fitness using more reduced bilins, such as phycocyanobilin, combined with a switch of the attachment site from a cysteine near the N terminus to one conserved within the cGMP phosphodiesterase/adenyl cyclase/FhlA domain. From analysis of site-directed mutants in the D. radiodurans phytochrome, we show that this bilin preference was partially driven by the change in binding site, which ultimately may have helped photosynthetic organisms optimize shade detection. Collectively, these three-dimensional structural results better clarify bilin/protein interactions and help explain how higher plant phytochromes evolved from prokaryotic progenitors.

  6. 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

  7. 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).

  8. 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.

  9. 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.

  10. Corvid caching : insights from a cognitive model

    NARCIS (Netherlands)

    van der Vaart, Elske; Verbrugge, Rineke; Hemelrijk, Charlotte K.

    Caching and recovery of food by corvids is well-studied, but some ambiguous results remain. To help clarify these, we built a computational cognitive model. It is inspired by similar models built for humans, and it assumes that memory strength depends on frequency and recency of use. We compared our

  11. Melatonin receptors: latest insights from mouse models

    Science.gov (United States)

    Tosini, Gianluca; Owino, Sharon; Guillame, Jean-Luc; Jockers, Ralf

    2014-01-01

    Summary Melatonin, the neuro-hormone synthesized during the night, has recently seen an unexpected extension of its functional implications towards type 2 diabetes development, visual functions, sleep disturbances and depression. Transgenic mouse models were instrumental for the establishment of the link between melatonin and these major human diseases. Most of the actions of melatonin are mediated by two types of G protein-coupled receptors, named MT1 and MT2, which are expressed in many different organs and tissues. Understanding the pharmacology and function of mouse MT1 and MT2 receptors, including MT1/MT2 heteromers, will be of crucial importance to evaluate the relevance of these mouse models for future therapeutic developments. This review will critically discuss these aspects, and give some perspectives including the generation of new mouse models. PMID:24903552

  12. Modeling Insights into the Lunar Exosphere

    Science.gov (United States)

    Hurley, D.; Feldman, P. D.; Retherford, K. D.; Cook, J.; Stern, S. A.

    2012-12-01

    In addition to Apollo data from the 1970s and ground-based observations, recent data from the Lyman Alpha Mapping Project (LAMP) onboard the Lunar Reconnaissance Orbiter (LRO) are revealing the structure and variability of the lunar exosphere. LAMP has detected helium in the lunar exosphere having many sources of variability. We use a Monte Carlo model to interpret variability in the observations of helium in the lunar exosphere from LAMP. Some of the variability stems from a time-varying source rate. Because the helium in the lunar exosphere predominately derives from the solar wind, we investigate the timescale of transport from release on the dayside to the nightside where it is observed. The model computes transport times for various assumptions about the energy distribution during the initial release and the effects of subsequent surface interactions on the ballistic transport. Owing to the changing geometry of the LRO orbit, spatial gradients also factor into the variability of the observations. We study the expected column density of helium as a function of latitude and longitude using surface temperatures measured by Diviner. The spatial distribution resulting from model runs is strongly influenced by the surface temperature and the assumed thermalization parameter. These dependencies can be used to extract information about the surface interactions. We compare model latitude and longitude dependences to LAMP and Apollo data. Finally, using upstream solar wind measurements and the position of LRO, we calculate the model time-varying helium exosphere of the Moon for comparison with LAMP data obtained in January, June, and July of 2012, including three passages of the Moon through Earth's magnetotail.

  13. 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.

  14. Mouse models of altered gonadotrophin action: insight into male reproductive disorders.

    Science.gov (United States)

    Jonas, Kim C; Oduwole, Olayiwola O; Peltoketo, Hellevi; Rulli, Susana B; Huhtaniemi, Ilpo T

    2014-10-01

    The advent of technologies to genetically manipulate the mouse genome has revolutionised research approaches, providing a unique platform to study the causality of reproductive disorders in vivo. With the relative ease of generating genetically modified (GM) mouse models, the last two decades have yielded multiple loss-of-function and gain-of-function mutation mouse models to explore the role of gonadotrophins and their receptors in reproductive pathologies. This work has provided key insights into the molecular mechanisms underlying reproductive disorders with altered gonadotrophin action, revealing the fundamental roles of these pituitary hormones and their receptors in the hypothalamic-pituitary-gonadal axis. This review will describe GM mouse models of gonadotrophins and their receptors with enhanced or diminished actions, specifically focusing on the male. We will discuss the mechanistic insights gained from these models into male reproductive disorders, and the relationship and understanding provided into male human reproductive disorders originating from altered gonadotrophin action. © 2014 Society for Reproduction and Fertility.

  15. Insight

    Science.gov (United States)

    Ramesh, Priya; Wei, Annan; Welter, Elisabeth; Bamps, Yvan; Stoll, Shelley; Bukach, Ashley; Sajatovic, Martha; Sahoo, Satya S

    2015-11-01

    Insight is a Semantic Web technology-based platform to support large-scale secondary analysis of healthcare data for neurology clinical research. Insight features the novel use of: (1) provenance metadata, which describes the history or origin of patient data, in clinical research analysis, and (2) support for patient cohort queries across multiple institutions conducting research in epilepsy, which is the one of the most common neurological disorders affecting 50 million persons worldwide. Insight is being developed as a healthcare informatics infrastructure to support a national network of eight epilepsy research centers across the U.S. funded by the U.S. Centers for Disease Control and Prevention (CDC). This paper describes the use of the World Wide Web Consortium (W3C) PROV recommendation for provenance metadata that allows researchers to create patient cohorts based on the provenance of the research studies. In addition, the paper describes the use of descriptive logic-based OWL2 epilepsy ontology for cohort queries with "expansion of query expression" using ontology reasoning. Finally, the evaluation results for the data integration and query performance are described using data from three research studies with 180 epilepsy patients. The experiment results demonstrate that Insight is a scalable approach to use Semantic provenance metadata for context-based data analysis in healthcare informatics.

  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

    traditional crop models, but likely at the cost of removing climate information. Our random forest models consistently discover the positive trend without removing any additional data. The application of random forests as a statistical crop model provides insight into understanding the impact of dust on yields in marginal food producing regions.

  17. Communicating Insights from Complex Simulation Models: A Gaming Approach.

    Science.gov (United States)

    Vennix, Jac A. M.; Geurts, Jac L. A.

    1987-01-01

    Describes design principles followed in developing an interactive microcomputer-based simulation to study financial and economic aspects of the Dutch social security system. The main goals are to improve participants' insights into the formal simulation model, and to improve policy development skills. Plans for future research are also discussed.…

  18. Hybrid discrete choice models: Gained insights versus increasing effort

    International Nuclear Information System (INIS)

    Mariel, Petr; Meyerhoff, Jürgen

    2016-01-01

    Hybrid choice models expand the standard models in discrete choice modelling by incorporating psychological factors as latent variables. They could therefore provide further insights into choice processes and underlying taste heterogeneity but the costs of estimating these models often significantly increase. This paper aims at comparing the results from a hybrid choice model and a classical random parameter logit. Point of departure for this analysis is whether researchers and practitioners should add hybrid choice models to their suite of models routinely estimated. Our comparison reveals, in line with the few prior studies, that hybrid models gain in efficiency by the inclusion of additional information. The use of one of the two proposed approaches, however, depends on the objective of the analysis. If disentangling preference heterogeneity is most important, hybrid model seems to be preferable. If the focus is on predictive power, a standard random parameter logit model might be the better choice. Finally, we give recommendations for an adequate use of hybrid choice models based on known principles of elementary scientific inference. - Highlights: • The paper compares performance of a Hybrid Choice Model (HCM) and a classical Random Parameter Logit (RPL) model. • The HCM indeed provides insights regarding preference heterogeneity not gained from the RPL. • The RPL has similar predictive power as the HCM in our data. • The costs of estimating HCM seem to be justified when learning more on taste heterogeneity is a major study objective.

  19. Hybrid discrete choice models: Gained insights versus increasing effort

    Energy Technology Data Exchange (ETDEWEB)

    Mariel, Petr, E-mail: petr.mariel@ehu.es [UPV/EHU, Economía Aplicada III, Avda. Lehendakari Aguire, 83, 48015 Bilbao (Spain); Meyerhoff, Jürgen [Institute for Landscape Architecture and Environmental Planning, Technical University of Berlin, D-10623 Berlin, Germany and The Kiel Institute for the World Economy, Duesternbrooker Weg 120, 24105 Kiel (Germany)

    2016-10-15

    Hybrid choice models expand the standard models in discrete choice modelling by incorporating psychological factors as latent variables. They could therefore provide further insights into choice processes and underlying taste heterogeneity but the costs of estimating these models often significantly increase. This paper aims at comparing the results from a hybrid choice model and a classical random parameter logit. Point of departure for this analysis is whether researchers and practitioners should add hybrid choice models to their suite of models routinely estimated. Our comparison reveals, in line with the few prior studies, that hybrid models gain in efficiency by the inclusion of additional information. The use of one of the two proposed approaches, however, depends on the objective of the analysis. If disentangling preference heterogeneity is most important, hybrid model seems to be preferable. If the focus is on predictive power, a standard random parameter logit model might be the better choice. Finally, we give recommendations for an adequate use of hybrid choice models based on known principles of elementary scientific inference. - Highlights: • The paper compares performance of a Hybrid Choice Model (HCM) and a classical Random Parameter Logit (RPL) model. • The HCM indeed provides insights regarding preference heterogeneity not gained from the RPL. • The RPL has similar predictive power as the HCM in our data. • The costs of estimating HCM seem to be justified when learning more on taste heterogeneity is a major study objective.

  20. The Turbulent Interstellar Medium: Insights and Questions from Numerical Models

    OpenAIRE

    Mac Low, Mordecai-Mark; de Avillez, Miguel A.; Korpi, Maarit J.

    2003-01-01

    "The purpose of numerical models is not numbers but insight." (Hamming) In the spirit of this adage, and of Don Cox's approach to scientific speaking, we discuss the questions that the latest generation of numerical models of the interstellar medium raise, at least for us. The energy source for the interstellar turbulence is still under discussion. We review the argument for supernovae dominating in star forming regions. Magnetorotational instability has been suggested as a way of coupling di...

  1. Dynamic statistical models of biological cognition: insights from communications theory

    Science.gov (United States)

    Wallace, Rodrick

    2014-10-01

    Maturana's cognitive perspective on the living state, Dretske's insight on how information theory constrains cognition, the Atlan/Cohen cognitive paradigm, and models of intelligence without representation, permit construction of a spectrum of dynamic necessary conditions statistical models of signal transduction, regulation, and metabolism at and across the many scales and levels of organisation of an organism and its context. Nonequilibrium critical phenomena analogous to physical phase transitions, driven by crosstalk, will be ubiquitous, representing not only signal switching, but the recruitment of underlying cognitive modules into tunable dynamic coalitions that address changing patterns of need and opportunity at all scales and levels of organisation. The models proposed here, while certainly providing much conceptual insight, should be most useful in the analysis of empirical data, much as are fitted regression equations.

  2. 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 ...

  3. 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.

  4. 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

  5. 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.

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

    Directory of Open Access Journals (Sweden)

    Th. Fischer

    2006-01-01

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

  7. 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 ...

  8. 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.

  9. Hybrid discrete choice models: Gained insights versus increasing effort.

    Science.gov (United States)

    Mariel, Petr; Meyerhoff, Jürgen

    2016-10-15

    Hybrid choice models expand the standard models in discrete choice modelling by incorporating psychological factors as latent variables. They could therefore provide further insights into choice processes and underlying taste heterogeneity but the costs of estimating these models often significantly increase. This paper aims at comparing the results from a hybrid choice model and a classical random parameter logit. Point of departure for this analysis is whether researchers and practitioners should add hybrid choice models to their suite of models routinely estimated. Our comparison reveals, in line with the few prior studies, that hybrid models gain in efficiency by the inclusion of additional information. The use of one of the two proposed approaches, however, depends on the objective of the analysis. If disentangling preference heterogeneity is most important, hybrid model seems to be preferable. If the focus is on predictive power, a standard random parameter logit model might be the better choice. Finally, we give recommendations for an adequate use of hybrid choice models based on known principles of elementary scientific inference. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. 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.

  11. 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 ...

  12. 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.

  13. Excellence in role modelling: insight and perspectives from the pros.

    Science.gov (United States)

    Wright, Scott M; Carrese, Joseph A

    2002-09-17

    Role modelling is an effective teaching method in medical education. We sought to better understand role modelling by examining the insights of respected physician role models. We conducted 30-minute in-depth interviews with 29 highly regarded role models at 2 large teaching hospitals. We coded the transcripts independently, and compared our coding for agreement. Content analysis identified several major categories of themes. The informants identified specific characteristics related to role modelling. Subcategories under the domain of personal qualities included interpersonal skills, a positive outlook, a commitment to excellence and growth, integrity and leadership. Under the domain of teaching, the subcategories were establishing rapport with learners, developing specific teaching philosophies and methods, and being committed to the growth of learners. Subjects thought there was some overlap between teaching and role modelling, but felt that the latter was more implicit and more encompassing. Being a strong clinician was regarded as necessary but not sufficient for being an exemplary physician role model. Perceived barriers to effective role modelling included being impatient and overly opinionated, being quiet, being overextended, and having difficulty remembering names and faces. Physician role models described role modeling consciousness, in that they specifically think about being role models when interacting with learners. Subjects believed that medical learners should emulate multiple role models. Highly regarded physician role models possess personal qualities, teaching abilities and exceptional clinical skills that outweigh their own barriers to serving as effective role models. Many of these positive attributes of role models represent behaviours that can be modified or skills that can be acquired.

  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. Mathematical modeling of microtubule dynamics: insights into physiology and disease.

    Science.gov (United States)

    Buxton, Gavin A; Siedlak, Sandra L; Perry, George; Smith, Mark A

    2010-12-01

    Computer models of microtubule dynamics have provided the basis for many of the theories on the cellular mechanics of the microtubules, their polymerization kinetics, and the diffusion of tubulin and tau. In the three-dimensional model presented here, we include the effects of tau concentration and the hydrolysis of GTP-tubulin to GDP-tubulin and observe the emergence of microtubule dynamic instability. This integrated approach simulates the essential physics of microtubule dynamics in a cellular environment. The model captures the structure of the microtubules as they undergo steady state dynamic instabilities in this simplified geometry, and also yields the average number, length, and cap size of the microtubules. The model achieves realistic geometries and simulates cellular structures found in degenerating neurons in disease states such as Alzheimer disease. Further, this model can be used to simulate microtubule changes following the addition of antimitotic drugs which have recently attracted attention as chemotherapeutic agents. Copyright © 2010 Elsevier Ltd. All rights reserved.

  16. Prediction, scenarios and insight: The uses of an end-to-end model

    Science.gov (United States)

    Steele, John H.

    2012-09-01

    A major function of ecosystem models is to provide extrapolations from observed data in terms of predictions or scenarios or insight. These models can be at various levels of taxonomic resolution such as total community production, abundance of functional groups, or species composition, depending on the data input as drivers. A 40-year dynamic simulation of end-to-end processes in the Georges Bank food web is used to illustrate the input/output relations and the insights gained at the three levels of food web aggregation. The focus is on the intermediate level and the longer term changes in three functional fish guilds - planktivores, benthivores and piscivores - in terms of three ecosystem-based metrics - nutrient input, relative productivity of plankton and benthos, and food intake by juvenile fish. These simulations can describe the long term constraints imposed on guild structure and productivity by energy fluxes over the 40 years but cannot explain concurrent switches in abundance of individual species within guilds. Comparing time series data for individual species with model output provides insights; but including the data in the model would confer only limited extra information. The advantages and limitations of the three levels of resolution of models in relation to ecosystem-based management are: The correlations between primary production and total yield of fish imply a “bottom-up” constraint on end-to-end energy flow through the food web that can provide predictions of such yields. Functionally defined metrics such as nutrient input, relative productivity of plankton and benthos and food intake by juvenile fish, represent bottom-up, mid-level and top-down forcing of the food web. Model scenarios using these metrics can demonstrate constraints on the productivity of these functionally defined guilds within the limits set by (1). Comparisons of guild simulations with time series of fish species provide insight into the switches in species dominance

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

    Directory of Open Access Journals (Sweden)

    Preksedis Marco Ndomba

    2008-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Preksedis M. Ndomba

    2008-01-01

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

  19. 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.

  20. Rooting for cassava: insights into photosynthesis and associated physiology as a route to improve yield potential.

    Science.gov (United States)

    De Souza, Amanda P; Massenburg, Lynnicia N; Jaiswal, Deepak; Cheng, Siyuan; Shekar, Rachel; Long, Stephen P

    2017-01-01

    Contents 50 I. 50 II. 52 III. 54 IV. 55 V. 57 VI. 57 VII. 59 60 References 61 SUMMARY: As a consequence of an increase in world population, food demand is expected to grow by up to 110% in the next 30-35 yr. The population of sub-Saharan Africa is projected to increase by > 120%. In this region, cassava (Manihot esculenta) is the second most important source of calories and contributes c. 30% of the daily calorie requirements per person. Despite its importance, the average yield of cassava in Africa has not increased significantly since 1961. An evaluation of modern cultivars of cassava showed that the interception efficiency (ɛ i ) of photosynthetically active radiation (PAR) and the efficiency of conversion of that intercepted PAR (ɛ c ) are major opportunities for genetic improvement of the yield potential. This review examines what is known of the physiological processes underlying productivity in cassava and seeks to provide some strategies and directions toward yield improvement through genetic alterations to physiology to increase ɛ i and ɛ c . Possible physiological limitations, as well as environmental constraints, are discussed. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

  1. Understanding N timing in corn yield and fertilizer N recovery: An insight from an isotopic labeled-N determination.

    Science.gov (United States)

    Maciel de Oliveira, Silas; Almeida, Rodrigo Estevam Munhoz de; Ciampitti, Ignacio A; Pierozan Junior, Clovis; Lago, Bruno Cocco; Trivelin, Paulo Cesar Ocheuze; Favarin, José Laércio

    2018-01-01

    Early fertilizer nitrogen (N) application on cover crops or their residues during the off-season is a practice adopted in Brazil subtropical conditions under no-tillage corn (Zea mays L.) systems. However, the effect of early N application on yield, plant N content, and N recovery efficiency (NRE) for corn is not yet well documented. Five fertilizer N timings in an oat-corn system were evaluated in two studies utilizing an isotopic-labeled N determination, 15N isotope. The N fertilization timings were: (i) oat tillering, (ii) 15 days before corn planting time, over the oat residues, (iii) at corn planting time, (iv) in-season at the three-leaf growth stage (V3), and (v) in-season split application at V3 and six-leaf (V6) growth stages. Based on the statistical analysis, the N fertilization timings were separated into three groups: 1) N-OATS, designated to N applied at oat; 2) N-PLANT, referred to pre-plant and planting N applications; and 3) N-CORN, designated to in-season corn N applications. Corn yield was not affected by the N fertilization timing. However, the N-CORN N fertilization timings enhanced NRE by 17% and 35% and final N recovery system (plant plus soil) by 16% and 24% all relative to N-OATS and N-PLANT groups, respectively. Overall, N-OATS resulted in the largest N derived from fertilizer (NDFF) amount in the deeper soil layer, in overall a delta of 10 kg N ha-1 relative to the rest of the groups. Notwithstanding corn yield was not affected, early N fertilization under subtropical conditions is not a viable option since NRE was diminished and the non-recovery N increased relative to the in-season N applications.

  2. Modeling Defibrillation of the Heart: Approaches and Insights

    Science.gov (United States)

    Trayanova, Natalia; Constantino, Jason; Ashihara, Takashi; Plank, Gernot

    2012-01-01

    Cardiac defibrillation, as accomplished nowadays by automatic, implantable devices (ICDs), constitutes the most important means of combating sudden cardiac death. While ICD therapy has proved to be efficient and reliable, defibrillation is a traumatic experience. Thus, research on defibrillation mechanisms, particularly aimed at lowering defibrillation voltage, remains an important topic. Advancing our understanding towards a full appreciation of the mechanisms by which a shock interacts with the heart is the most promising approach to achieve this goal. The aim of this paper is to assess the current state-of-the-art in ventricular defibrillation modeling, focusing on both numerical modeling approaches and major insights that have been obtained using defibrillation models, primarily those of realistic ventricular geometry. The paper showcases the contributions that modeling and simulation have made to our understanding of the defibrillation process. The review thus provides an example of biophysically based computational modeling of the heart (i.e., cardiac defibrillation) that has advanced the understanding of cardiac electrophysiological interaction at the organ level and has the potential to contribute to the betterment of the clinical practice of defibrillation. PMID:22273793

  3. 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 ...

  4. 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.

  5. 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

  6. [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.

  7. New Insights from Rodent Models of Fatty Liver Disease

    Science.gov (United States)

    2011-01-01

    Abstract Rodent models of fatty liver disease are essential research tools that provide a window into disease pathogenesis and a testing ground for prevention and treatment. Models come in many varieties involving dietary and genetic manipulations, and sometimes both. High-energy diets that induce obesity do not uniformly cause fatty liver disease; this has prompted close scrutiny of specific macronutrients and nutrient combinations to determine which have the greatest potential for hepatotoxicity. At the same time, diets that do not cause obesity or the metabolic syndrome but do cause severe steatohepatitis have been exploited to study factors important to progressive liver injury, including cell death, oxidative stress, and immune activation. Rodents with a genetic predisposition to overeating offer yet another model in which to explore the evolution of fatty liver disease. In some animals that overeat, steatohepatitis can develop even without resorting to a high-energy diet. Importantly, these models and others have been used to document that aerobic exercise can prevent or reduce fatty liver disease. This review focuses primarily on lessons learned about steatohepatitis from manipulations of diet and eating behavior. Numerous additional insights about hepatic lipid metabolism, which have been gained from genetically engineered mice, are also mentioned. Antioxid. Redox Signal. 15, 535–550. PMID:21126212

  8. Cholinergic modulation of cognitive processing: insights drawn from computational models

    Directory of Open Access Journals (Sweden)

    Ehren L Newman

    2012-06-01

    Full Text Available Acetylcholine plays an important role in cognitive function, as shown by pharmacological manipulations that impact working memory, attention, episodic memory and spatial memory function. Acetylcholine also shows striking modulatory influences on the cellular physiology of hippocampal and cortical neurons. Modeling of neural circuits provides a framework for understanding how the cognitive functions may arise from the influence of acetylcholine on neural and network dynamics. We review the influences of cholinergic manipulations on behavioral performance in working memory, attention, episodic memory and spatial memory tasks, the physiological effects of acetylcholine on neural and circuit dynamics, and the computational models that provide insight into the functional relationships between the physiology and behavior. Specifically, we discuss the important role of acetylcholine in governing mechanisms of active maintenance in working memory tasks and in regulating network dynamics important for effective processing of stimuli in attention and episodic memory tasks. We also propose that theta rhythm play a crucial role as an intermediary between the physiological influences of acetylcholine and behavior in episodic and spatial memory tasks. We conclude with a synthesis of the existing modeling work and highlight future directions that are likely to be rewarding given the existing state of the literature for both empiricists and modelers.

  9. 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.

  10. 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...

  11. Effective lactation yield

    NARCIS (Netherlands)

    Kok, Akke; Middelaar, van C.E.; Engel, B.; Knegsel, van A.T.M.; Hogeveen, H.; Kemp, B.; Boer, de I.J.M.

    2016-01-01

    To compare milk yields between cows or management strategies, lactations are traditionally standardized to 305-d yields. The 305-d yield, however, gives no insight into the combined effect of additional milk yield before calving, decreased milk yield after calving, and a possible shorter calving

  12. 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

  13. 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 ...

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. Genetic Aspects of Autism Spectrum Disorders: Insights from Animal Models

    Directory of Open Access Journals (Sweden)

    Swati eBanerjee

    2014-02-01

    Full Text Available Autism spectrum disorders (ASD are a complex neurodevelopmental disorder that display a triad of core behavioral deficits including restricted interests, often accompanied by repetitive behavior, deficits in language and communication, and an inability to engage in reciprocal social interactions. ASD is among the most heritable disorders but is not a simple disorder with a singular pathology and has a rather complex etiology. It is interesting to note that perturbations in synaptic growth, development and stability underlie a variety of neuropsychiatric disorders, including ASD, schizophrenia, epilepsy and intellectual disability. Biological characterization of an increasing repertoire of synaptic mutants in various model organisms indicates synaptic dysfunction as causal in the pathophysiology of ASD. Our understanding of the genes and genetic pathways that contribute towards the formation, stabilization and maintenance of functional synapses coupled with an in-depth phenotypic analysis of the cellular and behavioral characteristics is therefore essential to unraveling the pathogenesis of these disorders. In this review, we discuss the genetic aspects of ASD emphasizing on the well conserved set of genes and genetic pathways implicated in this disorder, many of which contribute to synapse assembly and maintenance across species. We also review how fundamental research using animal models is providing key insights into the various facets of human ASD.

  19. 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.

  20. 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.

  1. 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.

  2. 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...

  3. 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.

  4. 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.

  5. 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 ...

  6. 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...

  7. Opioid research in amphibians: an alternative pain model yielding insights on the evolution of opioid receptors

    Science.gov (United States)

    Stevens, Craig W.

    2011-01-01

    This review summarizes the work from our laboratory investigating mechanisms of opioid analgesia using the Northern grass frog, Rana pipiens. Over the last dozen years, we have accumulated data on the characterization of behavioral effects after opioid administration on radioligand binding by using opioid agonist and antagonist ligands in amphibian brain and spinal cord homogenates, and by cloning and sequencing opioid-like receptor cDNA from amphibian central nervous system (CNS) tissues. The relative analgesic potency of mu, delta, and kappa opioids is highly correlated between frogs and other mammals, including humans. Radioligand binding studies using selective opioid agonists show a similar selectivity profile in amphibians and mammals. In contrast, opioid antagonists that are highly selective for mammalian mu, delta, and kappa opioid receptors were not selective in behavioral and binding studies in amphibians. Three opioid-like receptor cDNAs were cloned and sequenced from amphibian brain tissues and are orthologs to mammalian mu, delta, and kappa opioid receptors. Bioinformatics analysis of the three types of opioid receptor cDNAs from all vertebrate species with full datasets gave a pattern of the molecular evolution of opioid receptors marked by the divergence of mu, delta, and kappa opioid receptor sequences during vertebrate evolution. This divergence in receptor amino acid sequence in later-evolved vertebrates underlies the hypothesis that opioid receptors are more type-selective in mammals than in nonmammalian vertebrates. The apparent order of receptor type evolution is kappa, then delta, and, most recently, the mu opioid receptor. Finally, novel bioinformatics analyses suggest that conserved extracellular receptor domains determine the type selectivity of vertebrate opioid receptors. PMID:15464208

  8. 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.

  9. Fracture development around deep underground excavations: Insights from FDEM modelling

    Directory of Open Access Journals (Sweden)

    Andrea Lisjak

    2014-12-01

    Full Text Available Over the past twenty years, there has been a growing interest in the development of numerical models that can realistically capture the progressive failure of rock masses. In particular, the investigation of damage development around underground excavations represents a key issue in several rock engineering applications, including tunnelling, mining, drilling, hydroelectric power generation, and the deep geological disposal of nuclear waste. The goal of this paper is to show the effectiveness of a hybrid finite-discrete element method (FDEM code to simulate the fracturing mechanisms associated with the excavation of underground openings in brittle rock formations. A brief review of the current state-of-the-art modelling approaches is initially provided, including the description of selecting continuum- and discontinuum-based techniques. Then, the influence of a number of factors, including mechanical and in situ stress anisotropy, as well as excavation geometry, on the simulated damage is analysed for three different geomechanical scenarios. Firstly, the fracture nucleation and growth process under isotropic rock mass conditions is simulated for a circular shaft. Secondly, the influence of mechanical anisotropy on the development of an excavation damaged zone (EDZ around a tunnel excavated in a layered rock formation is considered. Finally, the interaction mechanisms between two large caverns of an underground hydroelectric power station are investigated, with particular emphasis on the rock mass response sensitivity to the pillar width and excavation sequence. Overall, the numerical results indicate that FDEM simulations can provide unique geomechanical insights in cases where an explicit consideration of fracture and fragmentation processes is of paramount importance.

  10. 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.

  11. 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...

  12. 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.

  13. 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.

  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. 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....

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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 ...

  5. 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 ...

  6. 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

  7. 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...

  8. 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 ...

  9. 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,

  10. 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

  11. 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.

  12. Optogenetic versus Electrical Stimulation of Human Cardiomyocytes: Modeling Insights

    Science.gov (United States)

    Williams, John C.; Entcheva, Emilia

    2015-01-01

    Optogenetics provides an alternative to electrical stimulation to manipulate membrane voltage, and trigger or modify action potentials (APs) in excitable cells. We compare biophysically and energetically the cellular responses to direct electrical current injection versus optical stimulation mediated by genetically expressed light-sensitive ion channels, e.g., Channelrhodopsin-2 (ChR2). Using a computational model of ChR2(H134R mutant), we show that both stimulation modalities produce similar-in-morphology APs in human cardiomyocytes, and that electrical and optical excitability vary with cell type in a similar fashion. However, whereas the strength-duration curves for electrical excitation in ventricular and atrial cardiomyocytes closely follow the theoretical exponential relationship for an equivalent RC circuit, the respective optical strength-duration curves significantly deviate, exhibiting higher nonlinearity. We trace the origin of this deviation to the waveform of the excitatory current—a nonrectangular self-terminating inward current produced in optical stimulation due to ChR2 kinetics and voltage-dependent rectification. Using a unifying charge measure to compare energy needed for electrical and optical stimulation, we reveal that direct electrical current injection (rectangular pulse) is more efficient at short pulses, whereas voltage-mediated negative feedback leads to self-termination of ChR2 current and renders optical stimulation more efficient for long low-intensity pulses. This applies to cardiomyocytes but not to neuronal cells (with much shorter APs). Furthermore, we demonstrate the cell-specific use of ChR2 current as a unique modulator of intrinsic activity, allowing for optical control of AP duration in atrial and, to a lesser degree, in ventricular myocytes. For self-oscillatory cells, such as Purkinje, constant light at extremely low irradiance can be used for fine control of oscillatory frequency, whereas constant electrical stimulation

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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.

  18. Population genomic analysis of ancient and modern genomes yields new insights into the genetic ancestry of the Tyrolean Iceman and the genetic structure of Europe.

    Directory of Open Access Journals (Sweden)

    Martin Sikora

    2014-05-01

    Full Text Available Genome sequencing of the 5,300-year-old mummy of the Tyrolean Iceman, found in 1991 on a glacier near the border of Italy and Austria, has yielded new insights into his origin and relationship to modern European populations. A key finding of that study was an apparent recent common ancestry with individuals from Sardinia, based largely on the Y chromosome haplogroup and common autosomal SNP variation. Here, we compiled and analyzed genomic datasets from both modern and ancient Europeans, including genome sequence data from over 400 Sardinians and two ancient Thracians from Bulgaria, to investigate this result in greater detail and determine its implications for the genetic structure of Neolithic Europe. Using whole-genome sequencing data, we confirm that the Iceman is, indeed, most closely related to Sardinians. Furthermore, we show that this relationship extends to other individuals from cultural contexts associated with the spread of agriculture during the Neolithic transition, in contrast to individuals from a hunter-gatherer context. We hypothesize that this genetic affinity of ancient samples from different parts of Europe with Sardinians represents a common genetic component that was geographically widespread across Europe during the Neolithic, likely related to migrations and population expansions associated with the spread of agriculture.

  19. 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.

  20. 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.

  1. 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.

  2. Insight, psychopathology, explanatory models and outcome of schizophrenia in India: a prospective 5-year cohort study

    Directory of Open Access Journals (Sweden)

    Johnson Shanthi

    2012-09-01

    Full Text Available Abstract Background The sole focus of models of insight on bio-medical perspectives to the complete exclusion of local, non-medical and cultural constructs mandates review. This study attempted to investigate the impact of insight, psychopathology, explanatory models of illness on outcome of first episode schizophrenia. Method Patients diagnosed to have DSM IV schizophrenia (n = 131 were assessed prospectively for insight, psychopathology, explanatory models of illness at baseline, 6, 12 and 60 months using standard instruments. Multiple linear and logistic regression and generalized estimating equations (GEE were employed to assess predictors of outcome. Results We could follow up 95 (72.5% patients. Sixty-five of these patients (68.4% achieved remission. There was a negative relationship between psychosis rating and insight scores. Urban residence, fluctuating course of the initial illness, and improvement in global functioning at 6 months and lower psychosis rating at 12 months were significantly related to remission at 5 years. Insight scores, number of non-medical explanatory models and individual explanatory models held during the later course of the illness were significantly associated with outcome. Analysis of longitudinal data using GEE showed that women, rural residence, insight scores and number of non-medical explanatory models of illness held were significantly associated with BPRS scores during the study period. Conclusions Insight, the disease model and the number of non-medical model positively correlated with improvement in psychosis arguing for a complex interaction between the culture, context and illness variables. These finding argue that insight and explanatory models are secondary to psychopathology, course and outcome of the illness. The awareness of mental illness is a narrative act in which people make personal sense of the many challenges they face. The course and outcome of the illness, cultural context

  3. 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.

  4. Comparative Study of Lectin Domains in Model Species: New Insights into Evolutionary Dynamics

    Directory of Open Access Journals (Sweden)

    Sofie Van Holle

    2017-05-01

    Full Text Available Lectins are present throughout the plant kingdom and are reported to be involved in diverse biological processes. In this study, we provide a comparative analysis of the lectin families from model species in a phylogenetic framework. The analysis focuses on the different plant lectin domains identified in five representative core angiosperm genomes (Arabidopsis thaliana, Glycine max, Cucumis sativus, Oryza sativa ssp. japonica and Oryza sativa ssp. indica. The genomes were screened for genes encoding lectin domains using a combination of Basic Local Alignment Search Tool (BLAST, hidden Markov models, and InterProScan analysis. Additionally, phylogenetic relationships were investigated by constructing maximum likelihood phylogenetic trees. The results demonstrate that the majority of the lectin families are present in each of the species under study. Domain organization analysis showed that most identified proteins are multi-domain proteins, owing to the modular rearrangement of protein domains during evolution. Most of these multi-domain proteins are widespread, while others display a lineage-specific distribution. Furthermore, the phylogenetic analyses reveal that some lectin families evolved to be similar to the phylogeny of the plant species, while others share a closer evolutionary history based on the corresponding protein domain architecture. Our results yield insights into the evolutionary relationships and functional divergence of plant lectins.

  5. 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

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. 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

  12. Physically-insightful equivalent circuit models for electromagnetic periodic structures

    Science.gov (United States)

    Mesa, F.; Rodríguez-Berral, R.; Medina, F.

    2018-02-01

    In this presentation it will be discussed how to obtain analytical or quasi-analytical equivalent circuits to deal with periodic structures such as frequency selective surfaces and/or metasurfaces. Both the topology and the values of the involved elements of these circuits are obtained from a basic rationale to solve the corresponding integral equation. This procedure, besides providing a very efficient analysis/design tool, allows for a good physical insight into the operating mechanisms of the structure in contrast with the almost blind numerical scheme of commercial simulators.

  13. 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.

  14. Insights: Simple Models for Teaching Equilibrium and Le Chatelier's Principle.

    Science.gov (United States)

    Russell, Joan M.

    1988-01-01

    Presents three models that have been effective for teaching chemical equilibrium and Le Chatelier's principle: (1) the liquid transfer model, (2) the fish model, and (3) the teeter-totter model. Explains each model and its relation to Le Chatelier's principle. (MVL)

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. Climate change induced transformations of agricultural systems: insights from a global model

    International Nuclear Information System (INIS)

    Leclère, D; Havlík, P; Mosnier, A; Walsh, B; Valin, H; Khabarov, N; Obersteiner, M; Fuss, S; Schmid, E; Herrero, M

    2014-01-01

    Climate change might impact crop yields considerably and anticipated transformations of agricultural systems are needed in the coming decades to sustain affordable food provision. However, decision-making on transformational shifts in agricultural systems is plagued by uncertainties concerning the nature and geography of climate change, its impacts, and adequate responses. Locking agricultural systems into inadequate transformations costly to adjust is a significant risk and this acts as an incentive to delay action. It is crucial to gain insight into how much transformation is required from agricultural systems, how robust such strategies are, and how we can defuse the associated challenge for decision-making. While implementing a definition related to large changes in resource use into a global impact assessment modelling framework, we find transformational adaptations to be required of agricultural systems in most regions by 2050s in order to cope with climate change. However, these transformations widely differ across climate change scenarios: uncertainties in large-scale development of irrigation span in all continents from 2030s on, and affect two-thirds of regions by 2050s. Meanwhile, significant but uncertain reduction of major agricultural areas affects the Northern Hemisphere’s temperate latitudes, while increases to non-agricultural zones could be large but uncertain in one-third of regions. To help reducing the associated challenge for decision-making, we propose a methodology exploring which, when, where and why transformations could be required and uncertain, by means of scenario analysis. (letter)

  2. 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.

  3. On the Modelling of Biological Patterns with Mechanochemical Models: Insights from Analysis and Computation

    KAUST Repository

    Moreo, P.

    2009-11-14

    The diversity of biological form is generated by a relatively small number of underlying mechanisms. Consequently, mathematical and computational modelling can, and does, provide insight into how cellular level interactions ultimately give rise to higher level structure. Given cells respond to mechanical stimuli, it is therefore important to consider the effects of these responses within biological self-organisation models. Here, we consider the self-organisation properties of a mechanochemical model previously developed by three of the authors in Acta Biomater. 4, 613-621 (2008), which is capable of reproducing the behaviour of a population of cells cultured on an elastic substrate in response to a variety of stimuli. In particular, we examine the conditions under which stable spatial patterns can emerge with this model, focusing on the influence of mechanical stimuli and the interplay of non-local phenomena. To this end, we have performed a linear stability analysis and numerical simulations based on a mixed finite element formulation, which have allowed us to study the dynamical behaviour of the system in terms of the qualitative shape of the dispersion relation. We show that the consideration of mechanotaxis, namely changes in migration speeds and directions in response to mechanical stimuli alters the conditions for pattern formation in a singular manner. Furthermore without non-local effects, responses to mechanical stimuli are observed to result in dispersion relations with positive growth rates at arbitrarily large wavenumbers, in turn yielding heterogeneity at the cellular level in model predictions. This highlights the sensitivity and necessity of non-local effects in mechanically influenced biological pattern formation models and the ultimate failure of the continuum approximation in their absence. © 2009 Society for Mathematical Biology.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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).

  9. 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.

  10. 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...

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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)

  17. Insight, self-stigma and psychosocial outcomes in Schizophrenia: a structural equation modelling approach.

    Science.gov (United States)

    Lien, Y-J; Chang, H-A; Kao, Y-C; Tzeng, N-S; Lu, C-W; Loh, C-H

    2018-04-01

    Poor insight is prevalent in patients with schizophrenia and has been associated with acute illness severity, medication non-adherence and poor treatment outcomes. Paradoxically, high insight has been associated with various undesirable outcomes, including low self-esteem, depression and low subjective quality of life (QoL) in patients with schizophrenia. Despite the growing body of studies conducted in Western countries supporting the pernicious effects of improved insight in psychosis, which bases on the level of self-stigma, the effects are unclear in non-Western societies. The current study examined the role of self-stigma in the relationship between insight and psychosocial outcomes in a Chinese population. A total of 170 outpatients with schizophrenia spectrum disorders were recruited from two general university hospitals. Sociodemographic data and clinical variables were recorded and self-report scales were employed to measure self-stigma, depression, insight, self-esteem and subjective QoL. Structural equation modelling (SEM) was used to analyse the cross-sectional data. High levels of self-stigma were reported by 39% of the participants (n = 67). The influences of insight, self-stigma, self-esteem and depression on subjective QoL were confirmed by the SEM results. Our model with the closest fit to the data (χ 2 = 33.28; df = 20; p = 0.03; χ 2/df = 1.66; CFI = 0.98; TLI = 0.97; RMSEA = 0.06) demonstrated that self-stigma might fully mediate the association of insight with low self-esteem, depression and poor subjective QoL. High insight into illness contributed to self-stigma, which caused low self-esteem and depression and, consequently, low QoL. Notably, insight did not directly affect self-esteem, depression or QoL. Furthermore, the association of insight with poor psychosocial outcomes was not moderated by self-stigma. Our findings support the mediating model of insight relevant to the poor psychosocial outcomes of individuals diagnosed with

  18. 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.

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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.

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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...

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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

    Models predict that the climate of California will become hotter, drier and more variable under future climate change scenarios. This will lead to both increased irrigation demand and reduced irrigation water availability. In addition, it is predicted that most common Californian crops will suffer a concomitant decline in productivity. To remain productive and economically viable, future agricultural systems will need to have greater water use efficiency, tolerance of high temperatures, and tolerance of more erratic temperature and rainfall patterns. Canola (Brassica napus) is the third most important oilseed globally, supporting large and well-established agricultural industries in Canada, Europe and Australia. It is an agronomically useful and economically valuable crop, with multiple end markets, that can be grown in California as a dryland winter rotation with little to no irrigation demand. This gives canola great potential as a new crop for Californian farmers both now and as the climate changes. Given practical and financial limitations it is not always possible to immediately or widely evaluate a crop in a new region. Crop production models are therefore valuable tools for assessing the potential of new crops, better targeting further field research, and refining research questions. APSIM is a modular modeling framework developed by the Agricultural Production Systems Research Unit in Australia, it combines biophysical and management modules to simulate cropping systems. This study was undertaken to examine the yield potential of Australian canola varieties having different water requirements and maturity classes in California using APSIM. The objective of the work was to identify the agricultural regions of California most ideally suited to the production of Australian cultivars of canola and to simulate the production of canola in these regions to estimate yield-potential. This will establish whether the introduction and in-field evaluation of better

  17. Quantitative insight into models of Hedgehog signal transduction.

    Science.gov (United States)

    Farzan, Shohreh F; Ogden, Stacey K; Robbins, David J

    2010-01-01

    The Hedgehog (Hh) signaling pathway is an essential regulator of embryonic development and a key factor in carcinogenesis.(1,2) Hh, a secreted morphogen, activates intracellular signaling events via downstream effector proteins, which translate the signal to regulate target gene transcription.(3,4) In a recent publication, we quantitatively compared two commonly accepted models of Hh signal transduction.(5) Each model requires a different ratio of signaling components to be feasible. Thus, we hypothesized that knowing the steady-state ratio of core signaling components might allow us to distinguish between models. We reported vast differences in the molar concentrations of endogenous effectors of Hh signaling, with Smo present in limiting concentrations.(5) This extra view summarizes the implications of this endogenous ratio in relation to current models of Hh signaling and places our results in the context of recent work describing the involvement of guanine nucleotide binding protein Galphai and Cos2 motility.

  18. Uterine disorders and pregnancy complications: insights from mouse models

    OpenAIRE

    Lim, Hyunjung Jade; Wang, Haibin

    2010-01-01

    Much of our knowledge of human uterine physiology and pathology has been extrapolated from the study of diverse animal models, as there is no ideal system for studying human uterine biology in vitro. Although it remains debatable whether mouse models are the most suitable system for investigating human uterine function(s), gene-manipulated mice are considered by many the most useful tool for mechanistic analysis, and numerous studies have identified many similarities in female reproduction be...

  19. OBESITY AND CRITICAL ILLNESS: INSIGHTS FROM ANIMAL MODELS.

    Science.gov (United States)

    Mittwede, Peter N; Clemmer, John S; Bergin, Patrick F; Xiang, Lusha

    2016-04-01

    Critical illness is a major cause of morbidity and mortality around the world. While obesity is often detrimental in the context of trauma, it is paradoxically associated with improved outcomes in some septic patients. The reasons for these disparate outcomes are not well understood. A number of animal models have been used to study the obese response to various forms of critical illness. Just as there have been many animal models that have attempted to mimic clinical conditions, there are many clinical scenarios that can occur in the highly heterogeneous critically ill patient population that occupies hospitals and intensive care units. This poses a formidable challenge for clinicians and researchers attempting to understand the mechanisms of disease and develop appropriate therapies and treatment algorithms for specific subsets of patients, including the obese. The development of new, and the modification of existing animal models, is important in order to bring effective treatments to a wide range of patients. Not only do experimental variables need to be matched as closely as possible to clinical scenarios, but animal models with pre-existing comorbid conditions need to be studied. This review briefly summarizes animal models of hemorrhage, blunt trauma, traumatic brain injury, and sepsis. It also discusses what has been learned through the use of obese models to study the pathophysiology of critical illness in light of what has been demonstrated in the clinical literature.

  20. 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

  1. Hydraulic root water uptake models: old concerns and new insights

    Science.gov (United States)

    Couvreur, V.; Carminati, A.; Rothfuss, Y.; Meunier, F.; Vanderborght, J.; Javaux, M.

    2014-12-01

    Root water uptake (RWU) affects underground water dynamics, with consequences on plant water availability and groundwater recharge. Even though hydrological and climate models are sensitive to RWU parameters, no consensus exists on the modelling of this process. Back in the 1940ies, Van Den Honert's catenary approach was the first to investigate the use of connected hydraulic resistances to describe water flow in whole plants. However concerns such as the necessary computing when architectures get complex made this approach premature. Now that computing power increased dramatically, hydraulic RWU models are gaining popularity, notably because they naturally produce observed processes like compensatory RWU and hydraulic redistribution. Yet major concerns remain. Some are more fundamental: according to hydraulic principles, plant water potential should equilibrate with soil water potential when the plant does not transpire, which is not a general observation when using current definitions of bulk or average soil water potential. Other concerns regard the validation process: water uptake distribution is not directly measurable, which makes it hard to demonstrate whether or not hydraulic models are more accurate than other models. Eventually parameterization concerns exist: root hydraulic properties are not easily measurable, and would even fluctuate on an hourly basis due to processes like aquaporin gating. While offering opportunities to validate hydraulic RWU models, newly developed observation techniques also make us realize the increasing complexity of processes involved in soil-plant hydrodynamics, such as the change of rhizosphere hydraulic properties with soil drying. Surprisingly, once implemented into hydraulic models, these processes do not necessarily translate into more complex emerging behavior at plant scale, and might justify the use of simplified representations of the soil-plant hydraulic system.

  2. Obsessive-compulsive disorder: Insights from animal models.

    Science.gov (United States)

    Szechtman, Henry; Ahmari, Susanne E; Beninger, Richard J; Eilam, David; Harvey, Brian H; Edemann-Callesen, Henriette; Winter, Christine

    2017-05-01

    Research with animal models of obsessive-compulsive disorder (OCD) shows the following: (1) Optogenetic studies in mice provide evidence for a plausible cause-effect relation between increased activity in cortico-basal ganglia-thalamo-cortical (CBGTC) circuits and OCD by demonstrating the induction of compulsive behavior with the experimental manipulation of the CBGTC circuit. (2) Parallel use of several animal models is a fruitful paradigm to examine the mechanisms of treatment effects of deep brain stimulation in distinct OCD endophenotypes. (3) Features of spontaneous behavior in deer mice constitute a rich platform to investigate the neurobiology of OCD, social ramifications of a compulsive phenotype, and test novel drugs. (4) Studies in animal models for psychiatric disorders comorbid with OCD suggest comorbidity may involve shared neural circuits controlling expression of compulsive behavior. (5) Analysis of compulsive behavior into its constitutive components provides evidence from an animal model for a motivational perspective on OCD. (6) Methods of behavioral analysis in an animal model translate to dissection of compulsive rituals in OCD patients, leading to diagnostic tests. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Quantitative modeling of chronic myeloid leukemia: insights from radiobiology

    Science.gov (United States)

    Radivoyevitch, Tomas; Hlatky, Lynn; Landaw, Julian

    2012-01-01

    Mathematical models of chronic myeloid leukemia (CML) cell population dynamics are being developed to improve CML understanding and treatment. We review such models in light of relevant findings from radiobiology, emphasizing 3 points. First, the CML models almost all assert that the latency time, from CML initiation to diagnosis, is at most ∼ 10 years. Meanwhile, current radiobiologic estimates, based on Japanese atomic bomb survivor data, indicate a substantially higher maximum, suggesting longer-term relapses and extra resistance mutations. Second, different CML models assume different numbers, between 400 and 106, of normal HSCs. Radiobiologic estimates favor values > 106 for the number of normal cells (often assumed to be the HSCs) that are at risk for a CML-initiating BCR-ABL translocation. Moreover, there is some evidence for an HSC dead-band hypothesis, consistent with HSC numbers being very different across different healthy adults. Third, radiobiologists have found that sporadic (background, age-driven) chromosome translocation incidence increases with age during adulthood. BCR-ABL translocation incidence increasing with age would provide a hitherto underanalyzed contribution to observed background adult-onset CML incidence acceleration with age, and would cast some doubt on stage-number inferences from multistage carcinogenesis models in general. PMID:22353999

  4. 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.

  5. 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.

  6. 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 ...

  7. 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.

  8. Reactor pressure vessel embrittlement: Insights from neural network modelling

    Science.gov (United States)

    Mathew, J.; Parfitt, D.; Wilford, K.; Riddle, N.; Alamaniotis, M.; Chroneos, A.; Fitzpatrick, M. E.

    2018-04-01

    Irradiation embrittlement of steel pressure vessels is an important consideration for the operation of current and future light water nuclear reactors. In this study we employ an ensemble of artificial neural networks in order to provide predictions of the embrittlement using two literature datasets, one based on US surveillance data and the second from the IVAR experiment. We use these networks to examine trends with input variables and to assess various literature models including compositional effects and the role of flux and temperature. Overall, the networks agree with the existing literature models and we comment on their more general use in predicting irradiation embrittlement.

  9. 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.

  10. Managing Dog Waste: Campaign Insights from the Health Belief Model

    Science.gov (United States)

    Typhina, Eli; Yan, Changmin

    2014-01-01

    Aiming to help municipalities develop effective education and outreach campaigns to reduce stormwater pollutants, such as pet waste, this study applied the Health Belief Model (HBM) to identify perceptions of dog waste and corresponding collection behaviors from dog owners living in a small U.S. city. Results of 455 online survey responses…

  11. Insights on non-perturbative aspects of TMDs from models

    Energy Technology Data Exchange (ETDEWEB)

    H. Avakian, A. Efremov, P. Schweitzer, O. Teryaev, F. Yuan, P. Zavada

    2009-12-01

    Transverse momentum dependent parton distribution functions are a key ingredient in the description of spin and azimuthal asymmetries in deep-inelastic scattering processes. Recent results from non-perturbative calculations in effective approaches are reviewed, with focus on relations among different parton distribution functions in QCD and models.

  12. Application of hydropedological insights in hydrological modelling of ...

    African Journals Online (AJOL)

    In this paper the output of a digital soil mapping exercise was used as the soil input into a distributed hydrological model (ACRU) for a test site within the Stevenson-Hamilton Research Supersite, Kruger National Park (South ... The outputs evaluated included both streamflow and soil water content at selected soil profiles.

  13. Improving Perovskite Solar Cells: Insights From a Validated Device Model

    NARCIS (Netherlands)

    Sherkar, Tejas S.; Momblona, Cristina; Gil-Escrig, Lidon; Bolink, Henk J.; Koster, L. Jan Anton

    2017-01-01

    To improve the efficiency of existing perovskite solar cells (PSCs), a detailed understanding of the underlying device physics during their operation is essential. Here, a device model has been developed and validated that describes the operation of PSCs and quantitatively explains the role of

  14. 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.

  15. A logical model provides insights into T cell receptor signaling.

    Directory of Open Access Journals (Sweden)

    Julio Saez-Rodriguez

    2007-08-01

    Full Text Available Cellular decisions are determined by complex molecular interaction networks. Large-scale signaling networks are currently being reconstructed, but the kinetic parameters and quantitative data that would allow for dynamic modeling are still scarce. Therefore, computational studies based upon the structure of these networks are of great interest. Here, a methodology relying on a logical formalism is applied to the functional analysis of the complex signaling network governing the activation of T cells via the T cell receptor, the CD4/CD8 co-receptors, and the accessory signaling receptor CD28. Our large-scale Boolean model, which comprises 94 nodes and 123 interactions and is based upon well-established qualitative knowledge from primary T cells, reveals important structural features (e.g., feedback loops and network-wide dependencies and recapitulates the global behavior of this network for an array of published data on T cell activation in wild-type and knock-out conditions. More importantly, the model predicted unexpected signaling events after antibody-mediated perturbation of CD28 and after genetic knockout of the kinase Fyn that were subsequently experimentally validated. Finally, we show that the logical model reveals key elements and potential failure modes in network functioning and provides candidates for missing links. In summary, our large-scale logical model for T cell activation proved to be a promising in silico tool, and it inspires immunologists to ask new questions. We think that it holds valuable potential in foreseeing the effects of drugs and network modifications.

  16. CERES-Maize model-based simulation of climate change impacts on maize yields and potential adaptive measures in Heilongjiang Province, China.

    Science.gov (United States)

    Lin, Yumei; Wu, Wenxiang; Ge, Quansheng

    2015-11-01

    Climate change would cause negative impacts on future agricultural production and food security. Adaptive measures should be taken to mitigate the adverse effects. The objectives of this study were to simulate the potential effects of climate change on maize yields in Heilongjiang Province and to evaluate two selected typical household-level autonomous adaptive measures (cultivar changes and planting time adjustments) for mitigating the risks of climate change based on the CERES-Maize model. The results showed that flowering duration and maturity duration of maize would be shortened in the future climate and thus maize yield would reduce by 11-46% during 2011-2099 relative to 1981-2010. Increased CO2 concentration would not benefit maize production significantly. However, substituting local cultivars with later-maturing ones and delaying the planting date could increase yields as the climate changes. The results provide insight regarding the likely impacts of climate change on maize yields and the efficacy of selected adaptive measures by presenting evidence-based implications and mitigation strategies for the potential negative impacts of future climate change. © 2014 Society of Chemical Industry.

  17. Treacher Collins syndrome: New insights from animal models.

    Science.gov (United States)

    Tse, William Ka Fai

    2016-12-01

    Treacher Collins syndrome (TCS, OMIM: 154500), an autosomal-dominant craniofacial developmental syndrome that occurs in 1 out of every 50,000 live births, is characterized by craniofacial malformation. Mutations in TCOF1, POLR1C, or POLR1D have been identified in affected individuals. In addition to established mouse models, zebrafish models have recently emerged as an valuable method to study facial disease. In this report, we summarized the two updated articles working on the pathogenesis of the newly identified polr1c and polr1d TCS mutations (Lau et al., 2016; Noack Watt et al., 2016) and discussed the possibility of using the anti-oxidants to prevent or rescue the TCS facial phenotype (Sakai et al., 2016). Taken together, this article provides an update on the disease from basic information to pathogenesis, and further summarizes the suggested therapies from recent laboratory research. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Applications of the SWAT Model Special Section: Overview and Insights.

    Science.gov (United States)

    Gassman, Philip W; Sadeghi, Ali M; Srinivasan, Raghavan

    2014-01-01

    The Soil and Water Assessment Tool (SWAT) model has emerged as one of the most widely used water quality watershed- and river basin-scale models worldwide, applied extensively for a broad range of hydrologic and/or environmental problems. The international use of SWAT can be attributed to its flexibility in addressing water resource problems, extensive networking via dozens of training workshops and the several international conferences that have been held during the past decade, comprehensive online documentation and supporting software, and an open source code that can be adapted by model users for specific application needs. The catalyst for this special collection of papers was the 2011 International SWAT Conference & Workshops held in Toledo, Spain, which featured over 160 scientific presentations representing SWAT applications in 37 countries. This special collection presents 22 specific SWAT-related studies, most of which were presented at the 2011 SWAT Conference; it represents SWAT applications on five different continents, with the majority of studies being conducted in Europe and North America. The papers cover a variety of topics, including hydrologic testing at a wide range of watershed scales, transport of pollutants in northern European lowland watersheds, data input and routing method effects on sediment transport, development and testing of potential new model algorithms, and description and testing of supporting software. In this introduction to the special section, we provide a synthesis of these studies within four main categories: (i) hydrologic foundations, (ii) sediment transport and routing analyses, (iii) nutrient and pesticide transport, and (iv) scenario analyses. We conclude with a brief summary of key SWAT research and development needs. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  19. Rock Burst Mechanics: Insight from Physical and Mathematical Modelling

    Directory of Open Access Journals (Sweden)

    J. Vacek

    2008-01-01

    Full Text Available Rock burst processes in mines are studied by many groups active in the field of geomechanics. Physical and mathematical modelling can be used to better understand the phenomena and mechanisms involved in the bursts. In the present paper we describe both physical and mathematical models of a rock burst occurring in a gallery of a coal mine.For rock bursts (also called bumps to occur, the rock has to possess certain particular rock burst properties leading to accumulation of energy and the potential to release this energy. Such materials may be brittle, or the rock burst may arise at the interfacial zones of two parts of the rock, which have principally different material properties (e.g. in the Poíbram uranium mines.The solution is based on experimental and mathematical modelling. These two methods have to allow the problem to be studied on the basis of three presumptions:· the solution must be time dependent,· the solution must allow the creation of cracks in the rock mass,· the solution must allow an extrusion of rock into an open space (bump effect. 

  20. Cardiac disease and arrhythmogenesis: Mechanistic insights from mouse models

    Directory of Open Access Journals (Sweden)

    Lois Choy

    2016-09-01

    Full Text Available The mouse is the second mammalian species, after the human, in which substantial amount of the genomic information has been analyzed. With advances in transgenic technology, mutagenesis is now much easier to carry out in mice. Consequently, an increasing number of transgenic mouse systems have been generated for the study of cardiac arrhythmias in ion channelopathies and cardiomyopathies. Mouse hearts are also amenable to physical manipulation such as coronary artery ligation and transverse aortic constriction to induce heart failure, radiofrequency ablation of the AV node to model complete AV block and even implantation of a miniature pacemaker to induce cardiac dyssynchrony. Last but not least, pharmacological models, despite being simplistic, have enabled us to understand the physiological mechanisms of arrhythmias and evaluate the anti-arrhythmic properties of experimental agents, such as gap junction modulators, that may be exert therapeutic effects in other cardiac diseases. In this article, we examine these in turn, demonstrating that primary inherited arrhythmic syndromes are now recognized to be more complex than abnormality in a particular ion channel, involving alterations in gene expression and structural remodelling. Conversely, in cardiomyopathies and heart failure, mutations in ion channels and proteins have been identified as underlying causes, and electrophysiological remodelling are recognized pathological features. Transgenic techniques causing mutagenesis in mice are extremely powerful in dissecting the relative contributions of different genes play in producing disease phenotypes. Mouse models can serve as useful systems in which to explore how protein defects contribute to arrhythmias and direct future therapy.

  1. 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

  2. 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.

  3. Contemporary Phage Biology: From Classic Models to New Insights.

    Science.gov (United States)

    Ofir, Gal; Sorek, Rotem

    2018-03-08

    Bacteriophages, discovered about a century ago, have been pivotal as models for understanding the fundamental principles of molecular biology. While interest in phage biology declined after the phage "golden era," key recent developments, including advances in phage genomics, microscopy, and the discovery of the CRISPR-Cas anti-phage defense system, have sparked a renaissance in phage research in the past decade. This review highlights recently discovered unexpected complexities in phage biology, describes a new arsenal of phage genes that help them overcome bacterial defenses, and discusses advances toward documentation of the phage biodiversity on a global scale. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Subduction initiation and Obduction: insights from analog models

    Science.gov (United States)

    Agard, P.; Zuo, X.; Funiciello, F.; Bellahsen, N.; Faccenna, C.; Savva, D.

    2013-12-01

    Subduction initiation and obduction are two poorly constrained geodynamic processes which are interrelated in a number of natural settings. Subduction initiation can be viewed as the result of a regional-scale change in plate convergence partitioning between the set of existing subduction (and collision or obduction) zones worldwide. Intraoceanic subduction initiation may also ultimately lead to obduction of dense oceanic "ophiolites" atop light continental plates. A classic example is the short-lived Peri-Arabic obduction, which took place along thousands of km almost synchronously (within ~5-10 myr), from Turkey to Oman, while the subduction zone beneath Eurasia became temporarily jammed. We herein present analog models designed to study both processes and more specifically (1) subduction initiation through the partitioning of deformation between two convergent zones (a preexisting and a potential one) and, as a consequence, (2) the possible development of obduction, which has so far never been modeled. These models explore the mechanisms of subduction initiation and obduction and test various triggering hypotheses (i.e., plate acceleration, slab crossing the 660 km discontinuity, ridge subduction; Agard et al., 2007). The experimental setup comprises an upper mantle modelled as a low-viscosity transparent Newtonian glucose syrup filling a rigid Plexiglas tank and high-viscosity silicone plates. Convergence is simulated by pushing on a piston at one end of the model with plate tectonics like velocities (1-10 cm/yr) onto (i) a continental margin, (ii) a weakness zone with variable resistance and dip (W), (iii) an oceanic plate - with or without a spreading ridge, (iv) a subduction zone (S) dipping away from the piston and (v) an upper active continental margin, below which the oceanic plate is being subducted at the start of the experiment (as for the Oman case). Several configurations were tested over thirty-five parametric experiments. Special emphasis was

  5. Genomic insights from the oleaginous model alga Nannochloropsis gaditana.

    Science.gov (United States)

    Jinkerson, Robert E; Radakovits, Randor; Posewitz, Matthew C

    2013-01-01

    Nannochloropsis species have emerged as leading phototrophic microorganisms for the production of biofuels. Several isolates produce large quantities of triacylglycerols, grow rapidly, and can be cultivated at industrial scales. Recently, the mitochondrial, plastid and nuclear genomes of Nannochloropsis gaditana were sequenced. Genomic interrogation revealed several key features that likely facilitate the oleaginous phenotype observed in Nannochloropsis, including an over-representation of genes involved in lipid biosynthesis. Here we present additional analyses on gene orientation, vitamin B12 requiring enzymes, the acetyl-CoA metabolic node, and codon usage in N. gaditana. Nuclear genome transformation methods are established with exogenous DNA integration occurring via either random incorporation or by homologous recombination, making Nannochloropsis amenable to both forward and reverse genetic engineering. Completion of a draft genomic sequence, establishment of transformation techniques, and robust outdoor growth properties have positioned Nannochloropsis as a new model alga with significant potential for further development into an integrated photons-to-fuel production platform.

  6. Strabismus and the Oculomotor System: Insights from Macaque Models

    Science.gov (United States)

    Das, Vallabh E.

    2017-01-01

    Disrupting binocular vision in infancy leads to strabismus and oftentimes to a variety of associated visual sensory deficits and oculomotor abnormalities. Investigation of this disorder has been aided by the development of various animal models, each of which has advantages and disadvantages. In comparison to studies of binocular visual responses in cortical structures, investigations of neural oculomotor structures that mediate the misalignment and abnormalities of eye movements have been more recent, and these studies have shown that different brain areas are intimately involved in driving several aspects of the strabismic condition, including horizontal misalignment, dissociated deviations, A and V patterns of strabismus, disconjugate eye movements, nystagmus, and fixation switch. The responses of cells in visual and oculomotor areas that potentially drive the sensory deficits and also eye alignment and eye movement abnormalities follow a general theme of disrupted calibration, lower sensitivity, and poorer specificity compared with the normally developed visual oculomotor system. PMID:28532347

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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.

  12. 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

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

    Science.gov (United States)

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

    2015-12-01

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

  14. New insights on geomagnetic storms from observations and modeling

    Energy Technology Data Exchange (ETDEWEB)

    Jordanova, Vania K [Los Alamos National Laboratory

    2009-01-01

    Understanding the response at Earth of the Sun's varying energy output and forecasting geomagnetic activity is of central interest to space science, since intense geomagnetic storms may cause severe damages on technological systems and affect communications. Episodes of southward (Bzmodel (RAM), and investigate the mechanisms responsible for trapping particles and for causing their loss. We find that periods of increased magnetospheric convection coinciding with enhancements of plasma sheet density are needed for strong ring current buildup. During the HSS-driven storm the convection potential is highly variable and causes small sporadic injections into the ring current. The long period of enhanced convection during the CME-driven storm causes a continuous ring current injection penetrating to lower L shells and stronger ring current buildup.

  15. Defective membrane remodeling in neuromuscular diseases: insights from animal models.

    Directory of Open Access Journals (Sweden)

    Belinda S Cowling

    Full Text Available Proteins involved in membrane remodeling play an essential role in a plethora of cell functions including endocytosis and intracellular transport. Defects in several of them lead to human diseases. Myotubularins, amphiphysins, and dynamins are all proteins implicated in membrane trafficking and/or remodeling. Mutations in myotubularin, amphiphysin 2 (BIN1, and dynamin 2 lead to different forms of centronuclear myopathy, while mutations in myotubularin-related proteins cause Charcot-Marie-Tooth neuropathies. In addition to centronuclear myopathy, dynamin 2 is also mutated in a dominant form of Charcot-Marie-Tooth neuropathy. While several proteins from these different families are implicated in similar diseases, mutations in close homologues or in the same protein in the case of dynamin 2 lead to diseases affecting different tissues. This suggests (1 a common molecular pathway underlying these different neuromuscular diseases, and (2 tissue-specific regulation of these proteins. This review discusses the pathophysiology of the related neuromuscular diseases on the basis of animal models developed for proteins of the myotubularin, amphiphysin, and dynamin families. A better understanding of the common mechanisms between these neuromuscular disorders will lead to more specific health care and therapeutic approaches.

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

    Science.gov (United States)

    Balderama, O. F.

    2013-12-01

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

  17. Long term records provide insights on the relative influence of climate and forest community structure on water yield in the southern Appalachians

    Science.gov (United States)

    Peter Caldwell; Chelcy Ford Miniat; Steven Brantley; Katherine Elliott; Stephanie Laseter; Wayne Swank

    2016-01-01

    In forested watersheds, changes in climate and forest structure or age can affect water yield; yet few long-term observational records from such watersheds exist that allow an assessment of these impacts over time. In this study, we used long-term (~80 yrs) observational records of climate and water yield in six reference watersheds at the Coweeta Hydrologic Laboratory...

  18. IR sensor design insight from missile-plume prediction models

    Science.gov (United States)

    Rapanotti, John L.; Gilbert, Bruno; Richer, Guy; Stowe, Robert

    2002-08-01

    Modern anti-tank missiles and the requirement of rapid deployment have significantly reduced the use of passive armour in protecting land vehicles. Vehicle survivability is becoming more dependent on sensors, computers and countermeasures to detect and avoid threats. An analysis of missile propellants suggests that missile detection based on plume characteristics alone may be more difficult than anticipated. Currently, the passive detection of missiles depends on signatures with a significant ultraviolet component. This approach is effective in detecting anti-aircraft missiles that rely on powerful motors to pursue high-speed aircraft. The high temperature exhaust from these missiles contains significant levels of carbon dioxide, water and, often, metal oxides such as alumina. The plumes emits strongest in the infrared, 1 to 5micrometers , regions with a significant component of the signature extending into the ultraviolet domain. Many anti-tank missiles do not need the same level of propulsion and radiate significantly less. These low velocity missiles, relying on the destructive force of shaped-charge warhead, are more difficult to detect. There is virtually no ultraviolet component and detection based on UV sensors is impractical. The transition in missile detection from UV to IR is reasonable, based on trends in imaging technology, but from the analysis presented in this paper even IR imagers may have difficulty in detecting missile plumes. This suggests that the emphasis should be placed in the detection of the missile hard body in the longer wavelengths of 8 to 12micrometers . The analysis described in this paper is based on solution of the governing equations of plume physics and chemistry. These models will be used to develop better sensors and threat detection algorithms.

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. 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

  5. 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...

  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. Modeling the effects of climate change on water, sediment, and nutrient yields from the Maumee River watershed

    Directory of Open Access Journals (Sweden)

    Luke K. Cousino

    2015-09-01

    New hydrological insights for the region: Moderate climate change scenarios reduced annual flow (up to −24% and sediment (up to −26% yields, while a more extreme scenario showed smaller flow reductions (up to −10% and an increase in sediment (up to +11%. No-till practices had a negligible effect on flow but produced 16% lower average sediment loads than scenarios using current watershed conditions. At high implementation rates, no-till practices could offset any future increases in annual sediment loads, but they may have varied seasonal success. Regardless of future climate change intensity, increased remediation efforts will likely be necessary to significantly reduce HABs in Lake Erie's WB.

  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. 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.

  10. 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

  11. 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.

  12. 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.

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

    Science.gov (United States)

    Andrews, Benjamin J.

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

  14. An optimisation approach for capacity planning: modelling insights and empirical findings from a tactical perspective

    Directory of Open Access Journals (Sweden)

    Andréa Nunes Carvalho

    2017-09-01

    Full Text Available Abstract The academic literature presents a research-practice gap on the application of decision support tools to address tactical planning problems in real-world organisations. This paper addresses this gap and extends a previous action research relative to an optimisation model applied for tactical capacity planning in an engineer-to-order industrial setting. The issues discussed herein raise new insights to better understand the practical results that can be achieved through the proposed model. The topics presented include the modelling of objectives, the representation of the production process and the costing approach, as well as findings regarding managerial decisions and the scope of action considered. These insights may inspire ideas to academics and practitioners when developing tools for capacity planning problems in similar contexts.

  15. 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...

  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. 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...

  19. Understanding Isoprene Photo-oxidation from Continuous-Flow Chamber Experiments: Unexpectedly High SOA Yields and New Insights into Isoprene Oxidation Pathways

    Science.gov (United States)

    Liu, J.; D'Ambro, E.; Lee, B. H.; Zaveri, R. A.; Thornton, J. A.; Shilling, J.

    2014-12-01

    Secondary organic aerosol (SOA) accounts for a substantial fraction of tropospheric aerosol and has significant impacts on climate and human health. Results from the CARES (Carbonaceous Aerosol and Radiative Effects Study) field mission suggested that isoprene oxidation moderated by anthropogenic emissions plays a dominant role in SOA formation, but current literature isoprene yields and oxidation mechanisms are unable to explain the CARES observations. In this study, we conducted a series of continuous-flow chamber experiments to investigate the yield and chemical composition of SOA formed from isoprene photo-oxidation as a function of NOx concentration. Under low-NOx (continuous-flow experiments and the photochemical fate of the ISOPOOH intermediate under the high HO2 conditions of the chamber experiments. Online analysis of the SOA using the University of Washington FIGAERO HR-ToF-CIMS instrument shows that a C5H12O6 compound can explain a significant fraction of the mass measured by the AMS. We tentatively identify this compound as a dihydroxy dihydroperoxide produced from the oxidation of ISOPOOH. To our knowledge, we believe this represents the most direct confirmation that such dihydroperoxides form during isoprene oxidation and contribute to SOA. A van Krevelen analysis of HR-AMS data is consistent with hydroperoxide species forming the majority of the SOA. As progressively more NO was added to the system, yields initially increase to a maximum at an NO:isoprene ratio of ~1, and then rapidly decrease, to 3.6% at an NO:isoprene ratio of 4. As NO concentrations increased, alkyl nitrates accounts for an increasing portion of the SOA mass, though hydroperoxides remain significant. These observations of increased yields and the elucidation of isoprene oxidation pathways will allow for more accurate predictions of organic aerosol formation from the photochemical oxidation of isoprene in the ambient atmosphere.

  20. 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.

  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. New insights into mammalian signaling pathways using microfluidic pulsatile inputs and mathematical modeling

    Science.gov (United States)

    Sumit, M.; Takayama, S.; Linderman, J. J.

    2016-01-01

    Temporally modulated input mimics physiology. This chemical communication strategy filters the biochemical noise through entrainment and phase-locking. Under laboratory conditions, it also expands the observability space for downstream responses. A combined approach involving microfluidic pulsatile stimulation and mathematical modeling has led to deciphering of hidden/unknown temporal motifs in several mammalian signaling pathways and has provided mechanistic insights, including how these motifs combine to form distinct band-pass filters and govern fate regulation under dynamic microenvironment. This approach can be utilized to understand signaling circuit architectures and to gain mechanistic insights for several other signaling systems. Potential applications include synthetic biology and biotechnology, in developing pharmaceutical interventions, and in developing lab-on-chip models. PMID:27868126

  6. New insights into mammalian signaling pathways using microfluidic pulsatile inputs and mathematical modeling.

    Science.gov (United States)

    Sumit, M; Takayama, S; Linderman, J J

    2017-01-23

    Temporally modulated input mimics physiology. This chemical communication strategy filters the biochemical noise through entrainment and phase-locking. Under laboratory conditions, it also expands the observability space for downstream responses. A combined approach involving microfluidic pulsatile stimulation and mathematical modeling has led to deciphering of hidden/unknown temporal motifs in several mammalian signaling pathways and has provided mechanistic insights, including how these motifs combine to form distinct band-pass filters and govern fate regulation under dynamic microenvironment. This approach can be utilized to understand signaling circuit architectures and to gain mechanistic insights for several other signaling systems. Potential applications include synthetic biology and biotechnology, in developing pharmaceutical interventions, and in developing lab-on-chip models.

  7. Modeling Double Subjectivity for Gaining Programmable Insights: Framing the Case of Uber

    Directory of Open Access Journals (Sweden)

    Loretta Henderson Cheeks

    2017-09-01

    Full Text Available The Internet is the premier platform that enable the emergence of new technologies. Online news is unstructured narrative text that embeds facts, frames, and amplification that can influence society attitudes about technology adoption. Online news sources are carriers of voluminous amounts of news for reaching significantly large audience and have no geographical or time boundaries. The interplay of complex and dynamical forces among authors and readers allow for progressive emergent and latent properties to exhibit. Our concept of “Double subjectivity” provides a new paradigm for exploring complementary programmable insights of deeply buried meanings in a system. The ability to understand internal embeddedness in a large collection of related articles are beyond the reach of existing computational tools, and are hence left to human readers with unscalable results. This paper uncovers the potential to utilize advanced machine learning in a new way to automate the understanding of implicit structures and their associated latent meanings to give an early human-level insight into emergent technologies, with a concrete example of “Uber”. This paper establishes the new concept of double subjectivity as an instrument for large-scale machining of unstructured text and introduces a social influence model for the discovery of distinct pathways into emerging technology, and hence an insight. The programmable insight reveals early spatial and temporal opinion shift monitoring in complex networks in a structured way for computational treatment and visualization.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Marcin Studnicki

    2016-06-01

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

  14. Ratio between mature and immature enzymatic cross-links correlates with post-yield cortical bone behavior: An insight into greenstick fractures of the child fibula.

    Science.gov (United States)

    Berteau, Jean-Philippe; Gineyts, Evelyne; Pithioux, Martine; Baron, Cécile; Boivin, Georges; Lasaygues, Philippe; Chabrand, Patrick; Follet, Hélène

    2015-10-01

    As a determinant of skeletal fragility, the organic matrix is responsible for the post-yield and creep behavior of bone and for its toughness, while the mineral apatite acts on stiffness. Specific to the fibula and ulna in children, greenstick fractures show a plastic in vivo mechanical behavior before bone fracture. During growth, the immature form of collagen enzymatic cross-links gradually decreases, to be replaced by the mature form until adolescence, subsequently remaining constant throughout adult life. However, the link between the cortical bone organic matrix and greenstick fractures in children remains to be explored. Here, we sought to determine: 1) whether plastic bending fractures can occur in vitro, by testing cortical bone samples from children's fibula and 2) whether the post-yield behavior (ωp plastic energy) of cortical bone before fracture is related to total quantity of the collagen matrix, or to the quantity of mature and immature enzymatic cross-links and the quantity of non-enzymatic cross-links. We used a two-step approach; first, a 3-point microbending device tested 22 fibula machined bone samples from 7 children and 3 elderly adults until fracture. Second, biochemical analysis by HPLC was performed on the sample fragments. When pooling two groups of donors, children and elderly adults, results show a rank correlation between total energy dissipated before fracture and age and a linear correlation between plastic energy dissipated before fracture and ratio of immature/mature cross-links. A collagen matrix with more immature cross-links (i.e. a higher immature/mature cross-link ratio) is more likely to plastically deform before fracture. We conclude that this ratio in the sub-nanostructure of the organic matrix in cortical bone from the fibula may go some way towards explaining the variance in post-yield behavior. From a clinical point of view, therefore, our results provide a potential explanation of the presence of greenstick fractures in

  15. 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.

  16. 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.

  17. 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

  18. 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.)

  19. Study of PcaV from Streptomyces coelicolor yields new insights into ligand-responsive MarR family transcription factors.

    Science.gov (United States)

    Davis, Jennifer R; Brown, Breann L; Page, Rebecca; Sello, Jason K

    2013-04-01

    MarR family proteins constitute a group of >12 000 transcriptional regulators encoded in bacterial and archaeal genomes that control gene expression in metabolism, stress responses, virulence and multi-drug resistance. There is much interest in defining the molecular mechanism by which ligand binding attenuates the DNA-binding activities of these proteins. Here, we describe how PcaV, a MarR family regulator in Streptomyces coelicolor, controls transcription of genes encoding β-ketoadipate pathway enzymes through its interaction with the pathway substrate, protocatechuate. This transcriptional repressor is the only MarR protein known to regulate this essential pathway for aromatic catabolism. In in vitro assays, protocatechuate and other phenolic compounds disrupt the PcaV-DNA complex. We show that PcaV binds protocatechuate in a 1:1 stoichiometry with the highest affinity of any MarR family member. Moreover, we report structures of PcaV in its apo form and in complex with protocatechuate. We identify an arginine residue that is critical for ligand coordination and demonstrate that it is also required for binding DNA. We propose that interaction of ligand with this arginine residue dictates conformational changes that modulate DNA binding. Our results provide new insights into the molecular mechanism by which ligands attenuate DNA binding in this large family of transcription factors.

  20. Novel single-round PCR and cloning of full-length envelope genes of HIV-1 may yield new insight into biomolecular antibacterial drug development.

    Science.gov (United States)

    McDonald, Richard; Burnett, Virginia

    2005-06-01

    Nested or semi-nested polymerase chain reaction (PCR) with a 'hot start' is the preferred amplification method for full-length, in-frame envelope genes (gp160) of the human immunodeficiency virus type 1 (HIV-1). This generally follows an extensive screening process. This paper describes an effective single-round PCR method and cloning process for HIV-1 gp160 from clinical samples, and cell and tissue cultures developed during the early stages of construction of a molecular HIV-1 vaccine. The amplification method and cloning process are adaptable to full-length HIV-1, HIV-2, and other viral production processes. Also described within, is one solution to the most-often extensive screening process for inserts containing full-length, in-frame gp160. Of note, was a perceived toxicity of gp160 to bacteria during the culturing and the scaling-up process that created the extensive screening process. The toxicity association was not found with the individual gp160 genes, the gp120 or the gp41 gene, with other viral regions similar or larger in molecular weight to gp160, or with other non-gp160 full-length genes of HIV-1 such as pol and gag genes. The HIV-1 gp160 toxicity issue may provide insight towards the development of the next generation of novel biomolecular drugs against bacterial infections.

  1. Fundamental studies of novel zwitterionic hybrid membranes: kinetic model and mechanism insights into strontium removal.

    Science.gov (United States)

    Zhu, Wen; Liu, Junsheng; Li, Meng

    2014-01-01

    A series of zwitterionic hybrid membranes were prepared via the ring opening of 1,3-propanesultone with the amine groups in the chains of TMSPEDA and a subsequent sol-gel process. Their kinetic models for strontium removal were investigated using three two-parameter kinetic equations (i.e., Lagergren pseudo-first order, pseudo-second order, and Elovich models). Adsorption mechanism was evaluated using intraparticle diffusion model, diffusion-chemisorption model, and Boyd equation. It was found that the adsorption of strontium ions on these zwitterionic hybrid membranes fitted well with the Lagergren pseudo-second order model. Mechanism insights suggested that diffusion-chemisorption was one of the main adsorption mechanisms. Boyd equation exhibited that film-diffusion mechanism might be the control process during the starting period. These findings are very useful in strontium removal from the stimulated radioactive wastewater.

  2. Fundamental Studies of Novel Zwitterionic Hybrid Membranes: Kinetic Model and Mechanism Insights into Strontium Removal

    Directory of Open Access Journals (Sweden)

    Wen Zhu

    2014-01-01

    Full Text Available A series of zwitterionic hybrid membranes were prepared via the ring opening of 1,3-propanesultone with the amine groups in the chains of TMSPEDA and a subsequent sol-gel process. Their kinetic models for strontium removal were investigated using three two-parameter kinetic equations (i.e., Lagergren pseudo-first order, pseudo-second order, and Elovich models. Adsorption mechanism was evaluated using intraparticle diffusion model, diffusion-chemisorption model, and Boyd equation. It was found that the adsorption of strontium ions on these zwitterionic hybrid membranes fitted well with the Lagergren pseudo-second order model. Mechanism insights suggested that diffusion-chemisorption was one of the main adsorption mechanisms. Boyd equation exhibited that film-diffusion mechanism might be the control process during the starting period. These findings are very useful in strontium removal from the stimulated radioactive wastewater.

  3. 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.

  4. 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...

  5. 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

  6. 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...

  7. 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...

  8. CO2 conversion by plasma technology: insights from modeling the plasma chemistry and plasma reactor design

    Science.gov (United States)

    Bogaerts, A.; Berthelot, A.; Heijkers, S.; Kolev, St.; Snoeckx, R.; Sun, S.; Trenchev, G.; Van Laer, K.; Wang, W.

    2017-06-01

    In recent years there has been growing interest in the use of plasma technology for CO2 conversion. To improve this application, a good insight into the underlying mechanisms is of great importance. This can be obtained from modeling the detailed plasma chemistry in order to understand the chemical reaction pathways leading to CO2 conversion (either in pure form or mixed with another gas). Moreover, in practice, several plasma reactor types are being investigated for CO2 conversion, so in addition it is essential to be able to model these reactor geometries so that their design can be improved, and the most energy efficient CO2 conversion can be achieved. Modeling the detailed plasma chemistry of CO2 conversion in complex reactors is, however, very time-consuming. This problem can be overcome by using a combination of two different types of model: 0D chemical reaction kinetics models are very suitable for describing the detailed plasma chemistry, while the characteristic features of different reactor geometries can be studied by 2D or 3D fluid models. In the first instance the latter can be developed in argon or helium with a simple chemistry to limit the calculation time; however, the ultimate aim is to implement the more complex CO2 chemistry in these models. In the present paper, examples will be given of both the 0D plasma chemistry models and the 2D and 3D fluid models for the most common plasma reactors used for CO2 conversion in order to emphasize the complementarity of both approaches. Furthermore, based on the modeling insights, the paper discusses the possibilities and limitations of plasma-based CO2 conversion in different types of plasma reactors, as well as what is needed to make further progress in this field.

  9. The crystal structure of full-length Sizzled from Xenopus laevis yields insights into Wnt-antagonistic function of secreted Frizzled-related proteins.

    Science.gov (United States)

    Bu, Qixin; Li, Zhiqiang; Zhang, Junying; Xu, Fei; Liu, Jianmei; Liu, Heli

    2017-09-29

    The Wnt-signaling pathway is crucial to cell proliferation, differentiation, and migration. The secreted Frizzled-related proteins (sFRPs) represent the largest family of secreted Wnt inhibitors. However, their function in antagonizing Wnt signaling has remained somewhat controversial. Here, we report the crystal structure of Sizzled from Xenopus laevis , the first full-length structure of an sFRP. Tethered by an inter-domain disulfide bond and a linker, the N-terminal cysteine-rich domain (CRD) and the C-terminal netrin-like domain (NTR) of Sizzled are arranged in a tandem fashion, with the NTR domain occluding the groove of CRD for Wnt accessibility. A Dual-Luciferase assay demonstrated that removing the NTR domain and replacing the CRD groove residues His-116 and His-118 with aromatic residues may significantly enhance antagonistic function of Sizzled in inhibiting Wnt3A signaling. Sizzled is a monomer in solution, and Sizzled CRD exhibited different packing in the crystal, suggesting that sFRPs do not have a conserved CRD dimerization mode. Distinct from the canonical NTR domain, the Sizzled NTR adopts a novel α/β folding with two perpendicular helices facing the central mixed β-sheet. The subgroup of human sFRP1/2/5 and Sizzled should have a similar NTR domain that features a highly positively charged region, opposite the NTR-CRD interface, suggesting that the NTR domain in human sFRPs, at least sFRP1/2/5, is unlikely to bind to Wnt but is likely involved in biphasic Wnt signaling modulation. In summary, the Sizzled structure provides the first insights into how the CRD and the NTR domains relate to each other for modulating Wnt-antagonistic function of sFRPs. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  10. 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.

  11. The draft genomes of soft-shell turtle and green sea turtle yield insights into the development and evolution of the turtle-specific body plan.

    Science.gov (United States)

    Wang, Zhuo; Pascual-Anaya, Juan; Zadissa, Amonida; Li, Wenqi; Niimura, Yoshihito; Huang, Zhiyong; Li, Chunyi; White, Simon; Xiong, Zhiqiang; Fang, Dongming; Wang, Bo; Ming, Yao; Chen, Yan; Zheng, Yuan; Kuraku, Shigehiro; Pignatelli, Miguel; Herrero, Javier; Beal, Kathryn; Nozawa, Masafumi; Li, Qiye; Wang, Juan; Zhang, Hongyan; Yu, Lili; Shigenobu, Shuji; Wang, Junyi; Liu, Jiannan; Flicek, Paul; Searle, Steve; Wang, Jun; Kuratani, Shigeru; Yin, Ye; Aken, Bronwen; Zhang, Guojie; Irie, Naoki

    2013-06-01

    The unique anatomical features of turtles have raised unanswered questions about the origin of their unique body plan. We generated and analyzed draft genomes of the soft-shell turtle (Pelodiscus sinensis) and the green sea turtle (Chelonia mydas); our results indicated the close relationship of the turtles to the bird-crocodilian lineage, from which they split ∼267.9-248.3 million years ago (Upper Permian to Triassic). We also found extensive expansion of olfactory receptor genes in these turtles. Embryonic gene expression analysis identified an hourglass-like divergence of turtle and chicken embryogenesis, with maximal conservation around the vertebrate phylotypic period, rather than at later stages that show the amniote-common pattern. Wnt5a expression was found in the growth zone of the dorsal shell, supporting the possible co-option of limb-associated Wnt signaling in the acquisition of this turtle-specific novelty. Our results suggest that turtle evolution was accompanied by an unexpectedly conservative vertebrate phylotypic period, followed by turtle-specific repatterning of development to yield the novel structure of the shell.

  12. The draft genomes of soft–shell turtle and green sea turtle yield insights into the development and evolution of the turtle–specific body plan

    Science.gov (United States)

    Niimura, Yoshihito; Huang, Zhiyong; Li, Chunyi; White, Simon; Xiong, Zhiqiang; Fang, Dongming; Wang, Bo; Ming, Yao; Chen, Yan; Zheng, Yuan; Kuraku, Shigehiro; Pignatelli, Miguel; Herrero, Javier; Beal, Kathryn; Nozawa, Masafumi; Li, Qiye; Wang, Juan; Zhang, Hongyan; Yu, Lili; Shigenobu, Shuji; Wang, Junyi; Liu, Jiannan; Flicek, Paul; Searle, Steve; Wang, Jun; Kuratani, Shigeru; Yin, Ye; Aken, Bronwen; Zhang, Guojie; Irie, Naoki

    2014-01-01

    The unique anatomical features of turtles have raised unanswered questions about the origin of their unique body plan. We generated and analyzed draft genomes of the soft-shell turtle (Pelodiscus sinensis) and the green sea turtle (Chelonia mydas); our results indicated the close relationship of the turtles to the bird-crocodilian lineage, from which they split ~267.9–248.3 million years ago (Upper Permian to Triassic). We also found extensive expansion of olfactory receptor genes in these turtles. Embryonic gene expression analysis identified an hourglass-like divergence of turtle and chicken embryogenesis, with maximal conservation around the vertebrate phylotypic period, rather than at later stages that show the amniote-common pattern. Wnt5a expression was found in the growth zone of the dorsal shell, supporting the possible co-option of limb-associated Wnt signaling in the acquisition of this turtle-specific novelty. Our results suggest that turtle evolution was accompanied by an unexpectedly conservative vertebrate phylotypic period, followed by turtle-specific repatterning of development to yield the novel structure of the shell. PMID:23624526

  13. 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.

  14. 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...

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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

    Full Text Available 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 response to salinity and to evaluate the effectiveness of available mathematical models for the yield estimation of the Basil . Materials and Methods: The extensive experiments were conducted with 13 natural saline water treatments including 1.2, 1.8, 2, 2.2, 2.5, 2.8, 3, 3.5, 4, 5, 6, 8, and 10 dSm-1. Water salinity treatments were prepared by mixing Shoor River water with fresh water. In order to quantify the salinity effect on Basil yield, seven mathematical models including Maas and Hoffman (1977, van Genuchten and Hoffman (1984, Dirksen and Augustijn (1988, and Homaee et al., (2002 were used. One of the relatively recent methods for soil water content measurements is theta probes instrument. Theta probes instrument consists of four probes with 60 mm long and 3 mm diameter, a water proof container (probe structure, and a cable that links input and output signals to the data logger display. The advantages that have been attributed to this method are high precision and direct and rapid measurements in the field and greenhouse. The range of measurements is not limited like tensiometer and is from saturation to wilting point. In this study, Theta probes instrument was calibrated by weighing method for exact irrigation scheduling. Relative transpiration was calculated using daily soil water content changes. A coarse sand layer with 2 centimeters thick was used to decrease evaporation from the surface soil of the pots. Quantity comparison of the used models was done

  20. 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.

  1. 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.

  2. Effects of sub-clinical psychosis and cognitive insight on psychological well-being: a structural equation model.

    Science.gov (United States)

    Weintraub, Marc J; Weisman de Mamani, Amy

    2015-03-30

    Psychological well-being has been widely researched along the psychosis spectrum, and increased psychotic symptoms are generally associated with worse well-being. Additionally, the construct of insight has been extensively studied in schizophrenia. While having greater insight has many benefits for those with schizophrenia, a paradox exists in which greater insight is also associated with poorer psychological well-being. However, it is unclear whether the link between insight and poor well-being occurs only once serious psychopathology has been established, or whether this is a more universal process seen even at lower levels on the psychosis spectrum. We used a structural modeling approach in an ethnically diverse, non-clinical sample of 420 undergraduates to evaluate the association between sub-clinical psychosis, cognitive insight and psychological well-being. As hypothesized, results indicated that sub-clinical psychotic symptoms were negatively associated with psychological well-being. The insight paradox was also substantiated, as greater cognitive insight was associated with worse psychological well-being. However, cognitive insight did not moderate the association between symptoms and well-being. The link between sub-clinical psychotic symptoms and psychological well-being as well as the insight paradox appears to emerge even before reaching threshold for a psychotic disorder. Research and clinical implications are discussed. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  3. 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

  4. 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.

  5. 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)

  6. Mechanistic insights on ethanol dehydrogenation on Pd-Au model catalysts: a combined experimental and DFT study.

    Science.gov (United States)

    Evans, E J; Li, H; Yu, Wen-Yueh; Mullen, G M; Henkelman, G; Mullins, C Buddie

    2017-11-22

    In this study, we have combined ultra-high vacuum (UHV) experiments and density functional theory (DFT) calculations to investigate ethanol (EtOH) dehydrogenation on Pd-Au model catalysts. Using EtOH reactive molecular beam scattering (RMBS), EtOH temperature-programmed desorption (TPD), and DFT calculations, we show how different Pd ensemble sizes on Au(111) can affect the mechanism for EtOH dehydrogenation and H 2 production. The Au(111) surface with an initial coverage of 2 monolayers of Pd (2 ML Pd-Au) had the highest H 2 yield. However, the 1 ML Pd-Au catalyst showed the highest selectivity and stability, yielding appreciable amounts of only H 2 and acetaldehyde. Arrhenius plots of H 2 production confirm that the mechanisms for EtOH dehydrogenation differed between 1 and 2 ML Pd-Au, supporting the perceived difference in selectivity between the two surfaces. DFT calculations support this difference in mechanism, showing a dependence of the initial dehydrogenation selectivity of EtOH on the size of Pd ensemble. DFT binding energies and EtOH TPD confirm that EtOH has increasing surface affinity with increasing Pd ensemble size and Pd coverage, indicating that surfaces with more Pd are more likely to induce an EtOH reaction instead of desorb. Our theoretical results show that the synergistic influence of atomic ensemble and electronic effects on Pd/Au(111) can lead to different H 2 association energies and EtOH dehydrogenation capacities at different Pd ensembles. These results provide mechanistic insights into ethanol's dehydrogenation interactions with different sites on the Pd-Au surface and can potentially aid in bimetallic catalyst design for applications such as fuel cells.

  7. Recent Insights into the Neurobiology of Impulsivity

    Science.gov (United States)

    Mitchell, Marci R.; Potenza, Marc N.

    2014-01-01

    Impulsivity is associated with various psychopathologies, and elevated impulsivity is typically disadvantageous. This manuscript reviews recent investigations into the neurobiology of impulsivity using human imaging techniques and animal models. Both human imaging and preclinical pharmacological manipulations have yielded important insights into the neurobiological underpinnings of impulsivity. A more thorough understanding of the complex neurobiology underlying aspects of impulsivity may provide insight into new treatment options that target elevated impulsivity and psychopathologies such as addictions. PMID:25431750

  8. 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).

  9. New Insights Offered by a Computational Model of Deep Brain Stimulation

    DEFF Research Database (Denmark)

    Modolo, J.; Mosekilde, Erik; Beuter, A.

    2007-01-01

    Deep brain stimulation (DBS) is a standard neurosurgical procedure used to treat motor symptoms in about 5% of patients with Parkinson's disease (PD). Despite the indisputable success of this procedure, the biological mechanisms underlying the clinical benefits of DBS have not yet been fully...... and exploring the physiological mechanisms which respond to this treatment strategy (i.e., DBS). Finally, we present new insights into the ways this computational model may help to elucidate the dynamic network effects produced in a cerebral structure when DBS is applied. (C) 2007 Elsevier Ltd. All rights...

  10. 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.

  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. 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

  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. 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.

  16. Neurocognition, insight and medication nonadherence in schizophrenia: a structural equation modeling approach.

    Directory of Open Access Journals (Sweden)

    Laurent Boyer

    Full Text Available OBJECTIVE: The aim of this study was to examine the complex relationships among neurocognition, insight and nonadherence in patients with schizophrenia. METHODS: DESIGN: Cross-sectional study. INCLUSION CRITERIA: Diagnosis of schizophrenia according to the DSM-IV-TR criteria. DATA COLLECTION: Neurocognition was assessed using a global approach that addressed memory, attention, and executive functions; insight was analyzed using the multidimensional 'Scale to assess Unawareness of Mental Disorder;' and nonadherence was measured using the multidimensional 'Medication Adherence Rating Scale.' ANALYSIS: Structural equation modeling (SEM was applied to examine the non-straightforward relationships among the following latent variables: neurocognition, 'awareness of positive symptoms' and 'negative symptoms', 'awareness of mental disorder' and nonadherence. RESULTS: One hundred and sixty-nine patients were enrolled. The final testing model showed good fit, with normed χ(2 = 1.67, RMSEA = 0.063, CFI = 0.94, and SRMR = 0.092. The SEM revealed significant associations between (1 neurocognition and 'awareness of symptoms,' (2 'awareness of symptoms' and 'awareness of mental disorder' and (3 'awareness of mental disorder' and nonadherence, mainly in the 'attitude toward taking medication' dimension. In contrast, there were no significant links between neurocognition and nonadherence, neurocognition and 'awareness of mental disorder,' and 'awareness of symptoms' and nonadherence. CONCLUSIONS: Our findings support the hypothesis that neurocognition influences 'awareness of symptoms,' which must be integrated into a higher level of insight (i.e., the 'awareness of mental disorder' to have an impact on nonadherence. These findings have important implications for the development of effective strategies to enhance medication adherence.

  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. 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.

  19. Recent Insights in the Dynamical Structure of Cepheids' Atmosphere and Prospect Concerning Hydrodynamical Modelling

    Science.gov (United States)

    Nardetto, N.

    The link between the dynamical structure of Cepheid atmosphere and the distance scale calibration in the universe is now clearly established through a period-projection factor relation (Pp). However, to support future observations, we currently need fully consistent hydrodynamical models, including pulsating and evolutionary theories, convective energy transport, adaptive numerical meshes, and a refined calculation of the radiative transfer within the pulsating atmosphere and the expected circumstellar envelope (hereafter CSE). Confronting such models with observations (spectral line profiles, spatial- and spectral- visibility curves), will permit to resolve and/or strengthen subtle questions concerning (1) the limb-darkening, (2) the dynamical structure of Cepheids' atmosphere, (3) the expected interaction between the atmosphere and the CSE, and (4) it will bring new insights in determining the fundamental parameters of Cepheids. All these physical quantities are supposed furthermore to be linked to the pulsation period of Cepheids. From these studies, it will be possible to paint a glowing picture of all Cepheids within the instability strip, allowing an unprecedent calibration of the period-luminosity relation, leading to new insights in the fields of extragalactic distance scales and cosmology.

  20. Deep models for brain EM image segmentation: novel insights and improved performance.

    Science.gov (United States)

    Fakhry, Ahmed; Peng, Hanchuan; Ji, Shuiwang

    2016-08-01

    Accurate segmentation of brain electron microscopy (EM) images is a critical step in dense circuit reconstruction. Although deep neural networks (DNNs) have been widely used in a number of applications in computer vision, most of these models that proved to be effective on image classification tasks cannot be applied directly to EM image segmentation, due to the different objectives of these tasks. As a result, it is desirable to develop an optimized architecture that uses the full power of DNNs and tailored specifically for EM image segmentation. In this work, we proposed a novel design of DNNs for this task. We trained a pixel classifier that operates on raw pixel intensities with no preprocessing to generate probability values for each pixel being a membrane or not. Although the use of neural networks in image segmentation is not completely new, we developed novel insights and model architectures that allow us to achieve superior performance on EM image segmentation tasks. Our submission based on these insights to the 2D EM Image Segmentation Challenge achieved the best performance consistently across all the three evaluation metrics. This challenge is still ongoing and the results in this paper are as of June 5, 2015. https://github.com/ahmed-fakhry/dive : sji@eecs.wsu.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. 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.

  2. 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

  3. 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)

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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)

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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

  20. Genetic rodent models of obesity-associated ovarian dysfunction and subfertility: insights into polycystic ovary syndrome

    Directory of Open Access Journals (Sweden)

    Isabel eHuang-Doran

    2016-06-01

    Full Text Available Polycystic ovary syndrome (PCOS is the most common endocrinopathy affecting women, and a leading cause of female infertility worldwide. Defined clinically by the presence of hyperandrogenemia and oligomenorrhoea, PCOS represents a state of hormonal dysregulation, disrupted ovarian follicle dynamics, and subsequent oligo- or anovulation. The syndrome’s prevalence is attributed at least partly to a well-established association with obesity and insulin resistance (IR. Indeed, the presence of severe PCOS in human genetic obesity and IR syndromes supports a causal role for IR in the pathogenesis of PCOS. The molecular mechanisms underlying this causality, however, as well as the important role of hyperandrogenemia, remain poorly elucidated. As such, treatment of PCOS is necessarily empirical, focusing on symptom alleviation. The generation of knockout and transgenic rodent models of obesity and IR offer a promising platform in which to address mechanistic questions about reproductive dysfunction in the context of metabolic disease. The impact of primary perturbations in rodent gonadotrophin or androgen signaling has been similarly interrogated. The insights gained from such models, however, have been limited by the relatively poor fidelity of rodent models to human PCOS. In this minireview we evaluate the ovarian phenotypes associated with rodent models of obesity and IR, including the extent of endocrine disturbance, ovarian dysmorphology and subfertility. We compare them to both human PCOS and other animal models of the syndrome (genetic and hormonal, explore reasons for their discordance and consider the new opportunities that are emerging to better understand and treat this important condition.

  1. 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.

  2. 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

  3. 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

  4. 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,…

  5. 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

  6. 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 ...

  7. 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

  8. Is structural sensitivity a problem of oversimplified biological models? Insights from nested Dynamic Energy Budget models.

    Science.gov (United States)

    Aldebert, Clement; Kooi, Bob W; Nerini, David; Poggiale, Jean-Christophe

    2018-03-14

    Many current issues in ecology require predictions made by mathematical models, which are built on somewhat arbitrary choices. Their consequences are quantified by sensitivity analysis to quantify how changes in model parameters propagate into an uncertainty in model predictions. An extension called structural sensitivity analysis deals with changes in the mathematical description of complex processes like predation. Such processes are described at the population scale by a specific mathematical function taken among similar ones, a choice that can strongly drive model predictions. However, it has only been studied in simple theoretical models. Here, we ask whether structural sensitivity is a problem of oversimplified models. We found in predator-prey models describing chemostat experiments that these models are less structurally sensitive to the choice of a specific functional response if they include mass balance resource dynamics and individual maintenance. Neglecting these processes in an ecological model (for instance by using the well-known logistic growth equation) is not only an inappropriate description of the ecological system, but also a source of more uncertain predictions. Copyright © 2018. Published by Elsevier Ltd.

  9. 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

  10. 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

  11. Characterizing poliovirus transmission and evolution: insights from modeling experiences with wild and vaccine-related polioviruses.

    Science.gov (United States)

    Duintjer Tebbens, Radboud J; Pallansch, Mark A; Kalkowska, Dominika A; Wassilak, Steven G F; Cochi, Stephen L; Thompson, Kimberly M

    2013-04-01

    With national and global health policymakers facing numerous complex decisions related to achieving and maintaining polio eradication, we expanded our previously developed dynamic poliovirus transmission model using information from an expert literature review process and including additional immunity states and the evolution of oral poliovirus vaccine (OPV). The model explicitly considers serotype differences and distinguishes fecal-oral and oropharyngeal transmission. We evaluated the model by simulating diverse historical experiences with polioviruses, including one country that eliminated wild poliovirus using both OPV and inactivated poliovirus vaccine (IPV) (USA), three importation outbreaks of wild poliovirus (Albania, the Netherlands, Tajikistan), one situation in which no circulating vaccine-derived polioviruses (cVDPVs) emerge despite annual OPV use and cessation (Cuba), three cVDPV outbreaks (Haiti, Madura Island in Indonesia, northern Nigeria), one area of current endemic circulation of all three serotypes (northern Nigeria), and one area with recent endemic circulation and subsequent elimination of multiple serotypes (northern India). We find that when sufficient information about the conditions exists, the model can reproduce the general behavior of poliovirus transmission and outbreaks while maintaining consistency in the generic model inputs. The assumption of spatially homogeneous mixing remains a significant limitation that affects the performance of the differential equation-based model when significant heterogeneities in immunity and mixing may exist. Further studies on OPV virus evolution and improved understanding of the mechanisms of mixing and transmission may help to better characterize poliovirus transmission in populations. Broad application of the model promises to offer insights in the context of global and national policy and economic models. © 2013 Society for Risk Analysis.

  12. Factors affecting variation of different measures of cheese yield and milk nutrient recovery from an individual model cheese-manufacturing process.

    Science.gov (United States)

    Cipolat-Gotet, C; Cecchinato, A; De Marchi, M; Bittante, G

    2013-01-01

    procedure was used to process individual milk samples obtained from 1,167 Brown Swiss cows reared in 85 herds of the province of Trento (Italy). The assessed traits exhibited almost normal distributions, with the exception of REC(FAT). The average values (± SD) were as follows: %CY(CURD)=14.97±1.86, %CY(SOLIDS)=7.18±0.92, %CY(WATER)=7.77±1.27, dCY(CURD)=3.63±1.17, dCY(SOLIDS)=1.74±0.57, dCY(WATER)=1.88±0.63, REC(FAT)=89.79±3.55, REC(PROTEIN)=78.08±2.43, REC(SOLIDS)=51.88±3.52, and REC(ENERGY)=67.19±3.29. All traits were highly influenced by herd-test-date and days in milk of the cow, moderately influenced by parity, and weakly influenced by the utilized vat. Both %CY(CURD) and dCY(CURD) depended not only on the fat and protein (casein) contents of the milk, but also on their proportions retained in the curd; the water trapped in curd presented an higher variability than that of %CY(SOLIDS). All REC traits were variable and affected by days in milk and parity of the cows. The described model cheese-making procedure and the results obtained provided new insight into the phenotypic variation of cheese yield and recovery traits at the individual level. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  13. 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 ...

  14. 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.

  15. Morbillivirus Experimental Animal Models: Measles Virus Pathogenesis Insights from Canine Distemper Virus.

    Science.gov (United States)

    da Fontoura Budaszewski, Renata; von Messling, Veronika

    2016-10-11

    Morbilliviruses share considerable structural and functional similarities. Even though disease severity varies among the respective host species, the underlying pathogenesis and the clinical signs are comparable. Thus, insights gained with one morbillivirus often apply to the other members of the genus. Since the Canine distemper virus (CDV) causes severe and often lethal disease in dogs and ferrets, it is an attractive model to characterize morbillivirus pathogenesis mechanisms and to evaluate the efficacy of new prophylactic and therapeutic approaches. This review compares the cellular tropism, pathogenesis, mechanisms of persistence and immunosuppression of the Measles virus (MeV) and CDV. It then summarizes the contributions made by studies on the CDV in dogs and ferrets to our understanding of MeV pathogenesis and to vaccine and drugs development.

  16. Morbillivirus Experimental Animal Models: Measles Virus Pathogenesis Insights from Canine Distemper Virus

    Directory of Open Access Journals (Sweden)

    Renata da Fontoura Budaszewski

    2016-10-01

    Full Text Available Morbilliviruses share considerable structural and functional similarities. Even though disease severity varies among the respective host species, the underlying pathogenesis and the clinical signs are comparable. Thus, insights gained with one morbillivirus often apply to the other members of the genus. Since the Canine distemper virus (CDV causes severe and often lethal disease in dogs and ferrets, it is an attractive model to characterize morbillivirus pathogenesis mechanisms and to evaluate the efficacy of new prophylactic and therapeutic approaches. This review compares the cellular tropism, pathogenesis, mechanisms of persistence and immunosuppression of the Measles virus (MeV and CDV. It then summarizes the contributions made by studies on the CDV in dogs and ferrets to our understanding of MeV pathogenesis and to vaccine and drugs development.

  17. Spatiotemporal analysis of projected impacts of climate change on the major C3 and C4 crop yield under representative concentration pathway 4.5: Insight from the coasts of Tamil Nadu, South India.

    Science.gov (United States)

    A, Ramachandran; Praveen, Dhanya; R, Jaganathan; D, RajaLakshmi; K, Palanivelu

    2017-01-01

    India's dependence on a climate sensitive sector like agriculture makes it highly vulnerable to its impacts. However, agriculture is highly heterogeneous across the country owing to regional disparities in exposure, sensitivity, and adaptive capacity. It is essential to know and quantify the possible impacts of changes in climate on crop yield for successful agricultural management and planning at a local scale. The Hadley Centre Global Environment Model version 2-Earth System (HadGEM-ES) was employed to generate regional climate projections for the study area using the Regional Climate Model (RCM) RegCM4.4. The dynamics in potential impacts at the sub-district level were evaluated using the Representative Concentration Pathway 4.5 (RCPs). The aim of this study was to simulate the crop yield under a plausible change in climate for the coastal areas of South India through the end of this century. The crop simulation model, the Decision Support System for Agrotechnology Transfer (DSSAT) 4.5, was used to understand the plausible impacts on the major crop yields of rice, groundnuts, and sugarcane under the RCP 4.5 trajectory. The findings reveal that under the RCP 4.5 scenario there will be decreases in the major C3 and C4 crop yields in the study area. This would affect not only the local food security, but the livelihood security as well. This necessitates timely planning to achieve sustainable crop productivity and livelihood security. On the other hand, this situation warrants appropriate adaptations and policy intervention at the sub-district level for achieving sustainable crop productivity in the future.

  18. 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.

  19. Modeling shows that the NS5A inhibitor daclatasvir has two modes of action and yields a shorter estimate of the hepatitis C virus half-life.

    Science.gov (United States)

    Guedj, Jeremie; Dahari, Harel; Rong, Libin; Sansone, Natasha D; Nettles, Richard E; Cotler, Scott J; Layden, Thomas J; Uprichard, Susan L; Perelson, Alan S

    2013-03-05

    The nonstructural 5A (NS5A) protein is a target for drug development against hepatitis C virus (HCV). Interestingly, the NS5A inhibitor daclatasvir (BMS-790052) caused a decrease in serum HCV RNA levels by about two orders of magnitude within 6 h of administration. However, NS5A has no known enzymatic functions, making it difficult to understand daclatasvir's mode of action (MOA) and to estimate its antiviral effectiveness. Modeling viral kinetics during therapy has provided important insights into the MOA and effectiveness of a variety of anti-HCV agents. Here, we show that understanding the effects of daclatasvir in vivo requires a multiscale model that incorporates drug effects on the HCV intracellular lifecycle, and we validated this approach with in vitro HCV infection experiments. The model predicts that daclatasvir efficiently blocks two distinct stages of the viral lifecycle, namely viral RNA synthesis and virion assembly/secretion with mean effectiveness of 99% and 99.8%, respectively, and yields a more precise estimate of the serum HCV half-life, 45 min, i.e., around four times shorter than previous estimates. Intracellular HCV RNA in HCV-infected cells treated with daclatasvir and the HCV polymerase inhibitor NM107 showed a similar pattern of decline. However, daclatasvir treatment led to an immediate and rapid decline of extracellular HCV titers compared to a delayed (6-9 h) and slower decline with NM107, confirming an effect of daclatasvir on both viral replication and assembly/secretion. The multiscale modeling approach, validated with in vitro kinetic experiments, brings a unique conceptual framework for understanding the mechanism of action of a variety of agents in development for the treatment of HCV.

  20. Couples Counseling Directive Technique: A (Mis)communication Model to Promote Insight, Catharsis, Disclosure, and Problem Resolution

    Science.gov (United States)

    Mahaffey, Barbara A.

    2010-01-01

    A psychoeducational model for improving couple communication is proposed. An important goal in couples counseling is to assist couples in resolving communication conflicts. The proposed communication model helps to establish a therapeutic environment that encourages insight, therapeutic alliance formation, catharsis, self-disclosure, symptom…

  1. Insights into the relationships among capillary pressure, saturation, interfacial area and relative permeability using pore-network modeling

    NARCIS (Netherlands)

    Joekar-Niasar, V.; Hassanizadeh, S.M.; Leijnse, A.

    2008-01-01

    To gain insight in relationships among capillary pressure, interfacial area, saturation, and relative permeability in two-phase flow in porous media, we have developed two types of pore-network models. The first one, called tube model, has only one element type, namely pore throats. The second one

  2. Insights into the Relationships Among Capillary Pressure, Saturation, Interfacial Area and Relative Permeability Using Pore-Network Modeling

    NARCIS (Netherlands)

    Joekar-Niasar, V.; Hassanizadeh, S.M.; Leijnse, A.

    To gain insight in relationships among capillary pressure, interfacial area, saturation, and relative permeability in two-phase flow in porous media, we have developed two types of pore-network models. The first one, called tube model, has only one element type, namely pore throats. The second one

  3. Optimization of Catheter Ablation of Atrial Fibrillation: Insights Gained from Clinically-Derived Computer Models

    Directory of Open Access Journals (Sweden)

    Jichao Zhao

    2015-05-01

    Full Text Available Atrial fibrillation (AF is the most common heart rhythm disturbance, and its treatment is an increasing economic burden on the health care system. Despite recent intense clinical, experimental and basic research activity, the treatment of AF with current antiarrhythmic drugs and catheter/surgical therapies remains limited. Radiofrequency catheter ablation (RFCA is widely used to treat patients with AF. Current clinical ablation strategies are largely based on atrial anatomy and/or substrate detected using different approaches, and they vary from one clinical center to another. The nature of clinical ablation leads to ambiguity regarding the optimal patient personalization of the therapy partly due to the fact that each empirical configuration of ablation lines made in a patient is irreversible during one ablation procedure. To investigate optimized ablation lesion line sets, in silico experimentation is an ideal solution. 3D computer models give us a unique advantage to plan and assess the effectiveness of different ablation strategies before and during RFCA. Reliability of in silico assessment is ensured by inclusion of accurate 3D atrial geometry, realistic fiber orientation, accurate fibrosis distribution and cellular kinetics; however, most of this detailed information in the current computer models is extrapolated from animal models and not from the human heart. The predictive power of computer models will increase as they are validated with human experimental and clinical data. To make the most from a computer model, one needs to develop 3D computer models based on the same functionally and structurally mapped intact human atria with high spatial resolution. The purpose of this review paper is to summarize recent developments in clinically-derived computer models and the clinical insights they provide for catheter ablation.

  4. Analytical modeling provides new insight into complex mutual coupling between surface loops at ultrahigh fields.

    Science.gov (United States)

    Avdievich, N I; Pfrommer, A; Giapitzakis, I A; Henning, A

    2017-10-01

    Ultrahigh-field (UHF) (≥7 T) transmit (Tx) human head surface loop phased arrays improve both the Tx efficiency (B 1 + /√P) and homogeneity in comparison with single-channel quadrature Tx volume coils. For multi-channel arrays, decoupling becomes one of the major problems during the design process. Further insight into the coupling between array elements and its dependence on various factors can facilitate array development. The evaluation of the entire impedance matrix Z for an array loaded with a realistic voxel model or phantom is a time-consuming procedure when performed using electromagnetic (EM) solvers. This motivates the development of an analytical model, which could provide a quick assessment of the Z-matrix. In this work, an analytical model based on dyadic Green's functions was developed and validated using an EM solver and bench measurements. The model evaluates the complex coupling, including both the electric (mutual resistance) and magnetic (mutual inductance) coupling. Validation demonstrated that the model does well to describe the coupling at lower fields (≤3 T). At UHFs, the model also performs well for a practical case of low magnetic coupling. Based on the modeling, the geometry of a 400-MHz, two-loop transceiver array was optimized, such that, by simply overlapping the loops, both the mutual inductance and the mutual resistance were compensated at the same time. As a result, excellent decoupling (below -40 dB) was obtained without any additional decoupling circuits. An overlapped array prototype was compared (signal-to-noise ratio, Tx efficiency) favorably to a gapped array, a geometry which has been utilized previously in designs of UHF Tx arrays. Copyright © 2017 John Wiley & Sons, Ltd.

  5. Hydroclimatology of Dual-Peak Annual Cholera Incidence: Insights from a Spatially Explicit Model

    Science.gov (United States)

    Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.; Rinaldo, A.

    2012-12-01

    modeling framework suggests insights on how environmental drivers concert the generation of complex spatiotemporal infections and proposes an explanation for the different cholera patterns (dual or single annual peaks) exhibited by regions that share similar hydroclimatological forcings.

  6. Insight in Psychosis: An Indicator of Severity of Psychosis, an Explanatory Model of Illness, and a Coping Strategy

    Science.gov (United States)

    Jacob, K. S.

    2016-01-01

    Recent studies related to insight, explanatory models (EMs) of illness and their relationship to outcome of psychosis are reviewed. The traditional argument that insight predicts outcome in psychosis is not supported by recent longitudinal data, which has been analyzed using multivariable statistics that adjust for severity and quality of illness. While all cognition will have a neurobiological representation, if “insight” is related to the primary psychotic process, then insight cannot be seen as an independent predictor of outcome but a part of the progression of illness. The evidence suggests insight, like all EMs, is belief which interacts with the trajectory of the person's illness and the local culture to produce a unique understanding of the illness for the particular individual and his/her family. PMID:27335513

  7. Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield

    Science.gov (United States)

    Xiong, Wei; Skalský, Rastislav; Porter, Cheryl H.; Balkovič, Juraj; Jones, James W.; Yang, Di

    2016-09-01

    Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical data sets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global-gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter result in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation.

  8. 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...

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    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...

  10. 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

  11. 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

  12. 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.

  13. 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

  14. 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 ...

  15. Modeling fMRI signals can provide insights into neural processing in the cerebral cortex.

    Science.gov (United States)

    Vanni, Simo; Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

    2015-08-01

    Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. Copyright © 2015 the American Physiological Society.

  16. 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

  17. Biology and therapy of inherited retinal degenerative disease: insights from mouse models

    Science.gov (United States)

    Veleri, Shobi; Lazar, Csilla H.; Chang, Bo; Sieving, Paul A.; Banin, Eyal; Swaroop, Anand

    2015-01-01

    Retinal neurodegeneration associated with the dysfunction or death of photoreceptors is a major cause of incurable vision loss. Tremendous progress has been made over the last two decades in discovering genes and genetic defects that lead to retinal diseases. The primary focus has now shifted to uncovering disease mechanisms and designing treatment strategies, especially inspired by the successful application of gene therapy in some forms of congenital blindness in humans. Both spontaneous and laboratory-generated mouse mutants have been valuable for providing fundamental insights into normal retinal development and for deciphering disease pathology. Here, we provide a review of mouse models of human retinal degeneration, with a primary focus on diseases affecting photoreceptor function. We also describe models associated with retinal pigment epithelium dysfunction or synaptic abnormalities. Furthermore, we highlight the crucial role of mouse models in elucidating retinal and photoreceptor biology in health and disease, and in the assessment of novel therapeutic modalities, including gene- and stem-cell-based therapies, for retinal degenerative diseases. PMID:25650393

  18. Biology and therapy of inherited retinal degenerative disease: insights from mouse models

    Directory of Open Access Journals (Sweden)

    Shobi Veleri

    2015-02-01

    Full Text Available Retinal neurodegeneration associated with the dysfunction or death of photoreceptors is a major cause of incurable vision loss. Tremendous progress has been made over the last two decades in discovering genes and genetic defects that lead to retinal diseases. The primary focus has now shifted to uncovering disease mechanisms and designing treatment strategies, especially inspired by the successful application of gene therapy in some forms of congenital blindness in humans. Both spontaneous and laboratory-generated mouse mutants have been valuable for providing fundamental insights into normal retinal development and for deciphering disease pathology. Here, we provide a review of mouse models of human retinal degeneration, with a primary focus on diseases affecting photoreceptor function. We also describe models associated with retinal pigment epithelium dysfunction or synaptic abnormalities. Furthermore, we highlight the crucial role of mouse models in elucidating retinal and photoreceptor biology in health and disease, and in the assessment of novel therapeutic modalities, including gene- and stem-cell-based therapies, for retinal degenerative diseases.

  19. 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.

  20. A COMPARATIVE STUDY OF FORECASTING MODELS FOR TREND AND SEASONAL TIME SERIES DOES COMPLEX MODEL ALWAYS YIELD BETTER FORECAST THAN SIMPLE MODELS

    Directory of Open Access Journals (Sweden)

    Suhartono Suhartono

    2005-01-01

    Full Text Available Many business and economic time series are non-stationary time series that contain trend and seasonal variations. Seasonality is a periodic and recurrent pattern caused by factors such as weather, holidays, or repeating promotions. A stochastic trend is often accompanied with the seasonal variations and can have a significant impact on various forecasting methods. In this paper, we will investigate and compare some forecasting methods for modeling time series with both trend and seasonal patterns. These methods are Winter's, Decomposition, Time Series Regression, ARIMA and Neural Networks models. In this empirical research, we study on the effectiveness of the forecasting performance, particularly to answer whether a complex method always give a better forecast than a simpler method. We use a real data, that is airline passenger data. The result shows that the more complex model does not always yield a better result than a simpler one. Additionally, we also find the possibility to do further research especially the use of hybrid model by combining some forecasting method to get better forecast, for example combination between decomposition (as data preprocessing and neural network model.

  1. The physiology of blood loss and shock: New insights from a human laboratory model of hemorrhage.

    Science.gov (United States)

    Schiller, Alicia M; Howard, Jeffrey T; Convertino, Victor A

    2017-04-01

    The ability to quickly diagnose hemorrhagic shock is critical for favorable patient outcomes. Therefore, it is important to understand the time course and involvement of the various physiological mechanisms that are active during volume loss and that have the ability to stave off hemodynamic collapse. This review provides new insights about the physiology that underlies blood loss and shock in humans through the development of a simulated model of hemorrhage using lower body negative pressure. In this review, we present controlled experimental results through utilization of the lower body negative pressure human hemorrhage model that provide novel insights on the integration of physiological mechanisms critical to the compensation for volume loss. We provide data obtained from more than 250 human experiments to classify human subjects into two distinct groups: those who have a high tolerance and can compensate well for reduced central blood volume (e.g. hemorrhage) and those with low tolerance with poor capacity to compensate.We include the conceptual introduction of arterial pressure and cerebral blood flow oscillations, reflex-mediated autonomic and neuroendocrine responses, and respiration that function to protect adequate tissue oxygenation through adjustments in cardiac output and peripheral vascular resistance. Finally, unique time course data are presented that describe mechanistic events associated with the rapid onset of hemodynamic failure (i.e. decompensatory shock). Impact Statement Hemorrhage is the leading cause of death in both civilian and military trauma. The work submitted in this review is important because it advances the understanding of mechanisms that contribute to the total integrated physiological compensations for inadequate tissue oxygenation (i.e. shock) that arise from hemorrhage. Unlike an animal model, we introduce the utilization of lower body negative pressure as a noninvasive model that allows for the study of progressive

  2. Using Small Models for Big Issues : Exploratory System Dynamics Modelling and Analysis for Insightful Crisis Management

    NARCIS (Netherlands)

    Pruyt, E.

    2010-01-01

    The main goal of this paper is to explain and illustrate different exploratory uses of small System Dynamics models for analysis and decision support in case of dynamically complex issues that are deeply uncertain. The applied focuss of the paper is the field of inter/national safety and security.

  3. 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.

  4. 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...

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. Insights into the pathophysiology of ankylosing spondylitis: contributions from animal models.

    Science.gov (United States)

    Braem, Kirsten; Lories, Rik J

    2012-05-01

    The introduction of anti-tumor necrosis factor strategies has significantly changed the perspective and outcome of patients with ankylosing spondylitis and related spondyloarthritides. This breakthrough has also boosted further research efforts into the mechanisms of disease. As human tissue specimens of the spine and sacroiliac joints are very difficult to obtain and rarely allow mechanistic studies, most of the new concepts have emerged from different animal models of disease. In this review, we summarize insights into the role of HLA-B27 based on transgenic rat and mouse models, efforts into the identification of cell populations stimulating inflammation and molecular studies of pathological bone formation leading to ankylosis. Important progress has been made and novel hypotheses were put forward. These include the impact of HLA-B27 on endoplasmic reticulum stress and the unfolded protein response, the role of stromal cells in inflammation, the entheseal stress hypothesis and the identification of the bone morphogenetic protein and WNT signaling pathways as therapeutic targets for ankylosis. Copyright © 2011 Société française de rhumatologie. Published by Elsevier SAS. All rights reserved.

  11. Policy insights from the nutritional food market transformation model: the case of obesity prevention.

    Science.gov (United States)

    Struben, Jeroen; Chan, Derek; Dubé, Laurette

    2014-12-01

    This paper presents a system dynamics policy model of nutritional food market transformation, tracing over-time interactions between the nutritional quality of supply, consumer food choice, population health, and governmental policy. Applied to the Canadian context and with body mass index as the primary outcome, we examine policy portfolios for obesity prevention, including (1) industry self-regulation efforts, (2) health- and nutrition-sensitive governmental policy, and (3) efforts to foster health- and nutrition-sensitive innovation. This work provides novel theoretical and practical insights on drivers of nutritional market transformations, highlighting the importance of integrative policy portfolios to simultaneously shift food demand and supply for successful and self-sustaining nutrition and health sensitivity. We discuss model extensions for deeper and more comprehensive linkages of nutritional food market transformation with supply, demand, and policy in agrifood and health/health care. These aim toward system design and policy that can proactively, and with greater impact, scale, and resilience, address single as well as double malnutrition in varying country settings. © 2014 New York Academy of Sciences.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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...

  17. Insights from Modeling the Integrated Climate, Biogeochemical Cycles, Human Activities and Their Interactions in the ACME Earth System Model

    Science.gov (United States)

    Leung, L. R.; Thornton, P. E.; Riley, W. J.; Calvin, K. V.

    2017-12-01

    Towards the goal of understanding the contributions from natural and managed systems to current and future greenhouse gas fluxes and carbon-climate and carbon-CO2 feedbacks, efforts have been underway to improve representations of the terrestrial, river, and human components of the ACME earth system model. Broadly, our efforts include implementation and comparison of approaches to represent the nutrient cycles and nutrient limitations on ecosystem production, extending the river transport model to represent sediment and riverine biogeochemistry, and coupling of human systems such as irrigation, reservoir operations, and energy and land use with the ACME land and river components. Numerical experiments have been designed to understand how terrestrial carbon, nitrogen, and phosphorus cycles regulate climate system feedbacks and the sensitivity of the feedbacks to different model treatments, examine key processes governing sediment and biogeochemistry in the rivers and their role in the carbon cycle, and exploring the impacts of human systems in perturbing the hydrological and carbon cycles and their interactions. This presentation will briefly introduce the ACME modeling approaches and discuss preliminary results and insights from numerical experiments that lay the foundation for improving understanding of the integrated climate-biogeochemistry-human system.

  18. 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.

  19. Insights into Working Memory from The Perspective of The EPIC Architecture for Modeling Skilled Perceptual-Motor and Cognitive Human Performance

    National Research Council Canada - National Science Library

    Kieras, David

    1998-01-01

    Computational modeling of human perceptual-motor and cognitive performance based on a comprehensive detailed information- processing architecture leads to new insights about the components of working memory...

  20. Insights about data assimilation frameworks for integrating GRACE with hydrological models

    Science.gov (United States)

    Schumacher, Maike; Kusche, Jürgen; Van Dijk, Albert I. J. M.; Döll, Petra; Schuh, Wolf-Dieter

    2016-04-01

    Improving the understanding of changes in the water cycle represents a challenging objective that requires merging information from various disciplines. Debates exist on selecting an appropriate assimilation technique to integrate GRACE-derived terrestrial water storage changes (TWSC) into hydrological models in order to downscale and disaggregate GRACE TWSC, overcome model limitations, and improve monitoring and forecast skills. Yet, the effect of the specific data assimilation technique in conjunction with ill-conditioning, colored noise, resolution mismatch between GRACE and model, and other complications is still unclear. Due to its simplicity, ensemble Kalman filters or smoothers (EnKF/S) are often applied. In this study, we show that modification of the filter approach might open new avenues to improve the integration process. Particularly, we discuss an improved calibration and data assimilation (C/DA) framework (Schumacher et al., 2016), which is based on the EnKF and was extended by the square root analysis scheme (SQRA) and the singular evolutive interpolated Kalman (SEIK) filter. In addition, we discuss an off-line data blending approach (Van Dijk et al., 2014) that offers the chance to merge multi-model ensembles with GRACE observations. The investigations include: (i) a theoretical comparison, focusing on similarities and differences of the conceptual formulation of the filter algorithms, (ii) a practical comparison, for which the approaches were applied to an ensemble of runs of the WaterGAP Global Hydrology Model (WGHM), as well as (iii) an impact assessment of the GRACE error structure on C/DA results. First, a synthetic experiment over the Mississippi River Basin (USA) was used to gain insights about the C/DA set-up before applying it to real data. The results indicated promising performances when considering alternative methods, e.g. applying the SEIK algorithm improved the correlation coefficient and root mean square error (RMSE) of TWSC by 0

  1. Nitrogen Fixation by Gliding Arc Plasma: Better Insight by Chemical Kinetics Modelling.

    Science.gov (United States)

    Wang, Weizong; Patil, Bhaskar; Heijkers, Stjin; Hessel, Volker; Bogaerts, Annemie

    2017-05-22

    The conversion of atmospheric nitrogen into valuable compounds, that is, so-called nitrogen fixation, is gaining increased interest, owing to the essential role in the nitrogen cycle of the biosphere. Plasma technology, and more specifically gliding arc plasma, has great potential in this area, but little is known about the underlying mechanisms. Therefore, we developed a detailed chemical kinetics model for a pulsed-power gliding-arc reactor operating at atmospheric pressure for nitrogen oxide synthesis. Experiments are performed to validate the model and reasonable agreement is reached between the calculated and measured NO and NO 2 yields and the corresponding energy efficiency for NO x formation for different N 2 /O 2 ratios, indicating that the model can provide a realistic picture of the plasma chemistry. Therefore, we can use the model to investigate the reaction pathways for the formation and loss of NO x . The results indicate that vibrational excitation of N 2 in the gliding arc contributes significantly to activating the N 2 molecules, and leads to an energy efficient way of NO x production, compared to the thermal process. Based on the underlying chemistry, the model allows us to propose solutions on how to further improve the NO x formation by gliding arc technology. Although the energy efficiency of the gliding-arc-based nitrogen fixation process at the present stage is not comparable to the world-scale Haber-Bosch process, we believe our study helps us to come up with more realistic scenarios of entering a cutting-edge innovation in new business cases for the decentralised production of fertilisers for agriculture, in which low-temperature plasma technology might play an important role. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Sludge reduction by ozone: Insights and modeling of the dose-response effects.

    Science.gov (United States)

    Fall, C; Silva-Hernández, B C; Hooijmans, C M; Lopez-Vazquez, C M; Esparza-Soto, M; Lucero-Chávez, M; van Loosdrecht, M C M

    2018-01-15

    Applying ozone to the return flow in an activated sludge (AS) process is a way for reducing the residual solids production. To be able to extend the activated sludge models to the ozone-AS process, adequate prediction of the tri-atoms effects on the particulate COD fractions is needed. In this study, the biomass inactivation, COD mineralization, and solids dissolution were quantified in batch tests and dose-response models were developed as a function of the reacted ozone doses (ROD). Three kinds of model-sludge were used. S1 was a lab-cultivated synthetic sludge with two components (heterotrophs X H and X P ). S2 was a digestate of S1 almost made by the endogenous residues, X P . S3 was from a municipal activated sludge plant. The specific ozone uptake rate (SO 3 UR, mgO 3 /gCOD.h) was determined as a tool for characterizing the reactivity of the sludges. SO 3 UR increased with the X H fraction and decreased with more X P . Biomass inactivation was exponential (e -β.ROD ) as a function of the ROD doses. The percentage of solids reduction was predictable through a linear model (C Miner  + Y sol ROD), with a fixed part due to mineralization (C Miner ) and a variable part from the solubilization process. The parameters of the models, i.e. the inactivation and the dissolution yields (β, 0.008-0.029 (mgO 3 /mgCOD ini ) -1 vs Y sol , 0.5-2.8 mg COD sol /mgO 3 ) varied in magnitude, depending on the intensity of the scavenging reactions and potentially the compactness of the flocs for each sludge. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. 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)

  4. Security of supply and retail competition in the European gas market. Some model-based insights

    International Nuclear Information System (INIS)

    Abada, Ibrahim; Massol, Olivier

    2011-04-01

    In this paper, we analyze the impact of uncertain disruptions in gas supply upon gas retailer contracting behavior and consequent price and welfare implications in a gas market characterized by long-term gas contracts using a static Cournot model. In order to most realistically describe the economical situation, our representation divides the market into two stages: the upstream market that links, by means of long-term contracts, producers in exporting countries (Russia, Algeria, etc.) to local retailers who bring gas to the consuming countries to satisfy local demands in the downstream market. Disruption costs are modeled using short-run demand functions. First we mathematically develop a general model and write the associated KKT conditions, then we propose some case studies, under iso-elasticity assumptions, for the long-short-run inverse-demand curves in order to predict qualitatively and quantitatively the impacts of supply disruptions on Western European gas trade. In the second part, we study in detail the German gas market of the 1980's to explain the supply choices of the German retailer, and we derive interesting conclusions and insights concerning the amounts and prices of natural gas brought to the market. The last part of the paper is dedicated to a study of the Bulgarian gas market, which is greatly dependent on the Russian gas supplies and hence very sensitive to interruption risks. Some interesting conclusions are derived concerning the necessity to economically regulate the market, by means of gas amounts control, if the disruption probability is high enough. (authors)

  5. Sources of Sahelian-Sudan moisture: Insights from a moisture-tracing atmospheric model

    Science.gov (United States)

    Salih, Abubakr A. M.; Zhang, Qiong; Pausata, Francesco S. R.; Tjernström, Michael

    2016-07-01

    The summer rainfall across Sahelian-Sudan is one of the main sources of water for agriculture, human, and animal needs. However, the rainfall is characterized by large interannual variability, which has attracted extensive scientific efforts to understand it. This study attempts to identify the source regions that contribute to the Sahelian-Sudan moisture budget during July through September. We have used an atmospheric general circulation model with an embedded moisture-tracing module (Community Atmosphere Model version 3), forced by observed (1979-2013) sea-surface temperatures. The result suggests that about 40% of the moisture comes with the moisture flow associated with the seasonal migration of the Intertropical Convergence Zone (ITCZ) and originates from Guinea Coast, central Africa, and the Western Sahel. The Mediterranean Sea, Arabian Peninsula, and South Indian Ocean regions account for 10.2%, 8.1%, and 6.4%, respectively. Local evaporation and the rest of the globe supply the region with 20.3% and 13.2%, respectively. We also compared the result from this study to a previous analysis that used the Lagrangian model FLEXPART forced by ERA-Interim. The two approaches differ when comparing individual regions, but are in better agreement when neighboring regions of similar atmospheric flow features are grouped together. Interannual variability with the rainfall over the region is highly correlated with contributions from regions that are associated with the ITCZ movement, which is in turn linked to the Atlantic Multidecadal Oscillation. Our result is expected to provide insights for the effort on seasonal forecasting of the rainy season over Sahelian Sudan.

  6. Structural insights into high density lipoprotein: Old models and new facts

    Directory of Open Access Journals (Sweden)

    Valentin eGogonea

    2016-01-01

    Full Text Available The physiological link between circulating high density lipoprotein (HDL levels and cardiovascular disease is well documented, albeit its intricacies are not well understood. An improved appreciation of HDL function and overall role in vascular health and disease requires at its foundation a better understanding of the lipoprotein's molecular structure, its formation, and its process of maturation through interactions with various plasma enzymes and cell receptors that intervene along the pathway of reverse cholesterol transport. This review focuses on summarizing recent developments in the field of lipid free apoA-I and HDL structure, with emphasis on new insights revealed by newly published nascent and spherical HDL models constructed by combining low resolution structures obtained from small angle neutron scattering (SANS with contrast variation and geometrical constraints derived from hydrogen-deuterium exchange (HDX, crosslinking mass spectrometry, electron microscopy, Förster resonance energy transfer, and electron spin resonance. Recently published low resolution structures of nascent and spherical HDL obtained from SANS with contrast variation and isotopic labeling of apolipoprotein A-I (apoA-I will be critically reviewed and discussed in terms of how they accommodate existing biophysical structural data from alternative approaches. The new low resolution structures revealed and also provided some answers to long standing questions concerning lipid organization and particle maturation of lipoproteins. The review will discuss the merits of newly proposed SANS based all atom models for nascent and spherical HDL, and compare them with accepted models. Finally, naturally occurring and bioengineered mutations in apoA-I, and their impact on HDL phenotype, are reviewed and discuss together with new therapeutics employed for restoring HDL function.

  7. Modeling Huntington disease in Drosophila: Insights into axonal transport defects and modifiers of toxicity.

    Science.gov (United States)

    Krench, Megan; Littleton, J Troy

    2013-01-01

    Huntington disease (HD) is an inherited neurodegenerative disorder caused by a polyglutamine (polyQ) expansion in the huntingtin (Htt) gene. Despite years of research, there is no treatment that extends life for patients with the disorder. Similarly, little is known about which cellular pathways that are altered by pathogenic Huntingtin (Htt) protein expression are correlated with neuronal loss. As part of a longstanding effort to gain insights into HD pathology, we have been studying the protein in the context of the fruitfly Drosophila melanogaster. We generated transgenic HD models in Drosophila by engineering flies that carry a 12-exon fragment of the human Htt gene with or without the toxic trinucleotide repeat expansion. We also created variants with a monomeric red fluorescent protein (mRFP) tag fused to Htt that allows in vivo imaging of Htt protein localization and aggregation. While wild-type Htt remains diffuse throughout the cytoplasm of cells, pathogenic Htt forms insoluble aggregates that accumulate in neuronal soma and axons. Aggregates can physically block transport of numerous organelles along the axon. We have also observed that aggregates are formed quickly, within just a few hours of mutant Htt expression. To explore mechanisms of neurodegeneration in our HD model, we performed in vivo and in vitro screens to search for modifiers of viability and pathogenic Htt aggregation. Our results identified several novel candidates for HD therapeutics that can now be tested in mammalian models of HD. Furthermore, these experiments have highlighted the complex relationship between aggregates and toxicity that exists in HD.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. Inactive and active states and supramolecular organization of GPCRs: insights from computational modeling

    Science.gov (United States)

    Fanelli, Francesca; De Benedetti, Pier G.

    2006-08-01

    Herein we make an overview of the results of our computational experiments aimed at gaining insight into the molecular mechanisms of GPCR functioning either in their normal conditions or when hit by gain-of-function or loss-of-function mutations. Molecular simulations of a number of GPCRs in their wild type and mutated as well as free and ligand-bound forms were instrumental in inferring the structural features, which differentiate the mutation- and ligand-induced active from the inactive states. These features essentially reside in the interaction pattern of the E/DRY arginine and in the degree of solvent exposure of selected cytosolic domains. Indeed, the active states differ from the inactive ones in the weakening of the interactions made by the highly conserved arginine and in the increase in solvent accessibility of the cytosolic interface between helices 3 and 6. Where possible, the structural hallmarks of the active and inactive receptor states are translated into molecular descriptors useful for in silico functional screening of novel receptor mutants or ligands. Computational modeling of the supramolecular organization of GPCRs and their intracellular partners is the current challenge toward a deep understanding of their functioning mechanisms.

  13. Cognitive Enhancers for Facilitating Drug Cue Extinction: Insights from Animal Models

    Science.gov (United States)

    Nic Dhonnchadha, Bríd Áine; Kantak, Kathleen M.

    2011-01-01

    Given the success of cue exposure (extinction) therapy combined with a cognitive enhancer for reducing anxiety, it is anticipated that this approach will prove more efficacious than exposure therapy alone in preventing relapse in individuals with substance use disorders. Several factors may undermine the efficacy of exposure therapy for substance use disorders, but we suspect that neurocognitive impairments associated with chronic drug use are an important contributing factor. Numerous insights on these issues are gained from research using animal models of addiction. In this review, the relationship between brain sites whose learning, memory and executive functions are impaired by chronic drug use and brain sites that are important for effective drug cue extinction learning is explored first. This is followed by an overview of animal research showing improved treatment outcome for drug addiction (e.g. alcohol, amphetamine, cocaine, heroin) when explicit extinction training is conducted in combination with acute dosing of a cognitive-enhancing drug. The mechanism by which cognitive enhancers are thought to exert their benefits is by facilitating consolidation of drug cue extinction memory after activation of glutamatergic receptors. Based on the encouraging work in animals, factors that may be important for the treatment of drug addiction are considered. PMID:21295059

  14. 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.

  15. 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

  16. 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.

  17. 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

  18. Dilatant normal faulting in jointed cohesive rocks: insights from physical modeling

    Science.gov (United States)

    Kettermann, Michael; von Hagke, Christoph; Urai, Janos

    2016-04-01

    Dilatant faults often form in rocks containing pre-existing joints, but the effects of joints on fault segment linkage and fracture connectivity is not well understood. Studying evolution of dilatancy and influence of fractures on fault development provides insights on geometry of fault zones in brittle rocks and eventually allows for predicting their subsurface appearance. We assess the evolution of dilatant faults in fractured rocks using analogue models with cohesive powder. The upper layer contains pre-formed joint sets, and we vary the angle between joints and a rigid basement fault in our experiments. Analogue models were carried out in a manually driven deformation box (30x28x20 cm) with a 60° dipping pre-defined basement fault and 4.5 cm of displacement. To produce open joints prior to faulting, sheets of paper were mounted in the box to a depth of 5 cm at a spacing of 2.5 cm. Powder was then sieved into the box, embedding the paper almost entirely (column height of 19 cm), and the paper was removed. We tested the influence of different angles between the strike of the basement fault and the joint set (joint fault (JF) angles of 0°, 4°, 8°, 12°, 16°, 20°, and 25°). During deformation we captured structural information by time-lapse photography that allows particle imaging velocimetry analyses (PIV) to detect localized deformation at every increment of displacement. Post-mortem photogrammetry preserves the final 3-dimensional structure of the fault zone. Results show robust structural features in models: damage zone width increases by about 50 % and the number of secondary fractures within this zone by more than 100 % with increasing JF-angle. Interestingly, the map-view area fraction of open gaps increases by only 3%. Secondary joints and fault step-overs are oriented at a high angle to the primary joint orientation. Due to the length of the pre-existing open joints, areas far beyond the fractured regions are connected to the system. In contrast

  19. Zebrafish models of non-canonical Wnt/planar cell polarity signalling: fishing for valuable insight into vertebrate polarized cell behavior.

    Science.gov (United States)

    Jussila, Maria; Ciruna, Brian

    2017-05-01

    Planar cell polarity (PCP) coordinates the uniform orientation, structure and movement of cells within the plane of a tissue or organ system. It is beautifully illustrated in the polarized arrangement of bristles and hairs that project from specialized cell surfaces of the insect abdomen and wings, and pioneering genetic studies using the fruit fly, Drosophila melanogaster, have defined a core signalling network underlying PCP. This core PCP/non-canonical Wnt signalling pathway is evolutionarily conserved, and studies in zebrafish have helped transform our understanding of PCP from a peculiarity of polarized epithelia to a more universal cellular property that orchestrates a diverse suite of polarized cell behaviors that are required for normal vertebrate development. Furthermore, application of powerful genetics, embryonic cell-transplantation, and live-imaging capabilities afforded by the zebrafish model have yielded novel insights into the establishment and maintenance of vertebrate PCP, over the course of complex and dynamic morphogenetic events like gastrulation and neural tube morphogenesis. Although key questions regarding vertebrate PCP remain, with the emergence of new genome-editing technologies and the promise of endogenous labeling and Cre/LoxP conditional targeting strategies, zebrafish remains poised to deliver fundamental new insights into the function and molecular dynamic regulation of PCP signalling from embryonic development through to late-onset phenotypes and adult disease states. WIREs Dev Biol 2017, 6:e267. doi: 10.1002/wdev.267 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

  20. 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...

  1. Introductory lecture: atmospheric organic aerosols: insights from the combination of measurements and chemical transport models.

    Science.gov (United States)

    Pandis, Spyros N; Donahue, Neil M; Murphy, Benjamin N; Riipinen, Ilona; Fountoukis, Christos; Karnezi, Eleni; Patoulias, David; Skyllakou, Ksakousti

    2013-01-01

    The formation, atmospheric evolution, properties, and removal of organic particulate matter remain some of the least understood aspects of atmospheric chemistry despite the importance of organic aerosol (OA) for both human health and climate change. Here, we summarize our recent efforts to deal with the chemical complexity of the tens of thousands of organic compounds in the atmosphere using the volatility-oxygen content framework (often called the 2D-Volatility Basis Set, 2D-VBS). Our current ability to measure the ambient OA concentration as a function of its volatility and oxygen to carbon (O:C) ratio is evaluated. The combination of a thermodenuder, isothermal dilution and Aerosol Mass Spectrometry (AMS) together with a mathematical aerosol dynamics model is a promising approach. The development of computational modules based on the 2D-VBS that can be used in chemical transport models (CTMs) is described. Approaches of different complexity are tested against ambient observations, showing the challenge of simulating the complex chemical evolution of atmospheric OA. The results of the simplest approach describing the net change due to functionalization and fragmentation are quite encouraging, reproducing both the observed OA levels and O : C in a variety of conditions. The same CTM coupled with source-apportionment algorithms can be used to gain insights into the travel distances and age of atmospheric OA. We estimate that the average age of OA near the ground in continental locations is 1-2 days and most of it was emitted (either as precursor vapors or particles) hundreds of kilometers away. Condensation of organic vapors on fresh particles is critical for the growth of these new particles to larger sizes and eventually to cloud condensation nuclei (CCN) sizes. The semivolatile organics currently simulated by CTMs are too volatile to condense on these tiny particles with high curvature. We show that chemical aging reactions converting these semivolatile

  2. Water security, risk, and economic growth: Insights from a dynamical systems model

    Science.gov (United States)

    Dadson, Simon; Hall, Jim W.; Garrick, Dustin; Sadoff, Claudia; Grey, David; Whittington, Dale

    2017-08-01

    Investments in the physical infrastructure, human capital, and institutions needed for water resources management have been noteworthy in the development of most civilizations. These investments affect the economy in two distinct ways: (i) by improving the factor productivity of water in multiple economic sectors, especially those that are water intensive such as agriculture and energy and (ii) by reducing acute and chronic harmful effects of water-related hazards like floods, droughts, and water-related diseases. The need for capital investment to mitigate risks and promote economic growth is widely acknowledged, but prior conceptual work on the relationship between water-related investments and economic growth has focused on the productive and harmful roles of water in the economy independently. Here the two influences are combined using a simple, dynamical systems model of water-related investment, risk, and growth. In cases where initial water security is low, initial investment in water-related assets enables growth. Without such investment, losses due to water-related hazards exert a drag on economic growth and may create a poverty trap. The presence and location of the poverty trap is context-specific and depends on the exposure of productive water-related assets to water-related risk. Exogenous changes in water-related risk can potentially push an economy away from a growth path toward a poverty trap. Our investigation shows that an inverted-U-shaped investment relation between the level of investment in water security and the current level of water security leads to faster rates of growth than the alternatives that we consider here, and that this relation is responsible for the "S"-curve that is posited in the literature. These results illustrate the importance of accounting for environmental and health risks in economic models and offer insights for the design of robust policies for investment in water-related productive assets to manage risk, in the face

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. An integrated Biophysical CGE model to provide Sustainable Development Goal insights

    Science.gov (United States)

    Sanchez, Marko; Cicowiez, Martin; Howells, Mark; Zepeda, Eduardo

    2016-04-01

    Future projected changes in the energy system will inevitably result in changes to the level of appropriation of environmental resources, particularly land and water, and this will have wider implications for environmental sustainability, and may affect other sectors of the economy. An integrated climate, land, energy and water (CLEW) system will provide useful insights, particularly with regard to the environmental sustainability. However, it will require adequate integration with other tools to detect economic impacts and broaden the scope for policy analysis. A computable general equilibrium (CGE) model is a well suited tool to channel impacts, as detected in a CLEW analysis, onto all sectors of the economy, and evaluate trade-offs and synergies, including those of possible policy responses. This paper will show an application of such integration in a single-country CGE model with the following key characteristics. Climate is partly exogenous (as proxied by temperature and rainfall) and partly endogenous (as proxied by emissions generated by different sectors) and has an impact on endogenous variables such as land productivity and labor productivity. Land is a factor of production used in agricultural and forestry activities which can be of various types if land use alternatives (e.g., deforestation) are to be considered. Energy is an input to the production process of all economic sectors and a consumption good for households. Because it is possible to allow for substitution among different energy sources (e.g. renewable vs non-renewable) in the generation of electricity, the production process of energy products can consider the use of natural resources such as oil and water. Water, data permitting, can be considered as an input into the production process of agricultural sectors, which is particularly relevant in case of irrigation. It can also be considered as a determinant of total factor productivity in hydro-power generation. The integration of a CLEW

  10. Mechanism for cyclization reaction by clavaminic acid synthase. Insights from modeling studies.

    Science.gov (United States)

    Borowski, Tomasz; de Marothy, Sven; Broclawik, Ewa; Schofield, Christopher J; Siegbahn, Per E M

    2007-03-27

    The mechanism of the oxidative cyclization reaction catalyzed by clavaminic acid synthase (CAS) was studied in silico. First, a classical molecular dynamics (MD) simulation was performed to obtain a realistic structure of the CAS-Fe(IV)=O-succinate-substrate complex; then potential of mean force (PMF) was calculated to assess the feasibility of the beta-lactam ring, more specifically its C4' corner, approaching the oxo atom. Based on the MD structure, a relatively large model of the active site region was selected and used in the B3LYP investigation of the reaction mechanism. The computational results suggest that once the oxoferryl species is formed, the oxidative cyclization catalyzed by CAS most likely involves either a mechanism involving C4'(S)-H bond cleavage of the monocyclic beta-lactam ring, or a biosynthetically unprecedented mechanism comprising (1) oxidation of the hydroxyl group of PCA to an O-radical, (2) retro-aldol-like decomposition of the O-radical to an aldehyde and a C-centered radical, which is stabilized by the captodative effect, (3) abstraction of a hydrogen atom from the C4'(S) position of the C-centered radical by the Fe(III)-OH species yielding an azomethine ylide, and (4) 1,3-dipolar cycloaddition to the ylide with aldehyde acting as a dipolarophile. Precedent for the new proposed mechanism comes from the reported synthesis of oxapenams via 1,3-dipolar cycloaddition reactions of aldehydes and ketones.

  11. Quantitative Hydraulic Models Of Early Land Plants Provide Insight Into Middle Paleozoic Terrestrial Paleoenvironmental Conditions

    Science.gov (United States)

    Wilson, J. P.; Fischer, W. W.

    2010-12-01

    Fossil plants provide useful proxies of Earth’s climate because plants are closely connected, through physiology and morphology, to the environments in which they lived. Recent advances in quantitative hydraulic models of plant water transport provide new insight into the history of climate by allowing fossils to speak directly to environmental conditions based on preserved internal anatomy. We report results of a quantitative hydraulic model applied to one of the earliest terrestrial plants preserved in three dimensions, the ~396 million-year-old vascular plant Asteroxylon mackei. This model combines equations describing the rate of fluid flow through plant tissues with detailed observations of plant anatomy; this allows quantitative estimates of two critical aspects of plant function. First and foremost, results from these models quantify the supply of water to evaporative surfaces; second, results describe the ability of plant vascular systems to resist tensile damage from extreme environmental events, such as drought or frost. This approach permits quantitative comparisons of functional aspects of Asteroxylon with other extinct and extant plants, informs the quality of plant-based environmental proxies, and provides concrete data that can be input into climate models. Results indicate that despite their small size, water transport cells in Asteroxylon could supply a large volume of water to the plant's leaves--even greater than cells from some later-evolved seed plants. The smallest Asteroxylon tracheids have conductivities exceeding 0.015 m^2 / MPa * s, whereas Paleozoic conifer tracheids do not reach this threshold until they are three times wider. However, this increase in conductivity came at the cost of little to no adaptations for transport safety, placing the plant’s vegetative organs in jeopardy during drought events. Analysis of the thickness-to-span ratio of Asteroxylon’s tracheids suggests that environmental conditions of reduced relative

  12. 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.

  13. 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.)

  14. Insight into the relationship between impulsivity and substance abuse from studies using animal models.

    Science.gov (United States)

    Winstanley, Catharine A; Olausson, Peter; Taylor, Jane R; Jentsch, J David

    2010-08-01

    Drug use disorders are often accompanied by deficits in the capacity to efficiently process reward-related information and to monitor, suppress, or override reward-controlled behavior when goals are in conflict with aversive or immediate outcomes. This emerging deficit in behavioral flexibility and impulse control may be a central component of the progression to addiction, as behavior becomes increasingly driven by drugs and drug-associated cues at the expense of more advantageous activities. Understanding how neural mechanisms implicated in impulse control are affected by addictive drugs may therefore prove a useful strategy in the search for new treatment options. Animal models of impulsivity and addiction could make a significant contribution to this endeavor. Here, some of the more common behavioral paradigms used to measure different aspects of impulsivity across species are outlined, and the importance of the response to reward-paired cues in such paradigms is discussed. Naturally occurring differences in forms of impulsivity have been found to be predictive of future drug self-administration, but drug exposure can also increase impulsive responding. Such data are in keeping with the suggestion that impulsivity may contribute to multiple stages within the spiral of addiction. From a neurobiological perspective, converging evidence from rat, monkey, and human studies suggest that compromised functioning within the orbitofrontal cortex may critically contribute to the cognitive sequelae of drug abuse. Changes in gene transcription and protein expression within this region may provide insight into the mechanism underlying drug-induced cortical hypofunction, reflecting new molecular targets for the treatment of uncontrolled drug-seeking and drug-taking behavior.

  15. High pressure thermal inactivation of Clostridium botulinum type E endospores – kinetic modeling and mechanistic insights

    Directory of Open Access Journals (Sweden)

    Christian Andreas Lenz

    2015-07-01

    Full Text Available Cold-tolerant, neurotoxigenic, endospore forming Clostridium (C. botulinum type E belongs to the non-proteolytic physiological C. botulinum group II, is primarily associated with aquatic environments, and presents a safety risk for seafood. High pressure thermal (HPT processing exploiting the synergistic effect of pressure and temperature can be used to inactivate bacterial endospores.We investigated the inactivation of C. botulinum type E spores by (near isothermal HPT treatments at 300 – 1200 MPa at 30 – 75 °C for 1 s – 10 min. The occurrence of heat and lysozyme susceptible spore fractions after such treatments was determined. The experimental data were modeled to obtain kinetic parameters and represented graphically by isoeffect lines. In contrast to findings for spores of other species and within the range of treatment parameters applied, zones of spore stabilization (lower inactivation than heat treatments alone, large heat susceptible (HPT-induced germinated or lysozyme-dependently germinable (damaged coat layer spore fractions were not detected. Inactivation followed 1st order kinetics. DPA release kinetics allowed for insights into possible inactivation mechanisms suggesting a (poorly effective physiologic-like (similar to nutrient-induced germination at ≤ 450 MPa/≤ 45 °C and non-physiological germination at >500 MPa/>60 – 70 °C.Results of this study support the existence of some commonalities in the HPT inactivation mechanism of C. botulinum type E spores and Bacillus spores although both organisms have significantly different HPT resistance properties. The information presented here contributes to closing the gap in knowledge regarding the HPT inactivation of spore formers relevant to food safety and may help industrial implementation of HPT processing. The markedly lower HPT resistance of C. botulinum type E spores than spores from other C. botulinum types, could allow for the implementation of milder processes without

  16. Underperformance of African protected area networks and the case for new conservation models: insights from Zambia.

    Science.gov (United States)

    Lindsey, Peter A; Nyirenda, Vincent R; Barnes, Jonathan I; Becker, Matthew S; McRobb, Rachel; Tambling, Craig J; Taylor, W Andrew; Watson, Frederick G; t'Sas-Rolfes, Michael

    2014-01-01

    Many African protected areas (PAs) are not functioning effectively. We reviewed the performance of Zambia's PA network and provide insights into how their effectiveness might be improved. Zambia's PAs are under-performing in ecological, economic and social terms. Reasons include: a) rapidly expanding human populations, poverty and open-access systems in Game Management Areas (GMAs) resulting in widespread bushmeat poaching and habitat encroachment; b) underfunding of the Zambia Wildlife Authority (ZAWA) resulting in inadequate law enforcement; c) reliance of ZAWA on extracting revenues from GMAs to cover operational costs which has prevented proper devolution of user-rights over wildlife to communities; d) on-going marginalization of communities from legal benefits from wildlife; e) under-development of the photo-tourism industry with the effect that earnings are limited to a fraction of the PA network; f) unfavourable terms and corruption which discourage good practice and adequate investment by hunting operators in GMAs; g) blurred responsibilities regarding anti-poaching in GMAs resulting in under-investment by all stakeholders. The combined effect of these challenges has been a major reduction in wildlife densities in most PAs and the loss of habitat in GMAs. Wildlife fares better in areas with investment from the private and/or NGO sector and where human settlement is absent. There is a need for: elevated government funding for ZAWA; greater international donor investment in protected area management; a shift in the role of ZAWA such that they focus primarily on national parks while facilitating the development of wildlife-based land uses by other stakeholders elsewhere; and new models for the functioning of GMAs based on joint-ventures between communities and the private and/or NGO sector. Such joint-ventures should provide defined communities with ownership of land, user-rights over wildlife and aim to attract long-term private/donor investment. These

  17. What's statistical about learning? Insights from modelling statistical learning as a set of memory processes.

    Science.gov (United States)

    Thiessen, Erik D

    2017-01-05

    Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274: , 1926-1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105: , 2745-2750; Thiessen & Yee 2010 Child Development 81: , 1287-1303; Saffran 2002 Journal of Memory and Language 47: , 172-196; Misyak & Christiansen 2012 Language Learning 62: , 302-331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39: , 246-263; Thiessen et al. 2013 Psychological Bulletin 139: , 792-814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik

  18. Strain localisation in mechanically layered rocks beneath detachment zones: insights from numerical modelling

    Directory of Open Access Journals (Sweden)

    L. Le Pourhiet

    2013-04-01

    Full Text Available We have designed a series of fully dynamic numerical simulations aimed at assessing how the orientation of mechanical layering in rocks controls the orientation of shear bands and the depth of penetration of strain in the footwall of detachment zones. Two parametric studies are presented. In the first one, the influence of stratification orientation on the occurrence and mode of strain localisation is tested by varying initial dip of inherited layering in the footwall with regard to the orientation of simple shear applied at the rigid boundary simulating a rigid hanging wall, all scaling and rheological parameter kept constant. It appears that when Mohr–Coulomb plasticity is being used, shear bands are found to localise only when the layering is being stretched. This corresponds to early deformational stages for inital layering dipping in the same direction as the shear is applied, and to later stages for intial layering dipping towards the opposite direction of shear. In all the cases, localisation of the strain after only γ=1 requires plastic yielding to be activated in the strong layer. The second parametric study shows that results are length-scale independent and that orientation of shear bands is not sensitive to the viscosity contrast or the strain rate. However, decreasing or increasing strain rate is shown to reduce the capacity of the shear zone to localise strain. In the later case, the strain pattern resembles a mylonitic band but the rheology is shown to be effectively linear. Based on the results, a conceptual model for strain localisation under detachment faults is presented. In the early stages, strain localisation occurs at slow rates by viscous shear instabilities but as the layered media is exhumed, the temperature drops and the strong layers start yielding plastically, forming shear bands and localising strain at the top of the shear zone. Once strain localisation has occured, the deformation in the shear band becomes

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. A model of radiation-induced cell killing: insights into mechanisms and applications for hadron therapy.

    Science.gov (United States)

    Ballarini, Francesca; Altieri, Saverio; Bortolussi, Silva; Giroletti, Elio; Protti, Nicoletta

    2013-09-01

    A mechanism-based, two-parameter biophysical model of cell killing was developed with the aim of elucidating the mechanisms underlying radiation-induced cell death and predicting cell killing by different radiation types, including protons and carbon ions at energies and doses of interest for cancer therapy. The model assumed that certain chromosome aberrations (dicentrics, rings and large deletions, called "lethal aberrations") lead to clonogenic inactivation, and that aberrations derive from μm-scale misrejoining of chromatin fragments, which in turn are produced by "dirty" double-strand breaks called "cluster lesions" (CLs). The average numbers of CLs per Gy per cell were left as a semi-free parameter and the threshold distance for chromatin-fragment rejoining was defined the second parameter. The model was "translated" into Monte Carlo code and provided simulated survival curves, which were compared with survival data on V79 cells exposed to protons, carbon ions and X rays. The agreement was good between simulations and survival data and supported the assumptions of the model at least for doses up to a few Gy. Dicentrics, rings and large deletions were found to be lethal not only for AG1522 cells exposed to X rays, as already reported by others, but also for V79 cells exposed to protons and carbon ions of different energies. Furthermore, the derived CL yields suggest that the critical DNA lesions leading to clonogenic inactivation are more complex than "clean" DSBs. After initial validation, the model was applied to characterize the particle and LET dependence of proton and carbon cell killing. Consistent with the proton data, the predicted fraction of inactivated cells after 2 Gy protons was 40-50% below 7.7 keV/μm, increased by a factor ∼1.6 between 7.7-30.5 keV/μm, and decreased by a factor ∼1.1 between 30.5-34.6 keV/μm. These LET values correspond to proton energies below a few MeV, which are always present in the distal region of hadron therapy

  7. 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.

  8. Galaxy Evolution Insights from Spectral Modeling of Large Data Sets from the Sloan Digital Sky Survey

    Energy Technology Data Exchange (ETDEWEB)

    Hoversten, Erik A. [Johns Hopkins Univ., Baltimore, MD (United States)

    2007-10-01

    This thesis centers on the use of spectral modeling techniques on data from the Sloan Digital Sky Survey (SDSS) to gain new insights into current questions in galaxy evolution. The SDSS provides a large, uniform, high quality data set which can be exploited in a number of ways. One avenue pursued here is to use the large sample size to measure precisely the mean properties of galaxies of increasingly narrow parameter ranges. The other route taken is to look for rare objects which open up for exploration new areas in galaxy parameter space. The crux of this thesis is revisiting the classical Kennicutt method for inferring the stellar initial mass function (IMF) from the integrated light properties of galaxies. A large data set (~ 105 galaxies) from the SDSS DR4 is combined with more in-depth modeling and quantitative statistical analysis to search for systematic IMF variations as a function of galaxy luminosity. Galaxy Hα equivalent widths are compared to a broadband color index to constrain the IMF. It is found that for the sample as a whole the best fitting IMF power law slope above 0.5 M is Γ = 1.5 ± 0.1 with the error dominated by systematics. Galaxies brighter than around Mr,0.1 = -20 (including galaxies like the Milky Way which has Mr,0.1 ~ -21) are well fit by a universal Γ ~ 1.4 IMF, similar to the classical Salpeter slope, and smooth, exponential star formation histories (SFH). Fainter galaxies prefer steeper IMFs and the quality of the fits reveal that for these galaxies a universal IMF with smooth SFHs is actually a poor assumption. Related projects are also pursued. A targeted photometric search is conducted for strongly lensed Lyman break galaxies (LBG) similar to MS1512-cB58. The evolution of the photometric selection technique is described as are the results of spectroscopic follow-up of the best targets. The serendipitous discovery of two interesting blue compact dwarf galaxies is reported. These

  9. 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.

  10. 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

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

    Science.gov (United States)

    Gao, Ming; Li, Shiwei

    2017-05-01

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

  12. 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.

  13. APCVD of ZnO: Al, insight and control by modeling

    NARCIS (Netherlands)

    Deelen, J. van; Illiberi, A.; Kniknie, B.J.; Steijvers, H.L.A.H.; Lankhorst, A.M.; Simons, P.J.P.M.

    2013-01-01

    Atmospheric pressure chemical vapor deposition (APCVD) of ZnO from diethyl zinc (DEZn) and t-butanol was performed using an industrial reactor design. Deposition profiles were recorded to gain insight in the position dependent variations in layer thickness in such a reactor. We observed that for a

  14. Underperformance of African protected area networks and the case for new conservation models: insights from Zambia.

    Directory of Open Access Journals (Sweden)

    Peter A Lindsey

    Full Text Available Many African protected areas (PAs are not functioning effectively. We reviewed the performance of Zambia's PA network and provide insights into how their effectiveness might be improved. Zambia's PAs are under-performing in ecological, economic and social terms. Reasons include: a rapidly expanding human populations, poverty and open-access systems in Game Management Areas (GMAs resulting in widespread bushmeat poaching and habitat encroachment; b underfunding of the Zambia Wildlife Authority (ZAWA resulting in inadequate law enforcement; c reliance of ZAWA on extracting revenues from GMAs to cover operational costs which has prevented proper devolution of user-rights over wildlife to communities; d on-going marginalization of communities from legal benefits from wildlife; e under-development of the photo-tourism industry with the effect that earnings are limited to a fraction of the PA network; f unfavourable terms and corruption which discourage good practice and adequate investment by hunting operators in GMAs; g blurred responsibilities regarding anti-poaching in GMAs resulting in under-investment by all stakeholders. The combined effect of these challenges has been a major reduction in wildlife densities in most PAs and the loss of habitat in GMAs. Wildlife fares better in areas with investment from the private and/or NGO sector and where human settlement is absent. There is a need for: elevated government funding for ZAWA; greater international donor investment in protected area management; a shift in the role of ZAWA such that they focus primarily on national parks while facilitating the development of wildlife-based land uses by other stakeholders elsewhere; and new models for the functioning of GMAs based on joint-ventures between communities and the private and/or NGO sector. Such joint-ventures should provide defined communities with ownership of land, user-rights over wildlife and aim to attract long-term private/donor investment

  15. Behavioral and cognitive impact of early life stress: Insights from an animal model.

    Science.gov (United States)

    Liu, Hesong; Atrooz, Fatin; Salvi, Ankita; Salim, Samina

    2017-08-01

    Children subjected to traumatic events during childhood are reported to exhibit behavioral and cognitive deficits later in life, often leading to post-traumatic stress disorder (PTSD) and major depression. Interestingly, some children continue to remain normal despite being exposed to the same risk factors. These trauma-related behavioral and cognitive profiles across different stages of life are not well understood. Animal studies can offer useful insights. The goal of this study was to determine the impact of early life exposure to traumatic events on behavioral and cognitive profile in rats by tracking the behavior of each rat at different ages. We utilized the single prolonged stress (SPS), a rodent model of PTSD, to study the effects of early life stress. Male Sprague-Dawley rats were exposed to SPS on post-natal day (PND) 25. Tests to assess anxiety- and depression-like behavior, as well as learning and memory function were performed at PND32, 60 and 90. Rats exposed to SPS exhibited both anxiety- and depression-like behavior at PND32. And, short-term (STM) but not long-term memory (LTM) was impaired. Rats exposed to SPS at PND60 exhibited anxiety- but not depression-like behavior. STM but not LTM was impaired. Rats exposed to SPS at PND90 exhibited fearful (as indicated by elevated plus maze test) but not an overall anxiety-like behavior (in light and dark test). These rats also displayed significant depression-like behavior with no changes in STM or LTM. Interestingly, when data was further analyzed, two subsets of PND90 rats exposed to SPS were identified, "susceptible": with depression-like behavior and "resilient": without depression-like behavior. Importantly, while resilient group expressed early signs of anxiety- (at PND32 and PND60) and depression-like behavior (at PND32), these behavioral deficits were absent at PND90. On the other hand, susceptible PND90 rats exposed to SPS expressed later onset of anxiety-like behavior (at PND60), while depression

  16. Regression models of ultimate methane yields of fruits and vegetable solid wastes, sorghum and napiergrass on chemical composition

    Energy Technology Data Exchange (ETDEWEB)

    Gunaseelan, V.N. [PSG College of Arts and Science, Coimbatore (India). Department of Zoology

    2007-04-15

    Several fractions of fruits and vegetable solid wastes (FVSW), sorghum and napiergrass were analyzed for total solids (TS), volatile solids (VS), total organic carbon, total kjeldahl nitrogen, total soluble carbohydrate, extractable protein, acid-detergent fiber (ADF), lignin, cellulose and ash contents. Their ultimate methane yields (B{sub o}) were determined using the biochemical methane potential (BMP) assay. A series of simple and multiple regression models relating the B{sub o} to the various substrate constituents were generated and evaluated using computer statistical software, Statistical Package for Social Sciences (SPSS). The results of simple regression analyses revealed that, only weak relationship existed between the individual components such as carbohydrate, protein, ADF, lignin and cellulose versus B{sub o}. A regression of B{sub o} versus combination of two variables as a single independent variable such as carbohydrate/ADF and carbohydrate + protein/ADF also showed that the relationship is not strong. Thus it does not appear possible to relate the B{sub o} of FVSW, sorghum and napiergrass with single compositional characteristics. The results of multiple regression analyses showed promise and the relationship appeared to be good. When ADF and lignin/ADF were used as independent variables, the percentage of variation accounted for by the model is low for FVSW (r{sup 2}=0.665) and sorghum and napiergrass (r{sup 2}=0.746). Addition of nitrogen, ash and total soluble carbohydrate data to the model had a significantly higher effect on prediction of B{sub o} of these wastes with the r{sup 2} values ranging from 0.9 to 0.99. More than 90% of variation in B{sub o} of FVSW could be accounted for by the models when the variables carbohydrate, lignin, lignin/ADF, nitrogen and ash (r{sup 2}=0.904), carbohydrate, ADF, lignin/ADF, nitrogen and ash (r{sup 2}=0.90) and carbohydrate/ADF, lignin/ADF, lignin and ash (r{sup 2}=0.901) were used. All the models have

  17. 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

  18. 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...

  19. 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...

  20. 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)

  1. 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.

  2. 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.)

  3. 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.

  4. Social deprivation and burden of influenza: Testing hypotheses and gaining insights from a simulation model for the spread of influenza

    Directory of Open Access Journals (Sweden)

    Ayaz Hyder

    2015-06-01

    Full Text Available Factors associated with the burden of influenza among vulnerable populations have mainly been identified using statistical methodologies. Complex simulation models provide mechanistic explanations, in terms of spatial heterogeneity and contact rates, while controlling other factors and may be used to better understand statistical patterns and, ultimately, design optimal population-level interventions. We extended a sophisticated simulation model, which was applied to forecast epidemics and validated for predictive ability, to identify mechanisms for the empirical relationship between social deprivation and the burden of influenza. Our modeled scenarios and associated epidemic metrics systematically assessed whether neighborhood composition and/or spatial arrangement could qualitatively replicate this empirical relationship. We further used the model to determine consequences of local-scale heterogeneities on larger scale disease spread. Our findings indicated that both neighborhood composition and spatial arrangement were critical to qualitatively match the empirical relationship of interest. Also, when social deprivation was fully included in the model, we observed lower age-based attack rates and greater delay in epidemic peak week in the most socially deprived neighborhoods. Insights from simulation models complement current understandings from statistical-based association studies. Additional insights from our study are: (1 heterogeneous spatial arrangement of neighborhoods is a necessary condition for simulating observed disparities in the burden of influenza and (2 unmeasured factors may lead to a better quantitative match between simulated and observed rate ratio in the burden of influenza between the most and least socially deprived populations.