WorldWideScience

Sample records for model yields insights

  1. Further Insight into the Reaction FeO+ + H2 Yields Fe+ + H2O: Temperature Dependent Kinetics, Isotope Effects, and Statistical Modeling (Postprint)

    Science.gov (United States)

    2014-07-31

    a laminar flow tube via a Venturi inlet, where ∼104 to 105 collisions with a He buffer gas act to thermalize the ions and carry them downstream...transition-metal cations; adiabatic channel model; gas -phase; 2-state reactivity; configuration- interaction; rate constants; bare FEO+; H-H; C-H 16...remainder of the flow is pumped away by a roots pump through a throttled gate valve that acts to maintain the desired pressure within the flow tube

  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)

    , S. and ... factors to rice yield. Adebayo and Adebayo (1997) developed double log multiple regression model to predict rice yield in Adamawa State, Nigeria. The general form of .... the second are the crop yield/values for millet and sorghum ...

  4. 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.

  5. Track models and radiation chemical yields

    International Nuclear Information System (INIS)

    Chatterjee, A.; Magee, J.L.

    1987-01-01

    The authors are concerned only with systems in which single track effects dominate and radiation chemical yields are sums of yields for individual tracks. The authors know that the energy deposits of heavy particle tracks are composed of spurs along the particle trajectory (about one-half of the energy) and a more diffuse pattern composed of the tracks of knock-on electrons, called the penumbra (about one-half of the energy). The simplest way to introduce the concept of a unified track model for heavy particles is to consider the special case of the track of a heavy particle with an LET below 0.2-0.3eV/A, which in practice limits us to protons, deuterons, or particles with energy above 100 MeV per nucleon. At these LET values, to a good approximation, spurs formed by the main particle track can be considered to remain isolated throughout the radiation chemical reactions

  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. Genetic insight into yield-associated traits of wheat grown in multiple rain-fed environments.

    Directory of Open Access Journals (Sweden)

    Xianshan Wu

    Full Text Available BACKGROUND: Grain yield is a key economic driver of successful wheat production. Due to its complex nature, little is known regarding its genetic control. The goal of this study was to identify important quantitative trait loci (QTL directly and indirectly affecting grain yield using doubled haploid lines derived from a cross between Hanxuan 10 and Lumai 14. METHODOLOGY/PRINCIPAL FINDINGS: Ten yield-associated traits, including yield per plant (YP, number of spikes per plant (NSP, number of grains per spike (NGS, one-thousand grain weight (TGW, total number of spikelets per spike (TNSS, number of sterile spikelets per spike (NSSS, proportion of fertile spikelets per spike (PFSS, spike length (SL, density of spikelets per spike (DSS and plant height (PH, were assessed across 14 (for YP to 23 (for TGW year × location × water regime environments in China. Then, the genetic effects were partitioned into additive main effects (a, epistatic main effects (aa and their environment interaction effects (ae and aae by using composite interval mapping in a mixed linear model. CONCLUSIONS/SIGNIFICANCE: Twelve (YP to 33 (PH QTLs were identified on all 21 chromosomes except 6D. QTLs were more frequently observed on chromosomes 1B, 2B, 2D, 5A and 6B, and were concentrated in a few regions on individual chromosomes, exemplified by three striking yield-related QTL clusters on chromosomes 2B, 1B and 4B that explained the correlations between YP and other traits. The additive main-effect QTLs contributed more phenotypic variation than the epistasis and environmental interaction. Consistent with agronomic analyses, a group of progeny derived by selecting TGW and NGS, with higher grain yield, had an increased frequency of QTL for high YP, NGS, TGW, TNSS, PFSS, SL, PH and fewer NSSS, when compared to low yielding progeny. This indicated that it is feasible by marker-assisted selection to facilitate wheat production.

  8. Giant intracranial aneurysm embolization with a yield stress fluid material: insights from CFD analysis.

    Science.gov (United States)

    Wang, Weixiong; Graziano, Francesca; Russo, Vittorio; Ulm, Arthur J; De Kee, Daniel; Khismatullin, Damir B

    2013-01-01

    The endovascular treatment of intracranial aneurysms remains a challenge, especially when the aneurysm is large in size and has irregular, non-spherical geometry. In this paper, we use computational fluid dynamics to simulate blood flow in a vertebro-basilar junction giant aneurysm for the following three cases: (1) an empty aneurysm, (2) an aneurysm filled with platinum coils, and (3) an aneurysm filled with a yield stress fluid material. In the computational model, blood and the coil-filled region are treated as a non-Newtonian fluid and an isotropic porous medium, respectively. The results show that yield stress fluids can be used for aneurysm embolization provided the yield stress value is 20 Pa or higher. Specifically, flow recirculation in the aneurysm and the size of the inflow jet impingement zone on the aneurysm wall are substantially reduced by yield stress fluid treatment. Overall, this study opens up the possibility of using yield stress fluids for effective embolization of large-volume intracranial aneurysms.

  9. Champagne Pool (New Zealand) Thermophiles Yield Insights into the Evolution of Microbial Arsenic Resistance

    Science.gov (United States)

    Hug, K.; Krikowa, F.; Morgan, X.; Maher, W. A.; Stott, M. B.; Moreau, J. W.

    2011-12-01

    Arsenic is a highly toxic metalloid typically enriched in geothermal waters due to aqueous weathering of arsenic-bearing minerals. Investigation of enzymatic pathways by which thermophilic microorganisms cope with toxic arsenic levels may yield insights into the evolution of arsenic resistance mechanisms on the early Earth. At Wai-O-Tapu in the Taupo Volcanic Zone on the North Island of New Zealand, hot springs with temperatures of 30-90°C and elemental sulfur concentrations (expressed as equivalent sulfate) from 340 to 850 mg/l establish a range of environmental conditions. Total arsenic concentrations varied from 0.083 mg/l to 56 mg/l. Arsenic speciation analysis elucidated various biogeochemical arsenic transformations occurring within different springs. For example, in the Alum Cliff spring oxidizing conditions (Eh = 225 mV) were expected to stabilize dissolved arsenate (AsO43-). However, HPLC-ICPMS analyses yielded dissolved arsenate and arsenite (AsO33-) concentrations of 0.25 mg/l versus 43.3 mg/l, respectively, and point towards microbial arsenate reduction as the likely mechanism for arsenic redox transformation. 16S rRNA gene cloning of Alum Cliff DNA showed a predominantly archaeal population with the dominant clone "AC1_A1" most closely related (99% sequence similarity, NCBI BLAST°) to the uncultured Sulfolobus clone "ChP_97P" found in Champagne Pool (Childs et al., 2008). The closest isolated relative to AC1_A1 is Sulfolobus tokodaii str. TW with a sequence similarity of 94%. Arsenic speciation measurements from the Alum Cliff spring suggest that clone AC1_A1 features the arsenate reduction resistance mechanism, and we hypothesize therefore that an arsC (homolog or analog) provides this functionality. The organic arsenic species monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA), detected via HPLC-ICPMS at concentrations ranging from 1 μg/l to 12 μg/l in various springs, may also implicate microbial methyl-group transfers as an active

  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. Forest Growth and Yield Models Viewed From a Different Perspective

    Science.gov (United States)

    Jeffery C. Goelz

    2002-01-01

    Typically, when different forms of growth and yield models are considered, they are grouped into convenient discrete classes. As a heuristic device, I chose to use a contrasting perspective, that all growth and yield models are diameter distribution models that merely differ in regard to which diameter distribution is employed and how the distribution is projected to...

  12. 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, ...

  13. 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.

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

    Directory of Open Access Journals (Sweden)

    Lijun Su

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

  15. 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...

  16. 26Al yields from rotating Wolf--Rayet star models

    OpenAIRE

    Vuissoz, C.; Meynet, G.; Knoedlseder, J.; Cervino, M.; Schaerer, D.; Palacios, A.; Mowlavi, N.

    2003-01-01

    We present new $^{26}$Al stellar yields from rotating Wolf--Rayet stellar models which, at solar metallicity, well reproduce the observed properties of the Wolf-Rayet populations. These new yields are enhanced with respect to non--rotating models, even with respect to non--rotating models computed with enhanced mass loss rates. We briefly discuss some implications of the use of these new yields for estimating the global contribution of Wolf-Rayet stars to the quantity of $^{26}$Al now present...

  17. 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.

  18. Insights on PRA Review Practices: Necessity for Model Shaking

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Inn Seock; Jang, Mi suk; Kim, Seoung Rae [NESS, Daejeon (Korea, Republic of)

    2016-05-15

    Probabilistic risk assessment (PRA) is increasingly used as a technique to help ensure design and operational safety of nuclear power plants (NPPs) in the nuclear industry. Hence, there is considerable interest in the PRA quality, and as a result, a peer review of the PRA model is typically performed to ensure its technical adequacy as part of the PRA development process or for any other reason (e.g., regulatory requirement). For the PRA model to be used as a valuable vehicle for risk-informed applications, it is essential that the PRA model must yield correct and physically meaningful accident sequences and minimal cutsets for specific plant configurations or conditions relating to the applications. Hence, the existing peer review guidelines need to be updated to reflect these insights so that risk-informed applications could be more actively pursued with confidence.

  19. Genome-wide mapping of transcription start sites yields novel insights into the primary transcriptome of Pseudomonas putida

    DEFF Research Database (Denmark)

    D'Arrigo, Isotta; Bojanovic, Klara; Yang, Xiaochen

    2016-01-01

    was examined using an in vivo assay with GFP-fusion vectors and shown to function via a translational repression mechanism. Furthermore, 56 novel intergenic small RNAs and 8 putative actuaton transcripts were detected, as well as 8 novel open reading frames (ORFs). This study illustrates how global mapping...... of TSSs can yield novel insights into the transcriptional features and RNA output of bacterial genomes....

  20. Photodissociation of quantum state-selected diatomic molecules yields new insight into ultracold chemistry

    Science.gov (United States)

    McDonald, Mickey; McGuyer, Bart H.; Lee, Chih-Hsi; Apfelbeck, Florian; Zelevinsky, Tanya

    2016-05-01

    When a molecule is subjected to a sufficiently energetic photon it can break apart into fragments through a process called ``photodissociation''. For over 70 years this simple chemical reaction has served as a vital experimental tool for acquiring information about molecular structure, since the character of the photodissociative transition can be inferred by measuring the 3D photofragment angular distribution (PAD). While theoretical understanding of this process has gradually evolved from classical considerations to a fully quantum approach, experiments to date have not yet revealed the full quantum nature of this process. In my talk I will describe recent experiments involving the photodissociation of ultracold, optical lattice-trapped, and fully quantum state-resolved 88Sr2 molecules. Optical absorption images of the PADs produced in these experiments reveal features which are inherently quantum mechanical in nature, such as matter-wave interference between output channels, and are sensitive to the quantum statistics of the molecular wavefunctions. The results of these experiments cannot be predicted using quasiclassical methods. Instead, we describe our results with a fully quantum mechanical model yielding new intuition about ultracold chemistry.

  1. 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.

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

    KAUST Repository

    Hays, Spencer

    2012-09-01

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

  3. 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. A global water supply reservoir yield model with uncertainty analysis

    International Nuclear Information System (INIS)

    Kuria, Faith W; Vogel, Richard M

    2014-01-01

    Understanding the reliability and uncertainty associated with water supply yields derived from surface water reservoirs is central for planning purposes. Using a global dataset of monthly river discharge, we introduce a generalized model for estimating the mean and variance of water supply yield, Y, expected from a reservoir for a prespecified reliability, R, and storage capacity, S assuming a flow record of length n. The generalized storage–reliability–yield (SRY) relationships reported here have numerous water resource applications ranging from preliminary water supply investigations, to economic and climate change impact assessments. An example indicates how our generalized SRY relationship can be combined with a hydroclimatic model to determine the impact of climate change on surface reservoir water supply yields. We also document that the variability of estimates of water supply yield are invariant to characteristics of the reservoir system, including its storage capacity and reliability. Standardized metrics of the variability of water supply yields are shown to depend only on the sample size of the inflows and the statistical characteristics of the inflow series. (paper)

  7. Yield models for Eucalyptus globulus fuelwood plantations in Ethiopia

    Energy Technology Data Exchange (ETDEWEB)

    Pukkala, T.; Pohjonen, V. (Joensuu Univ. (FI). Faculty of Forestry)

    1990-01-01

    Based on 53 tree analyses and 105 sample plots of Eucalyptus globulus, models for volume and biomass at single tree and stand levels were developed. The possible growing sites were divided into four site classes. In seedling stands, the site class I corresponds to yield class 44 m{sup 3} ha{sup -1} year{sup -1}, in coppice stands to yield class 46 m{sup 3} ha{sup -1} year{sup -1}. The site class IV corresponds in seedling stand to yield class 9 m{sup 3} ha{sup -1} year{sup -1}, in coppice stands to yield class 13 m{sup 3} ha{sup -1} year{sup -1}. The maximum mean annual increment was reached in seedling stands at the age of 18-19 years, in coppice stands at the age of 14 years. (author).

  8. 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.

  9. A Remote Sensing-Derived Corn Yield Assessment Model

    Science.gov (United States)

    Shrestha, Ranjay Man

    be further associated with the actual yield. Utilizing satellite remote sensing products, such as daily NDVI derived from Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m pixel size, the crop yield estimation can be performed at a very fine spatial resolution. Therefore, this study examined the potential of these daily NDVI products within agricultural studies and crop yield assessments. In this study, a regression-based approach was proposed to estimate the annual corn yield through changes in MODIS daily NDVI time series. The relationship between daily NDVI and corn yield was well defined and established, and as changes in corn phenology and yield were directly reflected by the changes in NDVI within the growing season, these two entities were combined to develop a relational model. The model was trained using 15 years (2000-2014) of historical NDVI and county-level corn yield data for four major corn producing states: Kansas, Nebraska, Iowa, and Indiana, representing four climatic regions as South, West North Central, East North Central, and Central, respectively, within the U.S. Corn Belt area. The model's goodness of fit was well defined with a high coefficient of determination (R2>0.81). Similarly, using 2015 yield data for validation, 92% of average accuracy signified the performance of the model in estimating corn yield at county level. Besides providing the county-level corn yield estimations, the derived model was also accurate enough to estimate the yield at finer spatial resolution (field level). The model's assessment accuracy was evaluated using the randomly selected field level corn yield within the study area for 2014, 2015, and 2016. A total of over 120 plot level corn yield were used for validation, and the overall average accuracy was 87%, which statistically justified the model's capability to estimate plot-level corn yield. Additionally, the proposed model was applied to the impact estimation by examining the changes in corn yield

  10. Integrated model for predicting rice yield with climate change

    Science.gov (United States)

    Park, Jin-Ki; Das, Amrita; Park, Jong-Hwa

    2018-04-01

    Rice is the chief agricultural product and one of the primary food source. For this reason, it is of pivotal importance for worldwide economy and development. Therefore, in a decision-support-system both for the farmers and in the planning and management of the country's economy, forecasting yield is vital. However, crop yield, which is a dependent of the soil-bio-atmospheric system, is difficult to represent in statistical language. This paper describes a novel approach for predicting rice yield using artificial neural network, spatial interpolation, remote sensing and GIS methods. Herein, the variation in the yield is attributed to climatic parameters and crop health, and the normalized difference vegetation index from MODIS is used as an indicator of plant health and growth. Due importance was given to scaling up the input parameters using spatial interpolation and GIS and minimising the sources of error in every step of the modelling. The low percentage error (2.91) and high correlation (0.76) signifies the robust performance of the proposed model. This simple but effective approach is then used to estimate the influence of climate change on South Korean rice production. As proposed in the RCP8.5 scenario, an upswing in temperature may increase the rice yield throughout South Korea.

  11. 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 ...

  12. 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.

  13. Modelling of the process yields of a whey fermentation

    Energy Technology Data Exchange (ETDEWEB)

    Blakebrough, N; Moresi, M

    1981-01-01

    The biomass yields (y) and COD reduction efficiencies (eta) of a whey fermentation by Kluyveromyces fragilis were studied in a 100-l fermenter at various stirrer speeds and lactose concentrations, and compared to those obtained in 10-l and 15-l fermenters at constant values of the oxygen transfer coefficient (kla) and air velocity. The empirical models previously constructed by using the 15-l fermenter data could be used to predict the yields on the other scales by calculating for each run the 15-l fermenter which would provide the same oxygen transfer coefficient measured by the sulfite method on each fermenter under study. To make this model independent of stirrer speeds used in each generic fermenter, the effect of aeration and mixing was incorporated into an overall parameter (kla) and the values of y and eta were correlated only with temperature, lactose level and kla, since these variables were approximately orthogonal. The validity of this model was finally checked against the yields reported by Wasserman et al. (1961) in a 6-cubic metre fermenter, thus confirming the capability of the model to provide a reliable basis for further scale-up on the production scale. (Refs. 17).

  14. Modelling of the process yields of a whey fermentation

    Energy Technology Data Exchange (ETDEWEB)

    Blakebrough, N; Moresi, M

    1981-09-01

    The biomass yields (y) and COD reduction efficiencies (eta) of a whey fermentation by Kluyveromyces fragilis were studied in a 100-l fermenter at various stirrer speeds and lactose concentrations, and compared to those obtained in 10-l and 15-l fermenters at constant values of the oxygen transfer coefficient (ksub(L)a) and air velocity. The empirical models previously constructed by using the 15-l fermenter data could be used to predict the yields on the other scales by calculating for each run the 15-l fermenter which would provide the same oxygen transfer coefficient measured by the sulphite method on each fermenter under study. To make this model independent of stirrer speeds used in each generic fermenter, the effect of aeration and mixing was incorporated into an overall parameter (ksub(L)a) and the values of y and eta were correlated only with temperature, lactose level and ksub(L)a since these variables were approximately orthogonal.

  15. SCS-CN based time-distributed sediment yield model

    Science.gov (United States)

    Tyagi, J. V.; Mishra, S. K.; Singh, Ranvir; Singh, V. P.

    2008-05-01

    SummaryA sediment yield model is developed to estimate the temporal rates of sediment yield from rainfall events on natural watersheds. The model utilizes the SCS-CN based infiltration model for computation of rainfall-excess rate, and the SCS-CN-inspired proportionality concept for computation of sediment-excess. For computation of sedimentographs, the sediment-excess is routed to the watershed outlet using a single linear reservoir technique. Analytical development of the model shows the ratio of the potential maximum erosion (A) to the potential maximum retention (S) of the SCS-CN method is constant for a watershed. The model is calibrated and validated on a number of events using the data of seven watersheds from India and the USA. Representative values of the A/S ratio computed for the watersheds from calibration are used for the validation of the model. The encouraging results of the proposed simple four parameter model exhibit its potential in field application.

  16. 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

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

    Science.gov (United States)

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

    2013-01-01

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

  18. 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.

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

    Institute of Scientific and Technical Information of China (English)

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

    2013-01-01

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

  20. Monte Carlo simulation of a simple gene network yields new evolutionary insights.

    Science.gov (United States)

    Andrecut, M; Cloud, D; Kauffman, S A

    2008-02-07

    Monte Carlo simulations of a genetic toggle switch show that its behavior can be more complex than analytic models would suggest. We show here that as a result of the interplay between frequent and infrequent reaction events, such a switch can have more stable states than an analytic model would predict, and that the number and character of these states depend to a large extent on the propensity of transcription factors to bind to and dissociate from promoters. The effects of gene duplications differ even more; in analytic models, these seem to result in the disappearance of bi-stability and thus a loss of the switching function, but a Monte Carlo simulation shows that they can result in the appearance of new stable states without the loss of old ones, and thus in an increase of the complexity of the switch's behavior which may facilitate the evolution of new cellular functions. These differences are of interest with respect to the evolution of gene networks, particularly in clonal lines of cancer cells, where the duplication of active genes is an extremely common event, and often seems to result in the appearance of viable new cellular phenotypes.

  1. NEST: a comprehensive model for scintillation yield in liquid xenon

    Energy Technology Data Exchange (ETDEWEB)

    Szydagis, M; Barry, N; Mock, J; Stolp, D; Sweany, M; Tripathi, M; Uvarov, S; Walsh, N; Woods, M [University of California, Davis, One Shields Ave., Davis, CA 95616 (United States); Kazkaz, K, E-mail: mmszydagis@ucdavis.edu [Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA 94550 (United States)

    2011-10-15

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

  2. NEST: a comprehensive model for scintillation yield in liquid xenon

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  3. 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.

  4. 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.

  5. 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.

    2011-01-01

    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 non-ideal 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. PMID:22029390

  6. Yield surface investigation of alloys during model disk spin tests

    Directory of Open Access Journals (Sweden)

    E. P. Kuzmin

    2014-01-01

    Full Text Available Gas-turbine engines operate under heavy subsequently static loading conditions. Disks of gas-turbine engine are high loaded parts of irregular shape having intensive stress concentrators wherein a 3D stress strain state occurs. The loss of load-carrying capability or burst of disk can lead to severe accident or disaster. Therefore, development of methods to assess deformations and to predict burst is one of the most important problems.Strength assessment approaches are used at all levels of engine creation. In recent years due to actively developing numerical method, particularly FEA, it became possible to investigate load-carrying capability of irregular shape disks, to use 3D computing schemes including flow theory and different options of force and deformation failure criteria. In spite of a wide progress and practical use of strength assessment approaches, there is a lack of detailed research data on yield surface of disk alloys. The main purpose of this work is to validate the use of basis hypothesis of flow theory and investigate the yield surface of disk alloys during the disks spin test.The results of quasi-static numerical simulation of spin tests of model disk made from high-temperature forged alloy are presented. To determine stress-strain state of disk during loading finite element analysis is used. Simulation of elastic-plastic strain fields was carried out using incremental theory of plasticity with isotropic hardening. Hardening function was taken from the results of specimens tensile test. Specimens were cut from a sinkhead of model disk. The paper investigates the model sensitivity affected by V.Mises and Tresca yield criteria as well as the Hosford model. To identify the material model parameters the eddy current sensors were used in the experimental approach to measure rim radial displacements during the load-unload of spin test. The results of calculation made using different material models were compared with the

  7. Soybean yield modeling using bootstrap methods for small samples

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-11-01

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

  8. Modeling Growth and Yield of Schizolobium amazonicum under Different Spacings

    Directory of Open Access Journals (Sweden)

    Gilson Fernandes da Silva

    2013-01-01

    Full Text Available This study aimed to present an approach to model the growth and yield of the species Schizolobium amazonicum (Paricá based on a study of different spacings located in Pará, Brazil. Whole-stand models were employed, and two modeling strategies (Strategies A and B were tested. Moreover, the following three scenarios were evaluated to assess the accuracy of the model in estimating total and commercial volumes at five years of age: complete absence of data (S1; available information about the variables basal area, site index, dominant height, and number of trees at two years of age (S2; and this information available at five years of age (S3. The results indicated that the 3 × 2 spacing has a higher mortality rate than normal, and, in general, greater spacing corresponds to larger diameter and average height and smaller basal area and volume per hectare. In estimating the total and commercial volumes for the three scenarios tested, Strategy B seems to be the most appropriate method to estimate the growth and yield of Paricá plantations in the study region, particularly because Strategy A showed a significant bias in its estimates.

  9. Predicting paddlefish roe yields using an extension of the Beverton–Holt equilibrium yield-per-recruit model

    Science.gov (United States)

    Colvin, M.E.; Bettoli, Phillip William; Scholten, G.D.

    2013-01-01

    Equilibrium yield models predict the total biomass removed from an exploited stock; however, traditional yield models must be modified to simulate roe yields because a linear relationship between age (or length) and mature ovary weight does not typically exist. We extended the traditional Beverton-Holt equilibrium yield model to predict roe yields of Paddlefish Polyodon spathula in Kentucky Lake, Tennessee-Kentucky, as a function of varying conditional fishing mortality rates (10-70%), conditional natural mortality rates (cm; 9% and 18%), and four minimum size limits ranging from 864 to 1,016mm eye-to-fork length. These results were then compared to a biomass-based yield assessment. Analysis of roe yields indicated the potential for growth overfishing at lower exploitation rates and smaller minimum length limits than were suggested by the biomass-based assessment. Patterns of biomass and roe yields in relation to exploitation rates were similar regardless of the simulated value of cm, thus indicating that the results were insensitive to changes in cm. Our results also suggested that higher minimum length limits would increase roe yield and reduce the potential for growth overfishing and recruitment overfishing at the simulated cm values. Biomass-based equilibrium yield assessments are commonly used to assess the effects of harvest on other caviar-based fisheries; however, our analysis demonstrates that such assessments likely underestimate the probability and severity of growth overfishing when roe is targeted. Therefore, equilibrium roe yield-per-recruit models should also be considered to guide the management process for caviar-producing fish species.

  10. International codes and model intercomparison for intermediate energy activation yields

    International Nuclear Information System (INIS)

    Rolf, M.; Nagel, P.

    1997-01-01

    The motivation for this intercomparison came from data needs of accelerator-based waste transmutation, energy amplification and medical therapy. The aim of this exercise is to determine the degree of reliability of current nuclear reaction models and codes when calculating activation yields in the intermediate energy range up to 5000 MeV. Emphasis has been placed for a wide range of target elements ( O, Al, Fe, Co, Zr and Au). This work is mainly based on calculation of (P,xPyN) integral cross section for incident proton. A qualitative description of some of the nuclear models and code options employed is made. The systematics of graphical presentation of the results allows a quick quantitative measure of agreement or deviation. This code intercomparison highlights the fact that modeling calculations of energy activation yields may at best have uncertainties of a factor of two. The causes of such discrepancies are multi-factorial. Problems are encountered which are connected with the calculation of nuclear masses, binding energies, Q-values, shell effects, medium energy fission and Fermi break-up. (A.C.)

  11. Yield Stress Model for Molten Composition B-3

    Science.gov (United States)

    Davis, Stephen; Zerkle, David

    2017-06-01

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

  12. 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

  13. Statistical modelling and deconvolution of yield meter data

    DEFF Research Database (Denmark)

    Tøgersen, Frede Aakmann; Waagepetersen, Rasmus Plenge

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

  14. Osteoarthritis: new insights in animal models.

    Science.gov (United States)

    Longo, Umile Giuseppe; Loppini, Mattia; Fumo, Caterina; Rizzello, Giacomo; Khan, Wasim Sardar; Maffulli, Nicola; Denaro, Vincenzo

    2012-01-01

    Osteoarthritis (OA) is the most frequent and symptomatic health problem in the middle-aged and elderly population, with over one-half of all people over the age of 65 showing radiographic changes in painful knees. The aim of the present study was to perform an overview on the available animal models used in the research field on the OA. Discrepancies between the animal models and the human disease are present. As regards human 'idiopathic' OA, with late onset and slow progression, it is perhaps wise not to be overly enthusiastic about animal models that show severe chondrodysplasia and very early OA. Advantage by using genetically engineered mouse models, in comparison with other surgically induced models, is that molecular etiology is known. Find potential molecular markers for the onset of the disease and pay attention to the role of gender and environmental factors should be very helpful in the study of mice that acquire premature OA. Surgically induced destabilization of joint is the most widely used induction method. These models allow the temporal control of disease induction and follow predictable progression of the disease. In animals, ACL transection and meniscectomy show a speed of onset and severity of disease higher than in humans after same injury.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2018-02-01

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

  16. Mathematical model insights into arsenic detoxification

    Directory of Open Access Journals (Sweden)

    Nijhout H Frederik

    2011-08-01

    Full Text Available Abstract Background Arsenic in drinking water, a major health hazard to millions of people in South and East Asia and in other parts of the world, is ingested primarily as trivalent inorganic arsenic (iAs, which then undergoes hepatic methylation to methylarsonic acid (MMAs and a second methylation to dimethylarsinic acid (DMAs. Although MMAs and DMAs are also known to be toxic, DMAs is more easily excreted in the urine and therefore methylation has generally been considered a detoxification pathway. A collaborative modeling project between epidemiologists, biologists, and mathematicians has the purpose of explaining existing data on methylation in human studies in Bangladesh and also testing, by mathematical modeling, effects of nutritional supplements that could increase As methylation. Methods We develop a whole body mathematical model of arsenic metabolism including arsenic absorption, storage, methylation, and excretion. The parameters for arsenic methylation in the liver were taken from the biochemical literature. The transport parameters between compartments are largely unknown, so we adjust them so that the model accurately predicts the urine excretion rates of time for the iAs, MMAs, and DMAs in single dose experiments on human subjects. Results We test the model by showing that, with no changes in parameters, it predicts accurately the time courses of urinary excretion in mutiple dose experiments conducted on human subjects. Our main purpose is to use the model to study and interpret the data on the effects of folate supplementation on arsenic methylation and excretion in clinical trials in Bangladesh. Folate supplementation of folate-deficient individuals resulted in a 14% decrease in arsenicals in the blood. This is confirmed by the model and the model predicts that arsenicals in the liver will decrease by 19% and arsenicals in other body stores by 26% in these same individuals. In addition, the model predicts that arsenic

  17. 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

  18. Osteoarthritis: New Insights in Animal Models

    OpenAIRE

    Longo, Umile Giuseppe; Loppini, Mattia; Fumo, Caterina; Rizzello, Giacomo; Khan, Wasim Sardar; Maffulli, Nicola; Denaro, Vincenzo

    2012-01-01

    Osteoarthritis (OA) is the most frequent and symptomatic health problem in the middle-aged and elderly population, with over one-half of all people over the age of 65 showing radiographic changes in painful knees. The aim of the present study was to perform an overview on the available animal models used in the research field on the OA. Discrepancies between the animal models and the human disease are present. As regards human ‘idiopathic’ OA, with late onset and slow progression, it is perha...

  19. Esophageal Cancer: Insights from Mouse Models

    Directory of Open Access Journals (Sweden)

    Marie-Pier Tétreault

    2015-01-01

    Full Text Available Esophageal cancer is the eighth leading cause of cancer and the sixth most common cause of cancer-related death worldwide. Despite recent advances in the development of surgical techniques in combination with the use of radiotherapy and chemotherapy, the prognosis for esophageal cancer remains poor. The cellular and molecular mechanisms that drive the pathogenesis of esophageal cancer are still poorly understood. Hence, understanding these mechanisms is crucial to improving outcomes for patients with esophageal cancer. Mouse models constitute valuable tools for modeling human cancers and for the preclinical testing of therapeutic strategies in a manner not possible in human subjects. Mice are excellent models for studying human cancers because they are similar to humans at the physiological and molecular levels and because they have a shorter gestation time and life cycle. Moreover, a wide range of well-developed technologies for introducing genetic modifications into mice are currently available. In this review, we describe how different mouse models are used to study esophageal cancer.

  20. Cancer immunotherapy : insights from transgenic animal models

    NARCIS (Netherlands)

    McLaughlin, PMJ; Kroesen, BJ; Harmsen, MC; de Leij, LFMH

    2001-01-01

    A wide range of strategies in cancer immunotherapy has been developed in the last decade, some of which are currently being used in clinical settings. The development of these immunotherapeutical strategies has been facilitated by the generation of relevant transgenic animal models. Since the

  1. 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.

  2. Sequential Path Model for Grain Yield in Soybean

    Directory of Open Access Journals (Sweden)

    Mohammad SEDGHI

    2010-09-01

    Full Text Available This study was performed to determine some physiological traits that affect soybean,s grain yield via sequential path analysis. In a factorial experiment, two cultivars (Harcor and Williams were sown under four levels of nitrogen and two levels of weed management at the research station of Tabriz University, Iran, during 2004 and 2005. Grain yield, some yield components and physiological traits were measured. Correlation coefficient analysis showed that grain yield had significant positive and negative association with measured traits. A sequential path analysis was done in order to evaluate associations among grain yield and related traits by ordering the various variables in first, second and third order paths on the basis of their maximum direct effects and minimal collinearity. Two first-order variables, namely number of pods per plant and pre-flowering net photosynthesis revealed highest direct effect on total grain yield and explained 49, 44 and 47 % of the variation in grain yield based on 2004, 2005, and combined datasets, respectively. Four traits i.e. post-flowering net photosynthesis, plant height, leaf area index and intercepted radiation at the bottom layer of canopy were found to fit as second-order variables. Pre- and post-flowering chlorophyll content, main root length and intercepted radiation at the middle layer of canopy were placed at the third-order path. From the results concluded that, number of pods per plant and pre-flowering net photosynthesis are the best selection criteria in soybean for grain yield.

  3. Statistical modelling and deconvolution of yield meter data

    DEFF Research Database (Denmark)

    Tøgersen, Frede Aakmann; Waagepetersen, Rasmus Plenge

    2004-01-01

    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...

  4. 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.

  5. 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.

  6. 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.

  7. 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...

  8. 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 ...

  9. Modeling bromide effects on yields and speciation of dihaloacetonitriles formed in chlorinated drinking water.

    Science.gov (United States)

    Roccaro, Paolo; Chang, Hyun-shik; Vagliasindi, Federico G A; Korshin, Gregory V

    2013-10-15

    This study examined effects of bromide on yields and speciation of dihaloacetonitrile (DHAN) species that included dichloro-, bromochloro- and dibromoacetonitriles generated in chlorinated water. Experimental data obtained using two water sources, varying concentrations and characters of Natural Organic Matter (NOM), bromide concentrations, reaction times, chlorine doses, temperatures and pHs were interpreted using a semi-phenomenological model that assumed the presence of three kinetically distinct sites in NOM (denoted as sites S1, S2 and S3) and the occurrence of sequential incorporation of bromine and chlorine into them. One site was found to react very fast with the chlorine and bromine but its contribution in the DHAN generation was very low. The site with the highest contribution to the yield of DHAN (>70%) has the lowest reaction rates. The model introduced dimensionless coefficients (denoted as φ1(DHAN), φ2(DHAN) and φ3(DHAN)) applicable to the initial DHAN generation sites and their monochlorinated and monobrominated products, respectively. These parameters were used to quantify the kinetic preference to bromine incorporation over that of chlorine. Values of these coefficients optimized for DHAN formation were indicative of the strongly preferential incorporation of bromine into the engaged NOM sites. The same set of φ(i)(DHAN) coefficients could be used to model the speciation of DHAN released from their kinetically different precursors. The dimensionless speciation coefficients φ(i)(DHAN) were determined to be site specific and dependent on the NOM content and character as well as pH. The presented model of DHAN formation and speciation can help quantify in more detail the generation of DHAN and provide more insight necessary for further assessment of their potential health effects. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    Cerda, Rolando; Avelino, Jacques; Gary, Christian; Tixier, Philippe; Lechevallier, Esther; Allinne, Clémentine

    2017-01-01

    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.

  11. Growth models for ponderosa pine: I. Yield of unthinned plantations in northern California.

    Science.gov (United States)

    William W. Oliver; Robert F. Powers

    1978-01-01

    Yields for high-survival, unthinned ponderosa pine (Pinus ponderosa Laws.) plantations in northern California are estimated. Stems of 367 trees in 12 plantations were analyzed to produce a growth model simulating stand yields. Diameter, basal area, and net cubic volume yields by Site Indices50 40 through 120 are tabulated for...

  12. 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.

  13. 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

  14. 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 ...

  15. 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.

  16. Insights into pre-reversal paleosecular variation from stochastic models

    Directory of Open Access Journals (Sweden)

    Klaudio ePeqini

    2015-09-01

    Full Text Available To provide insights on the paleosecular variation of the geomagnetic field and the mechanism of reversals, long time series of the dipolar magnetic moment are generated by two different stochastic models, known as the domino model and the inhomogeneous Lebovitz disk dynamo model, with initial values taken from the from paleomagnetic data. The former model considers mutual interactions of N macrospins embedded in a uniformly rotating medium, where random forcing and dissipation act on each macrospin. With an appropriate set of the model’s parameters values, the series generated by this model have similar statistical behaviour to the time series of the SHA.DIF.14K model. The latter model is an extension of the classical two-disk Rikitake model, considering N dynamo elements with appropriate interactions between them.We varied the parameters set of both models aiming at generating suitable time series with behaviour similar to the long time series of recent secular variation (SV. Such series are then extended to the near future, obtaining reversals in both cases of models. The analysis of the time series generated by simulating the models show that the reversals appears after a persistent period of low intensity geomagnetic field, as it is occurring in the present times.

  17. 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.

  18. A General Microscopic Traffic Model Yielding Dissipative Shocks

    DEFF Research Database (Denmark)

    Gaididei, Yuri Borisovich; Caputo, Jean Guy; Christiansen, Peter Leth

    2018-01-01

    We consider a general microscopic traffic model with a delay. An algebraic traffic function reduces the equation to the Aw-Rascle microscopic model while a sigmoid function gives the standard “follow the leader”. For zero delay we prove that the homogeneous solution is globally stable...

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

    KAUST Repository

    Hays, Spencer; Shen, Haipeng; Huang, Jianhua Z.

    2012-01-01

    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

  20. Modeling precipitation-runoff relationships to determine water yield from a ponderosa pine forest watershed

    Science.gov (United States)

    Assefa S. Desta

    2006-01-01

    A stochastic precipitation-runoff modeling is used to estimate a cold and warm-seasons water yield from a ponderosa pine forested watershed in the north-central Arizona. The model consists of two parts namely, simulation of the temporal and spatial distribution of precipitation using a stochastic, event-based approach and estimation of water yield from the watershed...

  1. Modeling sediment yield in small catchments at event scale: Model comparison, development and evaluation

    Science.gov (United States)

    Tan, Z.; Leung, L. R.; Li, H. Y.; Tesfa, T. K.

    2017-12-01

    Sediment yield (SY) has significant impacts on river biogeochemistry and aquatic ecosystems but it is rarely represented in Earth System Models (ESMs). Existing SY models focus on estimating SY from large river basins or individual catchments so it is not clear how well they simulate SY in ESMs at larger spatial scales and globally. In this study, we compare the strengths and weaknesses of eight well-known SY models in simulating annual mean SY at about 400 small catchments ranging in size from 0.22 to 200 km2 in the US, Canada and Puerto Rico. In addition, we also investigate the performance of these models in simulating event-scale SY at six catchments in the US using high-quality hydrological inputs. The model comparison shows that none of the models can reproduce the SY at large spatial scales but the Morgan model performs the better than others despite its simplicity. In all model simulations, large underestimates occur in catchments with very high SY. A possible pathway to reduce the discrepancies is to incorporate sediment detachment by landsliding, which is currently not included in the models being evaluated. We propose a new SY model that is based on the Morgan model but including a landsliding soil detachment scheme that is being developed. Along with the results of the model comparison and evaluation, preliminary findings from the revised Morgan model will be presented.

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

    Science.gov (United States)

    de Almeida, Rodrigo Estevam Munhoz; Pierozan Junior, Clovis; Lago, Bruno Cocco; Trivelin, Paulo Cesar Ocheuze

    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. PMID:29462178

  3. 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.

  4. 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.

  5. 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.

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

    International Nuclear Information System (INIS)

    Jubaidah; Kurniadi, Rizal

    2015-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-09-30

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

  8. A Representation for Gaining Insight into Clinical Decision Models

    Science.gov (United States)

    Jimison, Holly B.

    1988-01-01

    For many medical domains uncertainty and patient preferences are important components of decision making. Decision theory is useful as a representation for such medical models in computer decision aids, but the methodology has typically had poor performance in the areas of explanation and user interface. The additional representation of probabilities and utilities as random variables serves to provide a framework for graphical and text insight into complicated decision models. The approach allows for efficient customization of a generic model that describes the general patient population of interest to a patient- specific model. Monte Carlo simulation is used to calculate the expected value of information and sensitivity for each model variable, thus providing a metric for deciding what to emphasize in the graphics and text summary. The computer-generated explanation includes variables that are sensitive with respect to the decision or that deviate significantly from what is typically observed. These techniques serve to keep the assessment and explanation of the patient's decision model concise, allowing the user to focus on the most important aspects for that patient.

  9. MODELING POLLINATION FACTORS THAT INFLUENCE ALFALFA SEED YIELD IN NORTH-CENTRAL NEVADA

    OpenAIRE

    BREAZEALE, Don; FERNANDEZ, George; NARAYANAN, Rangesan

    2008-01-01

    The relative importance of both environmental and management factors on alfalfa seed yield was investigated on North–Central Nevada farms. Multiple linear regression models using 2002-2003 data revealed that cumulative tripped fl owers increased seed yield in both years. Field location does not appear to make a difference in the observed variation in tripped fl ower production. The results suggest that seed yield can be increased by (a) by placing bee shelters closer and (b) cultural practice...

  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

    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....... The decline intensity and the value of several other model parameters, such as the maximum yield reached during the ceiling phase or the duration of the establishment phase, were highly variable. The highest maximum yields were obtained in the experiments located in the southern part of the studied area....... 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...

  11. An alternative approach for modeling strength differential effect in sheet metals with symmetric yield functions

    Science.gov (United States)

    Kurukuri, Srihari; Worswick, Michael J.

    2013-12-01

    An alternative approach is proposed to utilize symmetric yield functions for modeling the tension-compression asymmetry commonly observed in hcp materials. In this work, the strength differential (SD) effect is modeled by choosing separate symmetric plane stress yield functions (for example, Barlat Yld 2000-2d) for the tension i.e., in the first quadrant of principal stress space, and compression i.e., third quadrant of principal stress space. In the second and fourth quadrants, the yield locus is constructed by adopting interpolating functions between uniaxial tensile and compressive stress states. In this work, different interpolating functions are chosen and the predictive capability of each approach is discussed. The main advantage of this proposed approach is that the yield locus parameters are deterministic and relatively easy to identify when compared to the Cazacu family of yield functions commonly used for modeling SD effect observed in hcp materials.

  12. a metabolic wastage model for the rate-yield trade off

    Indian Academy of Sciences (India)

    A METABOLIC WASTAGE MODEL FOR THE RATE-YIELD TRADE OFF. There is a growth limiting step in which an intermediate metabolite (m) has to hit a target molecule (t). ... D= rate of diffusing out. S= the rate of formation of the metabolite. The equilibrium loss decides the yield. The no. of activated targets decide the rate ...

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

    African Journals Online (AJOL)

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

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

    Science.gov (United States)

    Pervin, Lia; Islam, Md Saiful

    2015-02-01

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

  15. [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.

  16. 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.

  17. 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

  18. Statistical modelling of grapevine yield in the Port Wine region under present and future climate conditions

    Science.gov (United States)

    Santos, João A.; Malheiro, Aureliano C.; Karremann, Melanie K.; Pinto, Joaquim G.

    2011-03-01

    The impact of projected climate change on wine production was analysed for the Demarcated Region of Douro, Portugal. A statistical grapevine yield model (GYM) was developed using climate parameters as predictors. Statistically significant correlations were identified between annual yield and monthly mean temperatures and monthly precipitation totals during the growing cycle. These atmospheric factors control grapevine yield in the region, with the GYM explaining 50.4% of the total variance in the yield time series in recent decades. Anomalously high March rainfall (during budburst, shoot and inflorescence development) favours yield, as well as anomalously high temperatures and low precipitation amounts in May and June (May: flowering and June: berry development). The GYM was applied to a regional climate model output, which was shown to realistically reproduce the GYM predictors. Finally, using ensemble simulations under the A1B emission scenario, projections for GYM-derived yield in the Douro Region, and for the whole of the twenty-first century, were analysed. A slight upward trend in yield is projected to occur until about 2050, followed by a steep and continuous increase until the end of the twenty-first century, when yield is projected to be about 800 kg/ha above current values. While this estimate is based on meteorological parameters alone, changes due to elevated CO2 may further enhance this effect. In spite of the associated uncertainties, it can be stated that projected climate change may significantly benefit wine yield in the Douro Valley.

  19. 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

  20. Variability of effects of spatial climate data aggregation on regional yield simulation by crop models

    NARCIS (Netherlands)

    Hoffmann, H.; Zhao, G.; Bussel, van L.G.J.

    2015-01-01

    Field-scale crop models are often applied at spatial resolutions coarser than that of the arable field. However, little is known about the response of the models to spatially aggregated climate input data and why these responses can differ across models. Depending on the model, regional yield

  1. Extended mitogenomic phylogenetic analyses yield new insight into crocodylian evolution and their survival of the Cretaceous-Tertiary boundary.

    Science.gov (United States)

    Roos, Jonas; Aggarwal, Ramesh K; Janke, Axel

    2007-11-01

    The mitochondrial genomes of the dwarf crocodile, Osteolaemus tetraspis, and two species of dwarf caimans, the smooth-fronted caiman, Paleosuchus trigonatus, and Cuvier's dwarf caiman, Paleosuchus palpebrosus, were sequenced and included in a mitogenomic phylogenetic study. The phylogenetic analyses, which included a total of ten crocodylian species, yielded strong support to a basal split between Crocodylidae and Alligatoridae. Osteolaemus fell within the Crocodylidae as the sister group to Crocodylus. Gavialis and Tomistoma, which joined on a common branch, constituted a sister group to Crocodylus/Osteolaemus. This suggests that extant crocodylians are organized in two families: Alligatoridae and Crocodylidae. Within the Alligatoridae there was a basal split between Alligator and a branch that contained Paleosuchus and Caiman. The analyses also provided molecular estimates of various divergences applying recently established crocodylian and outgroup fossil calibration points. Molecular estimates based on amino acid data placed the divergence between Crocodylidae and Alligatoridae at 97-103 million years ago and that between Alligator and Caiman/Paleosuchus at 65-72 million years ago. Other crocodilian divergences were placed after the Cretaceous-Tertiary boundary. Thus, according to the molecular estimates, three extant crocodylian lineages have their roots in the Cretaceous. Considering the crocodylian diversification in the Cretaceous the molecular datings suggest that the extinction of the dinosaurs was also to some extent paralleled in the crocodylian evolution. However, for whatever reason, some crocodylian lineages survived into the Tertiary.

  2. 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.

  3. Strip yielding model for calculation of COD in spheres with short cracks

    International Nuclear Information System (INIS)

    Miller, A.G.

    1981-08-01

    The crack opening displacement at the centre of a crack in a sphere with internal pressure has been calculated, using a strip yielding model. The results have been displayed for a range of geometrical parameters and loads. (author)

  4. 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.

  5. 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

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

    Science.gov (United States)

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

    2012-01-01

    Longleaf pine (Pinus palustris Mill.) is an important tree species of the southeast U.S. Currently there is no comprehensive stand-level growth and yield model for the species. The model system described here estimates site index (SI) if dominant height (Hdom) and stand age are known (inversely, the model can project H

  7. 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

  8. 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.

  9. Zebrafish Models of Human Leukemia: Technological Advances and Mechanistic Insights.

    Science.gov (United States)

    Harrison, Nicholas R; Laroche, Fabrice J F; Gutierrez, Alejandro; Feng, Hui

    2016-01-01

    Insights concerning leukemic pathophysiology have been acquired in various animal models and further efforts to understand the mechanisms underlying leukemic treatment resistance and disease relapse promise to improve therapeutic strategies. The zebrafish (Danio rerio) is a vertebrate organism with a conserved hematopoietic program and unique experimental strengths suiting it for the investigation of human leukemia. Recent technological advances in zebrafish research including efficient transgenesis, precise genome editing, and straightforward transplantation techniques have led to the generation of a number of leukemia models. The transparency of the zebrafish when coupled with improved lineage-tracing and imaging techniques has revealed exquisite details of leukemic initiation, progression, and regression. With these advantages, the zebrafish represents a unique experimental system for leukemic research and additionally, advances in zebrafish-based high-throughput drug screening promise to hasten the discovery of novel leukemia therapeutics. To date, investigators have accumulated knowledge of the genetic underpinnings critical to leukemic transformation and treatment resistance and without doubt, zebrafish are rapidly expanding our understanding of disease mechanisms and helping to shape therapeutic strategies for improved outcomes in leukemic patients.

  10. 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.

  11. 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.

  12. 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.

  13. Yield shear stress model of magnetorheological fluids based on exponential distribution

    International Nuclear Information System (INIS)

    Guo, Chu-wen; Chen, Fei; Meng, Qing-rui; Dong, Zi-xin

    2014-01-01

    The magnetic chain model that considers the interaction between particles and the external magnetic field in a magnetorheological fluid has been widely accepted. Based on the chain model, a yield shear stress model of magnetorheological fluids was proposed by introducing the exponential distribution to describe the distribution of angles between the direction of magnetic field and the chain formed by magnetic particles. The main influencing factors were considered in the model, such as magnetic flux density, intensity of magnetic field, particle size, volume fraction of particles, the angle of magnetic chain, and so on. The effect of magnetic flux density on the yield shear stress was discussed. The yield stress of aqueous Fe 3 O 4 magnetreological fluids with volume fraction of 7.6% and 16.2% were measured by a device designed by ourselves. The results indicate that the proposed model can be used for calculation of yield shear stress with acceptable errors. - Highlights: • A yield shear stress model of magnetorheological fluids was proposed. • Use exponential distribution to describe the distribution of magnetic chain angles. • Experimental and predicted results were in good agreement for 2 types of MR

  14. Stents: Biomechanics, Biomaterials, and Insights from Computational Modeling.

    Science.gov (United States)

    Karanasiou, Georgia S; Papafaklis, Michail I; Conway, Claire; Michalis, Lampros K; Tzafriri, Rami; Edelman, Elazer R; Fotiadis, Dimitrios I

    2017-04-01

    Coronary stents have revolutionized the treatment of coronary artery disease. Improvement in clinical outcomes requires detailed evaluation of the performance of stent biomechanics and the effectiveness as well as safety of biomaterials aiming at optimization of endovascular devices. Stents need to harmonize the hemodynamic environment and promote beneficial vessel healing processes with decreased thrombogenicity. Stent design variables and expansion properties are critical for vessel scaffolding. Drug-elution from stents, can help inhibit in-stent restenosis, but adds further complexity as drug release kinetics and coating formulations can dominate tissue responses. Biodegradable and bioabsorbable stents go one step further providing complete absorption over time governed by corrosion and erosion mechanisms. The advances in computing power and computational methods have enabled the application of numerical simulations and the in silico evaluation of the performance of stent devices made up of complex alloys and bioerodible materials in a range of dimensions and designs and with the capacity to retain and elute bioactive agents. This review presents the current knowledge on stent biomechanics, stent fatigue as well as drug release and mechanisms governing biodegradability focusing on the insights from computational modeling approaches.

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

    International Nuclear Information System (INIS)

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

    2009-01-01

    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.

  16. 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.

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

    Science.gov (United States)

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

    2015-12-01

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

  18. 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

  19. Prediction model of biocrude yield and nitrogen heterocyclic compounds analysis by hydrothermal liquefaction of microalgae with model compounds.

    Science.gov (United States)

    Sheng, Lili; Wang, Xin; Yang, Xiaoyi

    2018-01-01

    The model of biocrude yield and the nitrogen heterocyclic compounds in biocrude of microalgae hydrothermal liquefaction are two of the most concerned issues in this field at present. This study explored a hydrothermal liquefaction biocrude yield model involved in the interaction among biochemical compounds in microalgae and analysed nitrogen heterocyclic compounds in biocrude. The model compound (castor oil, soya protein and glucose) and Nanochloropsis were liquefied at 280°C for 1h. The products were analyzed by GC-MS, element analysis and FTIR. The results suggested that interactions among different components in microalgae enhanced biocrude yield. The biocrude yield prediction model involved cross-interactions performed more accurate than previous models.When the ratio of protein and carbohydrate around 3, the cross-interaction and nitrogen heterocyclic compounds in biocrude would both reach the highest extent. Copyright © 2017. Published by Elsevier Ltd.

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

    African Journals Online (AJOL)

    kusimi

    sediment delivery ratio; soil erosion modelling; sediment yield modelling. .... The basin falls within the wet semi-equitorial climatic belt which is ... influence of the moist south-west monsoons during the rainy season, with high .... availability of good satellite images covering the study area; because of thick cloud cover most.

  1. 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.

  2. 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.

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

    Science.gov (United States)

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

    1998-01-01

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

  4. 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......, Finland. This is the largest standardized crop model inter-comparison under different levels of N supply to date. The models were calibrated using data from 2002 and 2008, of which 2008 included six N rates ranging from 0 to 150 kg N/ha. Calibration data consisted of weather, soil, phenology, leaf area...... ranged from 170 to 870 kg/ha. During the test year 2009, most models failed to accurately reproduce the observed low yield without N fertilizer as well as the steep yield response to N applications. The multi-model predictions were closer to observations than most single-model predictions, but multi...

  5. 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....

  6. 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.

  7. New insight into unstable hillslopes hydrology from hydrogeochemical modelling.

    Science.gov (United States)

    Bertrand, C.; Marc, V.; Malet, J.-P.

    2010-05-01

    and mineralogical analyses or from the literature (kinetics constants). The simulations showed that pH, sulphate and calcium concentrations in groundwater could be reproduced from reasonable assumptions. However, the observed high concentrations in magnesium and sodium were not correctly simulated by the model. Furthermore, a particular anomaly in the Na+ concentration was observed in the most active part of the landslide. Lastly, isotopic investigation showed that groundwater 3H content in this sector was significantly lower than groundwater content in the other parts of the landslide and lower than the mean rainwater content. This result showed that the mean groundwater age in the active part was probably higher than elsewhere in the landslide. All these arguments led us to conclude that groundwater was locally recharged with saline waters from areas outside the watershed, coming up through the bedrock using major discontinuities. This assumption is in agreement with the geological context. de Montety, V., V. Marc, C. Emblanch, J.-P. Malet, C. Bertrand, O. Maquaire, and T. A. Bogaard, 2007, Identifying the origin of groundwater and flow processes in complex landslides affecting black marls: insights from a hydrochemical survey.: Earth Surface Processes and Landforms, v. 32, p. 32-48. Malet, J.-P. and Maquaire, O., 2003. Black marl earthflows mobility and long-term seasonal dynamic in southeastern France. In: Picarelli, L. (Ed). Proceedings of the International Conference on Fast Slope Movements: Prediction and Prevention for Risk Mitigation. Patron Editore, Bologna: 333-340. Maquaire, O., Malet, J.-P., Remaître, A., Locat, J., Klotz, S. and Guillon, J., 2003. Instability conditions of marly hillslopes: towards landsliding or gullying? The case of the Barcelonnette Bassin, South East France. Engineering Geology, 70(1-2): 109-130. Parkhurst, D.L. and Appelo, C.A.J., 1999, User's guide to PHREEQC (version 2)--A computer program for speciation, batch-reaction, one

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    Nathaniel K. Newlands

    2014-06-01

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

  10. 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.

  11. Crop Yield Simulations Using Multiple Regional Climate Models in the Southwestern United States

    Science.gov (United States)

    Stack, D.; Kafatos, M.; Kim, S.; Kim, J.; Walko, R. L.

    2013-12-01

    Agricultural productivity (described by crop yield) is strongly dependent on climate conditions determined by meteorological parameters (e.g., temperature, rainfall, and solar radiation). California is the largest producer of agricultural products in the United States, but crops in associated arid and semi-arid regions live near their physiological limits (e.g., in hot summer conditions with little precipitation). Thus, accurate climate data are essential in assessing the impact of climate variability on agricultural productivity in the Southwestern United States and other arid regions. To address this issue, we produced simulated climate datasets and used them as input for the crop production model. For climate data, we employed two different regional climate models (WRF and OLAM) using a fine-resolution (8km) grid. Performances of the two different models are evaluated in a fine-resolution regional climate hindcast experiment for 10 years from 2001 to 2010 by comparing them to the North American Regional Reanalysis (NARR) dataset. Based on this comparison, multi-model ensembles with variable weighting are used to alleviate model bias and improve the accuracy of crop model productivity over large geographic regions (county and state). Finally, by using a specific crop-yield simulation model (APSIM) in conjunction with meteorological forcings from the multi-regional climate model ensemble, we demonstrate the degree to which maize yields are sensitive to the regional climate in the Southwestern United States.

  12. 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.

  13. How model and input uncertainty impact maize yield simulations in West Africa

    Science.gov (United States)

    Waha, Katharina; Huth, Neil; Carberry, Peter; Wang, Enli

    2015-02-01

    Crop models are common tools for simulating crop yields and crop production in studies on food security and global change. Various uncertainties however exist, not only in the model design and model parameters, but also and maybe even more important in soil, climate and management input data. We analyze the performance of the point-scale crop model APSIM and the global scale crop model LPJmL with different climate and soil conditions under different agricultural management in the low-input maize-growing areas of Burkina Faso, West Africa. We test the models’ response to different levels of input information from little to detailed information on soil, climate (1961-2000) and agricultural management and compare the models’ ability to represent the observed spatial (between locations) and temporal variability (between years) in crop yields. We found that the resolution of different soil, climate and management information influences the simulated crop yields in both models. However, the difference between models is larger than between input data and larger between simulations with different climate and management information than between simulations with different soil information. The observed spatial variability can be represented well from both models even with little information on soils and management but APSIM simulates a higher variation between single locations than LPJmL. The agreement of simulated and observed temporal variability is lower due to non-climatic factors e.g. investment in agricultural research and development between 1987 and 1991 in Burkina Faso which resulted in a doubling of maize yields. The findings of our study highlight the importance of scale and model choice and show that the most detailed input data does not necessarily improve model performance.

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

    Science.gov (United States)

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

    2015-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Khanchoul Kamel

    2014-01-01

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

  16. 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,

  17. Implications of a visco-elastic model of the lithosphere for calculating yield strength envelopes

    NARCIS (Netherlands)

    Ershov, A.V.; Stephenson, R.A.

    2006-01-01

    The dominant deformation mechanism in the ductile part of the lithosphere is creep. From a mechanical point of view, creep can be modelled as a viscous phenomenon. On the other hand, yield-strength envelopes (YSEs), commonly used to describe lithosphere rheology, are constructed supposing creep to

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

    DEFF Research Database (Denmark)

    Boldrini, Lorenzo; Hillebrand, Eric Tobias

    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...

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

    Directory of Open Access Journals (Sweden)

    Edilberto Guevara-Pérez

    2007-01-01

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

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

    Science.gov (United States)

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

    2017-04-01

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

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

    Science.gov (United States)

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

    2015-12-15

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

  2. 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

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

    Science.gov (United States)

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

    2011-01-01

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

  4. 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

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

    Directory of Open Access Journals (Sweden)

    Stryczek Stanislaw

    2004-09-01

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

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

    Science.gov (United States)

    Wang, Haijun; Liang, Xiaomin; Wang, Hongzhu

    2017-07-01

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

  7. A Theoretical Model for Estimation of Yield Strength of Fiber Metal Laminate

    Science.gov (United States)

    Bhat, Sunil; Nagesh, Suresh; Umesh, C. K.; Narayanan, S.

    2017-08-01

    The paper presents a theoretical model for estimation of yield strength of fiber metal laminate. Principles of elasticity and formulation of residual stress are employed to determine the stress state in metal layer of the laminate that is found to be higher than the stress applied over the laminate resulting in reduced yield strength of the laminate in comparison with that of the metal layer. The model is tested over 4A-3/2 Glare laminate comprising three thin aerospace 2014-T6 aluminum alloy layers alternately bonded adhesively with two prepregs, each prepreg built up of three uni-directional glass fiber layers laid in longitudinal and transverse directions. Laminates with prepregs of E-Glass and S-Glass fibers are investigated separately under uni-axial tension. Yield strengths of both the Glare variants are found to be less than that of aluminum alloy with use of S-Glass fiber resulting in higher laminate yield strength than with the use of E-Glass fiber. Results from finite element analysis and tensile tests conducted over the laminates substantiate the theoretical model.

  8. Optomechanical Control of Quantum Yield in Trans-Cis Ultrafast Photoisomerization of a Retinal Chromophore Model.

    Science.gov (United States)

    Valentini, Alessio; Rivero, Daniel; Zapata, Felipe; García-Iriepa, Cristina; Marazzi, Marco; Palmeiro, Raúl; Fdez Galván, Ignacio; Sampedro, Diego; Olivucci, Massimo; Frutos, Luis Manuel

    2017-03-27

    The quantum yield of a photochemical reaction is one of the most fundamental quantities in photochemistry, as it measures the efficiency of the transduction of light energy into chemical energy. Nature has evolved photoreceptors in which the reactivity of a chromophore is enhanced by its molecular environment to achieve high quantum yields. The retinal chromophore sterically constrained inside rhodopsin proteins represents an outstanding example of such a control. In a more general framework, mechanical forces acting on a molecular system can strongly modify its reactivity. Herein, we show that the exertion of tensile forces on a simplified retinal chromophore model provokes a substantial and regular increase in the trans-to-cis photoisomerization quantum yield in a counterintuitive way, as these extension forces facilitate the formation of the more compressed cis photoisomer. A rationale for the mechanochemical effect on this photoisomerization mechanism is also proposed. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. 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

  10. 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.

  11. 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.

  12. Modeling Insight into Battery Electrolyte Electrochemical Stability and Interfacial Structure.

    Science.gov (United States)

    Borodin, Oleg; Ren, Xiaoming; Vatamanu, Jenel; von Wald Cresce, Arthur; Knap, Jaroslaw; Xu, Kang

    2017-12-19

    Electroactive interfaces distinguish electrochemistry from chemistry and enable electrochemical energy devices like batteries, fuel cells, and electric double layer capacitors. In batteries, electrolytes should be either thermodynamically stable at the electrode interfaces or kinetically stable by forming an electronically insulating but ionically conducting interphase. In addition to a traditional optimization of electrolytes by adding cosolvents and sacrificial additives to preferentially reduce or oxidize at the electrode surfaces, knowledge of the local electrolyte composition and structure within the double layer as a function of voltage constitutes the basis of manipulating an interphase and expanding the operating windows of electrochemical devices. In this work, we focus on how the molecular-scale insight into the solvent and ion partitioning in the electrolyte double layer as a function of applied potential could predict changes in electrolyte stability and its initial oxidation and reduction reactions. In molecular dynamics (MD) simulations, highly concentrated lithium aqueous and nonaqueous electrolytes were found to exclude the solvent molecules from directly interacting with the positive electrode surface, which provides an additional mechanism for extending the electrolyte oxidation stability in addition to the well-established simple elimination of "free" solvent at high salt concentrations. We demonstrate that depending on their chemical structures, the anions could be designed to preferentially adsorb or desorb from the positive electrode with increasing electrode potential. This provides additional leverage to dictate the order of anion oxidation and to effectively select a sacrificial anion for decomposition. The opposite electrosorption behaviors of bis(trifluoromethane)sulfonimide (TFSI) and trifluoromethanesulfonate (OTF) as predicted by MD simulation in highly concentrated aqueous electrolytes were confirmed by surface enhanced infrared

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

    International Nuclear Information System (INIS)

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

    2017-01-01

    Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the 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.

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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...... (If), deficit irrigated (Id) and not irrigated (I0) were investigated in three-years potato field experiment (2013–15) with four replicates in randomized complete block design. Tuber and total dry matter yield, canopy cover, dry matter production during the crop growth season, and soil water content...

  19. 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)

  20. When to stop drying fruit: Insights from hygrothermal modelling

    International Nuclear Information System (INIS)

    Defraeye, Thijs

    2017-01-01

    Highlights: • Partial dehydration reduces energy consumption and processing time and improves product quality. • This study gives a quantitative insight in when fruit drying should be stopped. • Decrease in dryer residence time of 2%, 24% and 70% are found for different stopping criteria. - Abstract: Stopping the drying process prior to complete dehydration reduces energy consumption and processing time but can also improve product quality. Using hygrothermal simulations, different stopping criteria are evaluated, which are based on the final water activity and residual moisture content in the fruit. Their impact on drying time and moisture redistribution kinetics inside fruit is quantified. One of the variants leads to a significant reduction in residence time in the dryer (24%), compared to full dehydration. For this variant, drying is stopped when the average moisture content in the sample reaches the value corresponding to an equilibrium water activity of 60% in the sample, as determined from the sorption isotherm. At the same time, this variant does not induce problems with fruit spoilage, as a sufficiently low water activity is reached after moisture redistribution during relaxation in the ambient environment. In addition, the relation of the drying time to the drying air temperature was quantified for all stopping criteria, as well as the impact of the humidity of the ambient environment in which the dried fruits are placed afterwards. This study gives a better quantitative insight in when fruit drying should be stopped, given specific drying conditions, without having to compromise food safety.

  1. 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.

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

    OpenAIRE

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

    2017-01-01

    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 reprodu...

  3. Genetic correlations among body condition score, yield and fertility in multiparous cows using random regression models

    OpenAIRE

    Bastin, Catherine; Gillon, Alain; Massart, Xavier; Bertozzi, Carlo; Vanderick, Sylvie; Gengler, Nicolas

    2010-01-01

    Genetic correlations between body condition score (BCS) in lactation 1 to 3 and four economically important traits (days open, 305-days milk, fat, and protein yields recorded in the first 3 lactations) were estimated on about 12,500 Walloon Holstein cows using 4-trait random regression models. Results indicated moderate favorable genetic correlations between BCS and days open (from -0.46 to -0.62) and suggested the use of BCS for indirect selection on fertility. However, unfavorable genetic c...

  4. 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.

  5. An overview of available crop growth and yield models for studies and assessments in agriculture.

    Science.gov (United States)

    Di Paola, Arianna; Valentini, Riccardo; Santini, Monia

    2016-02-01

    The scientific community offers numerous crop models with different levels of sophistication. In such a wide range of crop models, users should have the possibility to choose the most suitable, in terms of detail, scale and representativeness, to their objectives. However, even when an appropriate choice is made, model limitations should be clarified such that modelling studies are put in the proper perspective and robust applications are achieved. This work is an overview of available models to simulate crop growth and yield. A summary matrix with more than 70 crop models is provided, storing the main model characteristics that can help users to choose the proper tool according to their purposes. Overall, we found that two main aspects of models, despite their importance, are not always clear from the published references, i.e. the versatility of the models, in terms of reliable transferability to different conditions, and the degree of complexity. Hence, the developers of models should be encouraged to pay more attention to clarifying the model limitations and limits of applicability, and users should make an effort in proper model selection, to save time often devoted to iteration of tuning steps to force an inappropriate model to be adapted to their own purpose. © 2015 Society of Chemical Industry.

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

    Science.gov (United States)

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

    2014-12-01

    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.

  7. 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)

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

    Directory of Open Access Journals (Sweden)

    M Irfan Ashraf

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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

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

    Directory of Open Access Journals (Sweden)

    Laila Alejandra Puntel

    2016-11-01

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

  15. 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

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

    Science.gov (United States)

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

    2016-01-01

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

  17. 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.

  18. 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

  19. 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

  20. Using Models to Inform Policy: Insights from Modeling the Complexities of Global Polio Eradication

    Science.gov (United States)

    Thompson, Kimberly M.

    Drawing on over 20 years of experience modeling risks in complex systems, this talk will challenge SBP participants to develop models that provide timely and useful answers to critical policy questions when decision makers need them. The talk will include reflections on the opportunities and challenges associated with developing integrated models for complex problems and communicating their results effectively. Dr. Thompson will focus the talk largely on collaborative modeling related to global polio eradication and the application of system dynamics tools. After successful global eradication of wild polioviruses, live polioviruses will still present risks that could potentially lead to paralytic polio cases. This talk will present the insights of efforts to use integrated dynamic, probabilistic risk, decision, and economic models to address critical policy questions related to managing global polio risks. Using a dynamic disease transmission model combined with probabilistic model inputs that characterize uncertainty for a stratified world to account for variability, we find that global health leaders will face some difficult choices, but that they can take actions that will manage the risks effectively. The talk will emphasize the need for true collaboration between modelers and subject matter experts, and the importance of working with decision makers as partners to ensure the development of useful models that actually get used.

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

    Science.gov (United States)

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

    2016-12-01

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

  2. 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.

  3. Possible ecosystem impacts of applying maximum sustainable yield policy in food chain models.

    Science.gov (United States)

    Ghosh, Bapan; Kar, T K

    2013-07-21

    This paper describes the possible impacts of maximum sustainable yield (MSY) and maximum sustainable total yield (MSTY) policy in ecosystems. In general it is observed that exploitation at MSY (of single species) or MSTY (of multispecies) level may cause the extinction of several species. In particular, for traditional prey-predator system, fishing under combined harvesting effort at MSTY (if it exists) level may be a sustainable policy, but if MSTY does not exist then it is due to the extinction of the predator species only. In generalist prey-predator system, harvesting of any one of the species at MSY level is always a sustainable policy, but harvesting of both the species at MSTY level may or may not be a sustainable policy. In addition, we have also investigated the MSY and MSTY policy in a traditional tri-trophic and four trophic food chain models. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. 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

  5. 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)

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

    Directory of Open Access Journals (Sweden)

    E. A. C. Costantini

    2009-09-01

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

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

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

    Science.gov (United States)

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

    2017-08-01

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

  8. Extrapolating effects of conservation tillage on yield, soil moisture and dry spell mitigation using simulation modelling

    Science.gov (United States)

    Mkoga, Z. J.; Tumbo, S. D.; Kihupi, N.; Semoka, J.

    There is big effort to disseminate conservation tillage practices in Tanzania. Despite wide spread field demonstrations there has been some field experiments meant to assess and verify suitability of the tillage options in local areas. Much of the experiments are short lived and thus long term effects of the tillage options are unknown. Experiments to study long term effects of the tillage options are lacking because they are expensive and cannot be easily managed. Crop simulation models have the ability to use long term weather data and the local soil parameters to assess long term effects of the tillage practices. The Agricultural Production Systems Simulator (APSIM) crop simulation model; was used to simulate long term production series of soil moisture and grain yield based on the soil and weather conditions in Mkoji sub-catchment of the great Ruaha river basin in Tanzania. A 24 year simulated maize yield series based on conventional tillage with ox-plough, without surface crop residues (CT) treatment was compared with similar yield series based on conservation tillage (ox-ripping, with surface crop residues (RR)). Results showed that predicted yield averages were significantly higher in conservation tillage than in conventional tillage ( P APSIM simulation model, showed that average soil moisture in the conservation tillage was significantly higher ( P < 0.05) (about 0.29 mm/mm) than in conventional tillage (0.22 mm/mm) treatment during the seasons which received rainfall between 468 and 770 mm. Similarly the conservation tillage treatment recorded significantly higher yields (4.4 t/ha) ( P < 0.01) than the conventional tillage (3.6 t/ha) treatment in the same range of seasonal rainfall. On the other hand there was no significant difference in soil moisture for the seasons which received rainfall above 770 mm. In these seasons grain yield in conservation tillage treatment was significantly lower (3.1 kg/ha) than in the conventional tillage treatment (4.8 kg

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

    Science.gov (United States)

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

    2017-02-21

    Capillary rise from shallow groundwater can decrease the need for irrigation water. However, simple techniques do not exist to quantify the contribution of capillary flux to crop water use. In this study we develop the Agricultural Water Productivity Model for Shallow Groundwater (AWPM-SG) for calculating capillary fluxes from shallow groundwater using readily available data. The model combines an analytical solution of upward flux from groundwater with the EPIC crop growth model. AWPM-SG was calibrated and validated with 2-year lysimetric experiment with maize. Predicted soil moisture, groundwater depth and leaf area index agreed with the observations. To investigate the response of model, various scenarios were run in which the irrigation amount and groundwater depth were varied. Simulations shows that at groundwater depth of 1 m capillary upward supplied 41% of the evapotranspiration. This reduced to 6% at groundwater depth of 2 m. The yield per unit water consumed (water productivity) was nearly constant for 2.3 kg/m 3 . The yield per unit water applied (irrigation water productivity) increased with decreasing irrigation water because capillary rise made up in part for the lack of irrigation water. Consequently, using AWPM-SG in irrigation scheduling will be beneficial to save more water in areas with shallow groundwater.

  10. Effects of Source RDP Models and Near-source Propagation: Implication for Seismic Yield Estimation

    Science.gov (United States)

    Saikia, C. K.; Helmberger, D. V.; Stead, R. J.; Woods, B. B.

    - It has proven difficult to uniquely untangle the source and propagation effects on the observed seismic data from underground nuclear explosions, even when large quantities of near-source, broadband data are available for analysis. This leads to uncertainties in our ability to quantify the nuclear seismic source function and, consequently the accuracy of seismic yield estimates for underground explosions. Extensive deterministic modeling analyses of the seismic data recorded from underground explosions at a variety of test sites have been conducted over the years and the results of these studies suggest that variations in the seismic source characteristics between test sites may be contributing to the observed differences in the magnitude/yield relations applicable at those sites. This contributes to our uncertainty in the determination of seismic yield estimates for explosions at previously uncalibrated test sites. In this paper we review issues involving the relationship of Nevada Test Site (NTS) source scaling laws to those at other sites. The Joint Verification Experiment (JVE) indicates that a magnitude (mb) bias (δmb) exists between the Semipalatinsk test site (STS) in the former Soviet Union (FSU) and the Nevada test site (NTS) in the United States. Generally this δmb is attributed to differential attenuation in the upper-mantle beneath the two test sites. This assumption results in rather large estimates of yield for large mb tunnel shots at Novaya Zemlya. A re-examination of the US testing experiments suggests that this δmb bias can partly be explained by anomalous NTS (Pahute) source characteristics. This interpretation is based on the modeling of US events at a number of test sites. Using a modified Haskell source description, we investigated the influence of the source Reduced Displacement Potential (RDP) parameters ψ ∞ , K and B by fitting short- and long-period data simultaneously, including the near-field body and surface waves. In general

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

    Directory of Open Access Journals (Sweden)

    D. K. Henze

    2008-05-01

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

  12. Predicting oil and gas compositional yields via chemical structure-chemical yield modeling (CS-CYM): Part 1 - Concepts and implementation

    Energy Technology Data Exchange (ETDEWEB)

    Freund, H.; Walters, C.C.; Kelemen, S.R.; Siskin, M.; Gorbaty, M.L.; Curry, D.J.; Bence, A.E. [ExxonMobil Research & Engineering Co., Annandale, NJ (United States)

    2007-07-01

    We have developed a method to calculate the amounts and composition of products resulting from the thermal decomposition of a solid complex carbonaceous material. This procedure provides a means of using laboratory measurements of complex carbonaceous solids to construct a representative model of its chemical structure (CS) that is then coupled with elementary reaction pathways to predict the chemical yield (CY) upon thermal decomposition. Data from elemental analysis, H, N, O, S, solid state {sup 13}C NMR, X-ray photoelectron spectroscopy (XPS), sulfur X-ray absorption structure spectroscopy (XANES), and pyrolysis-gas chromatography (GC) are used to constrain the construction of core molecular structures representative of the complex carbonaceous material. These core structures are expanded stochastically to describe large macromolecules ({gt} 10{sup 6} cores with similar to 10{sup 6} atoms) with bulk properties that match the experimental results. Gas, liquid and solid product yields, resulting from thermal decomposition, are calculated by identifying reactive functional groups within the CS stochastic ensemble and imposing a reaction network constrained by fundamental thermodynamics and kinetics. An expulsion model is added to the decomposition model to calculate the chemical products in open and closed systems. Product yields may then be predicted under a wide range of time-temperature conditions used in rapid laboratory pyrolysis experiments, refinery processes, or geologic maturation.

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

    KAUST Repository

    Moreo, P.; Gaffney, E. A.; Garcí a-Aznar, J. M.; Doblaré , M.

    2009-01-01

    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

  14. Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development.

    Science.gov (United States)

    Tøndel, Kristin; Niederer, Steven A; Land, Sander; Smith, Nicolas P

    2014-05-20

    Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input-output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on

  15. Osteoarthritis and metabolic dysregulation: insights from a preclinical model

    NARCIS (Netherlands)

    Visser, H.M. de

    2018-01-01

    This thesis aims to identify the effect of metabolic factors, inflammatory processes and obesity in the pathophysiology of osteoarthritis (OA), using a high-fat diet and/or traumatic injury in a small animal model. The first part of this thesis describes, the rat Groove model of OA, using a one-time

  16. Genetic models of absence epilepsy: New concepts and insights

    NARCIS (Netherlands)

    Luijtelaar, E.L.J.M. van; Coenen, A.M.L.; Schwartzkroin, P.A.

    2009-01-01

    The discovery, development, and use of genetic rodent models of absence epilepsy have led to a new theory about the origin of absence seizures. A focal zone has been identified in the peri-oral region of the somatosensory cortex in WAG/Rij and GAERS – the two most commonly used models – from which

  17. 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

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

    Directory of Open Access Journals (Sweden)

    G. Bussi

    2013-08-01

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

  19. 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.

  20. 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

  1. Choosing algorithms for TB screening: a modelling study to compare yield, predictive value and diagnostic burden.

    Science.gov (United States)

    Van't Hoog, Anna H; Onozaki, Ikushi; Lonnroth, Knut

    2014-10-19

    To inform the choice of an appropriate screening and diagnostic algorithm for tuberculosis (TB) screening initiatives in different epidemiological settings, we compare algorithms composed of currently available methods. Of twelve algorithms composed of screening for symptoms (prolonged cough or any TB symptom) and/or chest radiography abnormalities, and either sputum-smear microscopy (SSM) or Xpert MTB/RIF (XP) as confirmatory test we model algorithm outcomes and summarize the yield, number needed to screen (NNS) and positive predictive value (PPV) for different levels of TB prevalence. Screening for prolonged cough has low yield, 22% if confirmatory testing is by SSM and 32% if XP, and a high NNS, exceeding 1000 if TB prevalence is ≤0.5%. Due to low specificity the PPV of screening for any TB symptom followed by SSM is less than 50%, even if TB prevalence is 2%. CXR screening for TB abnormalities followed by XP has the highest case detection (87%) and lowest NNS, but is resource intensive. CXR as a second screen for symptom screen positives improves efficiency. The ideal algorithm does not exist. The choice will be setting specific, for which this study provides guidance. Generally an algorithm composed of CXR screening followed by confirmatory testing with XP can achieve the lowest NNS and highest PPV, and is the least amenable to setting-specific variation. However resource requirements for tests and equipment may be prohibitive in some settings and a reason to opt for symptom screening and SSM. To better inform disease control programs we need empirical data to confirm the modeled yield, cost-effectiveness studies, transmission models and a better screening test.

  2. 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.

  3. 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.

  4. Incorporating Yearly Derived Winter Wheat Maps Into Winter Wheat Yield Forecasting Model

    Science.gov (United States)

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

    2016-01-01

    Wheat is one of the most important cereal crops in the world. Timely and accurate forecast of wheat yield and production at global scale is vital in implementing food security policy. Becker-Reshef et al. (2010) developed a generalized empirical model for forecasting winter wheat production using remote sensing data and official statistics. This model was implemented using static wheat maps. In this paper, we analyze the impact of incorporating yearly wheat masks into the forecasting model. We propose a new approach of producing in season winter wheat maps exploiting satellite data and official statistics on crop area only. Validation on independent data showed that the proposed approach reached 6% to 23% of omission error and 10% to 16% of commission error when mapping winter wheat 2-3 months before harvest. In general, we found a limited impact of using yearly winter wheat masks over a static mask for the study regions.

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

    Directory of Open Access Journals (Sweden)

    Chongfeng Lan

    2015-05-01

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

  6. 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

  7. 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.

  8. Business models for telehealth in the US: analyses and insights

    Directory of Open Access Journals (Sweden)

    Pereira F

    2017-02-01

    Full Text Available Francis Pereira Data Sciences and Operations, Marshall School of Business, University of Southern, Los Angeles, CA, USAAbstract: A growing shortage of medical doctors and nurses, globally, coupled with increasing life expectancy, is generating greater cost pressures on health care, in the US and globally. In this respect, telehealth can help alleviate these pressures, as well as extend medical services to underserved or unserved areas. However, its relatively slow adoption in the US, as well as in other markets, suggests the presence of barriers and challenges. The use of a business model framework helps identify the value proposition of telehealth as well as these challenges, which include identifying the right revenue model, organizational structure, and, perhaps more importantly, the stakeholders in the telehealth ecosystem. Successful and cost-effective deployment of telehealth require a redefinition of the ecosystem and a comprehensive review of all benefits and beneficiaries of such a system; hence a reassessment of all the stakeholders that could benefit from such a system, beyond the traditional patient–health provider–insurer model, and thus “who should pay” for such a system, and the driving efforts of a “keystone” player in developing this initiative would help. Keywords: telehealth, business model framework, stakeholders, ecosystem, VISOR business Model

  9. 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

  10. 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.

  11. 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.

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    Nader Naifar

    2016-09-01

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

  14. Insights into channel dysfunction from modelling and molecular dynamics simulations.

    Science.gov (United States)

    Musgaard, Maria; Paramo, Teresa; Domicevica, Laura; Andersen, Ole Juul; Biggin, Philip C

    2018-04-01

    Developments in structural biology mean that the number of different ion channel structures has increased significantly in recent years. Structures of ion channels enable us to rationalize how mutations may lead to channelopathies. However, determining the structures of ion channels is still not trivial, especially as they necessarily exist in many distinct functional states. Therefore, the use of computational modelling can provide complementary information that can refine working hypotheses of both wild type and mutant ion channels. The simplest but still powerful tool is homology modelling. Many structures are available now that can provide suitable templates for many different types of ion channels, allowing a full three-dimensional interpretation of mutational effects. These structural models, and indeed the structures themselves obtained by X-ray crystallography, and more recently cryo-electron microscopy, can be subjected to molecular dynamics simulations, either as a tool to help explore the conformational dynamics in detail or simply as a means to refine the models further. Here we review how these approaches have been used to improve our understanding of how diseases might be linked to specific mutations in ion channel proteins. This article is part of the Special Issue entitled 'Channelopathies.' Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  15. 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

  16. 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.

  17. Genetic models of absence epilepsy: New concepts and insights

    NARCIS (Netherlands)

    Luijtelaar, E.L.J.M. van; Stein, J.

    2017-01-01

    The discovery, development and use of genetic rodent models of absence epilepsy have led to a new theory about the origin of absence seizures, which has gained impact within the international epilepsy community. A focal zone has been identified in the perioral region of the somatosensory cortex in

  18. 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…

  19. 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.

  20. An advanced constitutive model in the sheet metal forming simulation: the Teodosiu microstructural model and the Cazacu Barlat yield criterion

    International Nuclear Information System (INIS)

    Alves, J.L.; Oliveira, M.C.; Menezes, L.F.

    2004-01-01

    Two constitutive models used to describe the plastic behavior of sheet metals in the numerical simulation of sheet metal forming process are studied: a recently proposed advanced constitutive model based on the Teodosiu microstructural model and the Cazacu Barlat yield criterion is compared with a more classical one, based on the Swift law and the Hill 1948 yield criterion. These constitutive models are implemented into DD3IMP, a finite element home code specifically developed to simulate sheet metal forming processes, which generically is a 3-D elastoplastic finite element code with an updated Lagrangian formulation, following a fully implicit time integration scheme, large elastoplastic strains and rotations. Solid finite elements and parametric surfaces are used to model the blank sheet and tool surfaces, respectively. Some details of the numerical implementation of the constitutive models are given. Finally, the theory is illustrated with the numerical simulation of the deep drawing of a cylindrical cup. The results show that the proposed advanced constitutive model predicts with more exactness the final shape (medium height and ears profile) of the formed part, as one can conclude from the comparison with the experimental results

  1. A hydrologic regression sediment-yield model for two ungaged watershed outlet stations in Africa

    International Nuclear Information System (INIS)

    Moussa, O.M.; Smith, S.E.; Shrestha, R.L.

    1991-01-01

    A hydrologic regression sediment-yield model was established to determine the relationship between water discharge and suspended sediment discharge at the Blue Nile and the Atbara River outlet stations during the flood season. The model consisted of two main submodels: (1) a suspended sediment discharge model, which was used to determine suspended sediment discharge for each basin outlet; and (2) a sediment rating model, which related water discharge and suspended sediment discharge for each outlet station. Due to the absence of suspended sediment concentration measurements at or near the outlet stations, a minimum norm solution, which is based on the minimization of the unknowns rather than the residuals, was used to determine the suspended sediment discharges at the stations. In addition, the sediment rating submodel was regressed by using an observation equations procedure. Verification analyses on the model were carried out and the mean percentage errors were found to be +12.59 and -12.39, respectively, for the Blue Nile and Atbara. The hydrologic regression model was found to be most sensitive to the relative weight matrix, moderately sensitive to the mean water discharge ratio, and slightly sensitive to the concentration variation along the River Nile's course

  2. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-10-06

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

  4. 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.

  5. Insights from quantum cognitive models for organizational decision making

    OpenAIRE

    White, L.C.; Pothos, E. M.; Busemeyer, J. R.

    2015-01-01

    Organizational decision making is often explored with theories from the heuristics and biases research program, which have demonstrated great value as descriptions of how people in organizations make decisions. Nevertheless, rational analysis and classical probability theory are still seen by many as the best accounts of how decisions should be made and classical probability theory is the preferred framework for cognitive modelling for many researchers. The focus of this work is quantum proba...

  6. 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. 

  7. 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.

  8. 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.

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

    Science.gov (United States)

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

    2016-12-01

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

  10. Ambient vibrations of unstable rock slopes - insights from numerical modeling

    Science.gov (United States)

    Burjanek, Jan; Kleinbrod, Ulrike; Fäh, Donat

    2017-04-01

    The recent events in Nepal (2015 M7.8 Gorkha) and New Zealand (2016 M7.8 Kaikoura) highlighted the importance of earthquake-induced landslides, which caused significant damages. Moreover, landslide created dams present a potential developing hazard. In order to reduce the costly consequences of such events it is important to detect and characterize earthquake susceptible rock slope instabilities before an event, and to take mitigation measures. For the characterisation of instable slopes, acquisition of ambient vibrations might be a new alternative to the already existing methods. We present both observations and 3D numerical simulations of the ambient vibrations of unstable slopes. In particular, models of representative real sites have been developed based on detailed terrain mapping and used for the comparison between synthetics and observations. A finite-difference code has been adopted for the seismic wave propagation in a 3D inhomogeneous visco-elastic media with irregular free surface. It utilizes a curvilinear grid for a precise modeling of curved topography and local mesh refinement to make computational mesh finer near the free surface. Topographic site effects, controlled merely by the shape of the topography, do not explain the observed seismic response. In contrast, steeply-dipping compliant fractures have been found to play a key role in fitting observations. Notably, the synthetized response is controlled by inertial mass of the unstable rock, and by stiffness, depth and network density of the fractures. The developed models fit observed extreme amplification levels (factors of 70!) and show directionality as well. This represents a possibility to characterize slope structure and infer depth or volume of the slope instability from the ambient noise recordings in the future.

  11. Giant Glial Cell: New Insight Through Mechanism-Based Modeling

    DEFF Research Database (Denmark)

    Postnov, D. E.; Ryazanova, L. S.; Brazhe, Nadezda

    2008-01-01

    The paper describes a detailed mechanism-based model of a tripartite synapse consisting of P- and R-neurons together with a giant glial cell in the ganglia of the medical leech (Hirudo medicinalis), which is a useful object for experimental studies in situ. We describe the two main pathways...... of the glial cell activation: (1) via IP3 production and Ca2+ release from the endoplasmic reticulum and (2) via increase of the extracellular potassium concentration, glia depolarization, and opening of voltage-dependent Ca2+ channels. We suggest that the second pathway is the more significant...

  12. 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

  13. Genetic Parameters for Body condition score, Body weigth, Milk yield and Fertility estimated using random regression models

    NARCIS (Netherlands)

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

    2003-01-01

    Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields

  14. Modelling insights on the partition of evapotranspiration components across biomes

    Science.gov (United States)

    Fatichi, Simone; Pappas, Christoforos

    2017-04-01

    Recent studies using various methodologies have found a large variability (from 35 to 90%) in the ratio of transpiration to total evapotranspiration (denoted as T:ET) across biomes or even at the global scale. Concurrently, previous results suggest that T:ET is independent of mean precipitation and has a positive correlation with Leaf Area Index (LAI). We used the mechanistic ecohydrological model, T&C, with a refined process-based description of soil resistance and a detailed treatment of canopy biophysics and ecophysiology, to investigate T:ET across multiple biomes. Contrary to observation-based estimates, simulation results highlight a well-constrained range of mean T:ET across biomes that is also robust to perturbations of the most sensitive parameters. Simulated T:ET was confirmed to be independent of average precipitation, while it was found to be uncorrelated with LAI across biomes. Higher values of LAI increase evaporation from interception but suppress ground evaporation with the two effects largely cancelling each other in many sites. These results offer mechanistic, model-based, evidence to the ongoing research about the range of T:ET and the factors affecting its magnitude across biomes.

  15. Elastase-induced pulmonary emphysema: insights from experimental models

    Directory of Open Access Journals (Sweden)

    Mariana A. Antunes

    2011-12-01

    Full Text Available Several distinct stimuli can be used to reproduce histological and functional features of human emphysema, a leading cause of disability and death. Since cigarette smoke is the main cause of emphysema in humans, experimental researches have attempted to reproduce this situation. However, this is an expensive and cumbersome method of emphysema induction, and simpler, more efficacious alternatives have been sought. Among these approaches, elastolytic enzymes have been widely used to reproduce some characteristics of human cigarette smoke-induced disease, such as: augmentation of airspaces, inflammatory cell influx into the lungs, and systemic inflammation. Nevertheless, the use of elastase-induced emphysema models is still controversial, since the disease pathways involved in elastase induction may differ from those occurring in smoke-induced emphysema. This indicates that the choice of an emphysema model may impact the results of new therapies or drugs being tested. The aim of this review is to compare the mechanisms of disease induction in smoke and elastase emphysema models, to describe the differences among various elastase models, and to establish the advantages and disadvantages of elastase-induced emphysema models. More studies are required to shed light on the mechanisms of elastase-induced emphysema.Diversos estímulos podem ser utilizados para reproduzir características histológicas e funcionais do enfisema humano, uma das principais causas de incapacidade e morte. Uma vez que a fumaça de cigarro é a principal causa de enfisema em humanos, estudos experimentais têm tentado reproduzir esta situação. No entanto, esse é um método dispendioso e complicado para a indução do enfisema e, alternativas mais simples e eficazes, têm sido pesquisadas. Entre essas abordagens, enzimas elastolíticas vêm sendo amplamente utilizadas para reproduzir algumas das características do enfisema humano, tais como: aumento dos espaços a

  16. Dynamic growth and yield model for Black pine stands in Spain

    Energy Technology Data Exchange (ETDEWEB)

    Mora, J. V.; Rio, M. del; Bravo-Oviedo, A.

    2012-07-01

    In a forestry context, modelling stand development over time relies on estimates of different stand characteristics obtained from equations which usually constitute a multivariate system. In this study we have developed a stand growth model for even-aged stands of Black pine (Pinus nigra Arn.) in Spain. The 53 plots used to fit the equations came from the permanent sample plot network established by the Forest Research Centre (INIA) in 1963 and 1964 in the main distribution regions of Black pine. The model is made up of a system of equations to predict growth and yield in volume and basal area. In the fitting phase we took into account the correlation between the measurements within the same plot and the cross-equation residual correlations. The model incorporates a control function to estimate the thinning effect and a function for predicting the reduction in tree number due to regular mortality. In addition, we use the three parameter Weibull distribution function to estimate the number of trees in each diameter class by recovering the parameters using the moment method. The developed model is useful for simulating the evolution of even-aged stands with and without thinnings and allows the estimation of number of trees by diameter classes. (Author) 44 refs.

  17. 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

  18. Cellulose synthases: new insights from crystallography and modeling.

    Science.gov (United States)

    Slabaugh, Erin; Davis, Jonathan K; Haigler, Candace H; Yingling, Yaroslava G; Zimmer, Jochen

    2014-02-01

    Detailed information about the structure and biochemical mechanisms of cellulose synthase (CelS) proteins remained elusive until a complex containing the catalytic subunit (BcsA) of CelS from Rhodobacter sphaeroides was crystalized. Additionally, a 3D structure of most of the cytosolic domain of a plant CelS (GhCESA1 from cotton, Gossypium hirsutum) was produced by computational modeling. This predicted structure contributes to our understanding of how plant CelS proteins may be similar and different as compared with BcsA. In this review, we highlight how these structures impact our understanding of the synthesis of cellulose and other extracellular polysaccharides. We show how the structures can be used to generate hypotheses for experiments testing mechanisms of glucan synthesis and translocation in plant CelS. Copyright © 2013 Elsevier Ltd. All rights reserved.

  19. Market Orientation within University Schools of Business: Can a Dynamical Systems Viewpoint Applied to a Non-Temporal Data Set Yield Valuable Insights for University Managers?

    Science.gov (United States)

    Cox, John C.; Webster, Robert L.; Hammond, Kevin L.

    2009-01-01

    This study investigates the use of using complexity theory--the study of nonlinear dynamical systems of which chaos and catastrophe theory are subsets--in the analysis of a non temporal data set to derive valuable insights into the functioning of university schools of business. The approach is unusual in that studies of nonlinearity in complex…

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

    Science.gov (United States)

    Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

    2017-07-01

    High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

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

    Science.gov (United States)

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

    2017-02-01

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

  6. 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

  7. 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.

  8. 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.

  9. Seismic variability of subduction thrust faults: Insights from laboratory models

    Science.gov (United States)

    Corbi, F.; Funiciello, F.; Faccenna, C.; Ranalli, G.; Heuret, A.

    2011-06-01

    Laboratory models are realized to investigate the role of interface roughness, driving rate, and pressure on friction dynamics. The setup consists of a gelatin block driven at constant velocity over sand paper. The interface roughness is quantified in terms of amplitude and wavelength of protrusions, jointly expressed by a reference roughness parameter obtained by their product. Frictional behavior shows a systematic dependence on system parameters. Both stick slip and stable sliding occur, depending on driving rate and interface roughness. Stress drop and frequency of slip episodes vary directly and inversely, respectively, with the reference roughness parameter, reflecting the fundamental role for the amplitude of protrusions. An increase in pressure tends to favor stick slip. Static friction is a steeply decreasing function of the reference roughness parameter. The velocity strengthening/weakening parameter in the state- and rate-dependent dynamic friction law becomes negative for specific values of the reference roughness parameter which are intermediate with respect to the explored range. Despite the simplifications of the adopted setup, which does not address the problem of off-fault fracturing, a comparison of the experimental results with the depth distribution of seismic energy release along subduction thrust faults leads to the hypothesis that their behavior is primarily controlled by the depth- and time-dependent distribution of protrusions. A rough subduction fault at shallow depths, unable to produce significant seismicity because of low lithostatic pressure, evolves into a moderately rough, velocity-weakening fault at intermediate depths. The magnitude of events in this range is calibrated by the interplay between surface roughness and subduction rate. At larger depths, the roughness further decreases and stable sliding becomes gradually more predominant. Thus, although interplate seismicity is ultimately controlled by tectonic parameters (velocity of

  10. The Morphological Characteristics and Mechanical Formation of Giant Radial Dike Swarms on Venus: An Overview Emphasizing Recent Numerical Modeling Insights

    Science.gov (United States)

    McGovern, P. J., Jr.; Grosfils, E. B.; Le Corvec, N.; Ernst, R. E.; Galgana, G. A.

    2017-12-01

    Over 200 giant radial dike swarms have been identified on Venus using Magellan data, yielding insight into morphological characteristics long since erased by erosion and other processes on Earth. Since such radial dike systems are typically associated with magma reservoirs, large volcanoes and/or larger-scale plume activity—and because dike geometry reflects stress conditions at the time of intrusion—assessing giant radial dike formation in the context of swarm morphology can place important constraints upon this fundamental volcanotectonic process. Recent numerical models reveal that, contrary to what is reported in much of the published literature, it is not easy, mechanically, to produce either large or small radial dike systems. After extensive numerical examination of reservoir inflation, however, under conditions ranging from a simple halfspace to complex flexural loading, we have thus far identified four scenarios that produce radial dike systems. Two of these scenarios yield dike systems akin to those often associated with shield and stratocone volcanoes on Earth, while the other two, our focus here, are more consistent with the giant radial dike system geometries catalogued on Venus. In this presentation we will (a) review key morphological characteristics of the giant radial systems identified on Venus, (b) briefly illustrate why it is not easy, mechanically, to produce a radial dike system, (c) present the two volcanological circumstances we have identified that do allow a giant radial dike system to form, and (d) discuss current model limitations and potentially fruitful directions for future research.

  11. Model-based approach for maize yield gap analysis related to climate variability and nitrogen management

    OpenAIRE

    Maria Carolina da Silva Andréa

    2016-01-01

    To achieve food security and meet environmental requirements, the average rates of major crop yields in crops such as maize are expected to increase instead of expansion of cultivated areas. Maize crop has as main factors responsible for the low yields in Brazil the water and nitrogen (N) deficits. The concept of yield gaps is the difference between the maximum yield that can be achieved in a given place, limited by water (Yw) or not (Yp), and the average yields, observed under practical cond...

  12. Measurements of fission yields

    International Nuclear Information System (INIS)

    Denschlag, H.O.

    2000-01-01

    After some historical introductory remarks on the discovery of nuclear fission and early fission yield determinations, the present status of knowledge on fission yields is briefly reviewed. Practical and fundamental reasons motivating the pursuit of fission yield measurements in the coming century are pointed out. Recent results and novel techniques are described that promise to provide new interesting insights into the fission process during the next century. (author)

  13. MODIS Data Assimilation in the CROPGRO model for improving soybean yield estimations

    Science.gov (United States)

    Richetti, J.; Monsivais-Huertero, A.; Ahmad, I.; Judge, J.

    2017-12-01

    Soybean is one of the main agricultural commodities in the world. Thus, having better estimates of its agricultural production is important. Improving the soybean crop models in Brazil is crucial for better understanding of the soybean market and enhancing decision making, because Brazil is the second largest soybean producer in the world, Parana state is responsible for almost 20% of it, and by itself would be the fourth greatest soybean producer in the world. Data assimilation techniques provide a method to improve spatio-temporal continuity of crops through integration of remotely sensed observations and crop growth models. This study aims to use MODIS EVI to improve DSSAT-CROPGRO soybean yield estimations in the Parana state, southern Brazil. The method uses the Ensemble Kalman filter which assimilates MODIS Terra and Aqua combined products (MOD13Q1 and MYD13Q1) into the CROPGRO model to improve the agricultural production estimates through update of light interception data over time. Expected results will be validated with monitored commercial farms during the period of 2013-2014.

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

    Science.gov (United States)

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

    2015-04-01

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

  15. Single Degenerate Models for Type Ia Supernovae: Progenitor's Evolution and Nucleosynthesis Yields

    Science.gov (United States)

    Nomoto, Ken'ichi; Leung, Shing-Chi

    2018-06-01

    . The companion star has become a He WD and CSM has disappeared: "SN Ia-He WD". We update nucleosynthesis yields of the carbon deflagration model W7, delayed detonation model WDD2, and the sub-Chandrasekhar mass model to provide some constraints on the yields (such as Mn) from the comparison with the observations. We note the important metallicity effects on 58Ni and 55Mn.

  16. 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

  17. 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

  18. 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

  19. Effect of Climate and Management Factors on Potential and Gap of Wheat Yield in Iran with Using WOFOST Model

    Directory of Open Access Journals (Sweden)

    A Koocheki

    2017-10-01

    intensification. We estimated a stochastic frontier production function to calculate global datasets of maximum attainable grain yields, yield gaps, and efficiencies of grain production at. Applying a stochastic frontier production function facilitates estimating the yield gap based on the actual grain yield data only, instead of using actual and potential grain yield data from different sources. Therefore, the method allows for a robust and consistent analysis of the yield gap. The factors determining the yield gap are quantified at both global and regional scales. For this purpose, climatic information and wheat yield of different provinces were obtained from Iran meteorological organization and Agriculture Jahade organization, respectively. Wheat potential yield in different provinces was simulated by WOFOST model. Wheat gap was gained by difference between actual and potential yield in different provinces. Relative share of climatic variables in potential yield and also relative share of management variables included irrigation, fertilizer application, mechanization, pesticide application and manure in wheat yield gap was calculated by frontier production function. Results and Discussion The results showed that the effect of precipitation and radiation on wheat potential yield was positive and the impact of temperature was negative. Precipitation had the highest impact on wheat potential yield among other climatic variables. The range of wheat yield gap was from 1646 to 4470 kg ha-1 and 29 to 58% in Iran. Generally, the effect of all management variables on wheat yield gap was negative so that wheat yield gap was reduced by improving of these variables. Among studied management variables, irrigation had the highest effect on yield gap reduction, especially in dry-warm climate and fertilizer application was the second factor which had high effect on yield gap reduction. Therefore, to reduce wheat yield gap in Iran, irrigation management and fertilizer application should be

  20. 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.

  1. 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.

  2. 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.

  3. Do maize models capture the impacts of heat and drought stresses on yield? Using algorithm ensembles to identify successful approaches.

    Science.gov (United States)

    Jin, Zhenong; Zhuang, Qianlai; Tan, Zeli; Dukes, Jeffrey S; Zheng, Bangyou; Melillo, Jerry M

    2016-09-01

    Stresses from heat and drought are expected to increasingly suppress crop yields, but the degree to which current models can represent these effects is uncertain. Here we evaluate the algorithms that determine impacts of heat and drought stress on maize in 16 major maize models by incorporating these algorithms into a standard model, the Agricultural Production Systems sIMulator (APSIM), and running an ensemble of simulations. Although both daily mean temperature and daylight temperature are common choice of forcing heat stress algorithms, current parameterizations in most models favor the use of daylight temperature even though the algorithm was designed for daily mean temperature. Different drought algorithms (i.e., a function of soil water content, of soil water supply to demand ratio, and of actual to potential transpiration ratio) simulated considerably different patterns of water shortage over the growing season, but nonetheless predicted similar decreases in annual yield. Using the selected combination of algorithms, our simulations show that maize yield reduction was more sensitive to drought stress than to heat stress for the US Midwest since the 1980s, and this pattern will continue under future scenarios; the influence of excessive heat will become increasingly prominent by the late 21st century. Our review of algorithms in 16 crop models suggests that the impacts of heat and drought stress on plant yield can be best described by crop models that: (i) incorporate event-based descriptions of heat and drought stress, (ii) consider the effects of nighttime warming, and (iii) coordinate the interactions among multiple stresses. Our study identifies the proficiency with which different model formulations capture the impacts of heat and drought stress on maize biomass and yield production. The framework presented here can be applied to other modeled processes and used to improve yield predictions of other crops with a wide variety of crop models. © 2016 John

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

    DEFF Research Database (Denmark)

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

    2013-01-01

    thresholds are more relevant for site-specific weed management, because weeds are unevenly distributed in fields. Precision of prediction of yield loss is influenced by various factors such as locations, yield potential at the site, variation in competitive ability of mix stands of weed species and emergence...

  5. 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

  6. 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...

  7. 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.

  8. Modeling the impact of climate change on watershed discharge and sediment yield in the black soil region, northeastern China

    Science.gov (United States)

    Li, Zhiying; Fang, Haiyan

    2017-09-01

    Climate change is expected to impact discharge and sediment yield in watersheds. The purpose of this paper is to assess the potential impacts of climate change on water discharge and sediment yield for the Yi'an watershed of the black soil region, northeastern China, based on the newly released Representative Concentration Pathways (RCPs) during 2071-2099. For this purpose, the TETIS model was implemented to simulate the hydrological and sedimentological responses to climate change. The model calibration (1971-1977) and validation (1978-1987) performances were rated as satisfactory. The modeling results for the four RCP scenarios relative to the control scenario under the same land use configuration indicated an increase in discharge of 16.3% (RCP 2.6), 14.3% (RCP 4.5), 36.7% (RCP 6.0) and 71.4% (RCP 8.5) and an increase in the sediment yield of 16.5% (RCP 2.6), 32.4% (RCP 4.5), 81.8% (RCP 6.0) and 170% (RCP 8.5). This implies that the negative impact of climate change on sediment yield is generally greater than that on discharge. At the monthly scale, both discharge and sediment yield increased dramatically in April to June and August to September. A more vigorous hydrological cycle and an increase in high values of sediment yield are also expected. These changes in annual discharge and sediment yield were closely linked with changes in precipitation, whereas monthly changes in late spring and autumn were mainly related to temperature. This study highlights the possible adverse impact of climate change on discharge and sediment yield in the black soil region of northeastern China and could provide scientific basis for adaptive management.

  9. 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.

  10. 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.

  11. 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

    observations at all sites and in all years, and none could unequivocally be labelled robust and accurate in terms of yield prediction across different environments and crop cultivars with only minimum calibration. The best performance regarding yield estimation was for DAISY and DSSAT, for which the RMSE...... and WOFOST furnished high total above-ground biomass estimates, whereas CROPSYST, DSSAT and FASSET provided low total above-ground estimates. Consequently, DSSAT and FASSET produced very high harvest index values, followed by HERMES and WOFOST. APES and DAISY, on the other hand, returned low harvest index...... of grain yield estimates provided by the models for all sites and years reflects substantial uncertainties in model estimates achieved with only minimum calibration. Mean predictions from the eight models, on the other hand, were in good agreement with measured data. This applies to both results across all...

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

    African Journals Online (AJOL)

    AJL

    2011-10-03

    Oct 3, 2011 ... Ridge regression analysis was used to derive a steady algorithmic .... included three replicates [3 × 6 = 18 plots (treatments), stochastic ..... The parameter estimates of the five seed yield components of a total of 327 samples.

  13. 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.

  14. 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.

  15. Narrowing the agronomic yield gap with improved nitrogen use efficiency: a modeling approach.

    Science.gov (United States)

    Ahrens, T D; Lobell, D B; Ortiz-Monasterio, J I; Li, Y; Matson, P A

    2010-01-01

    Improving nitrogen use efficiency (NUE) in the major cereals is critical for more sustainable nitrogen use in high-input agriculture, but our understanding of the potential for NUE improvement is limited by a paucity of reliable on-farm measurements. Limited on-farm data suggest that agronomic NUE (AE(N)) is lower and more variable than data from trials conducted at research stations, on which much of our understanding of AE(N) has been built. The purpose of this study was to determine the magnitude and causes of variability in AE(N) across an agricultural region, which we refer to as the achievement distribution of AE(N). The distribution of simulated AE(N) in 80 farmers' fields in an irrigated wheat system in the Yaqui Valley, Mexico, was compared with trials at a local research center (International Wheat and Maize Improvement Center; CIMMYT). An agroecosystem simulation model WNMM was used to understand factors controlling yield, AE(N), gaseous N emissions, and nitrate leaching in the region. Simulated AE(N) in the Yaqui Valley was highly variable, and mean on-farm AE(N) was 44% lower than trials with similar fertilization rates at CIMMYT. Variability in residual N supply was the most important factor determining simulated AE(N). Better split applications of N fertilizer led to almost a doubling of AE(N), increased profit, and reduced N pollution, and even larger improvements were possible with technologies that allow for direct measurement of soil N supply and plant N demand, such as site-specific nitrogen management.

  16. 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.

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

    Science.gov (United States)

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

    2014-05-01

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

  18. 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)

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. Success of mainstream partial nitritation/anammox demands integration of engineering, microbiome and modeling insights.

    Science.gov (United States)

    Agrawal, Shelesh; Seuntjens, Dries; Cocker, Pieter De; Lackner, Susanne; Vlaeminck, Siegfried E

    2018-04-01

    Twenty years ago, mainstream partial nitritation/anammox (PN/A) was conceptually proposed as pivotal for a more sustainable treatment of municipal wastewater. Its economic potential spurred research, yet practice awaits a comprehensive recipe for microbial resource management. Implementing mainstream PN/A requires transferable and operable ways to steer microbial competition as to meet discharge requirements on a year-round basis at satisfactory conversion rates. In essence, the competition for nitrogen, organic carbon and oxygen is grouped into 'ON/OFF' (suppression/promotion) and 'IN/OUT' (wash-out/retention and seeding) strategies, selecting for desirable conversions and microbes. Some insights need mechanistic understanding, while empirical observations suffice elsewhere. The provided methodological R&D framework integrates insights in engineering, microbiome and modeling. Such synergism should catalyze the implementation of energy-positive sewage treatment. Copyright © 2018 Elsevier Ltd. All rights reserved.

  5. The development of a tensile-shear punch correlation for yield properties of model austenitic alloys

    Energy Technology Data Exchange (ETDEWEB)

    Hankin, G.L.; Faulkner, R.G. [Loughborough Univ. (United Kingdom); Hamilton, M.L.; Garner, F.A. [Pacific Northwest National Lab., Richland, WA (United States)

    1997-08-01

    The effective shear yield and maximum strengths of a set of neutron-irradiated, isotopically tailored austentic alloys were evaluated using the shear punch test. The dependence on composition and neutron dose showed the same trends as were observed in the corresponding miniature tensile specimen study conducted earlier. A single tensile-shear punch correlation was developed for the three alloys in which the maximum shear stress or Tresca criterion was successfully applied to predict the slope. The correlation will predict the tensile yield strength of the three different austenitic alloys tested to within {+-}53 MPa. The accuracy of the correlation improves with increasing material strength, to within {+-} MPa for predicting tensile yield strengths in the range of 400-800 MPa.

  6. The development of a tensile-shear punch correlation for yield properties of model austenitic alloys

    International Nuclear Information System (INIS)

    Hankin, G.L.; Faulkner, R.G.; Hamilton, M.L.; Garner, F.A.

    1997-01-01

    The effective shear yield and maximum strengths of a set of neutron-irradiated, isotopically tailored austentic alloys were evaluated using the shear punch test. The dependence on composition and neutron dose showed the same trends as were observed in the corresponding miniature tensile specimen study conducted earlier. A single tensile-shear punch correlation was developed for the three alloys in which the maximum shear stress or Tresca criterion was successfully applied to predict the slope. The correlation will predict the tensile yield strength of the three different austenitic alloys tested to within ±53 MPa. The accuracy of the correlation improves with increasing material strength, to within ± MPa for predicting tensile yield strengths in the range of 400-800 MPa

  7. Simulations of CYP51A from Aspergillus fumigatus in a model bilayer provide insights into triazole drug resistance.

    Science.gov (United States)

    Nash, Anthony; Rhodes, Johanna

    2018-04-01

    Azole antifungal drugs target CYP51A in Aspergillus fumigatus by binding with the active site of the protein, blocking ergosterol biosynthesis. Resistance to azole antifungal drugs is now common, with a leucine to histidine amino acid substitution at position 98 the most frequent, predominantly conferring resistance to itraconazole, although cross-resistance has been reported in conjunction with other mutations. In this study, we create a homology model of CYP51A using a recently published crystal structure of the paralog protein CYP51B. The derived structures, wild type, and L98H mutant are positioned within a lipid membrane bilayer and subjected to molecular dynamics simulations in order improve the accuracy of both models. The structural analysis from our simulations suggests a decrease in active site surface from the formation of hydrogen bonds between the histidine substitution and neighboring polar side chains, potentially preventing the binding of azole drugs. This study yields a biologically relevant structure and set of dynamics of the A. fumigatus Lanosterol 14 alpha-demethylase enzyme and provides further insight into azole antifungal drug resistance.

  8. 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.

  9. Genetic parameters for body condition score, body weight, milk yield, and fertility estimated using random regression models.

    Science.gov (United States)

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

    2003-11-01

    Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields from 8725 multiparous Holstein-Friesian cows. A cubic random regression was sufficient to model the changing genetic variances for BCS, BW, and milk across different days in milk. The genetic correlations between BCS and fertility changed little over the lactation; genetic correlations between BCS and interval to first service and between BCS and pregnancy rate to first service varied from -0.47 to -0.31, and from 0.15 to 0.38, respectively. This suggests that maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in midlactation when the genetic variance for BCS is largest. Selection for increased BW resulted in shorter intervals to first service, but more services and poorer pregnancy rates; genetic correlations between BW and pregnancy rate to first service varied from -0.52 to -0.45. Genetic selection for higher lactation milk yield alone through selection on increased milk yield in early lactation is likely to have a more deleterious effect on genetic merit for fertility than selection on higher milk yield in late lactation.

  10. CROP YIELD AND CO2 FIXATION MONITORING IN ASIA USING A PHOTOSYNTHETICSTERILITY MODEL WITH SATELLITES AND METEOROLOGICAL DATA

    Energy Technology Data Exchange (ETDEWEB)

    Daijiro Kaneko [Department of Civil and Environmental Engineering, Matsue National College of Technology, Matsue (Japan); Toshiro Kumakura [Department of Civil and Environmental Engineering, Nagaoka University of Technology, Nagaoka (Japan); Peng Yang [Laboratory of Resources Remote Sensing and Digital Agriculture, Ministry of Agriculture, Beijing (China)

    2008-09-30

    This study is intended to develop a model for estimating carbon dioxide (CO{sub 2}) fixation in the carbon cycle and for monitoring grain yields using a photosynthetic-sterility model, which integrates solar radiation and air temperature effects on photosynthesis, along with grain-filling from heading to ripening. Grain production monitoring would support orderly crisis management to maintain food security in Asia, which is facing climate fluctuation through this century of global warming. The author improved a photosynthesis-and-sterility model to compute both the crop yield and crop situation index CSI, which gives a percentage of rice yields compared to normal annual production. The model calculates photosynthesis rates including biomass effects, lowtemperature sterility, and high-temperature injury by incorporating solar radiation, effective air temperature, the normalized difference vegetation index NDVI, and the effect of temperature on photosynthesis by grain plant leaves. A decision-tree method classifies the distribution of crop fields in Asia using MODIS fundamental landcover and SPOT VEGETATION data, which include the Normalized Vegetation index (NDVI) and Land Surface Water Index (LSWI). This study provides daily distributions of the photosynthesis rate, which is the CO2 fixation in Asian areas combined with the land-cover distribution, the Japanese geostationary meteorological satellite (GMS), and meteorological re-analysis data by National Centers for Environmental Prediction (NCEP). The method is based on routine observation data, enabling automated monitoring of crop yields.

  11. 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

  12. 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

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

    African Journals Online (AJOL)

    ozcan_eren

    Prediction of 305-day milk yield in Brown Swiss cattle using artificial ... cattle, based on a few test-day records, and some environmental factors such ... interval, as well as increase the intensity of selection, and thus create greater genetic progress. ... influential variables in predicting the incidence of clinical mastitis in dairy ...

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

    African Journals Online (AJOL)

    AJL

    2011-10-03

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

  15. 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. Manufacturing of par-fried french-fries. Part 2: Modelling yield efficiency of peeling

    NARCIS (Netherlands)

    Somsen, D.J.; Capelle, A.; Tramper, J.

    2004-01-01

    The paper outlines the yield efficiency of steam peeling. It was proven that peeling potatoes manually with sandpaper results in the lowest possible peel losses. These losses were desired or wanted losses. However, in practice steam peeling results not only in wanted losses but also in substantial

  17. Forecasting the Yield Curve in a Data-Rich Environment Using the Factor-Augmented Nelson-Siegel Model

    DEFF Research Database (Denmark)

    Exterkate, Peter; Dijk, Dick van; Heij, Christiaan

    2013-01-01

    This paper compares various ways of extracting macroeconomic information from a data-rich environment for forecasting the yield curve using the Nelson–Siegel model. Five issues in extracting factors from a large panel of macro variables are addressed; namely, selection of a subset of the available......, with principal component methods ranking second best. Reductions of mean squared prediction errors of 20–30% are attained, compared to the Nelson–Siegel model without macro factors....

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

    Science.gov (United States)

    S. Sun; Ge Sun; Erika Cohen Mack; Steve McNulty; Peter Caldwell; K. Duan; Y. Zhang

    2015-01-01

    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)...

  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. First insight into the viral community of the cnidarian model metaorganism Aiptasia using RNA-Seq data

    KAUST Repository

    Brü wer, Jan D.; Voolstra, Christian R.

    2018-01-01

    of the globally threatened coral reef ecosystems. To gain first insight into viruses associated with the coral model system Aiptasia (sensu Exaiptasia pallida), we analyzed an existing RNA-Seq dataset of aposymbiotic, partially populated, and fully symbiotic

  1. 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)

  2. 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

  3. An FSPM approach for modeling fruit yield and quality in mango trees

    OpenAIRE

    Boudon , Frédéric; Persello , Severine; Jestin , Alexandra; Briand , Anne-Sarah; Fernique , Pierre; Guédon , Yann; Léchaudel , Mathieu; Grechi , Isabelle; Normand , Frédéric

    2016-01-01

    International audience; Research focus-Mango (Mangifera indica L.), the fifth most cultivated fruit in the world, is mainly produced in tropical and subtropical regions. Its cultivation raises a number of issues: (i) mango yield is irregular across years, (ii) phenological asynchronisms within and between trees maintain long periods with phenological stages susceptible to pests and diseases, and (iii) fruit quality and maturity are heterogeneous at harvest. To address these issues, we develop...

  4. 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...

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

    DEFF Research Database (Denmark)

    Hagnestam-Nielsen, Christel; Østergaard, Søren

    2009-01-01

    The main aim of the present study was to examine the economic consequences of a reduction in the incidence of clinical mastitis (CM) at herd level under current Swedish farming conditions. A second objective was to ask whether the estimated cost of CM alters depending upon whether the model...... with 150 cows (9000 kg of energy-corrected milk per cow-year). Four herd types, defined by production level and reproductive performance, were modelled to investigate possible interactions between herd type and response to a reduction in the risk of CM. Technical and economic results, given the initial...... incidence of CM (25.6 per 100 cow-years), were studied together with the consequences of reducing the initial risk of CM by 50% and 90% throughout lactation and the consequences of reducing the initial risk by 50% and 90% before peak yield. A conventional way of modelling yield losses - i.e. one employing...

  6. Integrating remote sensing, geographic information system and modeling for estimating crop yield

    Science.gov (United States)

    Salazar, Luis Alonso

    This thesis explores various aspects of the use of remote sensing, geographic information system and digital signal processing technologies for broad-scale estimation of crop yield in Kansas. Recent dry and drought years in the Great Plains have emphasized the need for new sources of timely, objective and quantitative information on crop conditions. Crop growth monitoring and yield estimation can provide important information for government agencies, commodity traders and producers in planning harvest, storage, transportation and marketing activities. The sooner this information is available the lower the economic risk translating into greater efficiency and increased return on investments. Weather data is normally used when crop yield is forecasted. Such information, to provide adequate detail for effective predictions, is typically feasible only on small research sites due to expensive and time-consuming collections. In order for crop assessment systems to be economical, more efficient methods for data collection and analysis are necessary. The purpose of this research is to use satellite data which provides 50 times more spatial information about the environment than the weather station network in a short amount of time at a relatively low cost. Specifically, we are going to use Advanced Very High Resolution Radiometer (AVHRR) based vegetation health (VH) indices as proxies for characterization of weather conditions.

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

    Science.gov (United States)

    Celler, A; Hou, X; Bénard, F; Ruth, T

    2011-09-07

    Recent acute shortage of medical radioisotopes prompted investigations into alternative methods of production and the use of a cyclotron and ¹⁰⁰Mo(p,2n)(99m)Tc reaction has been considered. In this context, the production yields of (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 (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 (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 (99m)Tc and its ratio relative to (99g)Tc and other radioisotopes which must be considered reaction contaminants, potentially contributing to additional patient dose in diagnostic studies.

  8. Comments on the Dutton-Puls model: Temperature and yield stress dependences of crack growth rate in zirconium alloys

    International Nuclear Information System (INIS)

    Kim, Young S.

    2010-01-01

    Research highlights: → This study shows first that temperature and yield stress dependences of crack growth rate in zirconium alloys can analytically be understood not by the Dutton-Puls model but by Kim's new DHC model. → It is demonstrated that the driving force for DHC is ΔC, not the stress gradient, which is the core of Kim's DHC model. → The Dutton-Puls model reveals the invalidity of Puls' claim that the crack tip solubility would increase to the cooling solvus. - Abstract: This work was prompted by the publication of Puls's recent papers claiming that the Dutton-Puls model is valid enough to explain the stress and temperature dependences of the crack growth rate (CGR) in zirconium alloys. The first version of the Dutton-Puls model shows that the CGR has positive dependences on the concentration difference ΔC, hydrogen diffusivity D H , and the yield strength, and a negative dependence on the applied stress intensity factor K I , which is one of its critical defects. Thus, the Dutton-Puls model claiming that the temperature dependence of CGR is determined by D H C H turns out to be incorrect. Given that ΔC is independent of the stress, it is evident that the driving force for DHC is ΔC, not the stress gradient, corroborating the validity of Kim's model. Furthermore, the predicted activation energy for CGR in a cold-worked Zr-2.5Nb tube disagrees with the measured one for the Zr-2.5Nb tube, showing that the Dutton-Puls model is too defective to explain the temperature dependence of CGR. It is demonstrated that the revised Dutton-Puls model also cannot explain the yield stress dependence of CGR.

  9. Computational models of the pulmonary circulation: Insights and the move towards clinically directed studies

    Science.gov (United States)

    Tawhai, Merryn H.; Clark, Alys R.; Burrowes, Kelly S.

    2011-01-01

    Biophysically-based computational models provide a tool for integrating and explaining experimental data, observations, and hypotheses. Computational models of the pulmonary circulation have evolved from minimal and efficient constructs that have been used to study individual mechanisms that contribute to lung perfusion, to sophisticated multi-scale and -physics structure-based models that predict integrated structure-function relationships within a heterogeneous organ. This review considers the utility of computational models in providing new insights into the function of the pulmonary circulation, and their application in clinically motivated studies. We review mathematical and computational models of the pulmonary circulation based on their application; we begin with models that seek to answer questions in basic science and physiology and progress to models that aim to have clinical application. In looking forward, we discuss the relative merits and clinical relevance of computational models: what important features are still lacking; and how these models may ultimately be applied to further increasing our understanding of the mechanisms occurring in disease of the pulmonary circulation. PMID:22034608

  10. 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

  11. 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

  12. 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.

  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. 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.

  15. 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.

  16. A water stress index based on water balance modelling for discrimination of grapevine quality and yield

    Directory of Open Access Journals (Sweden)

    Rémi Gaudin

    2014-01-01

    Significance and impact of the study: This water stress index is a valuable tool for explaining the variations in grape yield and quality among various locations and years because it reflects the vineyard water stress history in relation to rainfall regime and soil conditions. Improvement would come from the simulation of FTSW during winter, notably for soils of high Total Transpirable Soil Water. One potential application is the quantification of water stress change brought by irrigation in Mediterranean vineyards, and its relation to grapevine production.

  17. [Response of water yield function of ecosystem to land use change in Nansi Lake Basin based on CLUE-S model and InVEST model .

    Science.gov (United States)

    Guo, Hong Wei; Sun, Xiao Yin; Lian, Li Shu; Zhang, Da Zhi; Xu, Yan

    2016-09-01

    Land use change has an important role in hydrological processes and utilization of water resources, and is the main driving force of water yield function of ecosystem. This paper analyzed the change of land use from 1990 to 2013 in Nansi Lake Basin, Shandong Province. The future land use in 2030 was also predicted and simulated by CLUE-S model. Based on land use scenarios, we analyzed the influence of land use change on ecosystem function of water yield in nearly 25 years through InVEST water yield model and spatial mapping. The results showed that the area of construction land increased by 3.5% in 2013 because of burgeoning urbanization process, but farmland area decreased by 2.4% which was conversed to construction land mostly. The simulated result of InVEST model suggested that water yield level of whole basin decreased firstly and increased subsequently during last 25 years and peaked at 232.1 mm in 2013. The construction land area would increase by 6.7% in 2030 based on the land use scenarios of fast urbanization, which would lead to a remarkable growth for water yield and risk of flowing flooding. However, the water yield level of whole basin would decrease by 1.2 % in 2013 if 300 meter-wide forest buffer strips around Nansi Lake were built up.

  18. 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.

  19. 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

  20. 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)

  1. 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

  2. A numerical insight into elastomer normally closed micro valve actuation with cohesive interfacial cracking modelling

    Science.gov (United States)

    Wang, Dongyang; Ba, Dechun; Hao, Ming; Duan, Qihui; Liu, Kun; Mei, Qi

    2018-05-01

    Pneumatic NC (normally closed) valves are widely used in high density microfluidics systems. To improve actuation reliability, the actuation pressure needs to be reduced. In this work, we utilize 3D FEM (finite element method) modelling to get an insight into the valve actuation process numerically. Specifically, the progressive debonding process at the elastomer interface is simulated with CZM (cohesive zone model) method. To minimize the actuation pressure, the V-shape design has been investigated and compared with a normal straight design. The geometrical effects of valve shape has been elaborated, in terms of valve actuation pressure. Based on our simulated results, we formulate the main concerns for micro valve design and fabrication, which is significant for minimizing actuation pressures and ensuring reliable operation.

  3. Water versus DNA: new insights into proton track-structure modelling in radiobiology and radiotherapy.

    Science.gov (United States)

    Champion, C; Quinto, M A; Monti, J M; Galassi, M E; Weck, P F; Fojón, O A; Hanssen, J; Rivarola, R D

    2015-10-21

    Water is a common surrogate of DNA for modelling the charged particle-induced ionizing processes in living tissue exposed to radiations. The present study aims at scrutinizing the validity of this approximation and then revealing new insights into proton-induced energy transfers by a comparative analysis between water and realistic biological medium. In this context, a self-consistent quantum mechanical modelling of the ionization and electron capture processes is reported within the continuum distorted wave-eikonal initial state framework for both isolated water molecules and DNA components impacted by proton beams. Their respective probability of occurrence-expressed in terms of total cross sections-as well as their energetic signature (potential and kinetic) are assessed in order to clearly emphasize the differences existing between realistic building blocks of living matter and the controverted water-medium surrogate. Consequences in radiobiology and radiotherapy will be discussed in particular in view of treatment planning refinement aiming at better radiotherapy strategies.

  4. 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.

  5. Spatial model of land use change related to sediment yield (case study: Cipeles and Cilutung watershed, West Java)

    Science.gov (United States)

    Wulandari, D. W.; Kusratmoko, E.; Indra, T. L.

    2018-05-01

    Land use changes (LUC) as a result of increasing human need for space are likely to destroy the hydrological function of the watershed, increase land degradation, stimulate erosion and drive the process of sedimentation. This study aimed to predict LUC during the period 1990 to 2030 in relation to sediment yield in Cilutung and Cipeles Watershed, West Java. LUC were simulated following the model of Cellular Automata-Marcov Chain, whereas land use composition in 2030 was predicted using Land Change Modeler on Idrisi Selva Software. Elevation, slope, distance from road, distance from river, and distance from settlement were selected as driving factors for LUC in this study. Erosion and sediment yield were predicted using WATEM/SEDEM model based on land use, rainfall, soil texture and topography. The results showed that the areas of forest and shrub have slightly declined up to 5% during the period 1990 to 2016, generally being converted into rice fields, settlements, non-irrigated fields and plantations. In addition, rice fields, settlements, and plantations were expected to substantially increase up to 50% in 2030. Furthermore, the study also revealed that erosion and sediment yield tend to increase every year. This is likely associated with LUC occurring in Cipeles and Cilutung Watershed.

  6. 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.

  7. Plateletpheresis efficiency and mathematical correction of software-derived platelet yield prediction: A linear regression and ROC modeling approach.

    Science.gov (United States)

    Jaime-Pérez, José Carlos; Jiménez-Castillo, Raúl Alberto; Vázquez-Hernández, Karina Elizabeth; Salazar-Riojas, Rosario; Méndez-Ramírez, Nereida; Gómez-Almaguer, David

    2017-10-01

    Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P Simple correction derived from linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP. © 2016 Wiley Periodicals, Inc.

  8. 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.

  9. Growth and yield models in Spain: Historical overview, Contemporary Examples and perspectives

    Energy Technology Data Exchange (ETDEWEB)

    Bravo, F.; Alvarez-Gonzalez, J. G.; Rio, M. del; Barrio, M.; Bonet, J. a.; Bravo-Oviedo, A.; Calama, R.; Castedo-Dorado, F.; Crecente-Campo, F.; Condes, S.; Dieguez-Aranda, U.; Gonzalez-Martinez, S. C.; Lizarralde, I.; Nanos, N.; Madrigal, A.; Martinez-Millan, F. J.; Montero, G.; Ordonez, C.; Palahi, M.; Pique, M.; Rodriguez, F.; Rodriguez-Soalleiro, R.; Rojo, A.; Ruiz-Peinado, R.; Sanchez-Gonzalez, M.; Trasobares, A.; Vazquez-Pique, J.

    2011-07-01

    In this paper we present a review of forest models developed in Spain in recent years for both timber and non timber production and forest dynamics (regeneration, mortality,..). Models developed are whole stand, size (diameter) class and individual-tree. The models developed to date have been developed using data from permanent plots, experimental sites and the National Forest Inventory. In this paper we show the different sub-models developed so far and the friendly use software. Main perspectives of forest modelling in Spain are presented. (Author) 107 refs.

  10. Modelling the Course of an HIV Infection: Insights from Ecology and Evolution

    Directory of Open Access Journals (Sweden)

    Carsten Magnus

    2012-10-01

    Full Text Available The Human Immunodeficiency Virus (HIV is one of the most threatening viral agents. This virus infects approximately 33 million people, many of whom are unaware of their status because, except for flu-like symptoms right at the beginning of the infection during the acute phase, the disease progresses more or less symptom-free for 5 to 10 years. During this asymptomatic phase, the virus slowly destroys the immune system until the onset of AIDS when opportunistic infections like pneumonia or Kaposi’s sarcoma can overcome immune defenses. Mathematical models have played a decisive role in estimating important parameters (e.g., virion clearance rate or life-span of infected cells. However, most models only account for the acute and asymptomatic latency phase and cannot explain the progression to AIDS. Models that account for the whole course of the infection rely on different hypotheses to explain the progression to AIDS. The aim of this study is to review these models, present their technical approaches and discuss the robustness of their biological hypotheses. Among the few models capturing all three phases of an HIV infection, we can distinguish between those that mainly rely on population dynamics and those that involve virus evolution. Overall, the modeling quest to capture the dynamics of an HIV infection has improved our understanding of the progression to AIDS but, more generally, it has also led to the insight that population dynamics and evolutionary processes can be necessary to explain the course of an infection.

  11. Simulation of runoff and sediment yield from a hilly watershed in the eastern Himalaya, India using the WEPP model

    Science.gov (United States)

    Singh, R. K.; Panda, R. K.; Satapathy, K. K.; Ngachan, S. V.

    2011-08-01

    SummaryA study was undertaken to develop appropriate vegetative as well as structural measures to control sediment yield from a 239.44 ha small multi-vegetated watershed in high rainfall and high land slope conditions of eastern Himalayan range in India using a physically based distributed parameters Water Erosion Prediction Project (WEPP) model. The model was calibrated and validated using field-measured data pertaining to 86 storms of monsoon season 2003 and 98 storms of 2004. The daily simulated runoff and sediment yield of the Umroi watershed for the calibration and validation periods were found to match with their measured counterparts at 95% significance level as shown by the Student's t-tests. The model simulated daily runoff quite well as corroborated by reasonably high Nash-Sutcliffe simulation coefficients of 0.94 and 0.87, low root mean square errors of 1.42 and 1.77 mm, and low percent deviations of -1.71 and -3.01, respectively for calibration and validation periods. The performance of the model for simulating daily sediment yield was also quite good with Nash-Sutcliffe simulation coefficients of 0.95 and 0.90, root mean square errors of 0.08 and 0.09 Mg ha -1 and percent deviations of 3.05 and -5.23, respectively for calibration and validation periods. Subsequently, the calibrated and validated model was used to simulate vegetative (crop, level of fertilization and tillage) and structural (rock-fill check dam and trash barrier) measures and combinations of vegetative and structural control to evaluate their impacts on runoff and sediment yield reduction. Simulations of different vegetative management scenarios indicated that replacing traditional bun agriculture and upland paddy crop with maize, soybean, and peanut would reduce sediment yield by 18.68, 29.60 and 27.70%, respectively. Field cultivator and drill-no-tillage systems have the potential to reduce sediment yield by 13.14 and 21.88%, respectively as compared to the existing practice of

  12. 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

    2014-09-01

    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 fcp during tensile extension; (b) the limiting value of fcp, extrapolated to far below the glass transition temperature Tg, 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 temperature

  13. Characterization of yield reduction in Ethiopia using a GIS-based crop water balance model

    Science.gov (United States)

    Senay, G.B.; Verdin, J.

    2003-01-01

    In many parts of sub-Saharan Africa, subsistence agriculture is characterized by significant fluctuations in yield and production due to variations in moisture availability to staple crops. Widespread drought can lead to crop failures, with associated deterioration in food security. Ground data collection networks are sparse, so methods using geospatial rainfall estimates derived from satellite and gauge observations, where available, have been developed to calculate seasonal crop water balances. Using conventional crop production data for 4 years in Ethiopia (1996-1999), it was found that water-limited and water-unlimited growing regions can be distinguished. Furthermore, maize growing conditions are also indicative of conditions for sorghum. However, another major staple, teff, was found to behave sufficiently differently from maize to warrant studies of its own.

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

    Science.gov (United States)

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

    2014-09-07

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

  15. Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models.

    Science.gov (United States)

    Veerkamp, R F; Koenen, E P; De Jong, G

    2001-10-01

    Twenty type classifiers scored body condition (BCS) of 91,738 first-parity cows from 601 sires and 5518 maternal grandsires. Fertility data during first lactation were extracted for 177,220 cows, of which 67,278 also had a BCS observation, and first-lactation 305-d milk, fat, and protein yields were added for 180,631 cows. Heritabilities and genetic correlations were estimated using a sire-maternal grandsire model. Heritability of BCS was 0.38. Heritabilities for fertility traits were low (0.01 to 0.07), but genetic standard deviations were substantial, 9 d for days to first service and calving interval, 0.25 for number of services, and 5% for first-service conception. Phenotypic correlations between fertility and yield or BCS were small (-0.15 to 0.20). Genetic correlations between yield and all fertility traits were unfavorable (0.37 to 0.74). Genetic correlations with BCS were between -0.4 and -0.6 for calving interval and days to first service. Random regression analysis (RR) showed that correlations changed with days in milk for BCS. Little agreement was found between variances and correlations from RR, and analysis including a single month (mo 1 to 10) of data for BCS, especially during early and late lactation. However, this was due to excluding data from the conventional analysis, rather than due to the polynomials used. RR and a conventional five-traits model where BCS in mo 1, 4, 7, and 10 was treated as a separate traits (plus yield or fertility) gave similar results. Thus a parsimonious random regression model gave more realistic estimates for the (co)variances than a series of bivariate analysis on subsets of the data for BCS. A higher genetic merit for yield has unfavorable effects on fertility, but the genetic correlation suggests that BCS (at some stages of lactation) might help to alleviate the unfavorable effect of selection for higher yield on fertility.

  16. Predicting watershed post-fire sediment yield with the InVEST sediment retention model: Accuracy and uncertainties

    Science.gov (United States)

    Sankey, Joel B.; McVay, Jason C.; Kreitler, Jason R.; Hawbaker, Todd J.; Vaillant, Nicole; Lowe, Scott

    2015-01-01

    Increased sedimentation following wildland fire can negatively impact water supply and water quality. Understanding how changing fire frequency, extent, and location will affect watersheds and the ecosystem services they supply to communities is of great societal importance in the western USA and throughout the world. In this work we assess the utility of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) Sediment Retention Model to accurately characterize erosion and sedimentation of burned watersheds. InVEST was developed by the Natural Capital Project at Stanford University (Tallis et al., 2014) and is a suite of GIS-based implementations of common process models, engineered for high-end computing to allow the faster simulation of larger landscapes and incorporation into decision-making. The InVEST Sediment Retention Model is based on common soil erosion models (e.g., USLE – Universal Soil Loss Equation) and determines which areas of the landscape contribute the greatest sediment loads to a hydrological network and conversely evaluate the ecosystem service of sediment retention on a watershed basis. In this study, we evaluate the accuracy and uncertainties for InVEST predictions of increased sedimentation after fire, using measured postfire sediment yields available for many watersheds throughout the western USA from an existing, published large database. We show that the model can be parameterized in a relatively simple fashion to predict post-fire sediment yield with accuracy. Our ultimate goal is to use the model to accurately predict variability in post-fire sediment yield at a watershed scale as a function of future wildfire conditions.

  17. Organization, maturation and plasticity of multisensory integration: Insights from computational modelling studies

    Directory of Open Access Journals (Sweden)

    Cristiano eCuppini

    2011-05-01

    Full Text Available In this paper, we present two neural network models - devoted to two specific and widely investigated aspects of multisensory integration - in order to evidence the potentialities of computational models to gain insight into the neural mechanisms underlying organization, development and plasticity of multisensory integration in the brain. The first model considers visual-auditory interaction in a midbrain structure named Superior Colliculus (SC. The model is able to reproduce and explain the main physiological features of multisensory integration in SC neurons and to describe how SC integrative capability – not present at birth - develops gradually during postnatal life depending on sensory experience with cross-modal stimuli. The second model tackles the problem of how tactile stimuli on a body part and visual (or auditory stimuli close to the same body part are integrated in multimodal parietal neurons to form the perception of peripersonal (i.e., near space. The model investigates how the extension of peripersonal space - where multimodal integration occurs - may be modified by experience such as use of a tool to interact with the far space. The utility of the modelling approach relies on several aspects: i The two models, although devoted to different problems and simulating different brain regions, share some common mechanisms (lateral inhibition and excitation, non-linear neuron characteristics, recurrent connections, competition, Hebbian rules of potentiation and depression that may govern more generally the fusion of senses in the brain, and the learning and plasticity of multisensory integration. ii The models may help interpretation of behavioural and psychophysical responses in terms of neural activity and synaptic connections. iii The models can make testable predictions that can help guiding future experiments in order to validate, reject, or modify the main assumptions.

  18. 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.

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

    OpenAIRE

    Salo , Tapio J.; Palosuo , Taru; Kersebaum , Kurt Christian; Nendel , Claas; Angulo , Carlos; Ewert , Frank; Bindi , Marco; Calanca , Pierluigi; Klein , Tommy; Moriondo , Marco; Ferrise , Roberto; Olesen , Jørgen Eivind; Patil , Rasmi H.; Ruget , Francoise; Takac , Jozef

    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, Finland. This is the largest standardized crop model inter-comparison under different levels of N supply to date. The models were calibrated using data from 2002 and 2008, of which 2008 included si...

  20. A simple 2D biofilm model yields a variety of morphological features.

    Science.gov (United States)

    Hermanowicz, S W

    2001-01-01

    A two-dimensional biofilm model was developed based on the concept of cellular automata. Three simple, generic processes were included in the model: cell growth, internal and external mass transport and cell detachment (erosion). The model generated a diverse range of biofilm morphologies (from dense layers to open, mushroom-like forms) similar to those observed in real biofilm systems. Bulk nutrient concentration and external mass transfer resistance had a large influence on the biofilm structure.

  1. Impacts of extreme heat and drought on crop yields in China: an assessment by using the DLEM-AG2 model

    Science.gov (United States)

    Zhang, J.; Yang, J.; Pan, S.; Tian, H.

    2016-12-01

    China is not only one of the major agricultural production countries with the largest population in the world, but it is also the most susceptible to climate change and extreme events. Much concern has been raised about how extreme climate has affected crop yield, which is crucial for China's food supply security. However, the quantitative assessment of extreme heat and drought impacts on crop yield in China has rarely been investigated. By using the Dynamic Land Ecosystem Model (DLEM-AG2), a highly integrated process-based ecosystem model with crop-specific simulation, here we quantified spatial and temporal patterns of extreme climatic heat and drought stress and their impacts on the yields of major food crops (rice, wheat, maize, and soybean) across China during 1981-2015, and further investigated the underlying mechanisms. Simulated results showed that extreme heat and drought stress significantly reduced national cereal production and increased the yield gaps between potential yield and rain-fed yield. The drought stress was the primary factor to reduce crop yields in the semi-arid and arid regions, and extreme heat stress slightly aggravated the yield loss. The yield gap between potential yield and rain-fed yield was larger at locations with lower precipitation. Our results suggest that a large exploitable yield gap in response to extreme climatic heat-drought stress offers an opportunity to increase productivity in China by optimizing agronomic practices, such as irrigation, fertilizer use, sowing density, and sowing date.

  2. Genetic Rodent Models of Obesity-Associated Ovarian Dysfunction and Subfertility: Insights into Polycystic Ovary Syndrome

    Science.gov (United States)

    Huang-Doran, Isabel; Franks, Stephen

    2016-01-01

    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. However, the molecular mechanisms underlying this causality, 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 offers a promising platform in which to address mechanistic questions about reproductive dysfunction in the context of metabolic disease. Similarly, the impact of primary perturbations in rodent gonadotrophin or androgen signaling has been interrogated. However, the insights gained from such models have been limited by the relatively poor fidelity of rodent models to human PCOS. In this mini review, 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. PMID:27375552

  3. 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

  4. High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling.

    Science.gov (United States)

    Rollin, Joseph A; Martin del Campo, Julia; Myung, Suwan; Sun, Fangfang; You, Chun; Bakovic, Allison; Castro, Roberto; Chandrayan, Sanjeev K; Wu, Chang-Hao; Adams, Michael W W; Senger, Ryan S; Zhang, Y-H Percival

    2015-04-21

    The use of hydrogen (H2) as a fuel offers enhanced energy conversion efficiency and tremendous potential to decrease greenhouse gas emissions, but producing it in a distributed, carbon-neutral, low-cost manner requires new technologies. Herein we demonstrate the complete conversion of glucose and xylose from plant biomass to H2 and CO2 based on an in vitro synthetic enzymatic pathway. Glucose and xylose were simultaneously converted to H2 with a yield of two H2 per carbon, the maximum possible yield. Parameters of a nonlinear kinetic model were fitted with experimental data using a genetic algorithm, and a global sensitivity analysis was used to identify the enzymes that have the greatest impact on reaction rate and yield. After optimizing enzyme loadings using this model, volumetric H2 productivity was increased 3-fold to 32 mmol H2⋅L(-1)⋅h(-1). The productivity was further enhanced to 54 mmol H2⋅L(-1)⋅h(-1) by increasing reaction temperature, substrate, and enzyme concentrations--an increase of 67-fold compared with the initial studies using this method. The production of hydrogen from locally produced biomass is a promising means to achieve global green energy production.

  5. A Stand-Class Growth and Yield Model for Mexico’s Northern Temperate, Mixed and Multiaged Forests

    Directory of Open Access Journals (Sweden)

    José Návar

    2014-12-01

    Full Text Available The aim of this research was to develop a stand-class growth and yield model based on the diameter growth dynamics of Pinus spp. and Quercus spp. of Mexico’s mixed temperate forests. Using a total of 2663 temporary, circular-sampling plots of 1000 m2 each, nine Weibull distribution techniques of parameter estimation were fitted to the diameter structures of pines and oaks. Statistical equations using stand attributes and the first three moments of the diameter distribution predicted and recovered the Weibull parameters. Using nearly 1200 and 100 harvested trees for pines and oaks, respectively, I developed the total height versus diameter at breast height relationship by fitting three non-linear functions. The Newnham model predicted stem taper and numerical integration was done to estimate merchantable timber volume for all trees in the stand for each diameter class. The independence of the diameter structures of pines and oaks was tested by regressing the Weibull parameters and projecting diameter structures. The model predicts diameter distributions transition from exponential (J inverse, logarithmic to well-balanced distributions with increasing mean stand diameter at breast height. Pine diameter distributions transition faster and the model predicts independent growth rates between pines and oaks. The stand-class growth and yield model must be completed with the diameter-age relationship for oaks in order to carry a full optimization procedure to find stand density and genera composition to maximize forest growth.

  6. 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

  7. 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

  8. 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 Institutional support: RVO:86652079 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 Subject RIV: GC - Agronomy OBOR OECD: Agronomy, plant breeding and plant protection Impact factor: 2.571, year: 2016

  9. 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

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

    International Nuclear Information System (INIS)

    Akel, M.

    2015-01-01

    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 t he 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 Po, z0 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 Lo, varying z0 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 propor ties on soft x-ray emission and its propor ties 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 k A. The results show that the line radiation emission and

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

    International Nuclear Information System (INIS)

    Akel, M.

    2012-09-01

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

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

    Science.gov (United States)

    Jaszczuk, Marek; Pawlikowski, Arkadiusz

    2017-12-01

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

  13. USA National Phenology Network’s volunteer-contributed observations yield predictive models of phenological transitions

    Science.gov (United States)

    Crimmins, Theresa M.; Crimmins, Michael A.; Gerst, Katherine L.; Rosemartin, Alyssa H.; Weltzin, Jake

    2017-01-01

    In support of science and society, the USA National Phenology Network (USA-NPN) maintains a rapidly growing, continental-scale, species-rich dataset of plant and animal phenology observations that with over 10 million records is the largest such database in the United States. Contributed voluntarily by professional and citizen scientists, these opportunistically collected observations are characterized by spatial clustering, inconsistent spatial and temporal sampling, and short temporal depth. We explore the potential for developing models of phenophase transitions suitable for use at the continental scale, which could be applied to a wide range of resource management contexts. We constructed predictive models of the onset of breaking leaf buds, leaves, open flowers, and ripe fruits – phenophases that are the most abundant in the database and also relevant to management applications – for all species with available data, regardless of plant growth habit, location, geographic extent, or temporal depth of the observations. We implemented a very basic model formulation - thermal time models with a fixed start date. Sufficient data were available to construct 107 individual species × phenophase models. Of these, fifteen models (14%) met our criteria for model fit and error and were suitable for use across the majority of the species’ geographic ranges. These findings indicate that the USA-NPN dataset holds promise for further and more refined modeling efforts. Further, the candidate models that emerged could be used to produce real-time and short-term forecast maps of the timing of such transitions to directly support natural resource management.

  14. Insights and models from medical anthropology for understanding the healing activity of the Historical Jesus

    Directory of Open Access Journals (Sweden)

    John J. Pilch

    1995-12-01

    Full Text Available This essay sketches a basic introdution to medical anthropology as a key to understanding and interpreting  the healing activity of the historical Jesus described in the gospels. It presents select literature, leading experts, fundamental concepts, and insights and models of special value to biblical specialists. Only a cross-cultural discipline like medical anthropology allows the investigator to  interpret texts and events from other cultures with respect for their distinctive cultural contexts in order to draw more appropriate conclusions and applications in other cultures. Applications to biblical texts are not included in this essay but may be found in other articles published by the author and listed in the bibliography.

  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. Combined Spectral and Spatial Modeling of Corn Yield Based on Aerial Images and Crop Surface Models Acquired with an Unmanned Aircraft System

    Directory of Open Access Journals (Sweden)

    Jakob Geipel

    2014-10-01

    Full Text Available Precision Farming (PF management strategies are commonly based on estimations of within-field yield potential, often derived from remotely-sensed products, e.g., Vegetation Index (VI maps. These well-established means, however, lack important information, like crop height. Combinations of VI-maps and detailed 3D Crop Surface Models (CSMs enable advanced methods for crop yield prediction. This work utilizes an Unmanned Aircraft System (UAS to capture standard RGB imagery datasets for corn grain yield prediction at three early- to mid-season growth stages. The imagery is processed into simple VI-orthoimages for crop/non-crop classification and 3D CSMs for crop height determination at different spatial resolutions. Three linear regression models are tested on their prediction ability using site-specific (i unclassified mean heights, (ii crop-classified mean heights and (iii a combination of crop-classified mean heights with according crop coverages. The models show determination coefficients \\({R}^{2}\\ of up to 0.74, whereas model (iii performs best with imagery captured at the end of stem elongation and intermediate spatial resolution (0.04m\\(\\cdot\\px\\(^{-1}\\.Following these results, combined spectral and spatial modeling, based on aerial images and CSMs, proves to be a suitable method for mid-season corn yield prediction.

  17. Natural and molecular history of prolactinoma: insights from a Prlr-/- mouse model.

    Science.gov (United States)

    Bernard, Valérie; Villa, Chiara; Auguste, Aurélie; Lamothe, Sophie; Guillou, Anne; Martin, Agnès; Caburet, Sandrine; Young, Jacques; Veitia, Reiner A; Binart, Nadine

    2018-01-19

    Lactotroph adenoma, also called prolactinoma, is the most common pituitary tumor but little is known about its pathogenesis. Mouse models of prolactinoma can be useful to better understand molecular mechanisms involved in abnormal lactotroph cell proliferation and secretion. We have previously developed a prolactin receptor deficient ( Prlr -/- ) mouse, which develops prolactinoma. The present study aims to explore the natural history of prolactinoma formation in Prlr -/- mice, using hormonal, radiological, histological and molecular analyses to uncover mechanisms involved in lactotroph adenoma development. Prlr -/- females develop large secreting prolactinomas from 12 months of age, with a penetrance of 100%, mimicking human aggressive densely granulated macroprolactinoma, which is a highly secreting subtype. Mean blood PRL measurements reach 14 902 ng/mL at 24 months in Prlr -/- females while PRL levels were below 15 ng/mL in control mice ( p model in ACI rats, we pinpointed 218 concordantly differentially expressed (DE) genes involved in cell cycle, mitosis, cell adhesion molecules, dopaminergic synapse and estrogen signaling. Pathway/gene-set enrichment analyses suggest that the transcriptomic dysregulation in both models of prolactinoma might be mediated by a limited set of transcription factors (i.e., STAT5, STAT3, AhR, ESR1, BRD4, CEBPD, YAP, FOXO1) and kinases (i.e., JAK2, AKT1, BRAF, BMPR1A, CDK8, HUNK, ALK, FGFR1, ILK). Our experimental results and their bioinformatic analysis provide insights into early genomic changes in murine models of the most frequent human pituitary tumor.

  18. Effects of prenatal alcohol exposure (PAE): insights into FASD using mouse models of PAE.

    Science.gov (United States)

    Petrelli, Berardino; Weinberg, Joanne; Hicks, Geoffrey G

    2018-04-01

    The potential impact of prenatal alcohol exposure (PAE) varies considerably among exposed individuals, with some displaying serious alcohol-related effects and many others showing few or no overt signs of fetal alcohol spectrum disorder (FASD). In animal models, variables such as nutrition, genetic background, health, other drugs, and stress, as well as dosage, duration, and gestational timing of exposure to alcohol can all be controlled in a way that is not possible in a clinical situation. In this review we examine mouse models of PAE and focus on those with demonstrated craniofacial malformations, abnormal brain development, or behavioral phenotypes that may be considered FASD-like outcomes. Analysis of these data should provide a valuable tool for researchers wishing to choose the PAE model best suited to their research questions or to investigate established PAE models for FASD comorbidities. It should also allow recognition of patterns linking gestational timing, dosage, and duration of PAE, such as recognizing that binge alcohol exposure(s) during early gestation can lead to severe FASD outcomes. Identified patterns could be particularly insightful and lead to a better understanding of the molecular mechanisms underlying FASD.

  19. Runoff and sediment yield model for predicting nuclide transport in watersheds using BIOTRAN

    Energy Technology Data Exchange (ETDEWEB)

    Gallegos, A.F.; Wenzel, W.J.

    1990-09-01

    The environmental risk simulation model BIOTRAN was interfaced with a series of new subroutines (RUNOFF, GEOFLX, EROSON, and AQUIFER) to predict the movement of nuclides, elements, and pertinent chemical compounds in association with sediments through lateral and channel flow of runoff water. In addition, the movement of water into and out of segmented portions of runoff channels was modeled to simulate the dynamics of moisture flow through specified aquifers within the watershed. The BIOTRAN soil water flux subroutine, WATFLX, was modified to interface the relationships found in the SPUR model for runoff and sediment transport into channels with the particle sorting relationships to predict radionuclide enrichment and movement in watersheds. The new subroutines were applied specifically to Mortandad Canyon within Los Alamos National Laboratory by simultaneous simulation of eight surface vegetational subdivisions and associated channel and aquifer segments of this watershed. This report focuses on descriptions of the construction and rationale for the new subroutines and on discussing both input characteristics and output relationships to known runoff events from Mortandad Canyon. Limitations of the simplified input on model behavior are also discussed. Uranium-238 was selected as the nuclide for demonstration of the model because it could be assumed to be homogeneously distributed over the watershed surface. 22 refs., 18 figs., 9 tabs.

  20. Constitutive modeling and structural analysis considering simultaneous phase transformation and plastic yield in shape memory alloys

    Science.gov (United States)

    Hartl, D. J.; Lagoudas, D. C.

    2009-10-01

    The new developments summarized in this work represent both theoretical and experimental investigations of the effects of plastic strain generation in shape memory alloys (SMAs). Based on the results of SMA experimental characterization described in the literature and additional testing described in this work, a new 3D constitutive model is proposed. This phenomenological model captures both the conventional shape memory effects of pseudoelasticity and thermal strain recovery, and additionally considers the initiation and evolution of plastic strains. The model is numerically implemented in a finite element framework using a return mapping algorithm to solve the constitutive equations at each material point. This combination of theory and implementation is unique in its ability to capture the simultaneous evolution of recoverable transformation strains and irrecoverable plastic strains. The consideration of isotropic and kinematic plastic hardening allows the derivation of a theoretical framework capturing the interactions between irrecoverable plastic strain and recoverable strain due to martensitic transformation. Further, the numerical integration of the constitutive equations is formulated such that objectivity is maintained for SMA structures undergoing moderate strains and large displacements. The implemented model has been used to perform 3D analysis of SMA structural components under uniaxial and bending loads, including a case of local buckling behavior. Experimentally validated results considering simultaneous transformation and plasticity in a bending member are provided, illustrating the predictive accuracy of the model and its implementation.

  1. Constitutive modeling and structural analysis considering simultaneous phase transformation and plastic yield in shape memory alloys

    International Nuclear Information System (INIS)

    Hartl, D J; Lagoudas, D C

    2009-01-01

    The new developments summarized in this work represent both theoretical and experimental investigations of the effects of plastic strain generation in shape memory alloys (SMAs). Based on the results of SMA experimental characterization described in the literature and additional testing described in this work, a new 3D constitutive model is proposed. This phenomenological model captures both the conventional shape memory effects of pseudoelasticity and thermal strain recovery, and additionally considers the initiation and evolution of plastic strains. The model is numerically implemented in a finite element framework using a return mapping algorithm to solve the constitutive equations at each material point. This combination of theory and implementation is unique in its ability to capture the simultaneous evolution of recoverable transformation strains and irrecoverable plastic strains. The consideration of isotropic and kinematic plastic hardening allows the derivation of a theoretical framework capturing the interactions between irrecoverable plastic strain and recoverable strain due to martensitic transformation. Further, the numerical integration of the constitutive equations is formulated such that objectivity is maintained for SMA structures undergoing moderate strains and large displacements. The implemented model has been used to perform 3D analysis of SMA structural components under uniaxial and bending loads, including a case of local buckling behavior. Experimentally validated results considering simultaneous transformation and plasticity in a bending member are provided, illustrating the predictive accuracy of the model and its implementation

  2. 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

  3. 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....... Indeed defining a universal and tractable framework for fully ``appropriate'' event trees is in our opinion an impossible task. A problem specific approach to designing such event trees is the way ahead. In this paper we propose a number of desirable properties which should be present in an event tree...

  4. Heavy-element yields and abundances of asymptotic giant branch models with a Small Magellanic Cloud metallicity

    Science.gov (United States)

    Karakas, Amanda I.; Lugaro, Maria; Carlos, Marília; Cseh, Borbála; Kamath, Devika; García-Hernández, D. A.

    2018-06-01

    We present new theoretical stellar yields and surface abundances for asymptotic giant branch (AGB) models with a metallicity appropriate for stars in the Small Magellanic Cloud (SMC, Z = 0.0028, [Fe/H] ≈ -0.7). New evolutionary sequences and post-processing nucleosynthesis results are presented for initial masses between 1 and 7 M⊙, where the 7 M⊙ is a super-AGB star with an O-Ne core. Models above 1.15 M⊙ become carbon rich during the AGB, and hot bottom burning begins in models M ≥ 3.75 M⊙. We present stellar surface abundances as a function of thermal pulse number for elements between C to Bi and for a selection of isotopic ratios for elements up to Fe and Ni (e.g. 12C/13C), which can be compared to observations. The integrated stellar yields are presented for each model in the grid for hydrogen, helium, and all stable elements from C to Bi. We present evolutionary sequences of intermediate-mass models between 4 and 7 M⊙ and nucleosynthesis results for three masses (M = 3.75, 5, and 7 M⊙) including s-process elements for two widely used AGB mass-loss prescriptions. We discuss our new models in the context of evolved AGB and post-AGB stars in the SMCs, barium stars in our Galaxy, the composition of Galactic globular clusters including Mg isotopes with a similar metallicity to our models, and to pre-solar grains which may have an origin in metal-poor AGB stars.

  5. Reducing a cortical network to a Potts model yields storage capacity estimates

    Science.gov (United States)

    Naim, Michelangelo; Boboeva, Vezha; Kang, Chol Jun; Treves, Alessandro

    2018-04-01

    An autoassociative network of Potts units, coupled via tensor connections, has been proposed and analysed as an effective model of an extensive cortical network with distinct short- and long-range synaptic connections, but it has not been clarified in what sense it can be regarded as an effective model. We draw here the correspondence between the two, which indicates the need to introduce a local feedback term in the reduced model, i.e. in the Potts network. An effective model allows the study of phase transitions. As an example, we study the storage capacity of the Potts network with this additional term, the local feedback w, which contributes to drive the activity of the network towards one of the stored patterns. The storage capacity calculation, performed using replica tools, is limited to fully connected networks, for which a Hamiltonian can be defined. To extend the results to the case of intermediate partial connectivity, we also derive the self-consistent signal-to-noise analysis for the Potts network; and finally we discuss the implications for semantic memory in humans.

  6. 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

  7. Hydrologic characteristics of freshwater mussel habitat: novel insights from modeled flows

    Science.gov (United States)

    Drew, C. Ashton; Eddy, Michele; Kwak, Thomas J.; Cope, W. Gregory; Augspurger, Tom

    2018-01-01

    The ability to model freshwater stream habitat and species distributions is limited by the spatially sparse flow data available from long-term gauging stations. Flow data beyond the immediate vicinity of gauging stations would enhance our ability to explore and characterize hydrologic habitat suitability. The southeastern USA supports high aquatic biodiversity, but threats, such as landuse alteration, climate change, conflicting water-resource demands, and pollution, have led to the imperilment and legal protection of many species. The ability to distinguish suitable from unsuitable habitat conditions, including hydrologic suitability, is a key criterion for successful conservation and restoration of aquatic species. We used the example of the critically endangered Tar River Spinymussel (Parvaspina steinstansana) and associated species to demonstrate the value of modeled flow data (WaterFALL™) to generate novel insights into population structure and testable hypotheses regarding hydrologic suitability. With ordination models, we: 1) identified all catchments with potentially suitable hydrology, 2) identified 2 distinct hydrologic environments occupied by the Tar River Spinymussel, and 3) estimated greater hydrological habitat niche breadth of assumed surrogate species associates at the catchment scale. Our findings provide the first demonstrated application of complete, continuous, regional modeled hydrologic data to freshwater mussel distribution and management. This research highlights the utility of modeling and data-mining methods to facilitate further exploration and application of such modeled environmental conditions to inform aquatic species management. We conclude that such an approach can support landscape-scale management decisions that require spatial information at fine resolution (e.g., enhanced National Hydrology Dataset catchments) and broad extent (e.g., multiple river basins).

  8. 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.

  9. A mathematical model for carbon dioxide elimination: an insight for tuning mechanical ventilation.

    Science.gov (United States)

    Pomprapa, Anake; Schwaiberger, David; Lachmann, Burkhard; Leonhardt, Steffen

    2014-01-01

    The aim is to provide better understanding of carbon dioxide (CO2) elimination during ventilation for both the healthy and atelectatic condition, derived in a pressure-controlled mode. Therefore, we present a theoretical analysis of CO2 elimination of healthy and diseased lungs. Based on a single-compartment model, CO2 elimination is mathematically modeled and its contours were plotted as a function of temporal settings and driving pressure. The model was validated within some level of tolerance on an average of 4.9% using porcine dynamics. CO2 elimination is affected by various factors, including driving pressure, temporal variables from mechanical ventilator settings, lung mechanics and metabolic rate. During respiratory care, CO2 elimination is a key parameter for bedside monitoring, especially for patients with pulmonary disease. This parameter provides valuable insight into the status of an atelectatic lung and of cardiopulmonary pathophysiology. Therefore, control of CO2 elimination should be based on the fine tuning of the driving pressure and temporal ventilator settings. However, for critical condition of hypercapnia, airway resistance during inspiration and expiration should be additionally measured to determine the optimal percent inspiratory time (%TI) to maximize CO2 elimination for treating patients with hypercapnia.

  10. Direct numerical simulation of turbulent combustion: fundamental insights towards predictive models

    International Nuclear Information System (INIS)

    Hawkes, Evatt R; Sankaran, Ramanan; Sutherland, James C; Chen, Jacqueline H

    2005-01-01

    The advancement of our basic understanding of turbulent combustion processes and the development of physics-based predictive tools for design and optimization of the next generation of combustion devices are strategic areas of research for the development of a secure, environmentally sound energy infrastructure. In direct numerical simulation (DNS) approaches, all scales of the reacting flow problem are resolved. However, because of the magnitude of this task, DNS of practical high Reynolds number turbulent hydrocarbon flames is out of reach of even terascale computing. For the foreseeable future, the approach to this complex multi-scale problem is to employ distinct but synergistic approaches to tackle smaller sub-ranges of the complete problem, which then require models for the small scale interactions. With full access to the spatially and temporally resolved fields, DNS can play a major role in the development of these models and in the development of fundamental understanding of the micro-physics of turbulence-chemistry interactions. Two examples, from simulations performed at terascale Office of Science computing facilities, are presented to illustrate the role of DNS in delivering new insights to advance the predictive capability of models. Results are presented from new three-dimensional DNS with detailed chemistry of turbulent non-premixed jet flames, revealing the differences between mixing of passive and reacting scalars, and determining an optimal lower dimensional representation of the full thermochemical state space

  11. 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

  12. 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.

  13. Application of the continuously-yielding joint model for studying disposal of high-level nuclear waste in crystalline rock

    International Nuclear Information System (INIS)

    Hakala, M.; Johansson, E.; Simonen, A.

    1993-04-01

    The non-linear Continuously-Yielding (CY) joint model and its use in numerical analyses of a nuclear waste repository are studied in the report. On major advantage of using CY-model is that laboratory test results, if available, can directly be used in analyses thus reducing uncertainties about joint input parameters. The new testing machine MTS-815 of Helsinki University of Technology was used to determine the joint behaviour of some granitic joints from the depth of 400-600 m below the ground surface. The procedure for triaxial joint tests was refined during this work. Two programs called NormFit and SherFit were developed and tested to determine the best fit parameter values for CY-model from laboratory test results

  14. 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

  15. Introducing a New Experimental Islet Transplantation Model using Biomimetic Hydrogel and a Simple High Yield Islet Isolation Technique.

    Science.gov (United States)

    Mohammadi Ayenehdeh, Jamal; Niknam, Bahareh; Hashemi, Seyed Mahmoud; Rahavi, Hossein; Rezaei, Nima; Soleimani, Masoud; Tajik, Nader

    2017-07-01

    Islet transplantation could be an ideal alternative treatment to insulin therapy for type 1 diabetes Mellitus (T1DM). This clinical and experimental field requires a model that covers problems such as requiring a large number of functional and viable islets, the optimal transplantation site, and the prevention of islet dispersion. Hence, the methods of choice for isolation of functional islets and transplantation are crucial. The present study has introduced an experimental model that overcomes some critical issues in islet transplantation, including in situ pancreas perfusion by digestive enzymes through common bile duct. In comparison with conventional methods, we inflated the pancreas in Petri dishes with only 1 ml collagenase type XI solution, which was followed by hand-picking isolation or Ficoll gradient separation to purify the islets. Then we used a hydrogel composite in which the islets were embedded and transplanted into the peritoneal cavity of the streptozotocin-induced diabetic C57BL/6 mice. As compared to the yield of the classical methods, in our modified technique, the mean yield of isolation was about 130-200 viable islets/mouse pancreas. In vitro glucose-mediated insulin secretion assay indicated an appropriate response in isolated islets. In addition, data from in vivo experiments revealed that the allograft remarkably maintained blood glucose levels under 400 mg/dl and hydrogel composite prevents the passage of immune cells. In the model presented here, the rapid islet isolation technique and the application of biomimetic hydrogel wrapping of islets could facilitate islet transplantation procedures.

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

    Science.gov (United States)

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

    2016-12-01

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

  17. 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

  18. Genomics approaches to unlock the high yield potential of cassava, a tropical model plant

    Directory of Open Access Journals (Sweden)

    Shengkui ZHANG,Ping'an MA,Haiyan WANG,Cheng LU,Xin CHEN,Zhiqiang XIA,Meiling ZOU,Xinchen ZHOU,Wenquan WANG

    2014-12-01

    Full Text Available Cassava, a tropical food, feed and biofuel crop, has great capacity for biomass accumulation and an extraordinary efficiency in water use and mineral nutrition, which makes it highly suitable as a model plant for tropical crops. However, the understanding of the metabolism and genomics of this important crop is limited. The recent breakthroughs in the genomics of cassava, including whole-genome sequencing and transcriptome analysis, as well as advances in the biology of photosynthesis, starch biosynthesis, adaptation to drought and high temperature, and resistance to virus and bacterial diseases, are reviewed here. Many of the new developments have come from comparative analyses between a wild ancestor and existing cultivars. Finally, the current challenges and future potential of cassava as a model plant are discussed.

  19. 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.

  20. 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

    Directory of Open Access Journals (Sweden)

    Kaare Græsbøll

    2016-12-01

    Full Text Available Typically, central milk recording data from dairy herds are recorded less than monthly. Over-fitting early in lactation periods is a challenge, which we explored in different ways by reducing the number of parameters needed to describe the milk yield and somatic cell count of individual cows. 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 (SCC for fitting to sparse data to parameterise herd- and cow-specific simulation of dairy herds.Data from 610 Danish Holstein herds were used to determine parity traits in milk production regarding milk yield and SCC of individual cows. Parity was stratified in first, second and third and higher for milk, and first to sixth and higher for SCC. Fitting of herd level parameters allowed for cow level lactation curves with three, two or one-parameters per lactation. Correlations of milk yield and SCC were estimated between lactations and between dam and offspring.The shape of the lactation curves varied markedly between farms. The correlation between lactations for milk yield and SCC were 0.2-0.6 and significant on more than 95% of farms. The variation in the daily milk yield was observed to be a source of variation to the SCC, and the total SCC was less correlated with the milk production than somatic cells per ml. A positive correlation was found between relative levels of the total SCC and the milk yield.The variation of lactation and SCC curves between farms highlights the importance of a herd level approach. The one-parameter per cow model 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

  1. Sensitivity of the ATLAS experiment to discover the decay H{yields} {tau}{tau} {yields}ll+4{nu} of the Standard Model Higgs Boson produced in vector boson fusion

    Energy Technology Data Exchange (ETDEWEB)

    Schmitz, Martin

    2011-05-17

    A study of the expected sensitivity of the ATLAS experiment to discover the Standard Model Higgs boson produced via vector boson fusion (VBF) and its decay to H{yields} {tau}{tau}{yields} ll+4{nu} is presented. The study is based on simulated proton-proton collisions at a centre-of-mass energy of 14 TeV. For the first time the discovery potential is evaluated in the presence of additional proton-proton interactions (pile-up) to the process of interest in a complete and consistent way. Special emphasis is placed on the development of background estimation techniques to extract the main background processes Z{yields}{tau}{tau} and t anti t production using data. The t anti t background is estimated using a control sample selected with the VBF analysis cuts and the inverted b-jet veto. The dominant background process Z{yields}{tau}{tau} is estimated using Z{yields}{mu}{mu} events. Replacing the muons of the Z{yields}{mu}{mu} event with simulated {tau}-leptons, Z{yields}{tau}{tau} events are modelled to high precision. For the replacement of the Z boson decay products a dedicated method based on tracks and calorimeter cells is developed. Without pile-up a discovery potential of 3{sigma} to 3.4{sigma} in the mass range 115 GeV

  2. 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.

  3. Use of a crop climate modeling system to evaluate climate change adaptation practices: maize yield in East Africa

    Science.gov (United States)

    Moore, N. J.; Alagarswamy, G.; Andresen, J.; Olson, J.; Thornton, P.

    2013-12-01

    Sub Saharan African agriculture is dominated by small-scale farmers and is heavily depend on growing season precipitation. Recent studies indicate that anthropogenic- induced warming including the Indian Ocean sea surface significantly influences precipitation in East Africa. East Africa is a useful region to assess impacts of future climate because of its large rainfall gradient, large percentage of its area being sub-humid or semi-arid, complex climatology and topography, varied soils, and because the population is particularly vulnerable to shifts in climate. Agronomic adaptation practices most commonly being considered include include a shift to short season, drought resistant maize varieties, better management practices especially fertilizer use, and irrigation. The effectiveness of these practices with climate change had not previously been tested. We used the WorldClim data set to represent current climate and compared the current and future climate scenarios of 4 Global Climate Models (GCMs) including a wetter (CCSM) and drier (HadCM3) GCM downscaled to 6 km resolution. The climate data was then used in the process-based CERES maize crop model to simulate the current period (representing 1960- 1990) and change in future maize production (from 2000 to 2050s). The effectiveness of agronomic practices, including short duration maize variety, fertilizer use and irrigation, to reduce projected future yield losses due to climate change were simulated. The GCMs project an increase in maximum temperature during growing season ranging from 1.5 to 3°C. Changes in precipitation were dependent on the GCM, with high variability across different topographies land cover types and elevations. Projected warmer temperatures in the future scenarios accelerated plant development and led to a reduction in growing season length and yields even where moisture was sufficient Maize yield changes in 2050 relative to the historical period were highly varied, in excess of +/- 500 kg

  4. 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.

  5. Epigenome remodelling in breast cancer: insights from an early in vitro model of carcinogenesis.

    Science.gov (United States)

    Locke, Warwick J; Clark, Susan J

    2012-11-15

    Epigenetic gene regulation has influence over a diverse range of cellular functions, including the maintenance of pluripotency, differentiation, and cellular identity, and is deregulated in many diseases, including cancer. Whereas the involvement of epigenetic dysregulation in cancer is well documented, much of the mechanistic detail involved in triggering these changes remains unclear. In the current age of genomics, the development of new sequencing technologies has seen an influx of genomic and epigenomic data and drastic improvements in both resolution and coverage. Studies in cancer cell lines and clinical samples using next-generation sequencing are rapidly delivering spectacular insights into the nature of the cancer genome and epigenome. Despite these improvements in technology, the timing and relationship between genetic and epigenetic changes that occur during the process of carcinogenesis are still unclear. In particular, what changes to the epigenome are playing a driving role during carcinogenesis and what influence the temporal nature of these changes has on cancer progression are not known. Understanding the early epigenetic changes driving breast cancer has the exciting potential to provide a novel set of therapeutic targets or early-disease biomarkers or both. Therefore, it is important to find novel systems that permit the study of initial epigenetic events that potentially occur during the first stages of breast cancer. Non-malignant human mammary epithelial cells (HMECs) provide an exciting in vitro model of very early breast carcinogenesis. When grown in culture, HMECs are able to temporarily escape senescence and acquire a pre-malignant breast cancer-like phenotype (variant HMECs, or vHMECs). Cultured HMECs are composed mainly of cells from the basal breast epithelial layer. Therefore, vHMECs are considered to represent the basal-like subtype of breast cancer. The transition from HMECs to vHMECs in culture recapitulates the epigenomic

  6. New Insight into Combined Model and Revised Model for RTD Curves in a Multi-strand Tundish

    Science.gov (United States)

    Lei, Hong

    2015-12-01

    The analysis for the residence time distribution (RTD) curve is one of the important experimental technologies to optimize the tundish design. But there are some issues about RTD analysis model. Firstly, the combined (or mixed) model and the revised model give different analysis results for the same RTD curve. Secondly, different upper limits of integral in the numerator for the mean residence time give different results for the same RTD curve. Thirdly, the negative dead volume fraction sometimes appears at the outer strand of the multi-strand tundish. In order to solve the above problems, it is necessary to have a deep insight into the RTD curve and to propose a reasonable method to analyze the RTD curve. The results show that (1) the revised model is not appropriate to treat with the RTD curve; (2) the conception of the visual single-strand tundish and the combined model with the dimensionless time at the cut-off point are applied to estimate the flow characteristics in the multi-strand tundish; and that (3) the mean residence time at each exit is the key parameter to estimate the similarity of fluid flow among strands.

  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. Using the UKCP09 probabilistic scenarios to model the amplified impact of climate change on drainage basin sediment yield

    Directory of Open Access Journals (Sweden)

    T. J. Coulthard

    2012-11-01

    Full Text Available Precipitation intensities and the frequency of extreme events are projected to increase under climate change. These rainfall changes will lead to increases in the magnitude and frequency of flood events that will, in turn, affect patterns of erosion and deposition within river basins. These geomorphic changes to river systems may affect flood conveyance, infrastructure resilience, channel pattern, and habitat status as well as sediment, nutrient and carbon fluxes. Previous research modelling climatic influences on geomorphic changes has been limited by how climate variability and change are represented by downscaling from global or regional climate models. Furthermore, the non-linearity of the climatic, hydrological and geomorphic systems involved generate large uncertainties at each stage of the modelling process creating an uncertainty "cascade".

    This study integrates state-of-the-art approaches from the climate change and geomorphic communities to address these issues in a probabilistic modelling study of the Swale catchment, UK. The UKCP09 weather generator is used to simulate hourly rainfall for the baseline and climate change scenarios up to 2099, and used to drive the CAESAR landscape evolution model to simulate geomorphic change. Results show that winter rainfall is projected to increase, with larger increases at the extremes. The impact of the increasing rainfall is amplified through the translation into catchment runoff and in turn sediment yield with a 100% increase in catchment mean sediment yield predicted between the baseline and the 2070–2099 High emissions scenario. Significant increases are shown between all climate change scenarios and baseline values. Analysis of extreme events also shows the amplification effect from rainfall to sediment delivery with even greater amplification associated with higher return period events. Furthermore, for the 2070–2099 High emissions scenario, sediment discharges from 50-yr

  9. Top Mysteries of the Mind: Insights From the Default Space Model of Consciousness

    Directory of Open Access Journals (Sweden)

    Ravinder Jerath

    2018-04-01

    Full Text Available Aside from the nature of consciousness itself, there are still many unsolved problems in the neurosciences. Despite the vast and quickly growing body of work in this field, we still find ourselves perplexed at seemingly simple qualities of our mental being such as why we need to sleep. The neurosciences are at least beginning to take a hold on these mysteries and are working toward solving them. We hold a perspective that metastable consciousness models, specifically the Default Space Model (DSM, provide insights into these mysteries. In this perspective article, we explore some of these curious questions in order to elucidate the interesting points they bring up. The DSM is a dynamic, global theory of consciousness that involves the maintenance of an internal, 3D simulation of the external, physical world which is the foundation and structure of consciousness. This space is created and filled by multiple frequencies of membrane potential oscillations throughout the brain and body which are organized, synchronized and harmonized by the thalamus. The veracity of the DSM is highlighted here in its ability to further understanding of some of the most puzzling problems in neuroscience.

  10. 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.

  11. Looking back to move forward on model validation: insights from a global model of agricultural land use

    International Nuclear Information System (INIS)

    Baldos, Uris Lantz C; Hertel, Thomas W

    2013-01-01

    Global agricultural models are becoming indispensable in the debate over climate change impacts and mitigation policies. Therefore, it is becoming increasingly important to validate these models and identify critical areas for improvement. In this letter, we illustrate both the opportunities and the challenges in undertaking such model validation, using the SIMPLE model of global agriculture. We look back at the long run historical period 1961–2006 and, using a few key historical drivers—population, incomes and total factor productivity—we find that SIMPLE is able to accurately reproduce historical changes in cropland use, crop price, crop production and average crop yields at the global scale. Equally important is our investigation into how the specific assumptions embedded in many agricultural models will likely influence these results. We find that those global models which are largely biophysical—thereby ignoring the price responsiveness of demand and supply—are likely to understate changes in crop production, while failing to capture the changes in cropland use and crop price. Likewise, global models which incorporate economic responses, but do so based on limited time series estimates of these responses, are likely to understate land use change and overstate price changes. (letter)

  12. 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

  13. Reliability of Monte Carlo simulations in modeling neutron yields from a shielded fission source

    Energy Technology Data Exchange (ETDEWEB)

    McArthur, Matthew S., E-mail: matthew.s.mcarthur@gmail.com; Rees, Lawrence B., E-mail: Lawrence_Rees@byu.edu; Czirr, J. Bart, E-mail: czirr@juno.com

    2016-08-11

    Using the combination of a neutron-sensitive {sup 6}Li glass scintillator detector with a neutron-insensitive {sup 7}Li glass scintillator detector, we are able to make an accurate measurement of the capture rate of fission neutrons on {sup 6}Li. We used this detector with a {sup 252}Cf neutron source to measure the effects of both non-borated polyethylene and 5% borated polyethylene shielding on detection rates over a range of shielding thicknesses. Both of these measurements were compared with MCNP calculations to determine how well the calculations reproduced the measurements. When the source is highly shielded, the number of interactions experienced by each neutron prior to arriving at the detector is large, so it is important to compare Monte Carlo modeling with actual experimental measurements. MCNP reproduces the data fairly well, but it does generally underestimate detector efficiency both with and without polyethylene shielding. For non-borated polyethylene it underestimates the measured value by an average of 8%. This increases to an average of 11% for borated polyethylene.

  14. 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

  15. 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...

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

    Directory of Open Access Journals (Sweden)

    K Abbasi

    2014-09-01

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

  17. Reduction of CMIP5 models bias using Cumulative Distribution Function transform and impact on crops yields simulations across West Africa.

    Science.gov (United States)

    Moise Famien, Adjoua; Defrance, Dimitri; Sultan, Benjamin; Janicot, Serge; Vrac, Mathieu

    2017-04-01

    Different CMIP exercises show that the simulations of the future/current temperature and precipitation are complex with a high uncertainty degree. For example, the African monsoon system is not correctly simulated and most of the CMIP5 models underestimate the precipitation. Therefore, Global Climate Models (GCMs) show significant systematic biases that require bias correction before it can be used in impacts studies. Several methods of bias corrections have been developed for several years and are increasingly using more complex statistical methods. The aims of this work is to show the interest of the CDFt (Cumulative Distribution Function transfom (Michelangeli et al.,2009)) method to reduce the data bias from 29 CMIP5 GCMs over Africa and to assess the impact of bias corrected data on crop yields prediction by the end of the 21st century. In this work, we apply the CDFt to daily data covering the period from 1950 to 2099 (Historical and RCP8.5) and we correct the climate variables (temperature, precipitation, solar radiation, wind) by the use of the new daily database from the EU project WATer and global CHange (WATCH) available from 1979 to 2013 as reference data. The performance of the method is assessed in several cases. First, data are corrected based on different calibrations periods and are compared, on one hand, with observations to estimate the sensitivity of the method to the calibration period and, on other hand, with another bias-correction method used in the ISIMIP project. We find that, whatever the calibration period used, CDFt corrects well the mean state of variables and preserves their trend, as well as daily rainfall occurrence and intensity distributions. However, some differences appear when compared to the outputs obtained with the method used in ISIMIP and show that the quality of the correction is strongly related to the reference data. Secondly, we validate the bias correction method with the agronomic simulations (SARRA-H model (Kouressy

  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. 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.

  20. 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.

  1. 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.

  2. 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)

  3. Seismic attenuation in fractured porous media: insights from a hybrid numerical and analytical model

    International Nuclear Information System (INIS)

    Ekanem, A M; Li, X Y; Chapman, M; Main, I G

    2015-01-01

    Seismic attenuation in fluid-saturated porous rocks can occur by geometric spreading, wave scattering or the internal dissipation of energy, most likely due to the squirt-flow mechanism. In principle, the pattern of seismic attenuation recorded on an array of sensors contains information about the medium, in terms of material heterogeneity and anisotropy, as well as material properties such as porosity, crack density, and pore-fluid composition and mobility. In practice, this inverse problem is challenging. Here we provide some insights into the effects of internal dissipation by analysing synthetic data produced by a hybrid numerical and analytical model for seismic wave propagation in a fractured medium embedded within a layered geological structure. The model is made up of one anisotropic and three isotropic horizontal layers. The anisotropic layer consists of a porous, fluid-saturated material containing vertically aligned inclusions representing a set of fractures. This combination allows squirt-flow to occur between the pores in the matrix and the model fractures. Our results show that the fluid mobility and the associated relaxation time of the fluid-pressure gradient control the frequency range over which attenuation occurs. This induced attenuation increases with incidence angle and azimuth away from the fracture strike-direction. Azimuthal variations in the induced attenuation are elliptical allowing the fracture orientations to be obtained from the axes of the ellipse. These observations hold out the potential of using seismic attenuation as an additional diagnostic in the characterisation of rock formations for a variety of applications including hydrocarbon exploration and production, subsurface storage of CO 2 , and geothermal energy extraction. (paper)

  4. 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)

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

    Science.gov (United States)

    Soms, Juris

    2015-04-01

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

  6. Insights Into the Bifunctional Aphidicolan-16-ß-ol Synthase Through Rapid Biomolecular Modeling Approaches.

    Science.gov (United States)

    Hirte, Max; Meese, Nicolas; Mertz, Michael; Fuchs, Monika; Brück, Thomas B

    2018-01-01

    Diterpene synthases catalyze complex, multi-step C-C coupling reactions thereby converting the universal, aliphatic precursor geranylgeranyl diphosphate into diverse olefinic macrocylces that form the basis for the structural diversity of the diterpene natural product family. Since catalytically relevant crystal structures of diterpene synthases are scarce, homology based biomolecular modeling techniques offer an alternative route to study the enzyme's reaction mechanism. However, precise identification of catalytically relevant amino acids is challenging since these models require careful preparation and refinement techniques prior to substrate docking studies. Targeted amino acid substitutions in this protein class can initiate premature quenching of the carbocation centered reaction cascade. The structural characterization of those alternative cyclization products allows for elucidation of the cyclization reaction cascade and provides a new source for complex macrocyclic synthons. In this study, new insights into structure and function of the fungal, bifunctional Aphidicolan-16-ß-ol synthase were achieved using a simplified biomolecular modeling strategy. The applied refinement methodologies could rapidly generate a reliable protein-ligand complex, which provides for an accurate in silico identification of catalytically relevant amino acids. Guided by our modeling data, ACS mutations lead to the identification of the catalytically relevant ACS amino acid network I626, T657, Y658, A786, F789, and Y923. Moreover, the ACS amino acid substitutions Y658L and D661A resulted in a premature termination of the cyclization reaction cascade en-route from syn-copalyl diphosphate to Aphidicolan-16-ß-ol. Both ACS mutants generated the diterpene macrocycle syn-copalol and a minor, non-hydroxylated labdane related diterpene, respectively. Our biomolecular modeling and mutational studies suggest that the ACS substrate cyclization occurs in a spatially restricted location of

  7. Insights Into the Bifunctional Aphidicolan-16-ß-ol Synthase Through Rapid Biomolecular Modeling Approaches

    Directory of Open Access Journals (Sweden)

    Max Hirte

    2018-04-01

    Full Text Available Diterpene synthases catalyze complex, multi-step C-C coupling reactions thereby converting the universal, aliphatic precursor geranylgeranyl diphosphate into diverse olefinic macrocylces that form the basis for the structural diversity of the diterpene natural product family. Since catalytically relevant crystal structures of diterpene synthases are scarce, homology based biomolecular modeling techniques offer an alternative route to study the enzyme's reaction mechanism. However, precise identification of catalytically relevant amino acids is challenging since these models require careful preparation and refinement techniques prior to substrate docking studies. Targeted amino acid substitutions in this protein class can initiate premature quenching of the carbocation centered reaction cascade. The structural characterization of those alternative cyclization products allows for elucidation of the cyclization reaction cascade and provides a new source for complex macrocyclic synthons. In this study, new insights into structure and function of the fungal, bifunctional Aphidicolan-16-ß-ol synthase were achieved using a simplified biomolecular modeling strategy. The applied refinement methodologies could rapidly generate a reliable protein-ligand complex, which provides for an accurate in silico identification of catalytically relevant amino acids. Guided by our modeling data, ACS mutations lead to the identification of the catalytically relevant ACS amino acid network I626, T657, Y658, A786, F789, and Y923. Moreover, the ACS amino acid substitutions Y658L and D661A resulted in a premature termination of the cyclization reaction cascade en-route from syn-copalyl diphosphate to Aphidicolan-16-ß-ol. Both ACS mutants generated the diterpene macrocycle syn-copalol and a minor, non-hydroxylated labdane related diterpene, respectively. Our biomolecular modeling and mutational studies suggest that the ACS substrate cyclization occurs in a spatially

  8. Insights into the bifunctional Aphidicolan-16-ß-ol synthase through rapid biomolecular modelling approaches

    Science.gov (United States)

    Hirte, Max; Meese, Nicolas; Mertz, Michael; Fuchs, Monika; Brück, Thomas B.

    2018-04-01

    Diterpene synthases catalyze complex, multi-step C-C coupling reactions thereby converting the universal, aliphatic precursor geranylgeranyl diphosphate into diverse olefinic macrocylces that form the basis for the structural diversity of the diterpene natural product family. Since catalytically relevant crystal structures of diterpene synthases are scarce, homology based biomolecular modelling techniques offer an alternative route to study the enzyme’s reaction mechanism. However, precise identification of catalytically relevant amino acids is challenging since these models require careful preparation and refinement techniques prior to substrate docking studies. Targeted amino acid substitutions in this protein class can initiate premature quenching of the carbocation centered reaction cascade. The structural characterization of those alternative cyclization products allows for elucidation of the cyclization reaction cascade and provides a new source for complex macrocyclic synthons. In this study, new insights into structure and function of the fungal, bifunctional Aphidicolan-16-ß-ol synthase were achieved using a simplified biomolecular modelling strategy. The applied refinement methodologies could rapidly generate a reliable protein-ligand complex, which provides for an accurate in silico identification of catalytically relevant amino acids. Guided by our modelling data, ACS mutations lead to the identification of the catalytically relevant ACS amino acid network I626, T657, Y658, A786, F789 and Y923. Moreover, the ACS amino acid substitutions Y658L and D661A resulted in a premature termination of the cyclization reaction cascade en-route from syn-copalyl diphosphate to Aphidicolan-16-ß-ol. Both ACS mutants generated the diterpene macrocycle syn-copalol and a minor, non-hydroxylated labdane related diterpene, respectively. Our biomolecular modelling and mutational studies suggest that the ACS substrate cyclization occurs in a spatially restricted location

  9. 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.

  10. Model evaluation of plant metal content and biomass yield for the phytoextraction of heavy metals by switchgrass.

    Science.gov (United States)

    Chen, Bo-Ching; Lai, Hung-Yu; Juang, Kai-Wei

    2012-06-01

    To better understand the ability of switchgrass (Panicum virgatum L.), a perennial grass often relegated to marginal agricultural areas with minimal inputs, to remove cadmium, chromium, and zinc by phytoextraction from contaminated sites, the relationship between plant metal content and biomass yield is expressed in different models to predict the amount of metals switchgrass can extract. These models are reliable in assessing the use of switchgrass for phytoremediation of heavy-metal-contaminated sites. In the present study, linear and exponential decay models are more suitable for presenting the relationship between plant cadmium and dry weight. The maximum extractions of cadmium using switchgrass, as predicted by the linear and exponential decay models, approached 40 and 34 μg pot(-1), respectively. The log normal model was superior in predicting the relationship between plant chromium and dry weight. The predicted maximum extraction of chromium by switchgrass was about 56 μg pot(-1). In addition, the exponential decay and log normal models were better than the linear model in predicting the relationship between plant zinc and dry weight. The maximum extractions of zinc by switchgrass, as predicted by the exponential decay and log normal models, were about 358 and 254 μg pot(-1), respectively. To meet the maximum removal of Cd, Cr, and Zn, one can adopt the optimal timing of harvest as plant Cd, Cr, and Zn approach 450 and 526 mg kg(-1), 266 mg kg(-1), and 3022 and 5000 mg kg(-1), respectively. Due to the well-known agronomic characteristics of cultivation and the high biomass production of switchgrass, it is practicable to use switchgrass for the phytoextraction of heavy metals in situ. Copyright © 2012 Elsevier Inc. All rights reserved.

  11. 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

  12. 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

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

    Science.gov (United States)

    Islam, M R; Clark, C E F; Garcia, S C; Kerrisk, K L

    2015-07-01

    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 (voluntary return

  14. Neuroprotective effects of estrogen in CNS injuries: insights from animal models

    Directory of Open Access Journals (Sweden)

    Raghava N

    2017-07-01

    Full Text Available Narayan Raghava,1 Bhaskar C Das,2 Swapan K Ray1 1Department of Pathology, Microbiology, and Immunology, University of South Carolina School of Medicine, Columbia, SC, USA; 2Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA Abstract: Among the estrogens that are biosynthesized in the human body, 17β-estradiol (estradiol or E2 is the most common and the best estrogen for neuroprotection in animal models of the central nervous system (CNS injuries such as spinal cord injury (SCI, traumatic brain injury (TBI, and ischemic brain injury (IBI. These CNS injuries are not only serious health problems, but also enormous economic burden on the patients, their families, and the society at large. Studies from animal models of these CNS injuries provide insights into the multiple neuroprotective mechanisms of E2 and also suggest the possibility of translating the therapeutic efficacy of E2 in the treatment SCI, TBI, and IBI in humans in the near future. The pathophysiology of these injuries includes loss of motor function in the limbs, arms and their extremities, cognitive deficit, and many other serious consequences including life-threatening paralysis, infection, and even death. The potential application of E2 therapy to treat the CNS injuries may become a trend as the results are showing significant therapeutic benefits of E2 for neuroprotection when administered into the animal models of SCI, TBI, and IBI. This article describes the plausible mechanisms how E2 works with or without the involvement of estrogen receptors and provides an overview of the known neuroprotective effects of E2 in these three CNS injuries in different animal models. Because activation of estrogen receptors has profound implications in maintaining and also affecting normal physiology, there are notable impediments in translating E2 therapy to the clinics for neuroprotection in CNS injuries in humans. While E2 may not yet be the sole molecule for

  15. 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.

  16. 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

  17. Learning from a paradox: recent insights into Fanconi anaemia through studying mouse models

    Directory of Open Access Journals (Sweden)

    Sietske T. Bakker

    2013-01-01

    Full Text Available Fanconi anaemia (FA is a rare autosomal recessive or X-linked inherited disease characterised by an increased incidence of bone marrow failure (BMF, haematological malignancies and solid tumours. Cells from individuals with FA show a pronounced sensitivity to DNA interstrand crosslink (ICL-inducing agents, which manifests as G2-M arrest, chromosomal aberrations and reduced cellular survival. To date, mutations in at least 15 different genes have been identified that cause FA; the products of all of these genes are thought to function together in the FA pathway, which is essential for ICL repair. Rapidly following the discovery of FA genes, mutant mice were generated to study the disease and the affected pathway. These mutant mice all show the characteristic cellular ICL-inducing agent sensitivity, but only partially recapitulate the developmental abnormalities, anaemia and cancer predisposition seen in individuals with FA. Therefore, the usefulness of modelling FA in mice has been questioned. In this Review, we argue that such scepticism is unjustified. We outline that haematopoietic defects and cancer predisposition are manifestations of FA gene defects in mice, albeit only in certain genetic backgrounds and under certain conditions. Most importantly, recent work has shown that developmental defects in FA mice also arise with concomitant inactivation of acetaldehyde metabolism, giving a strong clue about the nature of the endogenous lesion that must be repaired by the functional FA pathway. This body of work provides an excellent example of a paradox in FA research: that the dissimilarity, rather than the similarity, between mice and humans can provide insight into human disease. We expect that further study of mouse models of FA will help to uncover the mechanistic background of FA, ultimately leading to better treatment options for the disease.

  18. New insights into chromatin folding and dynamics from multi-scale modeling

    Science.gov (United States)

    Olson, Wilma

    The dynamic organization of chromatin plays an essential role in the regulation of gene expression and in other fundamental cellular processes. The underlying physical basis of these activities lies in the sequential positioning, chemical composition, and intermolecular interactions of the nucleosomes-the familiar assemblies of roughly 150 DNA base pairs and eight histone proteins-found on chromatin fibers. We have developed a mesoscale model of short nucleosomal arrays and a computational framework that make it possible to incorporate detailed structural features of DNA and histones in simulations of short chromatin constructs with 3-25 evenly spaced nucleosomes. The correspondence between the predicted and observed effects of nucleosome composition, spacing, and numbers on long-range communication between regulatory proteins bound to the ends of designed nucleosome arrays lends credence to the model and to the molecular insights gleaned from the simulated structures. We have extracted effective nucleosome-nucleosome potentials from the mesoscale simulations and introduced the potentials in a larger scale computational treatment of regularly repeating chromatin fibers. Our results reveal a remarkable influence of nucleosome spacing on chromatin flexibility. Small changes in the length of the DNA fragments linking successive nucleosomes introduce marked changes in the local interactions of the nucleosomes and in the spatial configurations of the fiber as a whole. The changes in nucleosome positioning influence the statistical properties of longer chromatin constructs with 100-10,000 nucleosomes. We are investigating the extent to which the `local' interactions of regularly spaced nucleosomes contribute to the corresponding interactions in chains with mixed spacings as a step toward the treatment of fibers with nucleosomes positioned at the sites mapped at base-pair resolution on genomic sequences. Support of the work by USPHS R01 GM 34809 is gratefully acknowledged.

  19. 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

  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. Using economic instruments to develop effective management of invasive species: insights from a bioeconomic model.

    Science.gov (United States)

    McDermott, Shana M; Irwin, Rebecca E; Taylor, Brad W

    2013-07-01

    Economic growth is recognized as an important factor associated with species invasions. Consequently, there is increasing need to develop solutions that combine economics and ecology to inform invasive species management. We developed a model combining economic, ecological, and sociological factors to assess the degree to which economic policies can be used to control invasive plants. Because invasive plants often spread across numerous properties, we explored whether property owners should manage invaders cooperatively as a group by incorporating the negative effects of invader spread in management decisions (collective management) or independently, whereby the negative effects of invasive plant spread are ignored (independent management). Our modeling approach used a dynamic optimization framework, and we applied the model to invader spread using Linaria vulgaris. Model simulations allowed us to determine the optimal management strategy based on net benefits for a range of invader densities. We found that optimal management strategies varied as a function of initial plant densities. At low densities, net benefits were high for both collective and independent management to eradicate the invader, suggesting the importance of early detection and eradication. At moderate densities, collective management led to faster and more frequent invader eradication compared to independent management. When we used a financial penalty to ensure that independent properties were managed collectively, we found that the penalty would be most feasible when levied on a property's perimeter boundary to control spread among properties. At the highest densities, the optimal management strategy was "do nothing" because the economic costs of removal were too high relative to the benefits of removal. Spatial variation in L. vulgaris densities resulted in different optimal management strategies for neighboring properties, making a formal economic policy to encourage invasive species removal

  2. Combined application of Sentinel2A data and growth modelling for novel monitoring and prediction of pasture yields

    Science.gov (United States)

    Verhoef, A.; Punalekar, S.; Quaife, T. L.; Humphries, D.; Reynolds, C.

    2017-12-01

    Currently, 30% of the world's land area is covered by permanent pasture. Grazing ruminants convert forage materials into milk and meat for human consumption; ruminant production is a key agricultural enterprise. Management of pasture farms (nutrient and herbi-/pesticides application, grazing rotations) is often suboptimal. Furthermore, adverse weather can have negative effects on pasture growth and quality. Near real-time herbage monitoring and prediction could help improve farm profitability. While the use of remote sensing (RS) in the context of arable crop growth prediction is becoming more established, the same is not true for pasture. However, recently launched Sentinel satellites offer real opportunities to exploit high spatio-temporal resolution datasets for effective monitoring of pastures, as well as crops. A perennial grazed ryegrass field in the Southwest of the UK was monitored regularly using field hyperspectral spectro-radiometers. Simultaneously, leaf area index (LAI) was measured using a ceptometer, and yield was measured, indirectly using a `plate meter' and directly by destructive sampling. Two sets of spectral data were used to retrieve LAI with the PROSAIL radiative transfer model: (i) Sentinel-2A bands convolved from field spectral data, (ii) actual Sentinel-2A image pixels for the sampling plots. Retrieved LAI was compared against field observations. LAI estimates were assimilated in a bespoke growth model (including grazing and management), driven by weather data, for calibration of sensitive parameters using a 4D-Var scheme, to obtain pasture biomass. The developed approach was used to study a pasture farm in the South of the UK, for which a large number of Sentinel-2A images were available throughout 2016-17. Retrieved LAI compared well with in-situ LAI, and significantly improved yield estimates. The calibrated model parameters compared well with literature values. The model, guided by satellite data and general information on farm

  3. 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

  4. 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.

  5. Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach.

    Science.gov (United States)

    Chenu, Karine; Chapman, Scott C; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L

    2009-12-01

    Under drought, substantial genotype-environment (G x E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this "gene-to-phenotype" gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G x E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such "leafy" genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G x E interactions for complex traits such as drought tolerance.

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Shiyan Zhai

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

  8. 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

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. 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

  18. 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.

  19. 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.)

  20. 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.

  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. 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.

  3. Hypogonadotropic hypogonadism and metabolic syndrome: insights from the high-fat diet experimental rabbit animal model.

    Science.gov (United States)

    Morelli, Annamaria; Vignozzi, Linda; Maggi, Mario

    2016-06-01

    The etiology of metabolic syndrome (MetS) is complex and involves the interplay between environmental, lifestyle and genetic determinants. MetS in men can be associated with a biochemical pattern of partial hypogonadotropic hypogonadism (HH). A similar pattern has been noted in both men and women with a variety of acute illnesses and chronic diseases, and there is ongoing debate regarding whether this phenomenon might adaptive (e.g. diverting resources from reproduction into survival), or maladaptive (e.g. anemia, sarcopenia, osteopenia and fatigue of androgen-deficiency amplify and widen the adverse consequences of the original disease-trigger). In women with hypothalamic amenorrhea (HA-HH secondary to chronic bioenergetic deficit from dietary restriction and/or intensive exercise), a genetic link to congenital HH (CHH) was recently established; women carrying monoallelic CHH gene mutations will typically not develop CHH, but are significantly more susceptible to HA. However, the male reproductive axis seems to be more resistant to similar environmental insults. In contrast, MetS-associated HH (mHH) is specifically a male phenomenon; the reproductive phenotype of females with MetS tending instead towards hyperandrogenism, rather than hypogonadism. The underlying pathogenic mechanisms responsible for mHH have not been clearly identified and, as yet, there has been no investigation of a potential role for CHH mutation carriage in its etiology. Over the decades, the use of either genetic- or diet-induced obesity and/or MetS animal models has greatly helped to illuminate the complex etiology of metabolic dysregulation, but the strong relationship between obesity/MetS and mHH in males has been largely neglected, with little or no information about the regulation of reproductive function by metabolic factors under conditions of bioenergetic excess. However, the pathogenic link between MetS and HH in males has been recently investigated in an animal model of high fat

  4. 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

  5. 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.

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

    Science.gov (United States)

    Gao, Ming; Li, Shiwei

    2017-05-01

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

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

    DEFF Research Database (Denmark)

    Patil, Raveendra Hanumantagoud; Lægdsmand, Mette; Olesen, Jørgen Eivind

    2012-01-01

    Sensitivity of wheat yield and soil nitrogen (N) losses to stepwise changes in means and variances of climatic variables were determined using the FASSET model. The LARS-WG was used to generate climate scenarios using observed climate data (1961–90) from two sites in Denmark, which differed...... loam. This study illustrates the importance of considering effects of changes to mean climatic factors, climatic variability and soil types on both crop yield and soil N losses....

  8. An Analytically Tractable Model for Pricing Multiasset Options with Correlated Jump-Diffusion Equity Processes and a Two-Factor Stochastic Yield Curve

    Directory of Open Access Journals (Sweden)

    Tristan Guillaume

    2016-01-01

    Full Text Available This paper shows how to value multiasset options analytically in a modeling framework that combines both continuous and discontinuous variations in the underlying equity or foreign exchange processes and a stochastic, two-factor yield curve. All correlations are taken into account, between the factors driving the yield curve, between fixed income and equity as asset classes, and between the individual equity assets themselves. The valuation method is applied to three of the most popular two-asset options.

  9. 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

  10. 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

  11. 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

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

    International Nuclear Information System (INIS)

    Ramarohetra, Johanna; Pohl, Benjamin; Sultan, Benjamin

    2015-01-01

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

  13. 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...

  14. 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...

  15. 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.

  16. 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.)