WorldWideScience

Sample records for model yields insights

  1. 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.

  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. 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.

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

    Science.gov (United States)

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

    2018-04-01

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

  5. 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.

  6. 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

  7. 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 ...

  8. 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....

  9. 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.

  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. 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

  12. 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.

  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. Temperature and precipitation effects on wheat yield across a European transect

    DEFF Research Database (Denmark)

    Pirttioja, N; Carter, T.; Fronzek, S

    2015-01-01

    his study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop s...... additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development....

  15. 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.

  16. A crop model-based approach for sunflower yields

    Directory of Open Access Journals (Sweden)

    João Guilherme Dal Belo Leite

    2014-10-01

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

  17. 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

  18. 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...

  19. 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)

  20. 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.

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

    KAUST Repository

    Hays, Spencer

    2012-09-01

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

  2. Modelling 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

  3. 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.

  4. Microstructural origins of yield-strength changes in AISI 316 during fission or fusion irradiation

    International Nuclear Information System (INIS)

    Garner, F.A.; Hamilton, M.L.; Panayotou, N.F.; Johnson, G.D.

    1981-08-01

    The changes in yield strength of AISI 316 irradiated in breeder reactors have been successfully modeled in terms of concurrent changes in microstructural components. Two new insights involving the strength contributions of voids and Frank loops have been incorporated into the hardening models. Both the radiation-induced microstructure and the yield strength exhibit transients which are then followed by saturation at a level dependent on the irradiation temperature. Extrapolation to anticipated fusion behavior based on microstructural comparisons leads to the conclusion that the primary influence of transmutational differences is only to alter the transient behavior and not the saturation level of yield strength

  5. 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, ...

  6. 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...

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

    Science.gov (United States)

    Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

    2017-09-01

    Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates

  13. 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. 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.

  15. 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)

  16. 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.

  17. 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.

  18. 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...

  19. 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.

  20. 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).

  1. 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.

  2. 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.

  3. Systematics of Fission-Product Yields

    International Nuclear Information System (INIS)

    Wahl, A.C.

    2002-01-01

    Empirical equations representing systematics of fission-product yields have been derived from experimental data. The systematics give some insight into nuclear-structure effects on yields, and the equations allow estimation of yields from fission of any nuclide with atomic number Z F = 90 thru 98, mass number A F = 230 thru 252, and precursor excitation energy (projectile kinetic plus binding energies) PE = 0 thru ∼200 MeV--the ranges of these quantities for the fissioning nuclei investigated. Calculations can be made with the computer program CYFP. Estimates of uncertainties in the yield estimates are given by equations, also in CYFP, and range from ∼ 15% for the highest yield values to several orders of magnitude for very small yield values. A summation method is used to calculate weighted average parameter values for fast-neutron (∼ fission spectrum) induced fission reactions

  4. Systematics of Fission-Product Yields

    Energy Technology Data Exchange (ETDEWEB)

    A.C. Wahl

    2002-05-01

    Empirical equations representing systematics of fission-product yields have been derived from experimental data. The systematics give some insight into nuclear-structure effects on yields, and the equations allow estimation of yields from fission of any nuclide with atomic number Z{sub F} = 90 thru 98, mass number A{sub F} = 230 thru 252, and precursor excitation energy (projectile kinetic plus binding energies) PE = 0 thru {approx}200 MeV--the ranges of these quantities for the fissioning nuclei investigated. Calculations can be made with the computer program CYFP. Estimates of uncertainties in the yield estimates are given by equations, also in CYFP, and range from {approx} 15% for the highest yield values to several orders of magnitude for very small yield values. A summation method is used to calculate weighted average parameter values for fast-neutron ({approx} fission spectrum) induced fission reactions.

  5. Yielding to Stress: Recent Developments in Viscoplastic Fluid Mechanics

    Science.gov (United States)

    Balmforth, Neil J.; Frigaard, Ian A.; Ovarlez, Guillaume

    2014-01-01

    The archetypal feature of a viscoplastic fluid is its yield stress: If the material is not sufficiently stressed, it behaves like a solid, but once the yield stress is exceeded, the material flows like a fluid. Such behavior characterizes materials common in industries such as petroleum and chemical processing, cosmetics, and food processing and in geophysical fluid dynamics. The most common idealization of a viscoplastic fluid is the Bingham model, which has been widely used to rationalize experimental data, even though it is a crude oversimplification of true rheological behavior. The popularity of the model is in its apparent simplicity. Despite this, the sudden transition between solid-like behavior and flow introduces significant complications into the dynamics, which, as a result, has resisted much analysis. Over recent decades, theoretical developments, both analytical and computational, have provided a better understanding of the effect of the yield stress. Simultaneously, greater insight into the material behavior of real fluids has been afforded by advances in rheometry. These developments have primed us for a better understanding of the various applications in the natural and engineering sciences.

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. 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).

  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. Effects of diurnal temperature range and drought on wheat yield in Spain

    Science.gov (United States)

    Hernandez-Barrera, S.; Rodriguez-Puebla, C.; Challinor, A. J.

    2017-07-01

    This study aims to provide new insight on the wheat yield historical response to climate processes throughout Spain by using statistical methods. Our data includes observed wheat yield, pseudo-observations E-OBS for the period 1979 to 2014, and outputs of general circulation models in phase 5 of the Coupled Models Inter-comparison Project (CMIP5) for the period 1901 to 2099. In investigating the relationship between climate and wheat variability, we have applied the approach known as the partial least-square regression, which captures the relevant climate drivers accounting for variations in wheat yield. We found that drought occurring in autumn and spring and the diurnal range of temperature experienced during the winter are major processes to characterize the wheat yield variability in Spain. These observable climate processes are used for an empirical model that is utilized in assessing the wheat yield trends in Spain under different climate conditions. To isolate the trend within the wheat time series, we implemented the adaptive approach known as Ensemble Empirical Mode Decomposition. Wheat yields in the twenty-first century are experiencing a downward trend that we claim is a consequence of widespread drought over the Iberian Peninsula and an increase in the diurnal range of temperature. These results are important to inform about the wheat vulnerability in this region to coming changes and to develop adaptation strategies.

  13. 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 ...

  14. 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.

  15. 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...

  16. 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.

  17. 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)

  18. 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.

  19. 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.

  20. 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).

  1. 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).

  2. 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

  3. Theory of mind correlates with clinical insight but not cognitive insight in patients with schizophrenia.

    Science.gov (United States)

    Zhang, Qi; Li, Xu; Parker, Giverny J; Hong, Xiao-Hong; Wang, Yi; Lui, Simon S Y; Neumann, David L; Cheung, Eric F C; Shum, David H K; Chan, Raymond C K

    2016-03-30

    Research on the relationship between insight and social cognition, in particular Theory of Mind (ToM), in schizophrenia has yielded mixed findings to date. Very few studies, however, have assessed both clinical insight and cognitive insight when examining their relationships with ToM in schizophrenia. The current study thus investigated the relationship between clinical insight, cognitive insight, and ToM in a sample of 56 patients with schizophrenia and 30 healthy controls. Twenty-seven patients were classified as low in clinical insight according to their scores on the 'insight' item (G12) of the Positive and Negative Syndrome Scale (PANSS). Moreover, cognitive insight and ToM were assessed with the Beck Cognitive Insight Scale (BCIS) and the Yoni task, respectively. The results indicated that patients with poor clinical insight performed worse on tasks of second-order cognitive and affective ToM, while the ToM performance of patients with high clinical insight was equivalent to that of healthy controls. Furthermore, while clinical insight was correlated with ToM and clinical symptoms, cognitive insight did not correlate with clinical insight, ToM, or clinical symptoms. Clinical insight thus appears to be an important factor related to ToM in schizophrenia. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  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. 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.

  6. 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.

  7. 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.

  8. An adapted yield criterion for the evolution of subsequent yield surfaces

    Science.gov (United States)

    Küsters, N.; Brosius, A.

    2017-09-01

    In numerical analysis of sheet metal forming processes, the anisotropic material behaviour is often modelled with isotropic work hardening and an average Lankford coefficient. In contrast, experimental observations show an evolution of the Lankford coefficients, which can be associated with a yield surface change due to kinematic and distortional hardening. Commonly, extensive efforts are carried out to describe these phenomena. In this paper an isotropic material model based on the Yld2000-2d criterion is adapted with an evolving yield exponent in order to change the yield surface shape. The yield exponent is linked to the accumulative plastic strain. This change has the effect of a rotating yield surface normal. As the normal is directly related to the Lankford coefficient, the change can be used to model the evolution of the Lankford coefficient during yielding. The paper will focus on the numerical implementation of the adapted material model for the FE-code LS-Dyna, mpi-version R7.1.2-d. A recently introduced identification scheme [1] is used to obtain the parameters for the evolving yield surface and will be briefly described for the proposed model. The suitability for numerical analysis will be discussed for deep drawing processes in general. Efforts for material characterization and modelling will be compared to other common yield surface descriptions. Besides experimental efforts and achieved accuracy, the potential of flexibility in material models and the risk of ambiguity during identification are of major interest in this paper.

  9. The effect of soil moisture anomalies on maize yield in Germany

    Science.gov (United States)

    Peichl, Michael; Thober, Stephan; Meyer, Volker; Samaniego, Luis

    2018-03-01

    Crop models routinely use meteorological variations to estimate crop yield. Soil moisture, however, is the primary source of water for plant growth. The aim of this study is to investigate the intraseasonal predictability of soil moisture to estimate silage maize yield in Germany. We also evaluate how approaches considering soil moisture perform compare to those using only meteorological variables. Silage maize is one of the most widely cultivated crops in Germany because it is used as a main biomass supplier for energy production in the course of the German Energiewende (energy transition). Reduced form fixed effect panel models are employed to investigate the relationships in this study. These models are estimated for each month of the growing season to gain insights into the time-varying effects of soil moisture and meteorological variables. Temperature, precipitation, and potential evapotranspiration are used as meteorological variables. Soil moisture is transformed into anomalies which provide a measure for the interannual variation within each month. The main result of this study is that soil moisture anomalies have predictive skills which vary in magnitude and direction depending on the month. For instance, dry soil moisture anomalies in August and September reduce silage maize yield more than 10 %, other factors being equal. In contrast, dry anomalies in May increase crop yield up to 7 % because absolute soil water content is higher in May compared to August due to its seasonality. With respect to the meteorological terms, models using both temperature and precipitation have higher predictability than models using only one meteorological variable. Also, models employing only temperature exhibit elevated effects.

  10. 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.

  11. 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.

  12. 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.

  13. Yield gap of rainfed rice in farmers’ fields in Central Java, Indonesia

    NARCIS (Netherlands)

    Boling, A.A.; Tuong, T.P.; Keulen, van H.; Bouman, B.A.M.; Suganda, H.; Spiertz, J.H.J.

    2010-01-01

    Yield constraint analysis for rainfed rice at a research station gives insight into the relative role of occurring yield-limiting factors. However, soil nutrient status and water conditions along toposequences in rainfed farmers’ fields may differ from those at the research station. Therefore, yield

  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. 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.

  16. 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.

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

    Science.gov (United States)

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

    2018-04-01

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

  18. 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

  19. 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.

  20. 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.

  1. 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...

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

    Science.gov (United States)

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

    2018-02-07

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

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

    Science.gov (United States)

    Ovando, Gustavo; Sayago, Silvina; Bocco, Mónica

    2018-04-01

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

  4. 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.

  5. 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.

  6. 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.

  7. 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...

  8. 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.

  9. Simulation of water management for fodder beet to reduce yield losses under late season drought

    Directory of Open Access Journals (Sweden)

    T. Noreldin

    2016-12-01

    Full Text Available The objectives of this study were to calibrate CropSyst model for fodder beet grown under full and late season drought and to use the simulation results to analyze the relationship between irrigation amount and yield, as well as in water management to reduce yield losses under full and late season drought. For this reason, two field experiments were implemented at El-Serw Agricultural Research Station in Demiatte governorate, during 2011/12 and 2012/13 growing seasons. Two irrigation treatments were studied: full irrigation and late season drought. The model was calibrated using the data obtained from the two seasons. Results indicated that the reduction in fodder beet yield under late season drought was 11 and 12% in 2011/12 and 2012/13 growing seasons, respectively. Calibration of CropSyst revealed that the percentage of difference between measured and predicted values were low in both growing seasons. The results also indicated that changing irrigation schedule after examining water stress index under full and late season drought led to increase in fodder beet yield, as well as water and land productivity. Thus, CropSyst model can give insight into when to apply irrigation water to minimize yield losses under late season drought.

  10. 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.

  11. Numerical Experiments Providing New Insights into Plasma Focus Fusion Devices

    Directory of Open Access Journals (Sweden)

    Sing Lee

    2010-04-01

    Full Text Available Recent extensive and systematic numerical experiments have uncovered new insights into plasma focus fusion devices including the following: (1 a plasma current limitation effect, as device static inductance is reduced towards very small values; (2 scaling laws of neutron yield and soft x-ray yield as functions of storage energies and currents; (3 a global scaling law for neutron yield as a function of storage energy combining experimental and numerical data showing that scaling deterioration has probably been interpreted as neutron ‘saturation’; and (4 a fundamental cause of neutron ‘saturation’. The ground-breaking insights thus gained may completely change the directions of plasma focus fusion research.

  12. 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.

  13. 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.

  14. 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

  15. 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 ...

  16. 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.

  17. Climate Variability and Yields of Major Staple Food Crops in Northern Ghana

    Science.gov (United States)

    Amikuzuno, J.

    2012-12-01

    Climate variability, the short-term fluctuations in average weather conditions, and agriculture affect each other. Climate variability affects the agroecological and growing conditions of crops and livestock, and is recently believed to be the greatest impediment to the realisation of the first Millennium Development Goal of reducing poverty and food insecurity in arid and semi-arid regions of developing countries. Conversely, agriculture is a major contributor to climate variability and change by emitting greenhouse gases and reducing the agroecology's potential for carbon sequestration. What however, is the empirical evidence of this inter-dependence of climate variability and agriculture in Sub-Sahara Africa? In this paper, we provide some insight into the long run relationship between inter-annual variations in temperature and rainfall, and annual yields of the most important staple food crops in Northern Ghana. Applying pooled panel data of rainfall, temperature and yields of the selected crops from 1976 to 2010 to cointegration and Granger causality models, there is cogent evidence of cointegration between seasonal, total rainfall and crop yields; and causality from rainfall to crop yields in the Sudano-Guinea Savannah and Guinea Savannah zones of Northern Ghana. This suggests that inter-annual yields of the crops have been influenced by the total mounts of rainfall in the planting season. Temperature variability over the study period is however stationary, and is suspected to have minimal effect if any on crop yields. Overall, the results confirm the appropriateness of our attempt in modelling long-term relationships between the climate and crop yield variables.

  18. 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.

  19. 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.

  20. 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.

  1. 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...

  2. 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

  3. 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

  4. 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.

  5. Effects of Nutrient Antagonism and Synergism on Yield and Fertilizer Use Efficiency

    NARCIS (Netherlands)

    Rietra, René P.J.J.; Heinen, Marius; Dimkpa, Chistian O.; Bindraban, Prem S.

    2017-01-01

    Interaction among plant nutrients can yield antagonistic or synergistic outcomes that influence nutrient use efficiency. To provide insight on this phenomenon, peer-reviewed articles were selected that quantified the interaction effects of nutrients on crop yield levels. In total 94 articles were

  6. 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.

  7. 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.)

  8. 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.

  9. 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.

  10. 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.

  11. 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)

  12. 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

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

    Science.gov (United States)

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

    2005-08-01

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

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. 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

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

    Directory of Open Access Journals (Sweden)

    Allen R Overman

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

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. 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 .

  6. 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...

  7. 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

  8. 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

  9. Quantifying potential yield and water-limited yield of summer maize in the North China Plain

    Science.gov (United States)

    Jiang, Mingnuo; Liu, Chaoshun; Chen, Maosi

    2017-09-01

    The North China Plain is a major food producing region in China, and climate change could pose a threat to food production in the region. Based on China Meteorological Forcing Dataset, simulating the growth of summer maize in North China Plain from 1979 to 2015 with the regional implementation of crop growth model WOFOST. The results showed that the model can reflect the potential yield and water-limited yield of Summer Maize in North China Plain through the calibration and validation of WOFOST model. After the regional implementation of model, combined with the reanalysis data, the model can better reproduce the regional history of summer maize yield in the North China Plain. The yield gap in Southeastern Beijing, southern Tianjin, southern Hebei province, Northwestern Shandong province is significant, these means the water condition is the main factor to summer maize yield in these regions.

  10. 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.

  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. 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.

  13. 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.

  14. 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...

  15. 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.

  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. 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

  18. 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

  19. 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.

  20. 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.

  1. Collisional Histories of Comets and Trojan Asteroids: Insights from Forsterite and Enstatite Impact Studies

    Science.gov (United States)

    Lederer. S. M.; Jensen, E. A.; Wooden, D. H.; Lindsay, S. S.; Smith, D. C.; Cintala, M. J.; Nakamura-Messenger, K.; Keller, L. P.

    2012-01-01

    Impacts into forsterite and orthoenstatite at speeds typically encountered by comets demonstrate that shock imparted by collisions is detectable in the infrared signatures of their dust. The spectral signatures can be traced to physical alterations in their crystalline structures, as observed in TEM imaging and modeled using a dipole approximation. These results yield tantalizing insights into the collisional history of our solar system, as well as the history of individual comets and Trojan asteroids.

  2. 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

  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. 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...

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. The critical domain size of stochastic population models.

    Science.gov (United States)

    Reimer, Jody R; Bonsall, Michael B; Maini, Philip K

    2017-02-01

    Identifying the critical domain size necessary for a population to persist is an important question in ecology. Both demographic and environmental stochasticity impact a population's ability to persist. Here we explore ways of including this variability. We study populations with distinct dispersal and sedentary stages, which have traditionally been modelled using a deterministic integrodifference equation (IDE) framework. Individual-based models (IBMs) are the most intuitive stochastic analogues to IDEs but yield few analytic insights. We explore two alternate approaches; one is a scaling up to the population level using the Central Limit Theorem, and the other a variation on both Galton-Watson branching processes and branching processes in random environments. These branching process models closely approximate the IBM and yield insight into the factors determining the critical domain size for a given population subject to stochasticity.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. 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....

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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)

  5. 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...

  6. 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.

  7. 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.

  8. 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

  9. Optimizing rice yields while minimizing yield-scaled global warming potential.

    Science.gov (United States)

    Pittelkow, Cameron M; Adviento-Borbe, Maria A; van Kessel, Chris; Hill, James E; Linquist, Bruce A

    2014-05-01

    To meet growing global food demand with limited land and reduced environmental impact, agricultural greenhouse gas (GHG) emissions are increasingly evaluated with respect to crop productivity, i.e., on a yield-scaled as opposed to area basis. Here, we compiled available field data on CH4 and N2 O emissions from rice production systems to test the hypothesis that in response to fertilizer nitrogen (N) addition, yield-scaled global warming potential (GWP) will be minimized at N rates that maximize yields. Within each study, yield N surplus was calculated to estimate deficit or excess N application rates with respect to the optimal N rate (defined as the N rate at which maximum yield was achieved). Relationships between yield N surplus and GHG emissions were assessed using linear and nonlinear mixed-effects models. Results indicate that yields increased in response to increasing N surplus when moving from deficit to optimal N rates. At N rates contributing to a yield N surplus, N2 O and yield-scaled N2 O emissions increased exponentially. In contrast, CH4 emissions were not impacted by N inputs. Accordingly, yield-scaled CH4 emissions decreased with N addition. Overall, yield-scaled GWP was minimized at optimal N rates, decreasing by 21% compared to treatments without N addition. These results are unique compared to aerobic cropping systems in which N2 O emissions are the primary contributor to GWP, meaning yield-scaled GWP may not necessarily decrease for aerobic crops when yields are optimized by N fertilizer addition. Balancing gains in agricultural productivity with climate change concerns, this work supports the concept that high rice yields can be achieved with minimal yield-scaled GWP through optimal N application rates. Moreover, additional improvements in N use efficiency may further reduce yield-scaled GWP, thereby strengthening the economic and environmental sustainability of rice systems. © 2013 John Wiley & Sons Ltd.

  10. 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.

  11. 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...

  12. Exclusive nonleptonic B{yields}VV decays

    Energy Technology Data Exchange (ETDEWEB)

    Barik, N [Department of Physics, Utkal University, Bhubaneswar-751004 (India); Naimuddin, Sk [Department of Physics, Maharishi College of Natural Law, Bhubaneswar-751007 (India); Dash, P C [Department of Physics, Prananath Autonomous College, Khurda-752057 (India); Kar, Susmita [Department of Physics, North Orissa University, Baripada-757003 (India)

    2009-07-01

    The exclusive two-body nonleptonic B{yields}VV decays are investigated, within the factorization approximation, in the relativistic independent quark model based on a confining potential in the scalar-vector harmonic form. The branching ratios and the longitudinal polarization fraction (R{sub L}) are calculated yielding the model predictions in agreement with experiment. Our predicted CP-odd fraction (R{sub perpendicular}) for B{yields}D*D{sub (s)}* decays are in general agreement with other model predictions and within the existing experimental limit.

  13. 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.

  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. 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...

  16. 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....

  17. 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

  18. 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

  19. [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.

  20. Oligodendrocyte differentiation and implantation : new insights for remyelinating cell therapy

    NARCIS (Netherlands)

    Sher, Falak; Balasubramaniyan, Veerakumar; Boddeke, Erik; Copray, Sjef

    2008-01-01

    Purpose of review Recent research on oligodendrocyte development has yielded new insights on the involvement of morphogens and differentiation factors in oligodendrogenesis. This knowledge has improved strategies to control neural stem cell-derived oligodendrocyte differentiation and functional

  1. 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.

  2. 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

  3. The small world yields the most effective information spreading

    International Nuclear Information System (INIS)

    Lü Linyuan; Chen Duanbing; Zhou Tao

    2011-01-01

    The spreading dynamics of information and diseases are usually analyzed by using a unified framework and analogous models. In this paper, we propose a model to emphasize the essential difference between information spreading and epidemic spreading, where the memory effects, the social reinforcement and the non-redundancy of contacts are taken into account. Under certain conditions, the information spreads faster and broader in regular networks than in random networks, which to some extent supports the recent experimental observation of spreading in online society (Centola D 2010 Science 329 1194). At the same time, the simulation result indicates that the random networks tend to be favorable for effective spreading when the network size increases. This challenges the validity of the above-mentioned experiment for large-scale systems. More importantly, we show that the spreading effectiveness can be sharply enhanced by introducing a little randomness into the regular structure, namely the small-world networks yield the most effective information spreading. This work provides insights into the role of local clustering in information spreading. (paper)

  4. 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.

  5. On the yield stress of complex materials

    Science.gov (United States)

    Calderas, F.; Herrera-Valencia, E. E.; Sanchez-Solis, A.; Manero, O.; Medina-Torres, L.; Renteria, A.; Sanchez-Olivares, G.

    2013-11-01

    In the present work, the yield stress of complex materials is analyzed and modeled using the Bautista-Manero-Puig (BMP) constitutive equation, consisting of the upper-convected Maxwell equation coupled to a kinetic equation to account for the breakdown and reformation of the fluid structure. BMP model predictions for a complex fluid in different flow situations are analyzed and compared with yield stress predictions of other rheological models, and with experiments on fluids that exhibit yield stresses. It is shown that one of the main features of the BMP model is that it predicts a real yield stress (elastic solid or Hookean behavior) as one of the material parameters, the zero shear-rate fluidity, is zero. In addition, the transition to fluid-like behavior is continuous, as opposed to predictions of more empirical models.

  6. 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

  7. Precise measurement of {gamma}(K{yields}e {nu}({gamma}))/{gamma}(K{yields}{mu} {nu}({gamma})) and study of K{yields}e {nu} {gamma}

    Energy Technology Data Exchange (ETDEWEB)

    Ambrosino, F.; Massarotti, P.; Meola, S.; Napolitano, M. [Dipartimento di Scienze Fisiche dell' Universita ' ' Federico II' ' , Napoli (Italy); INFN Sezione di Napoli, Napoli (Italy); Antonelli, A.; Antonelli, M.; Bencivenni, G.; Bloise, C.; Bossi, F.; Capon, G.; Capussela, T.; Ciambrone, P.; De Lucia, E.; De Simone, P.; Dreucci, M.; Felici, G.; Gatti, C.; Giovannella, S.; Jacewicz, M.; Lanfranchi, G.; Miscetti, S.; Moulson, M.; Murtas, F.; Palutan, M.; Santangelo, P.; Sciascia, B.; Sibidanov, A.; Spadaro, T.; Venanzoni, G. [Laboratori Nazionali di Frascati dell' INFN, Frascati (Italy); Archilli, F. [Dipartimento di Fisica dell' Universita ' ' Tor Vergata' ' , Rome (Italy); INFN Sezione di Roma Tor Vergata, Rome (Italy); Beltrame, P.; Denig, A.; Mueller, S. [Johannes Gutenberg-Universitaet, Institut fuer Kernphysik, Mainz (Germany); Bini, C.; De Santis, A.; De Zorzi, G.; Di Domenico, A.; Fiore, S.; Franzini, P.; Gauzzi, P. [Dipartimento di Fisica dell' Universita ' ' La Sapienza' ' , Rome (Italy); INFN Sezione di Roma, Rome (Italy); Bocchetta, S.; Ceradini, F.; Di Micco, B.; Nguyen, F. [Dipartimento di Fisica dell' Universita ' ' Roma Tre' ' , Rome (Italy); INFN Sezione di Roma Tre, Rome (Italy); Branchini, P.; Graziani, E.; Passeri, A.; Tortora, L. [INFN Sezione di Roma Tre, Rome (Italy); Capriotti, D. [Dipartimento di Fisica dell' Universita ' ' Roma Tre' ' , Rome (Italy); Di Donato, C. [INFN Sezione di Napoli, Napoli (Italy); Kulikov, V. [Institute for Theoretical and Experimental Physics, Moscow (Russian Federation); Lee-Franzini, J. [Laboratori Nazionali di Frascati dell' INFN, Frascati (Italy); State University of New York, Physics Department, Stony Brook (United States); Martini, M.; Patera, V.; Versaci, R. [Laboratori Nazionali di Frascati dell' INFN, Frascati (Italy); Dipartimento di Energetica dell' Universita ' ' La Sapienza' ' , Rome (Italy); Valente, P. [INFN Sezione di Roma, Rome (Italy)

    2009-12-15

    We present a precise measurement of the ratio R{sub K}={gamma}(K{yields}e{nu}({gamma}))/{gamma}(K{yields}{mu}{nu}({gamma})) and a study of the radiative process K{yields}e{nu}{gamma}, performed with the KLOE detector. The results are based on data collected at the Frascati e{sup +}e{sup -} collider DA {phi}NE for an integrated luminosity of 2.2 fb{sup -1}. We find R{sub K}=(2.493{+-}0.025{sub stat}{+-}0.019{sub syst}) x 10{sup -5}, in agreement with the Standard Model expectation. This result is used to improve constraints on parameters of the Minimal Supersymmetric Standard Model with lepton flavor violation. We also measured the differential decay rate d {gamma}(K{yields}e{nu}{gamma})/dE{sub {gamma}} for photon energies 10

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. Response of switchgrass yield to future climate change

    International Nuclear Information System (INIS)

    Tulbure, Mirela G; Wimberly, Michael C; Owens, Vance N

    2012-01-01

    A climate envelope approach was used to model the response of switchgrass, a model bioenergy species in the United States, to future climate change. The model was built using general additive models (GAMs), and switchgrass yields collected at 45 field trial locations as the response variable. The model incorporated variables previously shown to be the main determinants of switchgrass yield, and utilized current and predicted 1 km climate data from WorldClim. The models were run with current WorldClim data and compared with results of predicted yield obtained using two climate change scenarios across three global change models for three time steps. Results did not predict an increase in maximum switchgrass yield but showed an overall shift in areas of high switchgrass productivity for both cytotypes. For upland cytotypes, the shift in high yields was concentrated in northern and north-eastern areas where there were increases in average growing season temperature, whereas for lowland cultivars the areas where yields were projected to increase were associated with increases in average early growing season precipitation. These results highlight the fact that the influences of climate change on switchgrass yield are spatially heterogeneous and vary depending on cytotype. Knowledge of spatial distribution of suitable areas for switchgrass production under climate change should be incorporated into planning of current and future biofuel production. Understanding how switchgrass yields will be affected by future changes in climate is important for achieving a sustainable biofuels economy. (letter)

  13. Benefits of seasonal forecasts of crop yields

    Science.gov (United States)

    Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

    2017-12-01

    Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

  14. Radiative leptonic decay: B{sup -}{yields}{mu}{sup -}{nu}{sub {mu}}{gamma} in a relativistic independent quark model

    Energy Technology Data Exchange (ETDEWEB)

    Barik, N [Department of Physics, Utkal University, Bhubaneswar-751004 (India); Naimuddin, Sk; Dash, P C [Department of Physics, Prananath Autonomous College, Khurda-752057 (India); Kar, Susmita [Department of Physics, North Orissa University, Baripada-757003 (India)

    2008-01-01

    We study the radiative leptonic decay, B{sup -}{yields}{mu}{sup -}{nu}{sub {mu}}{gamma}, in the framework of a relativistic independent quark model, based on the confining potential in the scalar-vector harmonic form. As expected, we find that the photon emission in this decay overcomes the so-called helicity suppression inevitable in the case of pure leptonic decay (B{sup -}{yields}{mu}{sup -}{nu}{sub {mu}}). Our result for the branching ratio is Br(B{sup -}{yields}{mu}{sup -}{nu}{sub {mu}}{gamma})=1.70x10{sup -6}, which is comparable with other model predictions within the current experimental upper limit. The photon energy spectrum predicted in the model is slightly asymmetric with the peak value around 1.45 GeV, which should render it quite accessible to experimental analysis.

  15. CRISPR-Cas adaptation: insights into the mechanism of action.

    Science.gov (United States)

    Amitai, Gil; Sorek, Rotem

    2016-02-01

    Since the first demonstration that CRISPR-Cas systems provide bacteria and archaea with adaptive immunity against phages and plasmids, numerous studies have yielded key insights into the molecular mechanisms governing how these systems attack and degrade foreign DNA. However, the molecular mechanisms underlying the adaptation stage, in which new immunological memory is formed, have until recently represented a major unresolved question. In this Progress article, we discuss recent discoveries that have shown both how foreign DNA is identified by the CRISPR-Cas adaptation machinery and the molecular basis for its integration into the chromosome to form an immunological memory. Furthermore, we describe the roles of each of the specific CRISPR-Cas components that are involved in memory formation, and consider current models for their evolutionary origin.

  16. 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.

  17. 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

  18. 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.

  19. Influence of yield surface curvature on the macroscopic yielding and ductile failure of isotropic porous plastic materials

    Science.gov (United States)

    Dæhli, Lars Edvard Bryhni; Morin, David; Børvik, Tore; Hopperstad, Odd Sture

    2017-10-01

    Numerical unit cell models of an approximative representative volume element for a porous ductile solid are utilized to investigate differences in the mechanical response between a quadratic and a non-quadratic matrix yield surface. A Hershey equivalent stress measure with two distinct values of the yield surface exponent is employed as the matrix description. Results from the unit cell calculations are further used to calibrate a heuristic extension of the Gurson model which incorporates effects of the third deviatoric stress invariant. An assessment of the porous plasticity model reveals its ability to describe the unit cell response to some extent, however underestimating the effect of the Lode parameter for the lower triaxiality ratios imposed in this study when compared to unit cell simulations. Ductile failure predictions by means of finite element simulations using a unit cell model that resembles an imperfection band are then conducted to examine how the non-quadratic matrix yield surface influences the failure strain as compared to the quadratic matrix yield surface. Further, strain localization predictions based on bifurcation analyses and imperfection band analyses are undertaken using the calibrated porous plasticity model. These simulations are then compared to the unit cell calculations in order to elucidate the differences between the various modelling strategies. The current study reveals that strain localization analyses using an imperfection band model and a spatially discretized unit cell are in reasonable agreement, while the bifurcation analyses predict higher strain levels at localization. Imperfection band analyses are finally used to calculate failure loci for the quadratic and the non-quadratic matrix yield surface under a wide range of loading conditions. The underlying matrix yield surface is demonstrated to have a pronounced influence on the onset of strain localization.

  20. An evolutionary yield function based on Barlat 2000 yield function for the superconducting niobium sheet

    Science.gov (United States)

    Darbandi, Payam; Pourboghrat, Farhang

    2011-08-01

    Superconducting radio frequency (SRF) niobium cavities are widely used in high-energy physics to accelerate particle beams in particle accelerators. The performance of SRF cavities is affected by the microstructure and purity of the niobium sheet, surface quality, geometry, etc. Following optimum strain paths in the forming of these cavities can significantly control these parameters. To select these strain paths, however, information about the mechanical behavior, microstructure, and formability of the niobium sheet is required. In this study the Barlat 2000 yield function has been used as a yield function for high purity niobium. Results from this study showed that, due to intrinsic behavior, it is necessary to evolve the anisotropic coefficients of Barlat's yield function in order to properly model the plastic behavior of the niobium sheet. The accuracy of the newly developed evolutionary yield function was verified by applying it to the modeling of the hydrostatic bulging of the niobium sheet. Also, in a separate attempt crystal plasticity finite element method was use to model the behavior of the polycrystalline niobium sheet with a particular initial texture.

  1. An evolutionary yield function based on Barlat 2000 yield function for the superconducting niobium sheet

    International Nuclear Information System (INIS)

    Darbandi, Payam; Pourboghrat, Farhang

    2011-01-01

    Superconducting radio frequency (SRF) niobium cavities are widely used in high-energy physics to accelerate particle beams in particle accelerators. The performance of SRF cavities is affected by the microstructure and purity of the niobium sheet, surface quality, geometry, etc. Following optimum strain paths in the forming of these cavities can significantly control these parameters. To select these strain paths, however, information about the mechanical behavior, microstructure, and formability of the niobium sheet is required. In this study the Barlat 2000 yield function has been used as a yield function for high purity niobium. Results from this study showed that, due to intrinsic behavior, it is necessary to evolve the anisotropic coefficients of Barlat's yield function in order to properly model the plastic behavior of the niobium sheet. The accuracy of the newly developed evolutionary yield function was verified by applying it to the modeling of the hydrostatic bulging of the niobium sheet. Also, in a separate attempt crystal plasticity finite element method was use to model the behavior of the polycrystalline niobium sheet with a particular initial texture.

  2. Numerical insight into the micromechanics of jet erosion of a cohesive granular material

    Directory of Open Access Journals (Sweden)

    Cuéllar Pablo

    2017-01-01

    Full Text Available Here we investigate the physical mechanisms behind the surface erosion of a cohesive granular soil induced by an impinging jet by means of numerical simulations coupling fluid and grains at the microscale. The 2D numerical model combines the Discrete Element and Lattice Boltzmann methods (DEM-LBM and accounts for the granular cohesion with a contact model featuring a paraboloidal yield surface. Here we review first the hydrodynamical conditions imposed by the fluid jet on a solid granular packing, turning then the attention to the impact of cohesion on the erosion kinetics. Finally, the use of an additional subcritical debonding damage model based on the work of Silvani and co-workers provides a novel insight into the internal solicitation of the cohesive granular sample by the impinging jet.

  3. Numerical insight into the micromechanics of jet erosion of a cohesive granular material

    Science.gov (United States)

    Cuéllar, Pablo; Benseghier, Zeyd; Luu, Li-Hua; Bonelli, Stéphane; Delenne, Jean-Yves; Radjaï, Farhang; Philippe, Pierre

    2017-06-01

    Here we investigate the physical mechanisms behind the surface erosion of a cohesive granular soil induced by an impinging jet by means of numerical simulations coupling fluid and grains at the microscale. The 2D numerical model combines the Discrete Element and Lattice Boltzmann methods (DEM-LBM) and accounts for the granular cohesion with a contact model featuring a paraboloidal yield surface. Here we review first the hydrodynamical conditions imposed by the fluid jet on a solid granular packing, turning then the attention to the impact of cohesion on the erosion kinetics. Finally, the use of an additional subcritical debonding damage model based on the work of Silvani and co-workers provides a novel insight into the internal solicitation of the cohesive granular sample by the impinging jet.

  4. Insight in psychosis: Standards, science, ethics and value judgment.

    Science.gov (United States)

    Jacob, K S

    2017-06-01

    The clinical assessment of insight solely employs biomedical perspectives and criteria to the complete exclusion of context and culture and to the disregard of values and value judgments. The aim of this discussion article is to examine recent research from India on insight and explanatory models in psychosis and re-examine the framework of assessment, diagnosis and management of insight and explanatory models. Recent research from India on insight in psychosis and explanatory models is reviewed. Recent research, which has used longitudinal data and adjusted for pretreatment variables, suggests that insight and explanatory models of illness at baseline do not predict course, outcome and treatment response in schizophrenia, which seem to be dependent on the severity and quality of the psychosis. It supports the view that people with psychosis simultaneously hold multiple and contradictory explanatory models of illness, which change over time and with the trajectory of the illness. It suggests that insight, like all explanatory models, is a narrative of the person's reality and a coping strategy to handle with the varied impact of the illness. This article argues that the assessment of insight necessarily involves value entailments, commitments and consequences. It supports a need for a broad-based approach to assess awareness, attribution and action related to mental illness and to acknowledge the role of values and value judgment in the evaluation of insight in psychosis.

  5. 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.

  6. 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.

  7. Comparing predicted yield and yield stability of willow and Miscanthus across Denmark

    DEFF Research Database (Denmark)

    Larsen, Søren; Jaiswal, Deepak; Bentsen, Niclas Scott

    2016-01-01

    was 12.1 Mg DM ha−1 yr−1 for willow and 10.2 Mg DM ha−1 yr−1 for Miscanthus. Coefficent of variation as a measure for yield stability was poorest on the sandy soils of northern and western Jutland and the year-to-year variation in yield was greatest on these soils. Willow was predicted to outyield...... Miscanthus on poor, sandy soils whereas Miscanthus was higher yielding on clay-rich soils. The major driver of yield in both crops was variation in soil moisture, with radiation and precipitation exerting less influence. This is the first time these two major feedstocks for northern Europe have been compared....... The semi-mechanistic crop model BioCro was used to simulate the production of both short rotation coppice (SRC) willow and Miscanthus across Denmark. Predictions were made from high spatial resolution soil data and weather records across this area for 1990-2010. The potential average, rain-fed mean yield...

  8. 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.

  9. 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.

  10. 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

  11. Agent-Based Modeling in Systems Pharmacology.

    Science.gov (United States)

    Cosgrove, J; Butler, J; Alden, K; Read, M; Kumar, V; Cucurull-Sanchez, L; Timmis, J; Coles, M

    2015-11-01

    Modeling and simulation (M&S) techniques provide a platform for knowledge integration and hypothesis testing to gain insights into biological systems that would not be possible a priori. Agent-based modeling (ABM) is an M&S technique that focuses on describing individual components rather than homogenous populations. This tutorial introduces ABM to systems pharmacologists, using relevant case studies to highlight how ABM-specific strengths have yielded success in the area of preclinical mechanistic modeling.

  12. The stochastic seasonal behavior of energy commodity convenience yields

    International Nuclear Information System (INIS)

    Mirantes, Andrés García; Población, Javier; Serna, Gregorio

    2013-01-01

    This paper contributes to the commodity pricing literature by consistently modeling the convenience yield with its empirically observed properties. Specifically, in this paper, we show how a four-factor model for the stochastic behavior of commodity prices, with two long- and short-term factors and two additional seasonal factors, may accommodate some of the most important empirically observed characteristics of commodity convenience yields, such as the mean reversion and stochastic seasonality. Based on this evidence, a theoretical model is presented and estimated to characterize the commodity convenience yield dynamics that are consistent with previous findings. We also show that commodity price seasonality is better estimated through convenience yields than through futures prices. - Highlights: • Energy commodity convenience yields exhibit mean reversion and stochastic seasonality. • We present a model for convenience yields accounting for their observed characteristics. • Commodity price seasonality is better estimated through convenience yields

  13. Measurements of beryllium sputtering yields at JET

    Science.gov (United States)

    Jet-Efda Contributors Stamp, M. F.; Krieger, K.; Brezinsek, S.

    2011-08-01

    The lifetime of the beryllium first wall in ITER will depend on erosion and redeposition processes. The physical sputtering yields for beryllium (both deuterium on beryllium (Be) and Be on Be) are of crucial importance since they drive the erosion process. Literature values of experimental sputtering yields show an order of magnitude variation so predictive modelling of ITER wall lifetimes has large uncertainty. We have reviewed the old beryllium yield experiments on JET and used current beryllium atomic data to produce revised beryllium sputtering yields. These experimental measurements have been compared with a simple physical sputtering model based on TRIM.SP beryllium yield data. Fair agreement is seen for beryllium yields from a clean beryllium limiter. However the yield on a beryllium divertor tile (with C/Be co-deposits) shows poor agreement at low electron temperatures indicating that the effect of the higher sputtering threshold for beryllium carbide is important.

  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. Limonene ozonolysis in the presence of nitric oxide: Gas-phase reaction products and yields

    Science.gov (United States)

    Ham, Jason E.; Harrison, Joel C.; Jackson, Stephen R.; Wells, J. R.

    2016-05-01

    The reaction products from limonene ozonolysis were investigated using the new carbonyl derivatization agent, O-tert-butylhydroxylamine hydrochloride (TBOX). With ozone (O3) as the limiting reagent, five carbonyl compounds were detected. The yields of the carbonyl compounds are discussed with and without the presence of a hydroxyl radical (OHrad) scavenger, giving insight into the influence secondary OH radicals have on limonene ozonolysis products. The observed reaction product yields for limonaketone (LimaKet), 7-hydroxyl-6-oxo-3-(prop-1-en-2-yl)heptanal (7H6O), and 2-acetyl-5-oxohexanal (2A5O) were unchanged suggesting OHrad generated by the limonene + O3 reaction does not contribute to their formation. The molar yields of 3-isopropenyl-6-oxo-heptanal (IPOH) and 3-acetyl-6-oxoheptanal (3A6O) decreased by 68% and >95%; respectively, when OHrad was removed. This suggests that OHrad radicals significantly impact the formation of these products. Nitric oxide (NO) did not significantly affect the molar yields of limonaketone or IPOH. However, NO (20 ppb) considerably decreased the molar reaction product yields of 7H6O (62%), 2A5O (63%), and 3A6O (47%), suggesting NO reacted with peroxyl intermediates, generated during limonene ozonolysis, to form other carbonyls (not detected) or organic nitrates. These studies give insight into the transformation of limonene and its reaction products that can lead to indoor exposures.

  16. Weed management through herbicide application in direct-seeded rice and yield modeling by artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Ghosh, D.; Singh, U.P.; Ray, K.; Das, A.

    2016-11-01

    In direct seeded rice (DSR) cultivation, weed is the major constraint mainly due to absence of puddling in field. The yield loss due to weed interference is huge, may be up to 100%. In this perspective, the present experiment was conducted to study the efficacy of selected herbicides, and to predict the rice yield using artificial neural network (ANN) models. The dry weight and density of weeds were recorded at different growth stages and consequently herbicidal efficacy was evaluated. Experimental results revealed that pre-emergence (PRE) herbicide effectively controlled the germination of grassy weeds. Application bispyribac-sodium as post-emergence (POST) following PRE herbicides (clomazone or pendimethalin) or as tank-mixture with clomazone effectively reduced the density and biomass accumulation of diverse weed flora in DSR. Herbicidal treatments improved the plant height, yield attributes and grain yield (2.7 to 5.5 times) over weedy check. The sensitivity of the best ANN model clearly depicts that the weed control index (WCI) of herbicides was most important than their weed control efficiency (WCE). Besides, the early control of weeds is a better prescription to improve rice yield. Differences in sensitivity values of WCI and WCE across the crop growth stages also suggest that at 15, 30 and 60 days after sowing, herbicides most effectively controlled sedges, broad leaves and grasses, respectively. Based on the grain yield and herbicidal WCE, it can be concluded that the combined application of pendimethalin or clomazone as PRE followed by bispyribac-sodium as POST or tank-mixture of clomazone + bispyribac sodium can effectively control different weed flushes throughout the crop growth period in DSR. (Author)

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

    Directory of Open Access Journals (Sweden)

    Khanchoul Kamel

    2014-01-01

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

  18. 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.

  19. 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.

  20. A Mixed Application of Geographically Weighted Regression and Unsupervised Classification for Analyzing Latex Yield Variability in Yunnan, China

    Directory of Open Access Journals (Sweden)

    Oh Seok Kim

    2017-05-01

    Full Text Available This paper introduces a mixed method approach for analyzing the determinants of natural latex yields and the associated spatial variations and identifying the most suitable regions for producing latex. Geographically Weighted Regressions (GWR and Iterative Self-Organizing Data Analysis Technique (ISODATA are jointly applied to the georeferenced data points collected from the rubber plantations in Xishuangbanna (in Yunnan province, south China and other remotely-sensed spatial data. According to the GWR models, Age of rubber tree, Percent of clay in soil, Elevation, Solar radiation, Population, Distance from road, Distance from stream, Precipitation, and Mean temperature turn out statistically significant, indicating that these are the major determinants shaping latex yields at the prefecture level. However, the signs and magnitudes of the parameter estimates at the aggregate level are different from those at the lower spatial level, and the differences are due to diverse reasons. The ISODATA classifies the landscape into three categories: high, medium, and low potential yields. The map reveals that Mengla County has the majority of land with high potential yield, while Jinghong City and Menghai County show lower potential yield. In short, the mixed method can offer a means of providing greater insights in the prediction of agricultural production.

  1. Comparison of thermal cracking and hydro-cracking yield distributions

    Energy Technology Data Exchange (ETDEWEB)

    Romero, S.; Sayles, S. [KBC Advanced Technologies Inc., Houston, TX (United States)

    2009-07-01

    Operators of bitumen upgraders are faced with the challenge of obtaining maximum performance from existing equipment whose performance is already pushed to the limits. The main constraint is the primary upgrader processes, notably coking and hydrocracking. Under the current economic conditions, funding for new equipment is difficult. However, changes can be made to optimize unit performance by better understanding the basic kinetics in thermal cracking and hydrocracking. This paper reviewed the yield distribution differences between thermal cracking and hydrocracking to provide insight into the basic components of operational changes. The objective was to compare yields, product quality distributions and the elemental balances. The opportunities to increase production and improve performance were then analyzed quantitatively within the existing unit equipment limits. tabs., figs.

  2. Fluorescence Quantum Yield Measurements of Fluorescent Proteins: A Laboratory Experiment for a Biochemistry or Molecular Biophysics Laboratory Course

    Science.gov (United States)

    Wall, Kathryn P.; Dillon, Rebecca; Knowles, Michelle K.

    2015-01-01

    Fluorescent proteins are commonly used in cell biology to assess where proteins are within a cell as a function of time and provide insight into intracellular protein function. However, the usefulness of a fluorescent protein depends directly on the quantum yield. The quantum yield relates the efficiency at which a fluorescent molecule converts…

  3. 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.

  4. 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

  5. Soil Moisture Anomaly as Predictor of Crop Yield Deviation in Germany

    Science.gov (United States)

    Peichl, Michael; Thober, Stephan; Schwarze, Reimund; Meyer, Volker; Samaniego, Luis

    2016-04-01

    Natural hazards, such as droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany (COPA-COGECA 2003). Predicting crop yields allows to economize the mitigation of risks of weather extremes. Economic approaches for quantifying agricultural impacts of natural hazards mainly rely on temperature and related concepts. For instance extreme heat over the growing season is considered as best predictor of corn yield (Auffhammer and Schlenker 2014). However, those measures are only able to provide a proxy for the available water content in the root zone that ultimately determines plant growth and eventually crop yield. The aim of this paper is to analyse whether soil moisture has a causal effect on crop yield that can be exploited in improving adaptation measures. For this purpose, reduced form fixed effect panel models are developed with yield as dependent variable for both winter wheat and silo maize crops. The explanatory variables used are soil moisture anomalies, precipitation and temperature. The latter two are included to estimate the current state of the water balance. On the contrary, soil moisture provides an integrated signal over several months. It is also the primary source of water supply for plant growth. For each crop a single model is estimated for every month within the growing period to study the variation of the effects over time. Yield data is available for Germany as a whole on the level of administrative districts from 1990 to 2010. Station data by the German Weather Service are obtained for precipitation and temperature and are aggregated to the same spatial units. Simulated soil moisture computed by the mesoscale Hydrologic Model (mHM, www.ufz.de/mhm) is transformed into Soil Moisture Index (SMI), which represents the monthly soil water quantile and hence accounts directly for the water content available to plants. The results

  6. 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)

  7. 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.

  8. 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.)

  9. 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.

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    2007-01-01

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

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. Dimensions of insight in schizophrenia: Exploratory factor analysis of items from multiple self- and interviewer-rated measures of insight.

    Science.gov (United States)

    Konsztowicz, Susanna; Schmitz, Norbert; Lepage, Martin

    2018-03-10

    Insight in schizophrenia is regarded as a multidimensional construct that comprises aspects such as awareness of the disorder and recognition of the need for treatment. The proposed number of underlying dimensions of insight is variable in the literature. In an effort to identify a range of existing dimensions of insight, we conducted a factor analysis on combined items from multiple measures of insight. We recruited 165 participants with enduring schizophrenia (treated for >3years). Exploratory factor analysis was conducted on itemized scores from two interviewer-rated measures of insight: the Schedule for the Assessment of Insight-Expanded and the abbreviated Scale to assess Unawareness of Mental Disorder; and two self-report measures: the Birchwood Insight Scale and the Beck Cognitive Insight Scale. A five-factor solution was selected as the best-fitting model, with the following dimensions of insight: 1) awareness of illness and the need for treatment; 2) awareness and attribution of symptoms and consequences; 3) self-certainty; 4) self-reflectiveness for objectivity and fallibility; and 5) self-reflectiveness for errors in reasoning and openness to feedback. Insight in schizophrenia is a multidimensional construct comprised of distinct clinical and cognitive domains of awareness. Multiple measures of insight, both clinician- and self-rated, are needed to capture all of the existing dimensions of insight. Future exploration of associations between the various dimensions and their potential determinants will facilitate the development of clinically useful models of insight and effective interventions to improve outcome. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. 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

  19. Nut crop yield records show that budbreak-based chilling requirements may not reflect yield decline chill thresholds

    Science.gov (United States)

    Pope, Katherine S.; Dose, Volker; Da Silva, David; Brown, Patrick H.; DeJong, Theodore M.

    2015-06-01

    Warming winters due to climate change may critically affect temperate tree species. Insufficiently cold winters are thought to result in fewer viable flower buds and the subsequent development of fewer fruits or nuts, decreasing the yield of an orchard or fecundity of a species. The best existing approximation for a threshold of sufficient cold accumulation, the "chilling requirement" of a species or variety, has been quantified by manipulating or modeling the conditions that result in dormant bud breaking. However, the physiological processes that affect budbreak are not the same as those that determine yield. This study sought to test whether budbreak-based chilling thresholds can reasonably approximate the thresholds that affect yield, particularly regarding the potential impacts of climate change on temperate tree crop yields. County-wide yield records for almond ( Prunus dulcis), pistachio ( Pistacia vera), and walnut ( Juglans regia) in the Central Valley of California were compared with 50 years of weather records. Bayesian nonparametric function estimation was used to model yield potentials at varying amounts of chill accumulation. In almonds, average yields occurred when chill accumulation was close to the budbreak-based chilling requirement. However, in the other two crops, pistachios and walnuts, the best previous estimate of the budbreak-based chilling requirements was 19-32 % higher than the chilling accumulations associated with average or above average yields. This research indicates that physiological processes beyond requirements for budbreak should be considered when estimating chill accumulation thresholds of yield decline and potential impacts of climate change.

  20. Status of fission yield data

    International Nuclear Information System (INIS)

    England, T.R.; Blachot, J.

    1988-01-01

    In this paper we summarize the current status of the recent US evaluation for 34 fissioning nuclides at one or more neutron incident energies and for spontaneous fission. Currently there are 50 yields sets, and for each we have independent and cumulative yields and uncertainties for approximately 1100 fission products. When finalized the recommended data will become part of Version VI of the US ENDF/B. Other major evaluations in progress that are included in a recently formed IAEA Coordinated Research Program are also summarized. In a second part we review two empirical models in use to estimate independent yields. Comparison of model estimates with measured data is presented, including a comparison with some recent data obtained from Lohengrin (Cf-249 T). 18 refs., 13 figs., 3 tabs

  1. Dynamics of hERG closure allow novel insights into hERG blocking by small molecules.

    Science.gov (United States)

    Schmidtke, Peter; Ciantar, Marine; Theret, Isabelle; Ducrot, Pierre

    2014-08-25

    Today, drug discovery routinely uses experimental assays to determine very early if a lead compound can yield certain types of off-target activity. Among such off targets is hERG. The ion channel plays a primordial role in membrane repolarization and altering its activity can cause severe heart arrhythmia and sudden death. Despite routine tests for hERG activity, rather little information is available for helping medicinal chemists and molecular modelers to rationally circumvent hERG activity. In this article novel insights into the dynamics of hERG channel closure are described. Notably, helical pairwise closure movements have been observed. Implications and relations to hERG inactivation are presented. Based on these dynamics novel insights on hERG blocker placement are presented, compared to literature, and discussed. Last, new evidence for horizontal ligand positioning is shown in light of former studies on hERG blockers.

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

    Science.gov (United States)

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

    2017-03-24

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

  3. 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.

  4. 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.

  5. 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...

  6. 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.

  7. 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

  8. Ethiopian Wheat Yield and Yield Gap Estimation: A Spatial Small Area Integrated Data Approach

    Science.gov (United States)

    Mann, M.; Warner, J.

    2015-12-01

    Despite the collection of routine annual agricultural surveys and significant advances in GIS and remote sensing products, little econometric research has been undertaken in predicting developing nation's agricultural yields. In this paper, we explore the determinants of wheat output per hectare in Ethiopia during the 2011-2013 Meher crop seasons aggregated to the woreda administrative area. Using a panel data approach, combining national agricultural field surveys with relevant GIS and remote sensing products, the model explains nearly 40% of the total variation in wheat output per hectare across the country. The model also identifies specific contributors to wheat yields that include farm management techniques (eg. area planted, improved seed, fertilizer, irrigation), weather (eg. rainfall), water availability (vegetation and moisture deficit indexes) and policy intervention. Our findings suggest that woredas produce between 9.8 and 86.5% of their potential wheat output per hectare given their altitude, weather conditions, terrain, and plant health. At the median, Amhara, Oromiya, SNNP, and Tigray produce 48.6, 51.5, 49.7, and 61.3% of their local attainable yields, respectively. This research has a broad range of applications, especially from a public policy perspective: identifying causes of yield fluctuations, remotely evaluating larger agricultural intervention packages, and analyzing relative yield potential. Overall, the combination of field surveys with spatial data can be used to identify management priorities for improving production at a variety of administrative levels.

  9. 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.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  12. 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

  13. 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

  14. Yield stress of alumina-zirconia suspensions

    International Nuclear Information System (INIS)

    Ramakrishnan, V.; Pradip; Malghan, S.G.

    1996-01-01

    The yield stress of concentrated suspensions of alumina, zirconia, and mixed alumina-zirconia powders was measured by the vane technique as a function of solids loading, relative amounts of alumina and zirconia, and pH. At the isoelectric point (IEP), the yield stress varied as the fourth power of the solids loading. The relative ratio of alumina and zirconia particles was important in determining the yield stress of the suspension at the IEP. The yield stress of single and mixed suspensions showed a marked variation with pH. The maximum value occurred at or near the IEP of the suspension. The effect of electrical double-layer forces on the yield stress can be described on the basis of the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory. A normalized yield stress--that is, the ratio of the yield stress at a given pH to the yield stress at the IEP predicted by this model--showed good correlation with experimental data

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

    Directory of Open Access Journals (Sweden)

    F Mondani

    2015-09-01

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

  16. 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.

  17. Multi-omics analysis provides insight to the Ignicoccus hospitalis-Nanoarchaeum equitans association.

    Science.gov (United States)

    Rawle, Rachel A; Hamerly, Timothy; Tripet, Brian P; Giannone, Richard J; Wurch, Louie; Hettich, Robert L; Podar, Mircea; Copié, Valerie; Bothner, Brian

    2017-09-01

    Studies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted 'omics' analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea. We jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized using interaction maps generated using STRING. Key findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis-N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans. This multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis-N. equitans association. Our study applies statistical and visualization techniques to a mixed-source omics dataset to yield a more global insight into a complex system, that was not readily discernable from separate omics studies. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Rice yield estimation with multi-temporal Radarsat-2 data

    Science.gov (United States)

    Chen, Chi-Farn; Son, Nguyen-Thanh; Chen, Cheng-Ru

    2015-04-01

    Rice is the most important food crop in Taiwan. Monitoring rice crop yield is thus crucial for agronomic planners to formulate successful strategies to address national food security and rice grain export issues. However, there is a real challenge for this monitoring purpose because the size of rice fields in Taiwan was generally small and fragmented, and the cropping calendar was also different from region to region. Thus, satellite-based estimation of rice crop yield requires the data that have sufficient spatial and temporal resolutions. This study aimed to develop models to estimate rice crop yield from multi-temporal Radarsat-2 data (5 m resolution). Data processing were carried out for the first rice cropping season from February to July in 2014 in the western part of Taiwan, consisting of four main steps: (1) constructing time-series backscattering coefficient data, (2) spatiotemporal noise filtering of the time-series data, (3) establishment of crop yield models using the time-series backscattering coefficients and in-situ measured yield data, and (4) model validation using field data and government's yield statistics. The results indicated that backscattering behavior varied from region to region due to changes in cultural practices and cropping calendars. The highest correlation coefficient (R2 > 0.8) was obtained at the ripening period. The robustness of the established models was evaluated by comparisons between the estimated yields and in-situ measured yield data showed satisfactory results, with the root mean squared error (RMSE) smaller than 10%. Such results were reaffirmed by the correlation analysis between the estimated yields and government's rice yield statistics (R2 > 0.8). This study demonstrates advantages of using multi-temporal Radarsat-2 backscattering data for estimating rice crop yields in Taiwan prior to the harvesting period, and thus the methods were proposed for rice yield monitoring in other regions.

  19. 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...

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. Accelerated yield learning in agressive lithography

    Science.gov (United States)

    Monahan, Kevin M.; Ashkenaz, Scott M.; Chen, Xing; Lord, Patrick J.; Merrill, Mark A.; Quattrini, Rich; Wiley, James N.

    2000-06-01

    As exposure wavelengths decrease from 248 nm to 193, 157, and even 13 nm (EUV), small process defects can cause collapse of the lithographic process window near the limits of resolution, particularly for the gate and contact structures in high- performance devices. Such sensitivity poses a challenge for lithography process module control. In this work, we show that yield loss can be caused by a combination of macro, micro, CD, and overlay defects. A defect is defined as any yield- affecting process variation. Each defect, regardless of cause, is assumed to have a specific 'kill potential.' The accuracy of the lithographic yield model can be improved by identifying those defects with the highest kill potential or, more importantly, those that pose the highest economic risk. Such economic considerations have led us to develop a simple heuristic model for understanding sampling strategies in defect metrology and for linking metrology capability to yield and profitability.

  5. 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.

  6. 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.

  7. 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

  8. Changes in diurnal temperature range and national cereal yields

    Energy Technology Data Exchange (ETDEWEB)

    Lobell, D

    2007-04-26

    Models of yield responses to temperature change have often considered only changes in average temperature (Tavg), with the implicit assumption that changes in the diurnal temperature range (DTR) can safely be ignored. The goal of this study was to evaluate this assumption using a combination of historical datasets and climate model projections. Data on national crop yields for 1961-2002 in the 10 leading producers of wheat, rice, and maize were combined with datasets on climate and crop locations to evaluate the empirical relationships between Tavg, DTR, and crop yields. In several rice and maize growing regions, including the two major nations for each crop, there was a clear negative response of yields to increased DTR. This finding reflects a nonlinear response of yields to temperature, which likely results from greater water and heat stress during hot days. In many other cases, the effects of DTR were not statistically significant, in part because correlations of DTR with other climate variables and the relatively short length of the time series resulted in wide confidence intervals for the estimates. To evaluate whether future changes in DTR are relevant to crop impact assessments, yield responses to projected changes in Tavg and DTR by 2046-2065 from 11 climate models were estimated. The mean climate model projections indicated an increase in DTR in most seasons and locations where wheat is grown, mixed projections for maize, and a general decrease in DTR for rice. These mean projections were associated with wide ranges that included zero in nearly all cases. The estimated impacts of DTR changes on yields were generally small (<5% change in yields) relative to the consistently negative impact of projected warming of Tavg. However, DTR changes did significantly affect yield responses in several cases, such as in reducing US maize yields and increasing India rice yields. Because DTR projections tend to be positively correlated with Tavg, estimates of yields

  9. 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.

  10. 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

  11. Spatial Sampling of Weather Data for Regional Crop Yield Simulations

    Science.gov (United States)

    Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian; hide

    2016-01-01

    Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50, 100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management

  12. 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.

  13. 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

  14. Differential metabolite profiles during fruit development in high-yielding oil palm mesocarp.

    Directory of Open Access Journals (Sweden)

    Huey Fang Teh

    Full Text Available To better understand lipid biosynthesis in oil palm mesocarp, in particular the differences in gene regulation leading to and including de novo fatty acid biosynthesis, a multi-platform metabolomics technology was used to profile mesocarp metabolites during six critical stages of fruit development in comparatively high- and low-yielding oil palm populations. Significantly higher amino acid levels preceding lipid biosynthesis and nucleosides during lipid biosynthesis were observed in a higher yielding commercial palm population. Levels of metabolites involved in glycolysis revealed interesting divergence of flux towards glycerol-3-phosphate, while carbon utilization differences in the TCA cycle were proven by an increase in malic acid/citric acid ratio. Apart from insights into the regulation of enhanced lipid production in oil palm, these results provide potentially useful metabolite yield markers and genes of interest for use in breeding programmes.

  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. [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.

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

    Directory of Open Access Journals (Sweden)

    Javier Hernandez

    2015-02-01

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

  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. 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)

  20. 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.

  1. Yield surface evolution for columnar ice

    Science.gov (United States)

    Zhou, Zhiwei; Ma, Wei; Zhang, Shujuan; Mu, Yanhu; Zhao, Shunpin; Li, Guoyu

    A series of triaxial compression tests, which has capable of measuring the volumetric strain of the sample, were conducted on columnar ice. A new testing approach of probing the experimental yield surface was performed from a single sample in order to investigate yield and hardening behaviors of the columnar ice under complex stress states. Based on the characteristic of the volumetric strain, a new method of defined the multiaxial yield strengths of the columnar ice is proposed. The experimental yield surface remains elliptical shape in the stress space of effective stress versus mean stress. The effect of temperature, loading rate and loading path in the initial yield surface and deformation properties of the columnar ice were also studied. Subsequent yield surfaces of the columnar ice have been explored by using uniaxial and hydrostatic paths. The evolution of the subsequent yield surface exhibits significant path-dependent characteristics. The multiaxial hardening law of the columnar ice was established experimentally. A phenomenological yield criterion was presented for multiaxial yield and hardening behaviors of the columnar ice. The comparisons between the theoretical and measured results indicate that this current model is capable of giving a reasonable prediction for the multiaxial yield and post-yield properties of the columnar ice subjected to different temperature, loading rate and path conditions.

  2. Simulating potential growth and yield of oil palm with PALMSIM

    NARCIS (Netherlands)

    Hoffmann, M.P.; Vera, A.C.; Wijk, van M.T.; Giller, K.E.; Oberthur, R.; Donough, C.; Whitbread, A.M.; Fisher, M.J.

    2014-01-01

    The growing demand for palm oil can be met by reducing the gap between potential yield and actual yield. Simulation models can quantify potential yield, and therefore indicate the scope for intensification. A relatively simple physiological approach was used to develop PALMSIM, which is a model that

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

    Science.gov (United States)

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

    2016-11-01

    Viticulture is a key socio-economic sector in Europe. Owing to the strong sensitivity of grapevines to atmospheric factors, climate change may represent an important challenge for this sector. This study analyses viticultural suitability, yield, phenology, and water and nitrogen stress indices in Europe, for present climates (1980-2005) and future (2041-2070) climate change scenarios (RCP4.5 and 8.5). The STICS crop model is coupled with climate, soil and terrain databases, also taking into account 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.

  4. Quantifying yield gaps in wheat production in Russia

    International Nuclear Information System (INIS)

    Schierhorn, Florian; Prishchepov, Alexander V; Koch, Friedrich J; Müller, Daniel; Faramarzi, Monireh

    2014-01-01

    Crop yields must increase substantially to meet the increasing demands for agricultural products. Crop yield increases are particularly important for Russia because low crop yields prevail across Russia’s widespread and fertile land resources. However, reliable data are lacking regarding the spatial distribution of potential yields in Russia, which can be used to determine yield gaps. We used a crop growth model to determine the yield potentials and yield gaps of winter and spring wheat at the provincial level across European Russia. We modeled the annual yield potentials from 1995 to 2006 with optimal nitrogen supplies for both rainfed and irrigated conditions. Overall, the results suggest yield gaps of 1.51–2.10 t ha −1 , or 44–52% of the yield potential under rainfed conditions. Under irrigated conditions, yield gaps of 3.14–3.30 t ha −1 , or 62–63% of the yield potential, were observed. However, recurring droughts cause large fluctuations in yield potentials under rainfed conditions, even when the nitrogen supply is optimal, particularly in the highly fertile black soil areas of southern European Russia. The highest yield gaps (up to 4 t ha −1 ) under irrigated conditions were detected in the steppe areas in southeastern European Russia along the border of Kazakhstan. Improving the nutrient and water supply and using crop breeds that are adapted to the frequent drought conditions are important for reducing yield gaps in European Russia. Our regional assessment helps inform policy and agricultural investors and prioritize research that aims to increase crop production in this important region for global agricultural markets. (letter)

  5. Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection

    Directory of Open Access Journals (Sweden)

    Oscar Rojas

    2013-04-01

    Full Text Available Low resolution satellite imagery has been extensively used for crop monitoring and yield forecasting for over 30 years and plays an important role in a growing number of operational systems. The combination of their high temporal frequency with their extended geographical coverage generally associated with low costs per area unit makes these images a convenient choice at both national and regional scales. Several qualitative and quantitative approaches can be clearly distinguished, going from the use of low resolution satellite imagery as the main predictor of final crop yield to complex crop growth models where remote sensing-derived indicators play different roles, depending on the nature of the model and on the availability of data measured on the ground. Vegetation performance anomaly detection with low resolution images continues to be a fundamental component of early warning and drought monitoring systems at the regional scale. For applications at more detailed scales, the limitations created by the mixed nature of low resolution pixels are being progressively reduced by the higher resolution offered by new sensors, while the continuity of existing systems remains crucial for ensuring the availability of long time series as needed by the majority of the yield prediction methods used today.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. Modeling Photodetachment from HO2- Using the pd Case of the Generalized Mixed Character Molecular Orbital Model

    Science.gov (United States)

    Blackstone, Christopher C.; Sanov, Andrei

    2016-06-01

    Using the generalized model for photodetachment of electrons from mixed-character molecular orbitals, we gain insight into the nature of the HOMO of HO2- by treating it as a coherent superpostion of one p- and one d-type atomic orbital. Fitting the pd model function to the ab initio calculated HOMO of HO2- yields a fractional d-character, γp, of 0.979. The modeled curve of the anisotropy parameter, β, as a function of electron kinetic energy for a pd-type mixed character orbital is matched to the experimental data.

  15. Yield performance and stability of CMS-based triticale hybrids.

    Science.gov (United States)

    Mühleisen, Jonathan; Piepho, Hans-Peter; Maurer, Hans Peter; Reif, Jochen Christoph

    2015-02-01

    CMS-based triticale hybrids showed only marginal midparent heterosis for grain yield and lower dynamic yield stability compared to inbred lines. Hybrids of triticale (×Triticosecale Wittmack) are expected to possess outstanding yield performance and increased dynamic yield stability. The objectives of the present study were to (1) examine the optimum choice of the biometrical model to compare yield stability of hybrids versus lines, (2) investigate whether hybrids exhibit a more pronounced grain yield performance and yield stability, and (3) study optimal strategies to predict yield stability of hybrids. Thirteen female and seven male parental lines and their 91 factorial hybrids as well as 30 commercial lines were evaluated for grain yield in up to 20 environments. Hybrids were produced using a cytoplasmic male sterility (CMS)-inducing cytoplasm that originated from Triticumtimopheevii Zhuk. We found that the choice of the biometrical model can cause contrasting results and concluded that a group-by-environment interaction term should be added to the model when estimating stability variance of hybrids and lines. midparent heterosis for grain yield was on average 3 % with a range from -15.0 to 11.5 %. No hybrid outperformed the best inbred line. Hybrids had, on average, lower dynamic yield stability compared to the inbred lines. Grain yield performance of hybrids could be predicted based on midparent values and general combining ability (GCA)-predicted values. In contrast, stability variance of hybrids could be predicted only based on GCA-predicted values. We speculated that negative effects of the used CMS cytoplasm might be the reason for the low performance and yield stability of the hybrids. For this purpose a detailed study on the reasons for the drawback of the currently existing CMS system in triticale is urgently required comprising also the search of potentially alternative hybridization systems.

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

    International Nuclear Information System (INIS)

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

    2003-01-01

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

  17. Search for B {yields} K{ell}{sup +}{ell}{sup -} and B {yields} K*(892){ell}{sup +}{ell}{sup -}

    Energy Technology Data Exchange (ETDEWEB)

    Aubert, B.

    2004-02-12

    The authors present preliminary results from a search for the flavor-changing neutral current decays B {yields} K{ell}{sup +}{ell}{sup -} and B {yields} K*(892){ell}{sup +}{ell}{sup -} using a sample of 22.7 x 10{sup 6} {Upsilon}(4S) {yields} B{bar B} decays collected with the BABAR detector at the PEP-II B Factory. They have reconstructed the following final states: B{sup +} {yields} K{sup +}{ell}{sup +}{ell}{sup -}, B{sup 0} {yields} K{sup 0}{ell}{sup +}{ell}{sup -} (K{sub s}{sup 0} {yields} {pi}{sup +} {pi}{sup -}), B{sup +} {yields} K*{sup +}{ell}{sup +}{ell}{sup -} (K*{sup +} {yields} K{sub s}{sup 0}{pi}{sup +}), and B{sup 0} {yields} K*{sup 0}{ell}{sup +}{ell}{sup -} (K*{sup 0} {yields} K{sup +}{pi}{sup -}), where {ell}{sup +}{ell}{sup -} is either an e{sup +}e{sup -} or {mu}{sup +}{mu}{sup -} pair. They obtain the 90% C.L. upper limits {Beta}(B {yields} K{ell}{sup +}{ell}{sup -}) < 0.6 x 10{sup -6} and {Beta}(B {yields} K*{ell}{sup +}{ell}{sup -}) < 2.5 x 10{sup -6}, close to the Standard Model predictions for these branching fractions.

  18. Measurement of fluorophore concentrations and fluorescence quantum yield in tissue-simulating phantoms using three diffusion models of steady-state spatially resolved fluorescence

    Energy Technology Data Exchange (ETDEWEB)

    Diamond, Kevin R; Farrell, Thomas J; Patterson, Michael S [Department of Medical Physics, Juravinski Cancer Centre and McMaster University, 699 Concession Street, Hamilton, Ontario L8V 5C2 (Canada)

    2003-12-21

    Steady-state diffusion theory models of fluorescence in tissue have been investigated for recovering fluorophore concentrations and fluorescence quantum yield. Spatially resolved fluorescence, excitation and emission reflectance were calculated by diffusion theory and Monte Carlo simulations, and measured using a multi-fibre probe on tissue-simulating phantoms containing either aluminium phthalocyanine tetrasulfonate (AlPcS{sub 4}), Photofrin or meso-tetra-(4-sulfonatophenyl)-porphine dihydrochloride (TPPS{sub 4}). The accuracy of the fluorophore concentration and fluorescence quantum yield recovered by three different models of spatially resolved fluorescence were compared. The models were based on: (a) weighted difference of the excitation and emission reflectance, (b) fluorescence due to a point excitation source or (c) fluorescence due to a pencil beam excitation source. When literature values for the fluorescence quantum yield were used for each of the fluorophores, the fluorophore absorption coefficient (and hence concentration) at the excitation wavelengthwas recovered with a root-mean-square accuracy of 11.4% using the point source model of fluorescence and 8.0% using the more complicated pencil beam excitation model. The accuracy was calculated over a broad range of optical properties and fluorophore concentrations. The weighted difference of reflectance model performed poorly, with a root-mean-square error in concentration of about 50%. Monte Carlo simulations suggest that there are some situations where the weighted difference of reflectance is as accurate as the other two models, although this was not confirmed experimentally. Estimates of the fluorescence quantum yield in multiple scattering media were also made by determining independently from the fitted absorption spectrum and applying the various diffusion theory models. The fluorescence quantum yields for AlPcS{sub 4} and TPPS{sub 4} were calculated to be 0.59 {+-} 0.03 and 0.121 {+-} 0

  19. Measurement of fluorophore concentrations and fluorescence quantum yield in tissue-simulating phantoms using three diffusion models of steady-state spatially resolved fluorescence

    International Nuclear Information System (INIS)

    Diamond, Kevin R; Farrell, Thomas J; Patterson, Michael S

    2003-01-01

    Steady-state diffusion theory models of fluorescence in tissue have been investigated for recovering fluorophore concentrations and fluorescence quantum yield. Spatially resolved fluorescence, excitation and emission reflectance were calculated by diffusion theory and Monte Carlo simulations, and measured using a multi-fibre probe on tissue-simulating phantoms containing either aluminium phthalocyanine tetrasulfonate (AlPcS 4 ), Photofrin or meso-tetra-(4-sulfonatophenyl)-porphine dihydrochloride (TPPS 4 ). The accuracy of the fluorophore concentration and fluorescence quantum yield recovered by three different models of spatially resolved fluorescence were compared. The models were based on: (a) weighted difference of the excitation and emission reflectance, (b) fluorescence due to a point excitation source or (c) fluorescence due to a pencil beam excitation source. When literature values for the fluorescence quantum yield were used for each of the fluorophores, the fluorophore absorption coefficient (and hence concentration) at the excitation wavelengthwas recovered with a root-mean-square accuracy of 11.4% using the point source model of fluorescence and 8.0% using the more complicated pencil beam excitation model. The accuracy was calculated over a broad range of optical properties and fluorophore concentrations. The weighted difference of reflectance model performed poorly, with a root-mean-square error in concentration of about 50%. Monte Carlo simulations suggest that there are some situations where the weighted difference of reflectance is as accurate as the other two models, although this was not confirmed experimentally. Estimates of the fluorescence quantum yield in multiple scattering media were also made by determining independently from the fitted absorption spectrum and applying the various diffusion theory models. The fluorescence quantum yields for AlPcS 4 and TPPS 4 were calculated to be 0.59 ± 0.03 and 0.121 ± 0.001 respectively using the point

  20. Insights from simulations of star formation

    International Nuclear Information System (INIS)

    Larson, Richard B

    2007-01-01

    Although the basic physics of star formation is classical, numerical simulations have yielded essential insights into how stars form. They show that star formation is a highly nonuniform runaway process characterized by the emergence of nearly singular peaks in density, followed by the accretional growth of embryo stars that form at these density peaks. Circumstellar discs often form from the gas being accreted by the forming stars, and accretion from these discs may be episodic, driven by gravitational instabilities or by protostellar interactions. Star-forming clouds typically develop filamentary structures, which may, along with the thermal physics, play an important role in the origin of stellar masses because of the sensitivity of filament fragmentation to temperature variations. Simulations of the formation of star clusters show that the most massive stars form by continuing accretion in the dense cluster cores, and this again is a runaway process that couples star formation and cluster formation. Star-forming clouds also tend to develop hierarchical structures, and smaller groups of forming objects tend to merge into progressively larger ones, a generic feature of self-gravitating systems that is common to star formation and galaxy formation. Because of the large range of scales and the complex dynamics involved, analytic models cannot adequately describe many aspects of star formation, and detailed numerical simulations are needed to advance our understanding of the subject. 'The purpose of computing is insight, not numbers.' Richard W Hamming, in Numerical Methods for Scientists and Engineers (1962) 'There are more things in heaven and earth, Horatio, than are dreamt of in your philosophy.' William Shakespeare, in Hamlet, Prince of Denmark (1604) (key issues review)

  1. Insights from simulations of star formation

    Energy Technology Data Exchange (ETDEWEB)

    Larson, Richard B [Department of Astronomy, Yale University, Box 208101, New Haven, CT 06520-8101 (United States)

    2007-03-15

    Although the basic physics of star formation is classical, numerical simulations have yielded essential insights into how stars form. They show that star formation is a highly nonuniform runaway process characterized by the emergence of nearly singular peaks in density, followed by the accretional growth of embryo stars that form at these density peaks. Circumstellar discs often form from the gas being accreted by the forming stars, and accretion from these discs may be episodic, driven by gravitational instabilities or by protostellar interactions. Star-forming clouds typically develop filamentary structures, which may, along with the thermal physics, play an important role in the origin of stellar masses because of the sensitivity of filament fragmentation to temperature variations. Simulations of the formation of star clusters show that the most massive stars form by continuing accretion in the dense cluster cores, and this again is a runaway process that couples star formation and cluster formation. Star-forming clouds also tend to develop hierarchical structures, and smaller groups of forming objects tend to merge into progressively larger ones, a generic feature of self-gravitating systems that is common to star formation and galaxy formation. Because of the large range of scales and the complex dynamics involved, analytic models cannot adequately describe many aspects of star formation, and detailed numerical simulations are needed to advance our understanding of the subject. 'The purpose of computing is insight, not numbers.' Richard W Hamming, in Numerical Methods for Scientists and Engineers (1962) 'There are more things in heaven and earth, Horatio, than are dreamt of in your philosophy.' William Shakespeare, in Hamlet, Prince of Denmark (1604) (key issues review)

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

    Directory of Open Access Journals (Sweden)

    Luciana Miura Sugawara Berka

    2003-01-01

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

  3. simulating rice yields under climate change scenarios using

    African Journals Online (AJOL)

    Prof. Adipala Ekwamu

    The effects of climate change on rice production and yield cannot be overlooked in finding measures to increase production and yield. The CERES-Rice (Ver. 4.0) model was calibrated and evaluated for use in simulating rice yields under different climate change scenarios in Ghana using data from the Anum Valley ...

  4. 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.

  5. Negative impacts of climate change on cereal yields: statistical evidence from France

    Science.gov (United States)

    Gammans, Matthew; Mérel, Pierre; Ortiz-Bobea, Ariel

    2017-05-01

    In several world regions, climate change is predicted to negatively affect crop productivity. The recent statistical yield literature emphasizes the importance of flexibly accounting for the distribution of growing-season temperature to better represent the effects of warming on crop yields. We estimate a flexible statistical yield model using a long panel from France to investigate the impacts of temperature and precipitation changes on wheat and barley yields. Winter varieties appear sensitive to extreme cold after planting. All yields respond negatively to an increase in spring-summer temperatures and are a decreasing function of precipitation about historical precipitation levels. Crop yields are predicted to be negatively affected by climate change under a wide range of climate models and emissions scenarios. Under warming scenario RCP8.5 and holding growing areas and technology constant, our model ensemble predicts a 21.0% decline in winter wheat yield, a 17.3% decline in winter barley yield, and a 33.6% decline in spring barley yield by the end of the century. Uncertainty from climate projections dominates uncertainty from the statistical model. Finally, our model predicts that continuing technology trends would counterbalance most of the effects of climate change.

  6. Insight and suicidality in psychosis: A cross-sectional study.

    Science.gov (United States)

    Massons, Carmen; Lopez-Morinigo, Javier-David; Pousa, Esther; Ruiz, Ada; Ochoa, Susana; Usall, Judith; Nieto, Lourdes; Cobo, Jesus; David, Anthony S; Dutta, Rina

    2017-06-01

    We aimed to test whether specific insight dimensions are associated with suicidality in patients with psychotic disorders. 143 patients with schizophrenia spectrum disorders were recruited. Suicidality was assessed by item 8 of the Calgary Depression Scale for Schizophrenia (CDSS). Insight was measured by the Scale of Unawareness of Mental Disorder (SUMD) and the Markova and Berrios Insight Scale. Bivariate analyses and multivariable logistic regression models were conducted. Those subjects aware of having a mental illness and its social consequences had higher scores on suicidality than those with poor insight. Awareness of the need for treatment was not linked with suicidality. The Markova and Berrios Insight scale total score and two specific domains (awareness of "disturbed thinking and loss of control over the situation" and "having a vague feeling that something is wrong") were related to suicidality. However, no insight dimensions survived the multivariable regression model, which found depression and previous suicidal behaviour to predict suicidality. Suicidality in psychosis was linked with some insight dimensions: awareness of mental illness and awareness of social consequences, but not compliance. Depression and previous suicidal behaviour mediated the associations with insight; thus, predicting suicidality. Copyright © 2017. Published by Elsevier B.V.

  7. 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.

  8. Yielding physically-interpretable emulators - A Sparse PCA approach

    Science.gov (United States)

    Galelli, S.; Alsahaf, A.; Giuliani, M.; Castelletti, A.

    2015-12-01

    Projection-based techniques, such as Principal Orthogonal Decomposition (POD), are a common approach to surrogate high-fidelity process-based models by lower order dynamic emulators. With POD, the dimensionality reduction is achieved by using observations, or 'snapshots' - generated with the high-fidelity model -, to project the entire set of input and state variables of this model onto a smaller set of basis functions that account for most of the variability in the data. While reduction efficiency and variance control of POD techniques are usually very high, the resulting emulators are structurally highly complex and can hardly be given a physically meaningful interpretation as each basis is a projection of the entire set of inputs and states. In this work, we propose a novel approach based on Sparse Principal Component Analysis (SPCA) that combines the several assets of POD methods with the potential for ex-post interpretation of the emulator structure. SPCA reduces the number of non-zero coefficients in the basis functions by identifying a sparse matrix of coefficients. While the resulting set of basis functions may retain less variance of the snapshots, the presence of a few non-zero coefficients assists in the interpretation of the underlying physical processes. The SPCA approach is tested on the reduction of a 1D hydro-ecological model (DYRESM-CAEDYM) used to describe the main ecological and hydrodynamic processes in Tono Dam, Japan. An experimental comparison against a standard POD approach shows that SPCA achieves the same accuracy in emulating a given output variable - for the same level of dimensionality reduction - while yielding better insights of the main process dynamics.

  9. Impact of urbanization on the sediment yield in tropical watershed using temporal land-use changes and a GIS-based model

    Directory of Open Access Journals (Sweden)

    Bello Al-Amin D.

    2017-09-01

    Full Text Available Abundant rainfall areas promote sediment yield at both sub-watershed and watershed scale due to soil erosion and increase siltation of river channel, but it can be curtailed through planned urbanization. The urbanization of Skudai watershed is analysed from historical and future perspective. A GIS-based model (Hydrological Simulation Programme-FORTRAN-HSPF is used to modelled sediment flow using basin-wide simulation, and the output result is utilized in evaluating sediment yield reduction due to increased urbanization by swapping multiple temporal land-use of decadent time-steps. The analysis indicates that sediment yield reduces with increase urban built-up and decrease forest and agricultural land. An estimated 12 400 tons of sediment will be reduced for every 27% increase in built-up areas under high rainfall condition and 1 490 tons at low rainfall. The sensitivity analysis of land-use classes shows that built-up, forest and barren are more sensitive to sediment yield reduction compared to wetland and agricultural land at both high and low rainfall. The result of the study suggests that increased urbanization reduced sediment yield in proportion to the rainfall condition and can be used as an alternative approach for soil conservation at watershed scale independent of climate condition.

  10. Stigma as a predictor of insight in schizophrenia.

    Science.gov (United States)

    Pruß, Linda; Wiedl, Karl Heinz; Waldorf, Manuel

    2012-07-30

    Insight in schizophrenia can be seen as a multifactorial phenomenon. Although multifactorial pathways have also been suggested for insight formation, motivational explanations have rarely been tested. The present study explores stigma as one possible determinant of a motivated lack of insight in integrated models of insight formation. It examines the contribution of socio-demographic and clinical variables, neurocognitive functions, symptoms, and stigma to the prediction of insight into illness. Patients diagnosed with schizophrenia spectrum disorders (N=111) participated in a comprehensive battery of instruments to measure insight dimensions, stigma, neurocognitive functions, symptoms, socio-demographic and clinical variables. Blockwise multiple regression analysis indicates significant association of variability in insight dimensions with gender (7%) and stigma (i. e., stereotype agreement: 5%). Our findings demonstrate an incremental validity of stigma, which indicates a motivational pathway of insight formation. This study enables better understanding of the multifactorial nature of insight, which should be considered in therapeutic interventions to improve insight. The roles of gender and neurocognitive functions in insight formation are also discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  11. 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

  12. Path Analysis of Grain Yield and Yield Components and Some Agronomic Traits in Bread Wheat

    Directory of Open Access Journals (Sweden)

    Mohsen Janmohammadi

    2014-01-01

    Full Text Available Development of new bread wheat cultivars needs efficient tools to monitor trait association in a breeding program. This investigation was aimed to characterize grain yield components and some agronomic traits related to bread wheat grain yield. The efficiency of a breeding program depends mainly on the direction of the correlation between different traits and the relative importance of each component involved in contributing to grain yield. Correlation and path analysis were carried out in 56 bread wheat genotypes grown under field conditions of Maragheh, Iran. Observations were recorded on 18 wheat traits and correlation coefficient analysis revealed grain yield was positively correlated with stem diameter, spike length, floret number, spikelet number, grain diameter, grain length and 1000 seed weight traits. According to the variance inflation factor (VIF and tolerance as multicollinearity statistics, there are inconsistent relationships among the variables and all traits could be considered as first-order variables (Model I with grain yield as the response variable due to low multicollinearity of all measured traits. In the path coefficient analysis, grain yield represented the dependent variable and the spikelet number and 1000 seed weight traits were the independent ones. Our results indicated that the number of spikelets per spikes and leaf width and 1000 seed weight traits followed by the grain length, grain diameter and grain number per spike were the traits related to higher grain yield. The above mentioned traits along with their indirect causal factors should be considered simultaneously as an effective selection criteria evolving high yielding genotype because of their direct positive contribution to grain yield.

  13. Vortex wake investigation behind a wing-flap model with jet simulations

    NARCIS (Netherlands)

    Veldhuis, L.L.M.; De Kat, R.

    2008-01-01

    To get a better insight in the effect of jets on vortex development and decay, stereo-PIV measurements were performed in a towing tank behind a flapped aircraft model. The experimental data set yields the wake vortex behavior in a range that extends from the vortex formation stage up to the

  14. Femtosecond-laser induced dynamics of CO on Ru(0001): Deep insights from a hot-electron friction model including surface motion

    Science.gov (United States)

    Scholz, Robert; Floß, Gereon; Saalfrank, Peter; Füchsel, Gernot; Lončarić, Ivor; Juaristi, J. I.

    2016-10-01

    A Langevin model accounting for all six molecular degrees of freedom is applied to femtosecond-laser induced, hot-electron driven dynamics of Ru(0001)(2 ×2 ):CO. In our molecular dynamics with electronic friction approach, a recently developed potential energy surface based on gradient-corrected density functional theory accounting for van der Waals interactions is adopted. Electronic friction due to the coupling of molecular degrees of freedom to electron-hole pairs in the metal are included via a local density friction approximation, and surface phonons by a generalized Langevin oscillator model. The action of ultrashort laser pulses enters through a substrate-mediated, hot-electron mechanism via a time-dependent electronic temperature (derived from a two-temperature model), causing random forces acting on the molecule. The model is applied to laser induced lateral diffusion of CO on the surface, "hot adsorbate" formation, and laser induced desorption. Reaction probabilities are strongly enhanced compared to purely thermal processes, both for diffusion and desorption. Reaction yields depend in a characteristic (nonlinear) fashion on the applied laser fluence, as well as branching ratios for various reaction channels. Computed two-pulse correlation traces for desorption and other indicators suggest that aside from electron-hole pairs, phonons play a non-negligible role for laser induced dynamics in this system, acting on a surprisingly short time scale. Our simulations on precomputed potentials allow for good statistics and the treatment of long-time dynamics (300 ps), giving insight into this system which hitherto has not been reached. We find generally good agreement with experimental data where available and make predictions in addition. A recently proposed laser induced population of physisorbed precursor states could not be observed with the present low-coverage model.

  15. 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....

  16. 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

  17. Effect of nitrogen and water deficit type on the yield gap between the potential and attainable wheat yield

    Directory of Open Access Journals (Sweden)

    Jiangang Liu

    2015-12-01

    Full Text Available Water deficit and N fertilizer are the two primary limiting factors for wheat yield in the North China plain, the most important winter wheat (Triticum aestivum L. production area in China. Analyzing the yield gap between the potential yield and the attainable yield can quantify the potential for increasing wheat production and exploring the limiting factors to yield gap in the high-yielding farming region of North China Plain. The Decision Support System for Agrotechnology Transfer (DSSAT model was used to identify methods to increase the grain yield and decrease the gap. In order to explore the impact of N and cultivars on wheat yield in the different drought types, the climate conditions during 1981 to 2011 growing seasons was categorized into low, moderate, and severe water deficit classes according to the anomaly percentage of the water deficit rate during the entire wheat growing season. There are differences (P < 0.0001 in the variations of the potential yields among three cultivars over 30 yr. For all three water deficit types, the more recent cultivars Jimai22 and Shijiazhuang8 had higher yields compared to the older 'Jinan17'. As the N fertilizer rate increased, the yield gap decreased more substantially during the low water deficit years because of the significant increase in attainable yield. Overall, the yield gaps were smaller with less water stress. Replacement of cultivars and appropriate N fertilizer application based on the forecasted drought types can narrow the yield gap effectively.

  18. Principal component regression for crop yield estimation

    CERN Document Server

    Suryanarayana, T M V

    2016-01-01

    This book highlights the estimation of crop yield in Central Gujarat, especially with regard to the development of Multiple Regression Models and Principal Component Regression (PCR) models using climatological parameters as independent variables and crop yield as a dependent variable. It subsequently compares the multiple linear regression (MLR) and PCR results, and discusses the significance of PCR for crop yield estimation. In this context, the book also covers Principal Component Analysis (PCA), a statistical procedure used to reduce a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC). This book will be helpful to the students and researchers, starting their works on climate and agriculture, mainly focussing on estimation models. The flow of chapters takes the readers in a smooth path, in understanding climate and weather and impact of climate change, and gradually proceeds towards downscaling techniques and then finally towards development of ...

  19. Estimating Corporate Yield Curves

    OpenAIRE

    Antionio Diaz; Frank Skinner

    2001-01-01

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

  20. Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

    Science.gov (United States)

    Makowski, David; Asseng, Senthold; Ewert, Frank; Bassu, Simona; Durand, Jean-Louis; Martre, Pierre; Adam, Myriam; Aggarwal, Pramod K.; Angulo, Carlos; Baron, Chritian; hide

    2015-01-01

    Many studies have been carried out during the last decade to study the effect of climate change on crop yields and other key crop characteristics. In these studies, one or several crop models were used to simulate crop growth and development for different climate scenarios that correspond to different projections of atmospheric CO2 concentration, temperature, and rainfall changes (Semenov et al., 1996; Tubiello and Ewert, 2002; White et al., 2011). The Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013) builds on these studies with the goal of using an ensemble of multiple crop models in order to assess effects of climate change scenarios for several crops in contrasting environments. These studies generate large datasets, including thousands of simulated crop yield data. They include series of yield values obtained by combining several crop models with different climate scenarios that are defined by several climatic variables (temperature, CO2, rainfall, etc.). Such datasets potentially provide useful information on the possible effects of different climate change scenarios on crop yields. However, it is sometimes difficult to analyze these datasets and to summarize them in a useful way due to their structural complexity; simulated yield data can differ among contrasting climate scenarios, sites, and crop models. Another issue is that it is not straightforward to extrapolate the results obtained for the scenarios to alternative climate change scenarios not initially included in the simulation protocols. Additional dynamic crop model simulations for new climate change scenarios are an option but this approach is costly, especially when a large number of crop models are used to generate the simulated data, as in AgMIP. Statistical models have been used to analyze responses of measured yield data to climate variables in past studies (Lobell et al., 2011), but the use of a statistical model to analyze yields simulated by complex

  1. 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.

  2. Yield stress independent column buckling curves

    DEFF Research Database (Denmark)

    Stan, Tudor‐Cristian; Jönsson, Jeppe

    2017-01-01

    of the yield stress is to some inadequate degree taken into account in the Eurocode by specifying that steel grades of S460 and higher all belong to a common set of “raised” buckling curves. This is not satisfying as it can be shown theoretically that the current Eurocode formulation misses an epsilon factor......Using GMNIA and shell finite element modelling of steel columns it is ascertained that the buckling curves for given imperfections and residual stresses are not only dependent on the relative slenderness ratio and the cross section shape but also on the magnitude of the yield stress. The influence...... in the definition of the normalised imperfection magnitudes. By introducing this factor it seems that the GMNIA analysis and knowledge of the independency of residual stress levels on the yield stress can be brought together and give results showing consistency between numerical modelling and a simple modified...

  3. Satellite-based assessment of grassland yields

    Science.gov (United States)

    Grant, K.; Siegmund, R.; Wagner, M.; Hartmann, S.

    2015-04-01

    Cutting date and frequency are important parameters determining grassland yields in addition to the effects of weather, soil conditions, plant composition and fertilisation. Because accurate and area-wide data of grassland yields are currently not available, cutting frequency can be used to estimate yields. In this project, a method to detect cutting dates via surface changes in radar images is developed. The combination of this method with a grassland yield model will result in more reliable and regional-wide numbers of grassland yields. For the test-phase of the monitoring project, a study area situated southeast of Munich, Germany, was chosen due to its high density of managed grassland. For determining grassland cutting robust amplitude change detection techniques are used evaluating radar amplitude or backscatter statistics before and after the cutting event. CosmoSkyMed and Sentinel-1A data were analysed. All detected cuts were verified according to in-situ measurements recorded in a GIS database. Although the SAR systems had various acquisition geometries, the amount of detected grassland cut was quite similar. Of 154 tested grassland plots, covering in total 436 ha, 116 and 111 cuts were detected using CosmoSkyMed and Sentinel-1A radar data, respectively. Further improvement of radar data processes as well as additional analyses with higher sample number and wider land surface coverage will follow for optimisation of the method and for validation and generalisation of the results of this feasibility study. The automation of this method will than allow for an area-wide and cost efficient cutting date detection service improving grassland yield models.

  4. 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.

  5. Climate-induced yield variability and yield gaps of maize (Zea mays L.) in the Central Rift Valley of Ethiopia

    NARCIS (Netherlands)

    Kassie, B.T.; Ittersum, van M.K.; Hengsdijk, H.; Asseng, S.; Wolf, J.; Rotter, R.P.

    2014-01-01

    There is a high demand for quantitative information on impacts of climate on crop yields, yield gaps and their variability in Ethiopia, yet, quantitative studies that include an indication of uncertainties in the estimates are rare. A multi-model crop growth simulation approach using the two crop

  6. 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.

  7. 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

  8. 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.

  9. Studies of the physical, yield and failure behavior of aliphatic polyketones

    Science.gov (United States)

    Karttunen, Nicole Renee

    This thesis describes an investigation into the multiaxial yield and failure behavior of an aliphatic polyketone terpolymer. The behavior is studied as a function of: stress state, strain rate, temperature, and sample processing conditions. Results of this work include: elucidation of the behavior of a recently commercialized polymer, increased understanding of the effects listed above, insight into the effects of processing conditions on the morphology of the polyketone, and a description of yield strength of this material as a function of stress state, temperature, and strain rate. The first portion of work focuses on the behavior of a set of samples that are extruded under "common" processing conditions. Following this reference set of tests, the effect of testing this material at different temperatures is studied. A total of four different temperatures are examined. In addition, the effect of altering strain rate is examined. Testing is performed under pseudo-strain rate control at constant nominal octahedral shear strain rate for each failure envelope. A total of three different rates are studied. An extension of the first portion of work involves modeling the yield envelope. This is done by combining two approaches: continuum level and molecular level. The use of both methods allows the description of the yield envelope as a function of stress state, strain rate and temperature. The second portion of work involves the effects of processing conditions. For this work, additional samples are extruded with different shear and thermal histories than the "standard" material. One set of samples is processed with shear rates higher and lower than the standard. A second set is processed at higher and lower cooling rates than the standard. In order to understand the structural cause for changes in behavior with processing conditions, morphological characterization is performed on these samples. In particular, the effect on spherulitic structure is important. Residual

  10. High-resolution, regional-scale crop yield simulations for the Southwestern United States

    Science.gov (United States)

    Stack, D. H.; Kafatos, M.; Medvigy, D.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Prasad, A. K.; Tremback, C.; Walko, R. L.; Asrar, G. R.

    2012-12-01

    Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and

  11. Gastrointestinal Spatiotemporal mRNA Expression of Ghrelin vs Growth Hormone Receptor and New Growth Yield Machine Learning Model Based on Perturbation Theory.

    Science.gov (United States)

    Ran, Tao; Liu, Yong; Li, Hengzhi; Tang, Shaoxun; He, Zhixiong; Munteanu, Cristian R; González-Díaz, Humberto; Tan, Zhiliang; Zhou, Chuanshe

    2016-07-27

    The management of ruminant growth yield has economic importance. The current work presents a study of the spatiotemporal dynamic expression of Ghrelin and GHR at mRNA levels throughout the gastrointestinal tract (GIT) of kid goats under housing and grazing systems. The experiments show that the feeding system and age affected the expression of either Ghrelin or GHR with different mechanisms. Furthermore, the experimental data are used to build new Machine Learning models based on the Perturbation Theory, which can predict the effects of perturbations of Ghrelin and GHR mRNA expression on the growth yield. The models consider eight longitudinal GIT segments (rumen, abomasum, duodenum, jejunum, ileum, cecum, colon and rectum), seven time points (0, 7, 14, 28, 42, 56 and 70 d) and two feeding systems (Supplemental and Grazing feeding) as perturbations from the expected values of the growth yield. The best regression model was obtained using Random Forest, with the coefficient of determination R(2) of 0.781 for the test subset. The current results indicate that the non-linear regression model can accurately predict the growth yield and the key nodes during gastrointestinal development, which is helpful to optimize the feeding management strategies in ruminant production system.

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

    DEFF Research Database (Denmark)

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

    2013-01-01

    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...

  13. 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

  14. 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.

  15. Genetic correlates of insight in schizophrenia.

    Science.gov (United States)

    Xavier, Rose Mary; Vorderstrasse, Allison; Keefe, Richard S E; Dungan, Jennifer R

    2018-05-01

    Insight in schizophrenia is clinically important as it is associated with several adverse outcomes. Genetic contributions to insight are unknown. We examined genetic contributions to insight by investigating if polygenic risk scores (PRS) and candidate regions were associated with insight. Schizophrenia case-only analysis of the Clinical Antipsychotics Trials of Intervention Effectiveness trial. Schizophrenia PRS was constructed using Psychiatric Genomics Consortium (PGC) leave-one out GWAS as discovery data set. For candidate regions, we selected 105 schizophrenia-associated autosomal loci and 11 schizophrenia-related oligodendrocyte genes. We used regressions to examine PRS associations and set-based testing for candidate analysis. We examined data from 730 subjects. Best-fit PRS at p-threshold of 1e-07 was associated with total insight (R 2 =0.005, P=0.05, empirical P=0.054) and treatment insight (R 2 =0.005, P=0.048, empirical P=0.048). For models that controlled for neurocognition, PRS significantly predicted treatment insight but at higher p-thresholds (0.1 to 0.5) but did not survive correction. Patients with highest polygenic burden had 5.9 times increased risk for poor insight compared to patients with lowest burden. PRS explained 3.2% (P=0.002, empirical P=0.011) of variance in poor insight. Set-based analyses identified two variants associated with poor insight- rs320703, an intergenic variant (within-set P=6e-04, FDR P=0.046) and rs1479165 in SOX2-OT (within-set P=9e-04, FDR P=0.046). To the best of our knowledge, this is the first study examining genetic basis of insight. We provide evidence for genetic contributions to impaired insight. Relevance of findings and necessity for replication are discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. 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.

  17. Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield

    Directory of Open Access Journals (Sweden)

    Nahuel R. Peralta

    2016-10-01

    Full Text Available A timely and accurate crop yield forecast is crucial to make better decisions on crop management, marketing, and storage by assessing ahead and implementing based on expected crop performance. The objective of this study was to investigate the potential of high-resolution satellite imagery data collected at mid-growing season for identification of within-field variability and to forecast corn yield at different sites within a field. A test was conducted on yield monitor data and RapidEye satellite imagery obtained for 22 cornfields located in five different counties (Clay, Dickinson, Rice, Saline, and Washington of Kansas (total of 457 ha. Three basic tests were conducted on the data: (1 spatial dependence on each of the yield and vegetation indices (VIs using Moran’s I test; (2 model selection for the relationship between imagery data and actual yield using ordinary least square regression (OLS and spatial econometric (SPL models; and (3 model validation for yield forecasting purposes. Spatial autocorrelation analysis (Moran’s I test for both yield and VIs (red edge NDVI = NDVIre, normalized difference vegetation index = NDVIr, SRre = red-edge simple ratio, near infrared = NIR and green-NDVI = NDVIG was tested positive and statistically significant for most of the fields (p < 0.05, except for one. Inclusion of spatial adjustment to model improved the model fit on most fields as compared to OLS models, with the spatial adjustment coefficient significant for half of the fields studied. When selected models were used for prediction to validate dataset, a striking similarity (RMSE = 0.02 was obtained between predicted and observed yield within a field. Yield maps could assist implementing more effective site-specific management tools and could be utilized as a proxy of yield monitor data. In summary, high-resolution satellite imagery data can be reasonably used to forecast yield via utilization of models that include spatial adjustment to

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

    OpenAIRE

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

    2016-01-01

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

  19. 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.

  20. 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

  1. Rayleigh Wave Ellipticity Modeling and Inversion for Shallow Structure at the Proposed InSight Landing Site in Elysium Planitia, Mars

    Science.gov (United States)

    Knapmeyer-Endrun, Brigitte; Golombek, Matthew P.; Ohrnberger, Matthias

    2017-10-01

    The SEIS (Seismic Experiment for Interior Structure) instrument onboard the InSight mission will be the first seismometer directly deployed on the surface of Mars. From studies on the Earth and the Moon, it is well known that site amplification in low-velocity sediments on top of more competent rocks has a strong influence on seismic signals, but can also be used to constrain the subsurface structure. Here we simulate ambient vibration wavefields in a model of the shallow sub-surface at the InSight landing site in Elysium Planitia and demonstrate how the high-frequency Rayleigh wave ellipticity can be extracted from these data and inverted for shallow structure. We find that, depending on model parameters, higher mode ellipticity information can be extracted from single-station data, which significantly reduces uncertainties in inversion. Though the data are most sensitive to properties of the upper-most layer and show a strong trade-off between layer depth and velocity, it is possible to estimate the velocity and thickness of the sub-regolith layer by using reasonable constraints on regolith properties. Model parameters are best constrained if either higher mode data can be used or additional constraints on regolith properties from seismic analysis of the hammer strokes of InSight's heat flow probe HP3 are available. In addition, the Rayleigh wave ellipticity can distinguish between models with a constant regolith velocity and models with a velocity increase in the regolith, information which is difficult to obtain otherwise.

  2. 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.

  3. 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.

  4. Stock vs. Bond Yields, and Demographic Fluctuations

    DEFF Research Database (Denmark)

    Gozluklu, Arie; Morin, Annaïg

    This paper analyzes the strong comovement between real stock and nominal bond yields at generational (low) frequencies. Life-cycle patterns in savings behavior in an overlapping generations model with cash-in-advance constraints explain this persistent comovement between financial yields. We argue...... that the slow-evolving time-series covariation due to changing population age structure accounts for the equilibrium relation between stock and bond markets. As a result, by exploiting the demographic information into distant future, the forecasting performance of evaluation models improves. Finally, using...

  5. Neurocognitive functioning as an intermediary variable between psychopathology and insight in schizophrenia.

    Science.gov (United States)

    Hwang, Samuel Suk-Hyun; Ahn, Yong Min; Kim, Yong Sik

    2015-12-30

    Based on the neuropsychological deficit model of insight in schizophrenia, we constructed exploratory prediction models for insight, designating neurocognitive measures as the intermediary variables between psychopathology and insight into patients with schizophrenia. The models included the positive, negative, and autistic preoccupation symptoms as primary predictors, and activation symptoms as an intermediary variable for insight. Fifty-six Korean patients, in the acute stage of schizophrenia, completed the Positive and Negative Syndrome Scale, as well as a comprehensive neurocognitive battery of tests at the baseline, 8-weeks, and 1-year follow-ups. Among the neurocognitive measures, the Korean Wechsler Adult Intelligence Scale (K-WAIS) picture arrangement, Controlled Oral Word Association Test (COWAT) perseverative response, and the Continuous Performance Test (CPT) standard error of reaction time showed significant correlations with the symptoms and the insight. When these measures were fitted into the model as intermediaries between the symptoms and the insight, only the perseverative response was found to have a partial mediating effect - both cross-sectionally, and in the 8-week longitudinal change. Overall, the relationship between insight and neurocognitive functioning measures was found to be selective and weak. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  6. Climate Variability and Sugarcane Yield in Louisiana.

    Science.gov (United States)

    Greenland, David

    2005-11-01

    )], mean maximum August temperature, mean minimum February temperature, soil water surplus between April and September, and occurrence of autumn (fall) hurricanes, were built into a model to simulate adjusted yield values. The CCV model simulates the yield value with an rmse of 5.1 t ha-1. The mean of the adjusted yield data over the study period was 60.4 t ha-1, with values for the highest and lowest years being 73.1 and 50.6 t ha-1, respectively, and a standard deviation of 5.9 t ha-1. Presumably because of the almost constant high water table and soil water availability, higher precipitation totals, which are inversely related to radiation and temperature, tend to have a negative effect on the yields. Past trends in the values of critical climatic variables and general projections of future climate suggest that, with respect to the climatic environment and as long as land drainage is continued and maintained, future levels of sugarcane yield will rise in Louisiana.

  7. Development of estimation method for crop yield using MODIS satellite imagery data and process-based model for corn and soybean in US Corn-Belt region

    Science.gov (United States)

    Lee, J.; Kang, S.; Jang, K.; Ko, J.; Hong, S.

    2012-12-01

    Crop productivity is associated with the food security and hence, several models have been developed to estimate crop yield by combining remote sensing data with carbon cycle processes. In present study, we attempted to estimate crop GPP and NPP using algorithm based on the LUE model and a simplified respiration model. The state of Iowa and Illinois was chosen as the study site for estimating the crop yield for a period covering the 5 years (2006-2010), as it is the main Corn-Belt area in US. Present study focuses on developing crop-specific parameters for corn and soybean to estimate crop productivity and yield mapping using satellite remote sensing data. We utilized a 10 km spatial resolution daily meteorological data from WRF to provide cloudy-day meteorological variables but in clear-say days, MODIS-based meteorological data were utilized to estimate daily GPP, NPP, and biomass. County-level statistics on yield, area harvested, and productions were used to test model predicted crop yield. The estimated input meteorological variables from MODIS and WRF showed with good agreements with the ground observations from 6 Ameriflux tower sites in 2006. For examples, correlation coefficients ranged from 0.93 to 0.98 for Tmin and Tavg ; from 0.68 to 0.85 for daytime mean VPD; from 0.85 to 0.96 for daily shortwave radiation, respectively. We developed county-specific crop conversion coefficient, i.e. ratio of yield to biomass on 260 DOY and then, validated the estimated county-level crop yield with the statistical yield data. The estimated corn and soybean yields at the county level ranged from 671 gm-2 y-1 to 1393 gm-2 y-1 and from 213 gm-2 y-1 to 421 gm-2 y-1, respectively. The county-specific yield estimation mostly showed errors less than 10%. Furthermore, we estimated crop yields at the state level which were validated against the statistics data and showed errors less than 1%. Further analysis for crop conversion coefficient was conducted for 200 DOY and 280 DOY

  8. Unraveling interrelationships among psychopathology symptoms, cognitive domains and insight dimensions in chronic schizophrenia.

    Science.gov (United States)

    Xavier, Rose Mary; Pan, Wei; Dungan, Jennifer R; Keefe, Richard S E; Vorderstrasse, Allison

    2018-03-01

    Insight in schizophrenia is long known to have a complex relationship with psychopathology symptoms and cognition. However, very few studies have examined models that explain these interrelationships. In a large sample derived from the NIMH Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial (N=1391), we interrogated these interrelationships for potential causal pathways using structural equation modeling. Using the NIMH consensus model, latent variables were constructed for psychopathology symptom dimensions, including positive, negative, disorganized, excited and depressed from the Positive and Negative Syndrome Scale (PANSS) items. Neurocognitive variables were created from five predefined domains of working memory, verbal memory, reasoning, vigilance and processing speed. Illness insight and treatment insight were tested using latent variables constructed from the Illness and Treatment Attitude Questionnaire (ITAQ). Disorganized symptoms had the strongest effect on insight. Illness insight mediated the relationship of positive, depressed, and disorganized symptoms with treatment insight. Neurocognition mediated the relationship between disorganized and treatment insight and depressed symptoms and treatment insight. There was no effect of negative symptoms on either illness insight or treatment insight. Taken together, our results indicate overlapping and unique relational paths for illness and treatment insight dimensions, which could suggest differences in causal mechanisms and potential interventions to improve insight. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Using MODIS Data to Predict Regional Corn Yields

    Directory of Open Access Journals (Sweden)

    Ho-Young Ban

    2016-12-01

    Full Text Available A simple approach was developed to predict corn yields using the MoDerate Resolution Imaging Spectroradiometer (MODIS data product from two geographically separate major corn crop production regions: Illinois, USA and Heilongjiang, China. The MOD09A1 data, which are eight-day interval surface reflectance data, were obtained from day of the year (DOY 89 to 337 to calculate the leaf area index (LAI. The sum of the LAI from early in the season to a given date in the season (end of DOY (EOD was well fitted to a logistic function and represented seasonal changes in leaf area duration (LAD. A simple phenology model was derived to estimate the dates of emergence and maturity using the LAD-logistic function parameters b1 and b2, which represented the rate of increase in LAI and the date of maximum LAI, respectively. The phenology model predicted emergence and maturity dates fairly well, with root mean square error (RMSE values of 6.3 and 4.9 days for the validation dataset, respectively. Two simple linear regression models (YP and YF were established using LAD as the variable to predict corn yield. The yield model YP used LAD from predicted emergence to maturity, and the yield model YF used LAD for a predetermined period from DOY 89 to a particular EOD. When state/province corn yields for the validation dataset were predicted at DOY 321, near completion of the corn harvest, the YP model, including the predicted phenology, performed much better than the YF model, with RMSE values of 0.68 t/ha and 0.66 t/ha for Illinois and Heilongjiang, respectively. The YP model showed similar or better performance, even for the much earlier pre-harvest yield prediction at DOY 257. In addition, the model performance showed no difference between the two study regions with very different climates and cultivation methods, including cultivar and irrigation management. These results suggested that the approach described in this paper has potential for application to

  10. Understanding the weather signal in national crop-yield variability

    Science.gov (United States)

    Frieler, Katja; Schauberger, Bernhard; Arneth, Almut; Balkovič, Juraj; Chryssanthacopoulos, James; Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Khabarov, Nikolay; Müller, Christoph; Olin, Stefan; Pugh, Thomas A. M.; Schaphoff, Sibyll; Schewe, Jacob; Schmid, Erwin; Warszawski, Lila; Levermann, Anders

    2017-06-01

    Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the United States. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.

  11. Insight and satisfaction with life among adolescents with mental disorders: assessing associations with self-stigma and parental insight.

    Science.gov (United States)

    Gaziel, M; Hasson-Ohayon, I; Morag-Yaffe, M; Schapir, L; Zalsman, G; Shoval, G

    2015-02-01

    The purpose of the current study was to assess the associations of illness perception-related variables with satisfaction with life (SwL) among adolescents with mental disorders. Insight into mental disorder (SAI-E), Internalized stigma of mental illness (ISMI) and Multidimensional Students' Life Satisfaction Scale (MSLSS) were administrated to 30 adolescent patients. Adapted version for parents of the SAI-E was also administrated to 37 of their parents. Significant positive correlations were found between insight into the illness, self-stigma and parental insight. Insight and self-stigma were significantly negatively related to the total score of SwL and few of its dimensions while parental insight was significantly associated only with the SwL dimensions of school and self. Regression models revealed main negative effects of insight and self-stigma on SwL and no interaction effect. The possible independent contribution of insight and self-stigma to SwL should be addressed in interventions designed for family and adolescents coping with mental illness. Special attention should be given to the possible negative implications that insight possesses. In lack of support of the moderation role of self-stigma, reported in studies among adults with mental illness, future studies should trace other variables in order to further understand the insight paradox among adolescents. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  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. Yield Strength Testing in Human Cadaver Nasal Septal Cartilage and L-Strut Constructs.

    Science.gov (United States)

    Liu, Yuan F; Messinger, Kelton; Inman, Jared C

    2017-01-01

    To our knowledge, yield strength testing in human nasal septal cartilage has not been reported to date. An understanding of the basic mechanics of the nasal septum may help surgeons decide how much of an L-strut to preserve and how much grafting is needed. To determine the factors correlated with yield strength of the cartilaginous nasal septum and to explore the association between L-strut width and thickness in determining yield strength. In an anatomy laboratory, yield strength of rectangular pieces of fresh cadaver nasal septal cartilage was measured, and regression was performed to identify the factors correlated with yield strength. To measure yield strength in L-shaped models, 4 bonded paper L-struts models were constructed for every possible combination of the width and thickness, for a total of 240 models. Mathematical modeling using the resultant data with trend lines and surface fitting was performed to quantify the associations among L-strut width, thickness, and yield strength. The study dates were November 1, 2015, to April 1, 2016. The factors correlated with nasal cartilage yield strength and the associations among L-strut width, thickness, and yield strength in L-shaped models. Among 95 cartilage pieces from 12 human cadavers (mean [SD] age, 67.7 [12.6] years) and 240 constructed L-strut models, L-strut thickness was the only factor correlated with nasal septal cartilage yield strength (coefficient for thickness, 5.54; 95% CI, 4.08-7.00; P cadaver nasal septal cartilage, L-strut thickness was significantly associated with yield strength. In a bonded paper L-strut model, L-strut thickness had a more important role in determining yield strength than L-strut width. Surgeons should consider the thickness of potential L-struts when determining the amount of cartilaginous septum to harvest and graft. NA.

  14. Assessing Sediment Yield and the Effect of Best Management Practices on Sediment Yield Reduction for Tutuila Island, American Samoa

    Science.gov (United States)

    Leta, O. T.; Dulai, H.; El-Kadi, A. I.

    2017-12-01

    Upland soil erosion and sedimentation are the main threats for riparian and coastal reef ecosystems in Pacific islands. Here, due to small size of the watersheds and steep slope, the residence time of rainfall runoff and its suspended load is short. Fagaalu bay, located on the island of Tutuila (American Samoa) has been identified as a priority watershed, due to degraded coral reef condition and reduction of stream water quality from heavy anthropogenic activity yielding high nutrients and sediment loads to the receiving water bodies. This study aimed to estimate the sediment yield to the Fagaalu stream and assess the impact of Best Management Practices (BMP) on sediment yield reduction. For this, the Soil and Water Assessment Tool (SWAT) model was applied, calibrated, and validated for both daily streamflow and sediment load simulation. The model also estimated the sediment yield contributions from existing land use types of Fagaalu and identified soil erosion prone areas for introducing BMP scenarios in the watershed. Then, three BMP scenarios, such as stone bund, retention pond, and filter strip were treated on bare (quarry area), agricultural, and shrub land use types. It was found that the bare land with quarry activity yielded the highest annual average sediment yield of 133 ton per hectare (t ha-1) followed by agriculture (26.1 t ha-1) while the lowest sediment yield of 0.2 t ha-1 was estimated for the forested part of the watershed. Additionally, the bare land area (2 ha) contributed approximately 65% (207 ha) of the watershed's sediment yield, which is 4.0 t ha-1. The latter signifies the high impact as well as contribution of anthropogenic activity on sediment yield. The use of different BMP scenarios generally reduced the sediment yield to the coastal reef of Fagaalu watershed. However, treating the quarry activity area with stone bund showed the highest sediment yield reduction as compared to the other two BMP scenarios. This study provides an estimate

  15. Evaluation of the performance of SiBcrop model in predicting carbon fluxes and crop yields in the croplands of the US mid continental region

    Science.gov (United States)

    Lokupitiya, E.; Denning, S.; Paustian, K.; Corbin, K.; Baker, I.; Schaefer, K.

    2008-12-01

    The accurate representation of phenology, physiology, and major crop variables is important in the land- atmosphere carbon models being used to predict carbon and other exchanges of the man-made cropland ecosystems. We evaluated the performance of SiBcrop model (which is the Simple Biosphere model (SiB) with a new scheme for crop phenology and physiology) in predicting carbon exchanges of the US mid continental region which has several major crops. The use of the new phenology scheme within SiB remarkably improved the prediction of LAI and carbon fluxes for corn, soybean, and wheat crops as compared with the observed data at several Ameriflux eddy covariance flux tower sites with those crops. SiBcrop better predicted the onset and end of the growing season, harvest, interannual variability associated with crop rotation, day time carbon draw down, and day to day variability in the carbon exchanges. The model has been coupled with RAMS, the regional Atmospheric Modeling System (developed at Colorado State University), and the coupled SiBcrop-RAMS has predicted better carbon and other fluxes compared to the original SiB-RAMS. SiBcrop also predicted daily variation in biomass in different plant pools (i.e. roots, leaves, stems, and products). In this study, we further evaluated the performance of SiBcrop by comparing the yield estimates based on the grain/seed biomass at harvest predicted by SiBcrop for relevant major crops, against the county-level crop yields reported by the US National Agricultural Statistics Service (NASS). Initially, the model runs were based on crop maps scaled at 40 km resolution; the maps were used to derive the fraction of corn, soybean, and wheat at each grid cell across the US Mid Continental Intensive (MCI) region under the North American Carbon Program (NACP). The yield biomass carbon values (at harvest) predicted for each grid cell by SiBcrop were extrapolated to derive the county-level yield biomass carbon values, which were then

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

    Directory of Open Access Journals (Sweden)

    Bassou BOUAZZAM

    2017-09-01

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

  17. 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.

  18. 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

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

    National Research Council Canada - National Science Library

    Kieras, David

    1998-01-01

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

  20. Supersymmetric contribution to B{yields}{rho}K and B{yields}{pi}K{sup Low-Asterisk} decays in SCET

    Energy Technology Data Exchange (ETDEWEB)

    Faisel, Gaber, E-mail: gfaisel@cc.ncu.edu.tw [Department of Physics and Center for Mathematics and Theoretical Physics, National Central University, Chung-li, 32054, Taiwan (China); Egyptian Center for Theoretical Physics, Modern University for Information and Technology, Cairo (Egypt); Delepine, David [Departamento de Fisica, DCI, Campus Leon, Universidad de Guanajuato, C.P. 37150, Leon, Guanajuato (Mexico); Shalaby, M. [Ain Shams University, Faculty of Science, Cairo 11566 (Egypt)

    2011-11-17

    We analyze the supersymmetric contributions to the direct CP asymmetries of the decays B{yields}{pi}K{sup Low-Asterisk} and B{yields}{rho}K within Soft Collinear Effective Theory. We extend the Standard Model analysis of these asymmetries to include the next leading order QCD corrections. We find that, even with QCD correction, the Standard Model predictions cannot accommodate the direct CP asymmetries in these decay modes. Using Mass Insertion Approximation (MIA), we show that non-minimal flavor SUSY contributions mediated by gluino exchange can enhance the CP asymmetries significantly and thus can accommodate the experimental results.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-07-01

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

  2. 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.

  3. Insights into the latent multinomial model through mark-resight data on female grizzly bears with cubs-of-the-year

    Science.gov (United States)

    Higgs, Megan D.; Link, William; White, Gary C.; Haroldson, Mark A.; Bjornlie, Daniel D.

    2013-01-01

    Mark-resight designs for estimation of population abundance are common and attractive to researchers. However, inference from such designs is very limited when faced with sparse data, either from a low number of marked animals, a low probability of detection, or both. In the Greater Yellowstone Ecosystem, yearly mark-resight data are collected for female grizzly bears with cubs-of-the-year (FCOY), and inference suffers from both limitations. To overcome difficulties due to sparseness, we assume homogeneity in sighting probabilities over 16 years of bi-annual aerial surveys. We model counts of marked and unmarked animals as multinomial random variables, using the capture frequencies of marked animals for inference about the latent multinomial frequencies for unmarked animals. We discuss undesirable behavior of the commonly used discrete uniform prior distribution on the population size parameter and provide OpenBUGS code for fitting such models. The application provides valuable insights into subtleties of implementing Bayesian inference for latent multinomial models. We tie the discussion to our application, though the insights are broadly useful for applications of the latent multinomial model.

  4. Integrating modelling and phenotyping approaches to identify and screen complex traits - Illustration for transpiration efficiency in cereals.

    Science.gov (United States)

    Chenu, K; van Oosterom, E J; McLean, G; Deifel, K S; Fletcher, A; Geetika, G; Tirfessa, A; Mace, E S; Jordan, D R; Sulman, R; Hammer, G L

    2018-02-21

    Following advances in genetics, genomics, and phenotyping, trait selection in breeding is limited by our ability to understand interactions within the plants and with their environments, and to target traits of most relevance for the target population of environments. We propose an integrated approach that combines insights from crop modelling, physiology, genetics, and breeding to identify traits valuable for yield gain in the target population of environments, develop relevant high-throughput phenotyping platforms, and identify genetic controls and their values in production environments. This paper uses transpiration efficiency (biomass produced per unit of water used) as an example of a complex trait of interest to illustrate how the approach can guide modelling, phenotyping, and selection in a breeding program. We believe that this approach, by integrating insights from diverse disciplines, can increase the resource use efficiency of breeding programs for improving yield gains in target populations of environments.

  5. EMPIRICALLY DERIVED INTEGRATED STELLAR YIELDS OF Fe-PEAK ELEMENTS

    International Nuclear Information System (INIS)

    Henry, R. B. C.; Cowan, John J.; Sobeck, Jennifer

    2010-01-01

    We present here the initial results of a new study of massive star yields of Fe-peak elements. We have compiled from the literature a database of carefully determined solar neighborhood stellar abundances of seven iron-peak elements, Ti, V, Cr, Mn, Fe, Co, and Ni, and then plotted [X/Fe] versus [Fe/H] to study the trends as functions of metallicity. Chemical evolution models were then employed to force a fit to the observed trends by adjusting the input massive star metallicity-sensitive yields of Kobayashi et al. Our results suggest that yields of Ti, V, and Co are generally larger as well as anticorrelated with metallicity, in contrast to the Kobayashi et al. predictions. We also find the yields of Cr and Mn to be generally smaller and directly correlated with metallicity compared to the theoretical results. Our results for Ni are consistent with theory, although our model suggests that all Ni yields should be scaled up slightly. The outcome of this exercise is the computation of a set of integrated yields, i.e., stellar yields weighted by a slightly flattened time-independent Salpeter initial mass function and integrated over stellar mass, for each of the above elements at several metallicity points spanned by the broad range of observations. These results are designed to be used as empirical constraints on future iron-peak yield predictions by stellar evolution modelers. Special attention is paid to the interesting behavior of [Cr/Co] with metallicity-these two elements have opposite slopes-as well as the indirect correlation of [Ti/Fe] with [Fe/H]. These particular trends, as well as those exhibited by the inferred integrated yields of all iron-peak elements with metallicity, are discussed in terms of both supernova nucleosynthesis and atomic physics.

  6. Independent isomer yield ratio of 90Rb

    International Nuclear Information System (INIS)

    Reeder, P.L.; Warner, R.A.; Ford, G.P.; Willmes, H.

    1985-05-01

    The independent isomer yield ratio for 90 Rb from thermal neutron fission of 235 U has been measured by use of a new technique involving a pulsed reactor and an on-line mass spectrometer facility. The apparent isomer yield ratio was measured for different ion collection time intervals and extrapolated to zero collection time to eliminate interference from 90 Kr decay. The observed isomer yield ratio of 8.7 +- 1.0 is one of the largest ratios measured for a low energy fission process. However, a statistical model analysis shows that the average angular momentum ( = 4.5) deduced from this isomer yield ratio is consistent with average angular momentum for other products from low energy fission. 7 refs

  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. 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).

  9. The Association of Insight and Change in Insight with Clinical Symptoms in Depressed Inpatients.

    Science.gov (United States)

    He, Hongbo; Chang, Qing; Ma, Yarong

    2018-04-25

    Lack of insight has been extensively studied and was found to be adversely correlated with impaired treatment compliance and worse long term clinical outcomes among patients with schizophrenia, while not much is known about this phenonmenon in patients with severe depression. To explore the correlates of insight and its relation to symptom changes among the most seriously ill patients with affective disorders, those who require hospitalization. Patients hospitalized in a large psychiatric hospital in south China with either major depressive disorder (MDD)(N=55) or bipolar depression (BD) (N=85) based on ICD-10 diagnostic criteria were assessed with the Insight and Treatment Attitudes Questionnaire (ITAQ) one week after admission and at the time of discharge. Clinical symptoms were measured at the same time with the Hamilton Rating Scale for Depression (HAMD-17) and the Depression subscale of the Symptom Check list-90 (SCL-90). Length of stay (LOS), duration of illness, duration of untreated mood disorder, number of previous episodes of depression and previous admissions for depression were documented during interviews with patients and their families and from a review of medical records. Bivariate correlations and multiple regression analysis were used to examine the relationship of sociodemographic characteristics, clinical symptomatology and clinical history, to insight at the time of admission. The relationships between change in clinical symptoms and change in insight from admission to discharge were also examined. Stepwise multiple regression models suggested that any previous admissions for depression and higher anxiety factor scores on the HAMD-17 are significant independent predictors of insight accounting for 22.9% of the variance. Multiple regression analysis residual change scores (change scores adjusted for baseline values) on the ITAQ showed that improved insight over average stays of 51 days were inversely related to the residual psychomotor

  10. Low cost, high yield IFE reactors: Revisiting Velikhov's vaporizing blankets

    International Nuclear Information System (INIS)

    Logan, B.G.

    1992-01-01

    The performance (efficiency and cost) of IFE reactors using MHD conversion is explored for target blanket shells of various materials vaporized and ionized by high fusion yields (5 to 500 GJ). A magnetized, prestressed reactor chamber concept is modeled together with previously developed models for the Compact Fusion Advanced Rankine II (CFARII) MHD Balance-of-Plant (BoP). Using conservative 1-D neutronics models, high fusion yields (20 to 80 GJ) are found necessary to heat Flibe, lithium, and lead-lithium blankets to MHD plasma temperatures, at initial solid thicknesses sufficient to capture most of the fusion yield. Advanced drivers/targets would need to be developed to achieve a ''Bang per Buck'' figure-of-merit approx-gt 20 to 40 joules yield per driver $ for this scheme to be competitive with these blanket materials. Alternatively, more realistic neutronics models and better materials such as lithium hydride may lower the minimum required yields substantially. The very low CFARII BoP costs (contributing only 3 mills/kWehr to CoE) allows this type of reactor, given sufficient advances that non-driver costs dominate, to ultimately produce electricity at a much lower cost than any current nuclear plant

  11. Impact of the spatial resolution of climatic data and soil physical properties on regional corn yield predictions using the STICS crop model

    Science.gov (United States)

    Jégo, Guillaume; Pattey, Elizabeth; Mesbah, S. Morteza; Liu, Jiangui; Duchesne, Isabelle

    2015-09-01

    The assimilation of Earth observation (EO) data into crop models has proven to be an efficient way to improve yield prediction at a regional scale by estimating key unknown crop management practices. However, the efficiency of prediction depends on the uncertainty associated with the data provided to crop models, particularly climatic data and soil physical properties. In this study, the performance of the STICS (Simulateur mulTIdisciplinaire pour les Cultures Standard) crop model for predicting corn yield after assimilation of leaf area index derived from EO data was evaluated under different scenarios. The scenarios were designed to examine the impact of using fine-resolution soil physical properties, as well as the impact of using climatic data from either one or four weather stations across the region of interest. The results indicate that when only one weather station was used, the average annual yield by producer was predicted well (absolute error <5%), but the spatial variability lacked accuracy (root mean square error = 1.3 t ha-1). The model root mean square error for yield prediction was highly correlated with the distance between the weather stations and the fields, for distances smaller than 10 km, and reached 0.5 t ha-1 for a 5-km distance when fine-resolution soil properties were used. When four weather stations were used, no significant improvement in model performance was observed. This was because of a marginal decrease (30%) in the average distance between fields and weather stations (from 10 to 7 km). However, the yield predictions were improved by approximately 15% with fine-resolution soil properties regardless of the number of weather stations used. The impact of the uncertainty associated with the EO-derived soil textures and the impact of alterations in rainfall distribution were also evaluated. A variation of about 10% in any of the soil physical textures resulted in a change in dry yield of 0.4 t ha-1. Changes in rainfall distribution

  12. Simulation-based production planning for engineer-to-order systems with random yield

    NARCIS (Netherlands)

    Akcay, Alp; Martagan, Tugce

    2018-01-01

    We consider an engineer-to-order production system with unknown yield. We model the yield as a random variable which represents the percentage output obtained from one unit of production quantity. We develop a beta-regression model in which the mean value of the yield depends on the unique

  13. 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).

  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. Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene

    Science.gov (United States)

    Thompson, S. E.; Sivapalan, M.; Harman, C. J.; Srinivasan, V.; Hipsey, M. R.; Reed, P.; Montanari, A.; Blöschl, G.

    2013-12-01

    Globally, many different kinds of water resources management issues call for policy- and infrastructure-based responses. Yet responsible decision-making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal- to century-long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle - a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges from the perspectives of hydrologic science research. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management. Fully realizing the potential of this approach will ultimately require detailed integration of social science and physical science

  16. 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

  17. Respirometric assessment of storage yield for different substrates

    DEFF Research Database (Denmark)

    Karahan-Gül, Ö; Artan, N.; Orhon, D.

    2002-01-01

    A new procedure has been defined for the respirometric assessment of bacterial storage yield as defined in the Activated Sludge Model No.3. The procedure was used to determine the storage yield, YSTO, associated with acetate, glucose and domestic sewage, together with mixtures of acetate/glucose ...

  18. interrelationships between grain yield and other physiological traits

    African Journals Online (AJOL)

    Prof. Adipala Ekwamu

    Combined analysis of variance, cluster analysis and genotype-by- ... all phenological and morphological traits, except grain yield and associated yield components. ... egg, and other protein-rich foods (Alghali, 1991). ... systematic modelling approach. ... MD IT98 K -132 – 3 .... traits based on Principal Component axes (PC)1.

  19. Measurement of branching ratios and CP asymmetries for the decays B{sup 0}{yields}{pi}{sup +}{pi}{sup -}, B{sup 0}{yields}K{sup +}{pi}{sup -}, B{sup 0}{yields}K{sup +}K{sup -}

    Energy Technology Data Exchange (ETDEWEB)

    Prothmann, Kolja Andreas

    2013-01-30

    We present measurements of the branching fractions and CP violation parameters for the decay channels B{sup 0}{yields}{pi}{sup +}{pi}{sup -}, B{sup 0}{yields}K{sup +}{pi}{sup -} and B{sup 0}{yields}K{sup +}K{sup -}. The final Belle dataset of 772 million B anti B pairs produced at the {Upsilon}(4S) resonance at the KEKB asymmetric-energy e{sup +}e{sup -} collider is used. For the branching fractions, we obtain B(B{sup 0}{yields}{pi}{sup +}{pi}{sup -})=(5.63{+-} 0.16(stat){+-} 0.16(syst)) x 10{sup -6}, B(B{sup 0}{yields}K{sup {+-}}{pi}{sup -+})=(18.71{+-}0.25(stat){+-} 0.37(syst)) x 10{sup -6}, B(B{sup 0}{yields}K{sup +}K{sup -})<14 x 10{sup -8} at 90% CL. For the CP-asymmetries, we obtain following values: A{sub CP}(B{sup 0}{yields}{pi}{sup +}{pi}{sup -})=0.33{+-}0.06(stat){+-}0.03 (syst), S{sub CP}(B{sup 0}{yields}{pi}{sup +}{pi}{sup -})=-0.64{+-}0.08(stat){+-}0.03(syst), A{sub CP}(B{sup 0}{yields}K{sup {+-}}K{sup -+})=-0.061{+-}0.014(stat){+-}0.008 (syst), where A{sub CP} and S{sub CP} represent direct and mixing-induced CP violation, respectively. For the CP-violating weak phase {phi}{sub 2} we exclude the region 23.8 <{phi}{sub 2}<66.8 at the 1{sigma} level. A model independent test of new physics using a sum rule in the K{pi} system yields a mild deviation from the standard model of -0.289{+-}0.139(stat){+-}0.064(syst) with a 1.9{sigma} significance.

  20. Do soil organic carbon levels affect potential yields and nitrogen use efficiency?

    DEFF Research Database (Denmark)

    Oelofse, Myles; Markussen, Bo; Knudsen, Leif

    2015-01-01

    Soil organic carbon (SOC) is broadly recognised as an important parameter affecting soil quality, and can therefore contribute to improving a number of soil properties that influence crop yield. Previous research generally indicates that soil organic carbon has positive effects on crop yields......, the yield with no fertiliser N application and the N use efficiency would be positively affected by SOC level. A statistical model was developed to explore relationships between SOC and potential yield, yields at zero N application and N use efficiency (NUE). The model included a variety of variables...

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

    Science.gov (United States)

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

    2010-12-01

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

  2. A Multinomial Probit Model with Latent Factors

    DEFF Research Database (Denmark)

    Piatek, Rémi; Gensowski, Miriam

    2017-01-01

    be meaningfully linked to an economic model. We provide sufficient conditions that make this structure identified and interpretable. For inference, we design a Markov chain Monte Carlo sampler based on marginal data augmentation. A simulation exercise shows the good numerical performance of our sampler......We develop a parametrization of the multinomial probit model that yields greater insight into the underlying decision-making process, by decomposing the error terms of the utilities into latent factors and noise. The latent factors are identified without a measurement system, and they can...

  3. 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.

  4. 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)

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

    NARCIS (Netherlands)

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

    2003-01-01

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

  6. How Accurately Do Maize Crop Models Simulate the Interactions of Atmospheric CO2 Concentration Levels With Limited Water Supply on Water Use and Yield?

    Science.gov (United States)

    Durand, Jean-Louis; Delusca, Kenel; Boote, Ken; Lizaso, Jon; Manderscheid, Remy; Weigel, Hans Johachim; Ruane, Alexander Clark; Rosenzweig, Cynthia E.; Jones, Jim; Ahuja, Laj; hide

    2017-01-01

    This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration [CO2] on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thunen Institute in Braunschweig, Germany (Manderscheid et al. 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50 percent of models within a range of plus/minus 1 Mg ha(exp. -1) around the mean. The bias of the median of the 21 models was less than 1 Mg ha(exp. -1). However under water deficit in one of the two years, the models captured only 30 percent of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase.

  7. Wheat yield dynamics: a structural econometric analysis.

    Science.gov (United States)

    Sahin, Afsin; Akdi, Yilmaz; Arslan, Fahrettin

    2007-10-15

    In this study we initially have tried to explore the wheat situation in Turkey, which has a small-open economy and in the member countries of European Union (EU). We have observed that increasing the wheat yield is fundamental to obtain comparative advantage among countries by depressing domestic prices. Also the changing structure of supporting schemes in Turkey makes it necessary to increase its wheat yield level. For this purpose, we have used available data to determine the dynamics of wheat yield by Ordinary Least Square Regression methods. In order to find out whether there is a linear relationship among these series we have checked each series whether they are integrated at the same order or not. Consequently, we have pointed out that fertilizer usage and precipitation level are substantial inputs for producing high wheat yield. Furthermore, in respect for our model, fertilizer usage affects wheat yield more than precipitation level.

  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. 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

  10. 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.

  11. 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

  12. FACTORS INFLUENCING YIELD SPREADS OF THE MALAYSIAN BONDS

    Directory of Open Access Journals (Sweden)

    Norliza Ahmad

    2009-01-01

    Full Text Available Malaysian bond market is developing rapidly but not much is understood in terms of macroeconomic factors that could influence the yield spread of the Ringgit Malaysian denominated bonds. Based on a multifactor model, this paper examines the impact of four macroeconomic factors namely: Kuala Lumpur Composite Index (KLCI, Industry Production Index (IPI, Consumer Price Index (CPI and interest rates (IR on bond yield spread of the Malaysian Government Securities (MGS and Corporate Bonds (CBs for a period from January 2001 to December 2008. The findings support the expected hypotheses that CPI and IR are the major drivers that influence the changes in MGS yield spreads. However IPI and KLCI have weak and no influence on MGS yield spreads respectively Whilst IR, CPI and IPI have significant influence on the yield spreads of CB1, CB2 and CB3, KLCI has significant influence only on the CB1 yield spread but not on CB2 and CB3 yield spreads.

  13. 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.

  14. Modeling of Zymomonas mobilis central metabolism for novel metabolic engineering strategies.

    Science.gov (United States)

    Kalnenieks, Uldis; Pentjuss, Agris; Rutkis, Reinis; Stalidzans, Egils; Fell, David A

    2014-01-01

    Mathematical modeling of metabolism is essential for rational metabolic engineering. The present work focuses on several types of modeling approach to quantitative understanding of central metabolic network and energetics in the bioethanol-producing bacterium Zymomonas mobilis. Combined use of Flux Balance, Elementary Flux Mode, and thermodynamic analysis of its central metabolism, together with dynamic modeling of the core catabolic pathways, can help to design novel substrate and product pathways by systematically analyzing the solution space for metabolic engineering, and yields insights into the function of metabolic network, hardly achievable without applying modeling tools.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-07-01

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

  16. Genetic analysis of yield in peanut ( Arachis hypogaea L.) using ...

    African Journals Online (AJOL)

    The yield had significant major gene effect and the results implied that not only should the two major genes' effects be considered but also the polygene's effect should be considered in breeding to increase peanut yield. Key words: Peanut, yield, major gene plus polygene inheritance model, genetic analysis.

  17. Evolution of uranium fission-fragment charge yields with neutron number. Strong effect of multi-chance fission on yield asymmetries

    Energy Technology Data Exchange (ETDEWEB)

    Moeller, Peter [Los Alamos National Laboratory, Theoretical Division, Los Alamos, NM (United States); Schmitt, Christelle [CEA/DSM-CNRS/IN2P3, Grand Accelerateur National d' Ions Lourds, Caen (France)

    2017-01-15

    We use the Brownian shape-motion model, with its recent extensions, which allow modeling of odd-even staggering, to calculate the evolution of fission-fragment charge distributions with neutron number for the compound-system sequence {sup 234}U, {sup 236}U, {sup 238}U, and {sup 240}U. We compare to experimental data where available, for neutron- and electromagnetic-induced fission over a compound-nucleus excitation energy range from about 6 to 20 MeV. A notable result of the study is that the evolution of the location of the peak charge yield from Z = 54 in {sup 234}U towards Z = 52 in heavier isotopes, seen in the experimental data, is present also in the calculated yields. We further show that to describe yields at higher compound-nucleus excitation energies, then, already at 20 MeV, it is necessary to take multi-chance fission into account. (orig.)

  18. Compilation and evaluation of fission yield nuclear data

    International Nuclear Information System (INIS)

    Lammer, M.

    1991-09-01

    The task of this meeting was to review the progress made since the previous meeting on fission yield evaluation and to define the tasks for an IAEA Co-ordinated Research Programme in detail. Improvements have been noted in measured data, model calculations and the situation of fission yield evaluation. Tabs

  19. The “Insight Paradox” in Schizophrenia: Magnitude, Moderators and Mediators of the Association Between Insight and Depression

    Science.gov (United States)

    Belvederi Murri, Martino; Amore, Mario; Calcagno, Pietro; Respino, Matteo; Marozzi, Valentina; Masotti, Mattia; Bugliani, Michele; Innamorati, Marco; Pompili, Maurizio; Galderisi, Silvana; Maj, Mario

    2016-01-01

    The so-called “insight paradox” posits that among patients with schizophrenia higher levels of insight are associated with increased levels of depression. Although different studies examined this issue, only few took in account potential confounders or factors that could influence this association. In a sample of clinically stable patients with schizophrenia, insight and depression were evaluated using the Scale to assess Unawareness of Mental Disorder and the Calgary Depression Scale for Schizophrenia. Other rating scales were used to assess the severity of psychotic symptoms, extrapyramidal symptoms, hopelessness, internalized stigma, self-esteem, and service engagement. Regression models were used to estimate the magnitude of the association between insight and depression while accounting for the role of confounders. Putative psychological and sociodemographic factors that could act as mediators and moderators were examined using the PROCESS macro. By accounting for the role of confounding factors, the strength of the association between insight into symptoms and depression increased from 13% to 25% explained covariance. Patients with lower socioeconomic status (F = 8.5, P = .04), more severe illness (F = 4.8, P = .03) and lower levels of service engagement (F = 4.7, P = .03) displayed the strongest association between insight and depression. Lastly, hopelessness, internalized stigma and perceived discrimination acted as significant mediators. The relationship between insight and depression should be considered a well established phenomenon among patients with schizophrenia: it seems stronger than previously reported especially among patients with lower socioeconomic status, severe illness and poor engagement with services. These findings may have relevant implications for the promotion of insight among patients with schizophrenia. PMID:27069064

  20. Parsing multiple processes of high temperature impacts on corn/soybean yield using a newly developed CLM-APSIM modeling framework

    Science.gov (United States)

    Peng, B.; Guan, K.; Chen, M.

    2016-12-01

    Future agricultural production faces a grand challenge of higher temperature under climate change. There are multiple physiological or metabolic processes of how high temperature affects crop yield. Specifically, we consider the following major processes: (1) direct temperature effects on photosynthesis and respiration; (2) speed-up growth rate and the shortening of growing season; (3) heat stress during reproductive stage (flowering and grain-filling); (4) high-temperature induced increase of atmospheric water demands. In this work, we use a newly developed modeling framework (CLM-APSIM) to simulate the corn and soybean growth and explicitly parse the above four processes. By combining the strength of CLM in modeling surface biophysical (e.g., hydrology and energy balance) and biogeochemical (e.g., photosynthesis and carbon-nitrogen interactions), as well as that of APSIM in modeling crop phenology and reproductive stress, the newly developed CLM-APSIM modeling framework enables us to diagnose the impacts of high temperature stress through different processes at various crop phenology stages. Ground measurements from the advanced SoyFACE facility at University of Illinois is used here to calibrate, validate, and improve the CLM-APSIM modeling framework at the site level. We finally use the CLM-APSIM modeling framework to project crop yield for the whole US Corn Belt under different climate scenarios.

  1. Effect of Integrated Nutrient Management on Yield and Yield ...

    African Journals Online (AJOL)

    Declining soil fertility is one of the major problems causing yield reduction of barley ... (VC) with inorganic NP on growth, yield and yield components of food barley. ... The experiments were laid out in a randomized complete block design with ...

  2. 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.

  3. Yield gap analysis of Chickpea under semi-arid conditions: A simulation study

    OpenAIRE

    seyed Reza Amiri Deh ahmadi; mehdi parsa; mohammad bannayan aval; mahdi nassiri mahallati

    2016-01-01

    Yield gap analysis provides an essential framework to prioritize research and policy efforts aimed at reducing yield constraints. To identify options for increasing chickpea yield, the SSM-chickpea model was parameterized and evaluated to analyze yield potentials, water limited yields and yield gaps for nine regions representing major chickpea-growing areas of Razavi Khorasan province. The average potential yield of chickpea for the locations was 2251 kg ha-1, while the water limited yield wa...

  4. 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

  5. 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.

  6. Yield trends and yield gap analysis of major crops in the world

    OpenAIRE

    Hengsdijk, H.; Langeveld, J.W.A.

    2009-01-01

    This study aims to quantify the gap between current and potential yields of major crops in the world, and the production constraints that contribute to this yield gap. Using an expert-based evaluation of yield gaps and the literature, global and regional yields and yield trends of major crops are quantified, yield gaps evaluated by crop experts, current yield progress by breeding estimated, and different yield projections compared. Results show decreasing yield growth for wheat and rice, but ...

  7. 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...

  8. 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

  9. 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.

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

    Science.gov (United States)

    Chang, Shuhua; Wang, Xinyu

    2015-01-01

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

  11. 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.

  12. 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

  13. Archiving InSight Lander Science Data Using PDS4 Standards

    Science.gov (United States)

    Stein, T.; Guinness, E. A.; Slavney, S.

    2017-12-01

    The InSight Mars Lander is scheduled for launch in 2018, and science data from the mission will be archived in the NASA Planetary Data System (PDS) using the new PDS4 standards. InSight is a geophysical lander with a science payload that includes a seismometer, a probe to measure subsurface temperatures and heat flow, a suite of meteorology instruments, a magnetometer, an experiment using radio tracking, and a robotic arm that will provide soil physical property information based on interactions with the surface. InSight is not the first science mission to archive its data using PDS4. However, PDS4 archives do not currently contain examples of the kinds of data that several of the InSight instruments will produce. Whereas the existing common PDS4 standards were sufficient for most of archiving requirements of InSight, the data generated by a few instruments required development of several extensions to the PDS4 information model. For example, the seismometer will deliver a version of its data in SEED format, which is standard for the terrestrial seismology community. This format required the design of a new product type in the PDS4 information model. A local data dictionary has also been developed for InSight that contains attributes that are not part of the common PDS4 dictionary. The local dictionary provides metadata relevant to all InSight data sets, and attributes specific to several of the instruments. Additional classes and attributes were designed for the existing PDS4 geometry dictionary that will capture metadata for the lander position and orientation, along with camera models for stereo image processing. Much of the InSight archive planning and design work has been done by a Data Archiving Working Group (DAWG), which has members from the InSight project and the PDS. The group coordinates archive design, schedules and peer review of the archive documentation and test products. The InSight DAWG archiving effort for PDS is being led by the PDS Geosciences

  14. 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)...

  15. Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

    Science.gov (United States)

    Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

    2016-01-01

    We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

  16. A Covariance Generation Methodology for Fission Product Yields

    Directory of Open Access Journals (Sweden)

    Terranova N.

    2016-01-01

    Full Text Available Recent safety and economical concerns for modern nuclear reactor applications have fed an outstanding interest in basic nuclear data evaluation improvement and completion. It has been immediately clear that the accuracy of our predictive simulation models was strongly affected by our knowledge on input data. Therefore strong efforts have been made to improve nuclear data and to generate complete and reliable uncertainty information able to yield proper uncertainty propagation on integral reactor parameters. Since in modern nuclear data banks (such as JEFF-3.1.1 and ENDF/BVII.1 no correlations for fission yields are given, in the present work we propose a covariance generation methodology for fission product yields. The main goal is to reproduce the existing European library and to add covariance information to allow proper uncertainty propagation in depletion and decay heat calculations. To do so, we adopted the Generalized Least Square Method (GLSM implemented in CONRAD (COde for Nuclear Reaction Analysis and Data assimilation, developed at CEA-Cadarache. Theoretical values employed in the Bayesian parameter adjustment are delivered thanks to a convolution of different models, representing several quantities in fission yield calculations: the Brosa fission modes for pre-neutron mass distribution, a simplified Gaussian model for prompt neutron emission probability, theWahl systematics for charge distribution and the Madland-England model for the isomeric ratio. Some results will be presented for the thermal fission of U-235, Pu-239 and Pu-241.

  17. [Fission product yields of 60 fissioning reactions]. Final report

    International Nuclear Information System (INIS)

    Rider, B.F.

    1995-01-01

    In keeping with the statement of work, I have examined the fission product yields of 60 fissioning reactions. In co-authorship with the UTR (University Technical Representative) Talmadge R. England ''Evaluation and Compilation of Fission Product Yields 1993,'' LA-UR-94-3106(ENDF-349) October, (1994) was published. This is an evaluated set of fission product Yields for use in calculation of decay heat curves with improved accuracy has been prepared. These evaluated yields are based on all known experimental data through 1992. Unmeasured fission product yields are calculated from charge distribution, pairing effects, and isomeric state models developed at Los Alamos National Laboratory. The current evaluation has been distributed as the ENDF/B-VI fission product yield data set

  18. The "Insight Paradox" in Schizophrenia: Magnitude, Moderators and Mediators of the Association Between Insight and Depression.

    Science.gov (United States)

    Belvederi Murri, Martino; Amore, Mario; Calcagno, Pietro; Respino, Matteo; Marozzi, Valentina; Masotti, Mattia; Bugliani, Michele; Innamorati, Marco; Pompili, Maurizio; Galderisi, Silvana; Maj, Mario

    2016-09-01

    The so-called "insight paradox" posits that among patients with schizophrenia higher levels of insight are associated with increased levels of depression. Although different studies examined this issue, only few took in account potential confounders or factors that could influence this association. In a sample of clinically stable patients with schizophrenia, insight and depression were evaluated using the Scale to assess Unawareness of Mental Disorder and the Calgary Depression Scale for Schizophrenia. Other rating scales were used to assess the severity of psychotic symptoms, extrapyramidal symptoms, hopelessness, internalized stigma, self-esteem, and service engagement. Regression models were used to estimate the magnitude of the association between insight and depression while accounting for the role of confounders. Putative psychological and sociodemographic factors that could act as mediators and moderators were examined using the PROCESS macro. By accounting for the role of confounding factors, the strength of the association between insight into symptoms and depression increased from 13% to 25% explained covariance. Patients with lower socioeconomic status (F = 8.5, P = .04), more severe illness (F = 4.8, P = .03) and lower levels of service engagement (F = 4.7, P = .03) displayed the strongest association between insight and depression. Lastly, hopelessness, internalized stigma and perceived discrimination acted as significant mediators. The relationship between insight and depression should be considered a well established phenomenon among patients with schizophrenia: it seems stronger than previously reported especially among patients with lower socioeconomic status, severe illness and poor engagement with services. These findings may have relevant implications for the promotion of insight among patients with schizophrenia. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved

  19. 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...

  20. 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.

  1. 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.

  2. 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.

  3. Application of DSSAT-CROPGRO-Cotton Model to Assess Long Term (1924-2012) Cotton Yield under Different Irrigation Management Strategies

    Science.gov (United States)

    Adhikari, P.; Gowda, P. H.; Northup, B. K.; Rocateli, A.

    2017-12-01

    In this study a well calibrated and validated DSSAT-CROPGRO-Cotton model was used for assessing the irrigation management in the Texas High Plains (THP). Long term (1924-2012) historic lint yield were simulated under different irrigation management practices which were commonly used in the THP. The simulation treatments includes different amount of irrigation water high (H; 6.4 mm d-1), medium (M; 3.2 mm d-1) and low (L; 0 mm d-1) during emergence (S1), vegetative (S2) and maturity (S3) stage. The combination of these treatments resulted into 27 treatments. The amount and date of irrigation for each stage were obtained from the recent cotton irrigation experiment at Halfway, TX (Brodovsky, et al., 2015). Similarly, calibrated model was also used to observe the effect of plantation date on crop yield in the THP regions.

  4. Yield gap analysis in long-term experiments with intensive rice cultivation

    International Nuclear Information System (INIS)

    Laureles, E.V.; Correa, T. Jr.; Buresh, R.J.

    2007-01-01

    The long-term continuous cropping experiment at IRRI is cultivated with three rice crops in a year, making it the world's most intensively cropped long-term rice experiment. The availability of comprehensive rice production records, compiled weather data, and tested crop models provides a means to evaluate long-term trends in measured and potential yields and yield gaps in this rice production system. Yield trends were assessed using the highest yielding cultivar in each cropping season from 1979 to 2005. Potential yield of the highest yielding cultivar in each season was determined using three rice models (ORYZA, TERM, and CERES) run with the actual transplanting and harvest dates for the cultivar. The yield gap was determined from the difference between the simulated potential grain yield and the measured grain yield. Measured and potential yields and the yield gap varied across seasons and years. Measured yields were higher in the dry season than in the early and late wet seasons. The yield gap tended to be higher in the wet season than in the dry season. Climatic parameters, particularly solar radiation, influenced the performance of rice cultivars. The relatively larger yield gaps in the late wet season than in the dry season were associated with increased spikelet sterility. The cumulative measured yield for the three annual rice crop was near 80 percent of the annual yield potential in years with best practices for fertilizer N and crop management. The long term trends suggest that effective timing and rates of N fertilization and effective control of diseases were critical in achieving 80 percent of the annual yield potential

  5. 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

  6. 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.

  7. 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.

  8. Use of Aquacrop Model to predict Maize Yields under Varying Rainfall and Temperature in a Semi-Arid Environment in Kenya

    International Nuclear Information System (INIS)

    Wamari, O. J.; Sijali, V. I; Heng, N. K; Joseph Mutwiri Miriti, M. J; Esilaba, O A

    2012-01-01

    There has been increasing concern that drier and hotter seasons are becoming more frequent due to climate change especially in semi-arid environments causing adverse effects on agricultural production. Analysis of long-term (1980-2010) trends of rainfall in the first growing season (i.e. March and July) at Katumani, Kenya showed that about 55% of the seasons were below the long-term average, with an all time low occurring in the year 2000. Although the wettest years (1998 and 1985 ) had relatively higher percentages above the long-term average (143.9% and 138.4% ) compared to lower percentages ( 61.7% and 59.7%) of the driest years ( 2000 and 1987), the latter were relatively less in numbers (i.e. 45%). Mean seasonal temperatures however did not show high variation from the long term mean implying that rainfall was the main cause of yield variation in this area. The AquaCrop model (Ver. 3.1) evaluated using three years (i.e. 1999, 2000 and 2001) of experimental results at Katumani, gave reasonable estimates of above ground biomass and grain yield of Katumani composite maize variety. The model was then used to predict Katumani maize yields under 20% depletion of rainfall and 3°C temperature elevation scenarios. Biomass and grain yields simulated respectively ranged between 2.971 to 6.558 and 0.910 to 2.564 T Ha-1 with probabilities of obtaining 3-5 T Ha-1 biomass and 1-2 T Ha-1 grain yields each dropping from 98 to 25%. Adaptation measures are given as management recommendations in line with the changed climatic scenario. (author)

  9. Effects of rainfall intensity and slope gradient on runoff and sediment yield characteristics of bare loess soil.

    Science.gov (United States)

    Wu, Lei; Peng, Mengling; Qiao, Shanshan; Ma, Xiao-Yi

    2018-02-01

    Soil erosion is a universal phenomenon on the Loess Plateau but it exhibits complex and typical mechanism which makes it difficult to understand soil loss laws on slopes. We design artificial simulated rainfall experiments including six rainfall intensities (45, 60, 75, 90, 105, 120 mm/h) and five slopes (5°, 10°, 15°, 20°, 25°) to reveal the fundamental changing trends of runoff and sediment yield on bare loess soil. Here, we show that the runoff yield within the initial 15 min increased rapidly and its trend gradually became stable. Trends of sediment yield under different rainfall intensities are various. The linear correlation between runoff and rainfall intensity is obvious for different slopes, but the correlations between sediment yield and rainfall intensity are weak. Runoff and sediment yield on the slope surface both presents an increasing trend when the rainfall intensity increases from 45 mm/h to 120 mm/h, but the increasing trend of runoff yield is higher than that of sediment yield. The sediment yield also has an overall increasing trend when the slope changes from 5° to 25°, but the trend of runoff yield is not obvious. Our results may provide data support and underlying insights needed to guide the management of soil conservation planning on the Loess Plateau.

  10. Predicting Great Lakes fish yields: tools and constraints

    Science.gov (United States)

    Lewis, C.A.; Schupp, D.H.; Taylor, W.W.; Collins, J.J.; Hatch, Richard W.

    1987-01-01

    Prediction of yield is a critical component of fisheries management. The development of sound yield prediction methodology and the application of the results of yield prediction are central to the evolution of strategies to achieve stated goals for Great Lakes fisheries and to the measurement of progress toward those goals. Despite general availability of species yield models, yield prediction for many Great Lakes fisheries has been poor due to the instability of the fish communities and the inadequacy of available data. A host of biological, institutional, and societal factors constrain both the development of sound predictions and their application to management. Improved predictive capability requires increased stability of Great Lakes fisheries through rehabilitation of well-integrated communities, improvement of data collection, data standardization and information-sharing mechanisms, and further development of the methodology for yield prediction. Most important is the creation of a better-informed public that will in turn establish the political will to do what is required.

  11. Impact assessment of recent climate change on rice yields in the Heilongjiang Reclamation Area of north-east China.

    Science.gov (United States)

    Zhou, Yang; Li, Ning; Dong, Guanpeng; Wu, Wenxiang

    2013-08-30

    Investigating the degree to which climate change may have impacted on rice yields can provide an insight into how to adapt to climate change in the future. Meteorological and rice yield data over the period 1960-2009 from the Heilongjiang Reclamation Area of north-east China (HRANC) were used to explore the possible impacts of climate change on rice yields at sub-regional scale. Results showed that a warming trend was obvious in the HRANC and discernible climate fluctuations and yield variations on inter-annual scale were detected to have occurred in the 1980s and 1990s, respectively. Statistically positive correlation was observed between growing season temperature and rice yields, with an increase rate by approximately 3.60% for each 1°C rise in the minimum temperature during growing season. Such findings are consistent with the current mainstream view that warming climate may exert positive impacts on crop yields in the middle and higher latitude regions. Our study indicated that the growing season minimum temperature was a major driver of all the climatic factors to the recent increase trends in rice yield in HRANC over the last five decades. © 2013 Society of Chemical Industry.

  12. Systematics of neutron-induced fission yields

    International Nuclear Information System (INIS)

    Blachot, J.; Brissot, R.

    1983-10-01

    The main characteristics of the mass and charge distributions for thermal neutron induced fission of actinides are reviewed. We show that these distributions can be reasonably reproduced with only 24 data as input. We use a representation where the element yields together with the most probable mass Ap(Z) play the dominant role. The ability of this model to calculate mass yields for the fission of not yet measured actinides is also shown. The influence of the excitation energy of the fissile system on charge and mass distribution is also discussed

  13. New approach for regional crop yield gap analysis in the Borujen ...

    African Journals Online (AJOL)

    enoh

    2012-03-20

    Mar 20, 2012 ... for model calibration and evaluation of WOFOST as a crop growth ... In general, simulated results matched well with the measured ... regional-scale yield prediction and assessment (Jagtap ... the benchmark value and most of the variation in yield ... The model simulates daily crop growth rate, based on.

  14. Quantitative analysis of microbial biomass yield in aerobic bioreactor.

    Science.gov (United States)

    Watanabe, Osamu; Isoda, Satoru

    2013-12-01

    We have studied the integrated model of reaction rate equations with thermal energy balance in aerobic bioreactor for food waste decomposition and showed that the integrated model has the capability both of monitoring microbial activity in real time and of analyzing biodegradation kinetics and thermal-hydrodynamic properties. On the other hand, concerning microbial metabolism, it was known that balancing catabolic reactions with anabolic reactions in terms of energy and electron flow provides stoichiometric metabolic reactions and enables the estimation of microbial biomass yield (stoichiometric reaction model). We have studied a method for estimating real-time microbial biomass yield in the bioreactor during food waste decomposition by combining the integrated model with the stoichiometric reaction model. As a result, it was found that the time course of microbial biomass yield in the bioreactor during decomposition can be evaluated using the operational data of the bioreactor (weight of input food waste and bed temperature) by the combined model. The combined model can be applied to manage a food waste decomposition not only for controlling system operation to keep microbial activity stable, but also for producing value-added products such as compost on optimum condition. Copyright © 2013 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

  15. 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 ...

  16. 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.

  17. Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

    Science.gov (United States)

    Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

    2016-01-01

    We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

  18. Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

    Directory of Open Access Journals (Sweden)

    Holger Hoffmann

    Full Text Available We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

  19. Fluence-dependent sputtering yield of micro-architectured materials

    Energy Technology Data Exchange (ETDEWEB)

    Matthes, Christopher S.R.; Ghoniem, Nasr M., E-mail: ghoniem@ucla.edu; Li, Gary Z.; Matlock, Taylor S.; Goebel, Dan M.; Dodson, Chris A.; Wirz, Richard E.

    2017-06-15

    Highlights: • Sputtering yield is shown to be transient and heavily dependent on surface architecture. • Fabricated nano- and Microstructures cause geometric re-trapping of sputtered material, which leads to a self-healing mechanism. • Initially, the sputtering yield of micro-architectured Mo is approximately 1/2 the value as that of a planar surface. • The study demonstrates that the sputtering yield is a dynamic property, dependent on the surface structure of a material. • A developed phenomenological model mathematically describes the transient behavior of the sputtering yield as a function of plasma fluence. - Abstract: We present an experimental examination of the relationship between the surface morphology of Mo and its instantaneous sputtering rate as function of low-energy plasma ion fluence. We quantify the dynamic evolution of nano/micro features of surfaces with built-in architecture, and the corresponding variation in the sputtering yield. Ballistic deposition of sputtered atoms as a result of geometric re-trapping is observed, and re-growth of surface layers is confirmed. This provides a self-healing mechanism of micro-architectured surfaces during plasma exposure. A variety of material characterization techniques are used to show that the sputtering yield is not a fundamental property, but that it is quantitatively related to the initial surface architecture and to its subsequent evolution. The sputtering yield of textured molybdenum samples exposed to 300 eV Ar plasma is roughly 1/2 of the corresponding value for flat samples, and increases with ion fluence. Mo samples exhibited a sputtering yield initially as low as 0.22 ± 5%, converging to 0.4 ± 5% at high fluence. The sputtering yield exhibits a transient behavior as function of the integrated ion fluence, reaching a steady-state value that is independent of initial surface conditions. A phenomenological model is proposed to explain the observed transient sputtering phenomenon, and to

  20. 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

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

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

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

  2. 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.

  3. Microstructure, Slip Systems and Yield Stress Anisotropy in Plastic Deformation

    DEFF Research Database (Denmark)

    Winther, Grethe; You, Ze Sheng; Lu, Lei

    The highly anisotropic microstructures in nanotwinned copper produced by electrodeposition provide an excellent opportunity to evaluate models for microstructurally induced mechanical anisotropy. A crystal plasticity model originally developed for the integration of deformation induced dislocatio...... boundaries with texture is applied to account for the effects of texture as well as twin and grain boundaries, providing good qualitative agreement with experimental yield stress and yield stress anisotropy data....

  4. 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.

  5. 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...

  6. Yield, yield components and dry matter digestibility of alfalfa experimental populations

    Directory of Open Access Journals (Sweden)

    Katić Slobodan

    2010-01-01

    Full Text Available Alfalfa is the most important forage crop grown in the temperate regions. It is cultivated for production of vegetative aerial mass used fresh or as hay, and recently as haylage and silage. In many centres worldwide, efforts are made to breed and create new alfalfa cultivars with both higher yields and of higher nutritional value. The aim of this paper was to determine yield and digestibility of 12 experimental populations of alfalfa, and to compare their results to the yields of well-known domestic alfalfa commercial cultivars. The results show significant differences in yield of green forage and dry matter among alfalfa populations, as well as in yield components, height, proportion of leaves in yield and growth rate (tab. 1, 2 and 3. Differences between in vitro digestible dry matter (% and yields of in vitro digestible dry matter (t ha-1 were also significant (tab. 5 and 6. Yield and quality of experimental populations were at the same level or higher than of control cultivars. Synthetic SINUSA exceeded the control cutivars (NS Mediana ZMS V and Banat VS in yield and quality of dry matter. .

  7. 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

  8. Analysis of the static yield stress for giant electrorheological fluids

    Science.gov (United States)

    Seo, Youngwook P.; Choi, Hyoung Jin; Seo, Yongsok

    2017-08-01

    Cheng et al. (2010)'s experimental results for the static yield stress of giant electrorheological (GER) fluids over the full range of electric field strengths were reanalyzed by applying Seo's scaling function which could include both the polarization and the conductivity models. The Seo's scaling function could correctly fit the yield stress behavior of GER suspensions behavior after if a proper normalization of the yield stress data was taken which collapse them onto a single curve. The model predictions were also contrasted with recently proposed Choi et al.'s scaling function to rouse the attention for a proper consideration of the GER fluid mechanisms.

  9. Changes in yields and their variability at different levels of global warming

    Science.gov (United States)

    Childers, Katelin

    2015-04-01

    An assessment of climate change impacts at different levels of global warming is crucial to inform the political discussion about mitigation targets as well as for the inclusion of climate change impacts in Integrated Assessment Models (IAMs) that generally only provide global mean temperature change as an indicator of climate change. While there is a well-established framework for the scalability of regional temperature and precipitation changes with global mean temperature change we provide an assessment of the extent to which impacts such as crop yield changes can also be described in terms of global mean temperature changes without accounting for the specific underlying emissions scenario. Based on multi-crop-model simulations of the four major cereal crops (maize, rice, soy, and wheat) on a 0.5 x 0.5 degree global grid generated within ISI-MIP, we show the average spatial patterns of projected crop yield changes at one half degree warming steps. We find that emissions scenario dependence is a minor component of the overall variance of projected yield changes at different levels of global warming. Furthermore, scenario dependence can be reduced by accounting for the direct effects of CO2 fertilization in each global climate model (GCM)/impact model combination through an inclusion of the global atmospheric CO2 concentration as a second predictor. The choice of GCM output used to force the crop model simulations accounts for a slightly larger portion of the total yield variance, but the greatest contributor to variance in both global and regional crop yields and at all levels of warming, is the inter-crop-model spread. The unique multi impact model ensemble available with ISI-MIP data also indicates that the overall variability of crop yields is projected to increase in conjunction with increasing global mean temperature. This result is consistent throughout the ensemble of impact models and across many world regions. Such a hike in yield volatility could have

  10. Slope Controls Grain Yield and Climatic Yield in Mountainous Yunnan province, China

    Science.gov (United States)

    Duan, X.; Rong, L.; Gu, Z.; Feng, D.

    2017-12-01

    Mountainous regions are increasingly vulnerable to food insecurity because of limited arable land, growing population pressure, and climate change. Development of sustainable mountain agriculture will require an increased understanding of the effects of environmental factors on grain and climatic yields. The objective of this study was to explore the relationships between actual grain yield, climatic yield, and environmental factors in a mountainous region in China. We collected data on the average grain yield per unit area in 119 counties in Yunnan province from 1985 to 2012, and chose 17 environmental factors for the same period. Our results showed that actual grain yield ranged from 1.43 to 6.92 t·ha-1, and the climatic yield ranged from -0.15 to -0.01 t·ha-1. Lower climatic yield but higher grain yield was generally found in central areas and at lower slopes and elevations in the western and southwestern counties of Yunnan province. Higher climatic yield but lower grain yield were found in northwestern parts of Yunnan province on steep slopes. Annual precipation and temperature had a weak influence on the climatic yield. Slope explained 44.62 and 26.29% of the variation in grain yield and climatic yield. The effects of topography on grain and climatic yields were greater than climatic factors. Slope was the most important environmental variable for the variability in climatic and grain yields in the mountainous Yunnan province due to the highly heterogeneous topographic conditions. Conversion of slopes to terraces in areas with higher climatic yields is an effective way to maintain grain production in response to climate variability. Additionally, soil amendments and soil and water conservation measures should be considered to maintain soil fertility and aid in sustainable development in central areas, and in counties at lower slopes and elevations in western and southwestern Yunnan province.

  11. ENDF/B yield evaluation for 1992: Methods and content

    International Nuclear Information System (INIS)

    England, T.R.; Rider, B.F.

    1992-01-01

    The basic evaluation process, completed in May 1992, for 60 independent, plus corresponding cumulative yield sets is described thirty-six fissioning nuclides at one-or-more neutron fission energies or spontaneous fission are included. The resulting recommended yields include approximately 1200 nuclides per set; these will be slightly extended to encompass all nuclides in the ENDF/B-VI decay files and issued as the second release of ENDF/B-VI yields. All current yield sets in ENDF/B-VI have been reevaluated using ∼3000 new measurements and model parameters for distribution along mass chains. Compiled measurements through 1992 will be included in the documentation of the recommended yields. This paper can only summarize the primary features of the evaluations

  12. The use of additives for reducing hydrogen yield in mortar containing slag and chloride salts

    International Nuclear Information System (INIS)

    Lewis, M.A.; Warren, D.W.

    1989-01-01

    Cementitious waste forms are being considered for immobilizing nuclear waste before disposal. In earlier work, it was found that irradiation of a mortar formulation consisting of slag, portland cement, fly ash, water, and up to 10 wt% KCl endash LiCl salt resulted in the generation of hydrogen. Yields were relatively high and the rates of generation were constant for the irradiation period investigated. The addition of small amounts of oxygen-rich electron scavengers to the mortar was investigated as a means for reducing hydrogen yields. The addition of NaNO 3 reduced the hydrogen yield; changed the radiolytic products from hydrogen to a mixture of hydrogen, nitrogen, and N 2 O; and reduced the pressurization rate after exposure to 400 Mrads. The addition of NaIO 4 and KMnO 4 reduced hydrogen yields slightly while the addition of Ag 2 O increased the yield. Moreover, the addition of FeS to a non-slag mortar changed the radiolysis mechanism but the addition of FeO did not. The results of these experiments provided an insight into the nature of the radiolytic reactions occurring in the mortar formulations and indicated that the radiolytic generation of gases might be controlled with the proper choice of additive. 14 refs., 3 figs., 2 tabs

  13. Understanding the Changes in Global Crop Yields Through Changes in Climate and Technology

    Science.gov (United States)

    Najafi, Ehsan; Devineni, Naresh; Khanbilvardi, Reza M.; Kogan, Felix

    2018-03-01

    During the last few decades, the global agricultural production has risen and technology enhancement is still contributing to yield growth. However, population growth, water crisis, deforestation, and climate change threaten the global food security. An understanding of the variables that caused past changes in crop yields can help improve future crop prediction models. In this article, we present a comprehensive global analysis of the changes in the crop yields and how they relate to different large-scale and regional climate variables, climate change variables and technology in a unified framework. A new multilevel model for yield prediction at the country level is developed and demonstrated. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. El Niño-southern oscillation (ENSO), Palmer drought severity index (PDSI), geopotential height anomalies (GPH), historical carbon dioxide (CO2) concentration and country-based time series of GDP per capita as an approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2013. Results indicate that these variables can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications. While some countries were not generally affected by climatic factors, PDSI and GPH acted both positively and negatively in different regions for crop yields in many countries.

  14. ISOL yield predictions from holdup-time measurements

    International Nuclear Information System (INIS)

    Spejewski, Eugene H.; Carter, H Kennon; Mervin, Brenden T.; Prettyman, Emily S.; Kronenberg, Andreas; Stracener, Daniel W

    2008-01-01

    A formalism based on a simple model is derived to predict ISOL yields for all isotopes of a given element based on a holdup-time measurement of a single isotope of that element. Model predictions, based on parameters obtained from holdup-time measurements, are compared to independently-measured experimental values

  15. Adjusting slash pine growth and yield for silvicultural treatments

    Science.gov (United States)

    Stephen R. Logan; Barry D. Shiver

    2006-01-01

    With intensive silvicultural treatments such as fertilization and competition control now commonplace in today's slash pine (Pinus elliottii Engelm.) plantations, a method to adjust current growth and yield models is required to accurately account for yield increases due to these practices. Some commonly used ad-hoc methods, such as raising site...

  16. Variability in yield of faba beans (Vicia faba L.)

    NARCIS (Netherlands)

    Grashoff, C.

    1992-01-01

    Yield variability is one of the major problems in growing faba beans. In this thesis, the effect of water supply pattern on yield variability of the crop is studied with experiments in the field and under controlled conditions, and with a simulation model. In a series of field experiments,

  17. Simulating maize yield and bomass with spatial variability of soil field capacity

    Science.gov (United States)

    Ma, Liwang; Ahuja, Lajpat; Trout, Thomas; Nolan, Bernard T.; Malone, Robert W.

    2015-01-01

    Spatial variability in field soil properties is a challenge for system modelers who use single representative values, such as means, for model inputs, rather than their distributions. In this study, the root zone water quality model (RZWQM2) was first calibrated for 4 yr of maize (Zea mays L.) data at six irrigation levels in northern Colorado and then used to study spatial variability of soil field capacity (FC) estimated in 96 plots on maize yield and biomass. The best results were obtained when the crop parameters were fitted along with FCs, with a root mean squared error (RMSE) of 354 kg ha–1 for yield and 1202 kg ha–1 for biomass. When running the model using each of the 96 sets of field-estimated FC values, instead of calibrating FCs, the average simulated yield and biomass from the 96 runs were close to measured values with a RMSE of 376 kg ha–1 for yield and 1504 kg ha–1 for biomass. When an average of the 96 FC values for each soil layer was used, simulated yield and biomass were also acceptable with a RMSE of 438 kg ha–1 for yield and 1627 kg ha–1 for biomass. Therefore, when there are large numbers of FC measurements, an average value might be sufficient for model inputs. However, when the ranges of FC measurements were known for each soil layer, a sampled distribution of FCs using the Latin hypercube sampling (LHS) might be used for model inputs.

  18. Fission product yield evaluation for the USA evaluated nuclear data files

    International Nuclear Information System (INIS)

    Rider, B.F.; England, T.R.

    1994-01-01

    An evaluated set of fission product yields for use in calculation of decay heat curves with improved accuracy has been prepared. These evaluated yields are based on all known experimental data through 1992. Unmeasured fission product yields are calculated from charge distribution, pairing effects, and isomeric state models developed at Los Alamos National Laboratory. The current evaluation has been distributed as the ENDF/B-VI fission product yield data set

  19. Yield trends and yield gap analysis of major crops in the world

    NARCIS (Netherlands)

    Hengsdijk, H.; Langeveld, J.W.A.

    2009-01-01

    This study aims to quantify the gap between current and potential yields of major crops in the world, and the production constraints that contribute to this yield gap. Using an expert-based evaluation of yield gaps and the literature, global and regional yields and yield trends of major crops are

  20. 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.

  1. Remotely sensed rice yield prediction using multi-temporal NDVI data derived from NOAA's-AVHRR.

    Science.gov (United States)

    Huang, Jingfeng; Wang, Xiuzhen; Li, Xinxing; Tian, Hanqin; Pan, Zhuokun

    2013-01-01

    Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha(-1). Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly.

  2. Measure of the e+e-{yields}bb Cross Section at the LEP Energies; Medida de la seccion eficaz e''+e''-{yields}bb a las Energias de LEP

    Energy Technology Data Exchange (ETDEWEB)

    Arce Dubois, P

    1992-07-01

    In the present work I analyse the data collected during 1990 by the L3 detector, situated in the electron-positron collider LEP. After selecting the events e''+e''-{yields} bb through their semileptonic decays into muons, I calculate the cross section for the process e''+e''- {yields} bb at different energy points around the mass of the vectorial boson Z, and I measure some parameters of the Standard Model, namely, the Br(b{yields}{mu} ),{gamma}{sub z}n-{yields}bb/{gamma}{sub z}n{yields}had and {gamma}{sub z}n{yields}bb{gamma}{sub z}n{yields}e''+e''-. (Author) 26 refs.

  3. 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.

  4. 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...

  5. Insights to Engineered Geothermal System Performance Using Gringarten-Witherspoon-Ohnishi Analytical Solutions and Fracture Network Models

    Science.gov (United States)

    Doe, T.; McLaren, R.; Finilla, A.

    2017-12-01

    An enduring legacy of Paul Witherspoon and his students and colleagues has been both the development of geothermal energy and the bases of modern fractured-rock hydrogeology. One of the seminal contributions to the geothermal field was Gringarten, Witherspoon, and Ohnishi's analytical models for enhanced geothermal systems. Although discrete fracture network (DFN) modeling developed somewhat independently in the late 1970s, Paul Witherspoon's foresight in promoting underground in situ testing at the Stripa Mine in Sweden was a major driver in Lawrence Berkeley Laboratory's contributions to its development.This presentation looks extensions of Gringarten's analytical model into discrete fracture network modeling as a basis for providing further insights into the challenges and opportunities of engineered geothermal systems. The analytical solution itself has many insightful applications beyond those presented in the original paper. The definition of dimensionless time by itself shows that thermal breakthrough has a second power dependence on surface area and on flow rate. The fracture intensity also plays a strong role, as it both increases the surface area and decrease his flow rate per fracture. The improvement of EGS performance with fracture intensity reaches a limit where thermal depletion of the rock lags only slightly behind the thermal breakthrough of cold water in the fracture network.Simple network models, which couple a DFN generator (FracMan) with a hydrothermally coupled flow solver (HydroGeoSphere) expand on Gringarten's concepts to show that realistic heterogeneity of spacing and transmissivity significantly degrades EGS performance. EGS production in networks of stimulated fractures initially follows Gringarten's type curves, with a later deviation is the smaller rock blocks thermally deplete and the entire stimulated volume acts as a single sink. Three-dimensional models of EGS performance show the critical importance of the relative magnitudes of

  6. 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.

  7. Changes in crop yields and their variability at different levels of global warming

    Science.gov (United States)

    Ostberg, Sebastian; Schewe, Jacob; Childers, Katelin; Frieler, Katja

    2018-05-01

    An assessment of climate change impacts at different levels of global warming is crucial to inform the policy discussion about mitigation targets, as well as for the economic evaluation of climate change impacts. Integrated assessment models often use global mean temperature change (ΔGMT) as a sole measure of climate change and, therefore, need to describe impacts as a function of ΔGMT. There is already a well-established framework for the scalability of regional temperature and precipitation changes with ΔGMT. It is less clear to what extent more complex biological or physiological impacts such as crop yield changes can also be described in terms of ΔGMT, even though such impacts may often be more directly relevant for human livelihoods than changes in the physical climate. Here we show that crop yield projections can indeed be described in terms of ΔGMT to a large extent, allowing for a fast estimation of crop yield changes for emissions scenarios not originally covered by climate and crop model projections. We use an ensemble of global gridded crop model simulations for the four major staple crops to show that the scenario dependence is a minor component of the overall variance of projected yield changes at different levels of ΔGMT. In contrast, the variance is dominated by the spread across crop models. Varying CO2 concentrations are shown to explain only a minor component of crop yield variability at different levels of global warming. In addition, we find that the variability in crop yields is expected to increase with increasing warming in many world regions. We provide, for each crop model, geographical patterns of mean yield changes that allow for a simplified description of yield changes under arbitrary pathways of global mean temperature and CO2 changes, without the need for additional climate and crop model simulations.

  8. Measurement of jets production in association with a Z boson and in the search for the SM Higgs boson via H {yields} {tau}{tau} {yields} ll + 4{nu} with ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Psoroulas, Serena

    2012-10-15

    Three measurements focussing on the understanding of jet final states in ATLAS, in dijet, Z and Higgs boson candidate events, using data corresponding to an integrated luminosity of 35 pb{sup -1} in 2010 and 4.7 fb{sup -1} in 2011, are presented. In the first part, a calibration method, based on the transverse momentum balance in dijet events, is described. The method is used to estimate the uncertainty of the jet energy scale in the forward region. The results show that the parton shower models are limited in reproducing the results in data, mostly for jets of low transverse momentum. In the second part, the differential cross section measurement of the Z{yields}ll+jets process is reported. Phase space regions not been previously studied at other experiments are investigated. The models used for the theory predictions provide a good description of the data, within the relative uncertainties. In the last part, two contribution to the Higgs searches in the H {yields}{tau}{tau} channel are shown: the modelling of the Z{yields}{tau}{tau} background, and the modelling of jet final states. The Z{yields}{tau}{tau} background is derived from data and validated in the H{yields}{tau}{tau}{yields}ll+4{nu} channel. The modelling of jet final states in simulations is in good agreement with the data, when low-energy pile-up effects are subtracted.

  9. 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...

  10. Uncertainty in Simulating Wheat Yields Under Climate Change

    Science.gov (United States)

    Asseng, S.; Ewert, F.; Rosenzweig, Cynthia; Jones, J. W.; Hatfield, J. W.; Ruane, A. C.; Boote, K. J.; Thornburn, P. J.; Rotter, R. P.; Cammarano, D.; hide

    2013-01-01

    Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1,3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking.

  11. The ASIND-MEPhI library of independent actinide fission product yields

    International Nuclear Information System (INIS)

    Bogomolova, E.S.; Grashin, A.F.; Efimenko, A.D.; Lukasevich, I.B.

    1997-01-01

    This data base of independent fission product yields has been set up at the Moscow Engineering Physics Institute on the basis of theoretical calculations within the framework of the super-nonequilibrium thermodynamic model. The database consists of independent yield sets for 1163 fission products in the wide range of fissile nuclides from thorium-229 to fermium-257 with excitation energies up to 20 MeV. The use of the theoretical model made it possible to raise the accuracy of prediction for poorly explored fission reactions. The number of yield sets is larger than in the ENDF/B. For example, photofission product yields are included in the ASIND-MEPhI database as virtual sets. (author). 14 refs, 17 figs, 2 tabs

  12. Lowland rice yield estimates based on air temperature and solar radiation

    International Nuclear Information System (INIS)

    Pedro Júnior, M.J.; Sentelhas, P.C.; Moraes, A.V.C.; Villela, O.V.

    1995-01-01

    Two regression equations were developed to estimate lowland rice yield as a function of air temperature and incoming solar radiation, during the crop yield production period in Pindamonhangaba, SP, Brazil. The following rice cultivars were used: IAC-242, IAC-100, IAC-101 and IAC-102. The value of optimum air temperature obtained was 25.0°C and of optimum global solar radiation was 475 cal.cm -2 , day -1 . The best agrometeorological model was the one that related least deviation of air temperature and solar radiation in relation to the optimum value obtained through a multiple linear regression. The yield values estimated by the model showed good fit to actual yields of lowland rice (less than 10%). (author) [pt

  13. On yield gaps and yield gains in intercropping

    NARCIS (Netherlands)

    Gou, Fang; Yin, Wen; Hong, Yu; Werf, van der Wopke; Chai, Qiang; Heerink, Nico; Ittersum, van Martin K.

    2017-01-01

    Wheat-maize relay intercropping has been widely used by farmers in northwest China, and based on field experiments agronomists report it has a higher productivity than sole crops. However, the yields from farmers’ fields have not been investigated yet. Yield gap analysis provides a framework to

  14. Predicting spring barley yield from variety-specific yield potential, disease resistance and straw length, and from environment-specific disease loads and weed pressure

    DEFF Research Database (Denmark)

    Østergård, Hanne; Kristensen, Kristian; Pinnschmidt, Hans O.

    2008-01-01

    For low-input crop production, well-characterised varieties increase the possibilities of managing diseases and weeds. This analysis aims at developing a framework for analyzing grain yield using external varietal information about disease resistance, weed competitiveness and yield potential and ...... growth habit. Higher grain yield was thus predicted for taller plants under weed pressure. The results are discussed in relation to the model framework, impact of the considered traits and use of information from conventional variety testing in organic cropping systems....

  15. 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.

  16. KEY ISSUES REVIEW: Insights from simulations of star formation

    Science.gov (United States)

    Larson, Richard B.

    2007-03-01

    Although the basic physics of star formation is classical, numerical simulations have yielded essential insights into how stars form. They show that star formation is a highly nonuniform runaway process characterized by the emergence of nearly singular peaks in density, followed by the accretional growth of embryo stars that form at these density peaks. Circumstellar discs often form from the gas being accreted by the forming stars, and accretion from these discs may be episodic, driven by gravitational instabilities or by protostellar interactions. Star-forming clouds typically develop filamentary structures, which may, along with the thermal physics, play an important role in the origin of stellar masses because of the sensitivity of filament fragmentation to temperature variations. Simulations of the formation of star clusters show that the most massive stars form by continuing accretion in the dense cluster cores, and this again is a runaway process that couples star formation and cluster formation. Star-forming clouds also tend to develop hierarchical structures, and smaller groups of forming objects tend to merge into progressively larger ones, a generic feature of self-gravitating systems that is common to star formation and galaxy formation. Because of the large range of scales and the complex dynamics involved, analytic models cannot adequately describe many aspects of star formation, and detailed numerical simulations are needed to advance our understanding of the subject. 'The purpose of computing is insight, not numbers.' Richard W Hamming, in Numerical Methods for Scientists and Engineers (1962) 'There are more things in heaven and earth, Horatio, than are dreamt of in your philosophy.' William Shakespeare, in Hamlet, Prince of Denmark (1604)

  17. 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.

  18. Insight and analysis problem solving in microbes to machines.

    Science.gov (United States)

    Clark, Kevin B

    2015-11-01

    A key feature for obtaining solutions to difficult problems, insight is oftentimes vaguely regarded as a special discontinuous intellectual process and/or a cognitive restructuring of problem representation or goal approach. However, this nearly century-old state of art devised by the Gestalt tradition to explain the non-analytical or non-trial-and-error, goal-seeking aptitude of primate mentality tends to neglect problem-solving capabilities of lower animal phyla, Kingdoms other than Animalia, and advancing smart computational technologies built from biological, artificial, and composite media. Attempting to provide an inclusive, precise definition of insight, two major criteria of insight, discontinuous processing and problem restructuring, are here reframed using terminology and statistical mechanical properties of computational complexity classes. Discontinuous processing becomes abrupt state transitions in algorithmic/heuristic outcomes or in types of algorithms/heuristics executed by agents using classical and/or quantum computational models. And problem restructuring becomes combinatorial reorganization of resources, problem-type substitution, and/or exchange of computational models. With insight bounded by computational complexity, humans, ciliated protozoa, and complex technological networks, for example, show insight when restructuring time requirements, combinatorial complexity, and problem type to solve polynomial and nondeterministic polynomial decision problems. Similar effects are expected from other problem types, supporting the idea that insight might be an epiphenomenon of analytical problem solving and consequently a larger information processing framework. Thus, this computational complexity definition of insight improves the power, external and internal validity, and reliability of operational parameters with which to classify, investigate, and produce the phenomenon for computational agents ranging from microbes to man-made devices. Copyright

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

    Science.gov (United States)

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

    2016-01-01

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

  20. [Poor insight and psychosis].

    Science.gov (United States)

    Giotakos, O

    2017-01-01

    A variety of phenomena might be considered as reflecting impaired insight in psychosis, like failure to recognize signs, symptoms or disease, failure to derive appropriate cognitive representations, despite recognition of the disease, and misattribution of the source or cause of the disease. The unawareness of tardive dyskinesia symptoms in schizophrenic patients points that self-awareness deficits in schizophrenia may be domain specific. Poor insight is an independent phenomenological and a prevalent feature in psychotic disorders in general, and in schizophrenia in particular, but we don't know yet if delusions in schizophrenia are the result of an entirely normal attempt to account for abnormal perceptual experiences or a product of abnormal experience but of normal reasoning. The theoretical approaches regarding impaired insight include the disturbed perceptual input, the impaired linkage between thought and emotion and the breakdown of the process of self-monitoring and error checking. The inability to distinguish between internally and externally generated mental events has been described by the metarepresentation theory. This theory includes the awareness of ones' goals, which leads to disorders of willed action, the awareness of intention, which leads to movement disorders, and the awareness of intentions of others, which leads to paranoid delusions. The theory of metarepresentation implies mainly output mechanisms, like the frontal cortex, while the input mechanism implies posterior brain systems, including the parietal lobe. There are many similarities between the disturbances of awareness seen in schizophrenia and those seen as a result of known neurological impairment. Neuropsychological models of impaired insight typically attribute the disturbance to any of a variety of core deficits in the processing of information. In this respect, lack of insight is on conceptual par with alogia, apraxia or aphasia in reflecting disturbed cognitive processing. In

  1. Fission product yield data for the transmutation of minor actinide nuclear waste

    International Nuclear Information System (INIS)

    2008-04-01

    A report issued by an international study group for the transmutation of nuclear waste using accelerator driven systems has highlighted the need for specific sets of nuclear data. These authoritative requirements include fission product yields at an intermediate incident neutron energy of up to 150 MeV. Before the start of the present CRP on fission product yield data for the transmutation of nuclear waste, only four types of evaluated fission yield data sets existed, namely for spontaneous fission, and for fission induced by thermal, fast (or fission) spectrum, and by 'high energy' (14-15 MeV) neutrons. A new type of evaluation for energy dependent neutron induced fission yields was required for this project. In view of the scarcity of experimental data, such an evaluation has to be based on systematics and theoretical model calculations. Unlike fission cross-sections, where nuclear models are being used successfully for the calculation of unmeasured cross-section ranges, such models or theories existed only for low energy fission yields. Hence the CRP participants entered a completely new field of research for which the progress and outcome were unpredictable. Clearly the ultimate goal of such an effort, namely an evaluation of energy dependent fission yields, could not be realized within the perceived lifetime of a CRP. The main emphasis of the CRP was on the development of adequate systematics and models for the calculation of energy dependent fission yields up to 150 MeV incident neutron energy. Several problems had to be solved, such as the correct choice of model parameters and multiplicity distributions of emitted neutrons, and the effect of multi-chance fission. Models and systematics have been tested for lower energy yields, but they failed to reproduce recent experimental data, particularly at higher energies, and the parameters had to be modified. Other models have been developed from the analysis of experimental data in order to derive systematic

  2. 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.

  3. Optimizing selective cutting strategies for maximum carbon stocks and yield of Moso bamboo forest using BIOME-BGC model.

    Science.gov (United States)

    Mao, Fangjie; Zhou, Guomo; Li, Pingheng; Du, Huaqiang; Xu, Xiaojun; Shi, Yongjun; Mo, Lufeng; Zhou, Yufeng; Tu, Guoqing

    2017-04-15

    The selective cutting method currently used in Moso bamboo forests has resulted in a reduction of stand productivity and carbon sequestration capacity. Given the time and labor expense involved in addressing this problem manually, simulation using an ecosystem model is the most suitable approach. The BIOME-BGC model was improved to suit managed Moso bamboo forests, which was adapted to include age structure, specific ecological processes and management measures of Moso bamboo forest. A field selective cutting experiment was done in nine plots with three cutting intensities (high-intensity, moderate-intensity and low-intensity) during 2010-2013, and biomass of these plots was measured for model validation. Then four selective cutting scenarios were simulated by the improved BIOME-BGC model to optimize the selective cutting timings, intervals, retained ages and intensities. The improved model matched the observed aboveground carbon density and yield of different plots, with a range of relative error from 9.83% to 15.74%. The results of different selective cutting scenarios suggested that the optimal selective cutting measure should be cutting 30% culms of age 6, 80% culms of age 7, and all culms thereafter (above age 8) in winter every other year. The vegetation carbon density and harvested carbon density of this selective cutting method can increase by 74.63% and 21.5%, respectively, compared with the current selective cutting measure. The optimized selective cutting measure developed in this study can significantly promote carbon density, yield, and carbon sink capacity in Moso bamboo forests. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Correlation maps to assess soybean yield from EVI data in Paraná State, Brazil

    Directory of Open Access Journals (Sweden)

    Gleyce Kelly Dantas Araújo Figueiredo

    Full Text Available ABSTRACT Vegetation indices are widely used to monitor crop development and generally used as input data in models to forecast yield. The first step of this study consisted of using monthly Maximum Value Composites to create correlation maps using Enhanced Vegetation Index (EVI from Moderate Resolution Imaging Spectroradiometer (MODIS sensor mounted on Terra satellite and historical yield during the soybean crop cycle in Paraná State, Brazil, from 2000/2001 to 2010/2011. We compared the ability of forecasting crop yield based on correlation maps and crop specific masks. We ran a preliminary regression model to test its ability on yield estimation for four municipalities during the soybean growing season. A regression model was developed for both methodologies to forecast soybean crop yield using leave-one-out cross validation. The Root Mean Squared Error (RMSE values in the implementation of the model ranged from 0.037 t ha−1 to 0.19 t ha−1 using correlation maps, while for crop specific masks, it varied from 0.21 t ha−1 to 0.35 t ha−1. The model was able to explain 96 % to 98 % of the variance in estimated yield from correlation maps, while it was able to explain only 2 % to 67 % for crop specific mask approach. The results showed that the correlation maps could be used to predict crop yield more effectively than crop specific masks. In addition, this method can provide an indication of soybean yield prior to harvesting.

  5. Yield gap analysis of feed-crop livestock systems

    NARCIS (Netherlands)

    Linden, van der Aart; Oosting, Simon J.; Ven, van de Gerrie W.J.; Veysset, Patrick; Boer, de Imke J.M.; Ittersum, van Martin K.

    2018-01-01

    Sustainable intensification is a strategy contributing to global food security. The scope for sustainable intensification in crop sciences can be assessed through yield gap analysis, using crop growth models based on concepts of production ecology. Recently, an analogous cattle production model

  6. Yield gap analysis of Chickpea under semi-arid conditions: A simulation study

    Directory of Open Access Journals (Sweden)

    seyed Reza Amiri Deh ahmadi

    2016-05-01

    Full Text Available Yield gap analysis provides an essential framework to prioritize research and policy efforts aimed at reducing yield constraints. To identify options for increasing chickpea yield, the SSM-chickpea model was parameterized and evaluated to analyze yield potentials, water limited yields and yield gaps for nine regions representing major chickpea-growing areas of Razavi Khorasan province. The average potential yield of chickpea for the locations was 2251 kg ha-1, while the water limited yield was 1026 kg ha-1 indicating a 54% reduction in yield due to adverse soil moisture conditions. Also, the average irrigated and rainfed actual yields were respectively 64% and 79% less than simulated potential and water limited yields. Maximum and minimum yield gap between potential yield and actual yield were observed in Quchan and Torbat-jam respectively. Generally, yield gap showed an increasing trend from the north (including Nishabur, Mashhad, Quchan and Daregaz regions to the south of the province (Torbat- Jam and Gonabad. In addition, yield gap between simulated water limited potential yield and rainfed actual yield were very low because both simulated water limiting potential and average rainfed actual yields were low in these regions. Yield gap analysis provides an essential framework to prioritize research and policy efforts aimed at reducing yield constraints. To identify options for increasing chickpea yield, the SSM-chickpea model was parameterized and evaluated to analyze yield potentials, water limited yields and yield gaps for nine regions representing major chickpea-growing areas of Razavi Khorasan province. The average potential yield of chickpea for the locations was 2251 kg ha-1, while the water limited yield was 1026 kg ha-1 indicating a 54% reduction in yield due to adverse soil moisture conditions. Also, the average irrigated and rainfed actual yields were respectively 64% and 79% less than simulated potential and water limited yields

  7. In-Season Yield Prediction of Cabbage with a Hand-Held Active Canopy Sensor.

    Science.gov (United States)

    Ji, Rongting; Min, Ju; Wang, Yuan; Cheng, Hu; Zhang, Hailin; Shi, Weiming

    2017-10-08

    Efficient and precise yield prediction is critical to optimize cabbage yields and guide fertilizer application. A two-year field experiment was conducted to establish a yield prediction model for cabbage by using the Greenseeker hand-held optical sensor. Two cabbage cultivars (Jianbao and Pingbao) were used and Jianbao cultivar was grown for 2 consecutive seasons but Pingbao was only grown in the second season. Four chemical nitrogen application rates were implemented: 0, 80, 140, and 200 kg·N·ha -1 . Normalized difference vegetation index (NDVI) was collected 20, 50, 70, 80, 90, 100, 110, 120, 130, and 140 days after transplanting (DAT). Pearson correlation analysis and regression analysis were performed to identify the relationship between the NDVI measurements and harvested yields of cabbage. NDVI measurements obtained at 110 DAT were significantly correlated to yield and explained 87-89% and 75-82% of the cabbage yield variation of Jianbao cultivar over the two-year experiment and 77-81% of the yield variability of Pingbao cultivar. Adjusting the yield prediction models with CGDD (cumulative growing degree days) could make remarkable improvement to the accuracy of the prediction model and increase the determination coefficient to 0.82, while the modification with DFP (days from transplanting when GDD > 0) values did not. The integrated exponential yield prediction equation was better than linear or quadratic functions and could accurately make in-season estimation of cabbage yields with different cultivars between years.

  8. Rigid particle revisited: Extrinsic curvature yields the Dirac equation

    Energy Technology Data Exchange (ETDEWEB)

    Deriglazov, Alexei, E-mail: alexei.deriglazov@ufjf.edu.br [Depto. de Matemática, ICE, Universidade Federal de Juiz de Fora, MG (Brazil); Laboratory of Mathematical Physics, Tomsk Polytechnic University, 634050 Tomsk, Lenin Ave. 30 (Russian Federation); Nersessian, Armen, E-mail: arnerses@ysu.am [Yerevan State University, 1 Alex Manoogian St., Yerevan 0025 (Armenia); Laboratory of Mathematical Physics, Tomsk Polytechnic University, 634050 Tomsk, Lenin Ave. 30 (Russian Federation)

    2014-03-01

    We reexamine the model of relativistic particle with higher-derivative linear term on the first extrinsic curvature (rigidity). The passage from classical to quantum theory requires a number of rather unexpected steps which we report here. We found that, contrary to common opinion, quantization of the model in terms of so(3.2)-algebra yields massive Dirac equation. -- Highlights: •New way of canonical quantization of relativistic rigid particle is proposed. •Quantization made in terms of so(3.2) angular momentum algebra. •Quantization yields massive Dirac equation.

  9. 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.

  10. The heuristic value of redundancy models of aging.

    Science.gov (United States)

    Boonekamp, Jelle J; Briga, Michael; Verhulst, Simon

    2015-11-01

    Molecular studies of aging aim to unravel the cause(s) of aging bottom-up, but linking these mechanisms to organismal level processes remains a challenge. We propose that complementary top-down data-directed modelling of organismal level empirical findings may contribute to developing these links. To this end, we explore the heuristic value of redundancy models of aging to develop a deeper insight into the mechanisms causing variation in senescence and lifespan. We start by showing (i) how different redundancy model parameters affect projected aging and mortality, and (ii) how variation in redundancy model parameters relates to variation in parameters of the Gompertz equation. Lifestyle changes or medical interventions during life can modify mortality rate, and we investigate (iii) how interventions that change specific redundancy parameters within the model affect subsequent mortality and actuarial senescence. Lastly, as an example of data-directed modelling and the insights that can be gained from this, (iv) we fit a redundancy model to mortality patterns observed by Mair et al. (2003; Science 301: 1731-1733) in Drosophila that were subjected to dietary restriction and temperature manipulations. Mair et al. found that dietary restriction instantaneously reduced mortality rate without affecting aging, while temperature manipulations had more transient effects on mortality rate and did affect aging. We show that after adjusting model parameters the redundancy model describes both effects well, and a comparison of the parameter values yields a deeper insight in the mechanisms causing these contrasting effects. We see replacement of the redundancy model parameters by more detailed sub-models of these parameters as a next step in linking demographic patterns to underlying molecular mechanisms. Copyright © 2015 Elsevier Inc. All rights reserved.

  11. Using yield gap analysis to give sustainable intensification local meaning

    NARCIS (Netherlands)

    Silva, João Vasco

    2017-01-01

    Yield gap analysis is useful to understand the relative contribution of growth-defining, -limiting and -reducing factors to actual yields. This is traditionally performed at the field level using mechanistic crop growth simulation models, and directly up-scaled to the regional and global levels

  12. 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

  13. Assessment of climate change impact on yield of major crops in the Banas River Basin, India.

    Science.gov (United States)

    Dubey, Swatantra Kumar; Sharma, Devesh

    2018-09-01

    Crop growth models like AquaCrop are useful in understanding the impact of climate change on crop production considering the various projections from global circulation models and regional climate models. The present study aims to assess the climate change impact on yield of major crops in the Banas River Basin i.e., wheat, barley and maize. Banas basin is part of the semi-arid region of Rajasthan state in India. AquaCrop model is used to calculate the yield of all the three crops for a historical period of 30years (1981-2010) and then compared with observed yield data. Root Mean Square Error (RMSE) values are calculated to assess the model accuracy in prediction of yield. Further, the calibrated model is used to predict the possible impacts of climate change and CO 2 concentration on crop yield using CORDEX-SA climate projections of three driving climate models (CNRM-CM5, CCSM4 and MPI-ESM-LR) for two different scenarios (RCP4.5 and RCP8.5) for the future period 2021-2050. RMSE values of simulated yield with respect to observed yield of wheat, barley and maize are 11.99, 16.15 and 19.13, respectively. It is predicted that crop yield of all three crops will increase under the climate change conditions for future period (2021-2050). Copyright © 2018 Elsevier B.V. All rights reserved.

  14. Long Term Evaluation of Yield Stability Trend for Cereal Crops in Iran

    Directory of Open Access Journals (Sweden)

    mehdi nassiri mahalati

    2016-05-01

    Full Text Available During the last few decades cereals yield have increased drastically at the national level however, information about yield stability and its resistance to annual environmental variability are scare. In this study long term stability of grin yield of wheat, barley, rice, corn and overall cereals in Iran were evaluated during a 40-year period (1971-2011. Stability analysis was conducted using two different methods. In the first method the residuals of regression between crop yield and time (years were calculated as stability index. For this different segmented regression models including linear, bi-linear and tri-linear were fitted to yield trend data and the best model for each crop was selected based on statistical measures. Absolute residuals (the difference between actual and predicted yields for each year as well as relative residuals (absolute residuals as percent of predicted yield were estimated. In the second method yield stability was estimated from the slope of the regression line between average annual yield of all cereals (environmental index and the yield of each crop in the same year. Results indicted that in wheat and barley absolute and relative residuals were increased during the study period leading to reduction of stability despite considerable yield increment. However, for rice and corn residuals followed a decreasing trend and therefore yield stability of these crops was increased during the last 40 years. The same result was obtained with the environmental index but in this method reduction of yield stability in barley was lower than wheat. Based on the results, yield and yield stability of cereals crops in Iran increased during the last 40 years. However, the percentage increase in stability is lower than that of yield. Application of nitrogen fertilizers was led to reduction in stability. Yield stability of wheat, barley, rice, corn and overall cereals was improved with increasing their cultivated area.

  15. Exploring the persona model as a tool to generate user insight through co-creation with users in the early phase of a design project

    DEFF Research Database (Denmark)

    Hansen, Jane Holm; Haase, Louise Møller

    2017-01-01

    The persona model is a widely know tool for synthesizing user research. A persona is a hypothetical archetype based on actual users, which is typically created to create a shared understanding of the user in the design team. Previous research has focused on the personal model as a consensus......-making tool. However, in this paper the aim is to explore, whether the persona model can also be useful and valuable for collecting user insights. More specifically, the paper investigates the potentials and challenges of using the persona model as a generative tool to achieve user insight, when co......-creating with the user in the early phase of a design project. A modified persona template with fixed parameters has been introduced to users in two co-creation workshops. The users were asked to fill in the persona template based on their own experiences. This study is a first endeavor into exploring the persona model...

  16. Bulk yields of nucleosynthesis from massive stars

    International Nuclear Information System (INIS)

    Arnett, W.D.

    1978-01-01

    Preliminary estimates are made of the absolute yields of abundant nuclei synthesized in observed stars. The compositions of nine helium stars of mass 3 or =10M/sub sun/ is estimated. A variety of choices for the initial mass function (IMF) are used to calculate the yield per stellar generation. For standard choices of the (IMF) the absolute and relative yields of 12 C, 16 O, 20 Ne, 24 Mg, the Si to Ca group, and the iron group agree with solar system values, to the accuracy of the calculations. The relative yields are surprisingly insensitive to the slope of the IMF. In a second approach, using standard estimates (Ostriker, Richstone, and Thuan) for the current rate of stellar death, I find the present rate of nucleosynthesis in the solar neighborhood to be about 10%of the average rate over galactic history. This result is consistent with many standard models of galactic evolution (for example, the Schmidt model in which star formation goes as gas density squared). It appears that if the star formation rate is high enough to produce the stars we see around us, then the nucleosynthesis rate is large enough to produce the processed nuclei (except 4 He) seen in those stars. The typical nucleosynthesis source is massive (Mapprox. =30 M/sub sun/); the death rate of such stars is a small fraction (3-10%) of recent estimates of the total rate of supernovae

  17. 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.

  18. Climate impacts on palm oil yields in the Nigerian Niger Delta

    Science.gov (United States)

    Okoro, Stanley U.; Schickhoff, Udo; Boehner, Juergen; Schneider, Uwe A.; Huth, Neil

    2016-04-01

    Palm oil production has increased in recent decades and is estimated to increase further. The optimal role of palm oil production, however, is controversial because of resource conflicts with alternative land uses. Local conditions and climate change affect resource competition and the desirability of palm oil production. Based on this, crop yield simulations using different climate model output under different climate scenarios could be important tool in addressing the problem of uncertainty quantification among different climate model outputs. Previous studies on this region have focused mostly on single experimental fields, not considering variations in Agro-Ecological Zones, climatic conditions, varieties and management practices and, in most cases not extending to various IPCC climate scenarios and were mostly based on single climate model output. Furthermore, the uncertainty quantification of the climate- impact model has rarely been investigated on this region. To this end we use the biophysical simulation model APSIM (Agricultural Production Systems Simulator) to simulate the regional climate impact on oil palm yield over the Nigerian Niger Delta. We also examine whether the use of crop yield model output ensemble reduces the uncertainty rather than the use of climate model output ensemble. The results could serve as a baseline for policy makers in this region in understanding the interaction between potentials of energy crop production of the region as well as its food security and other negative feedbacks that could be associated with bioenergy from oil palm. Keywords: Climate Change, Climate impacts, Land use and Crop yields.

  19. Navigating the flow: individual and continuum models for homing in flowing environments.

    Science.gov (United States)

    Painter, Kevin J; Hillen, Thomas

    2015-11-06

    Navigation for aquatic and airborne species often takes place in the face of complicated flows, from persistent currents to highly unpredictable storms. Hydrodynamic models are capable of simulating flow dynamics and provide the impetus for much individual-based modelling, in which particle-sized individuals are immersed into a flowing medium. These models yield insights on the impact of currents on population distributions from fish eggs to large organisms, yet their computational demands and intractability reduce their capacity to generate the broader, less parameter-specific, insights allowed by traditional continuous approaches. In this paper, we formulate an individual-based model for navigation within a flowing field and apply scaling to derive its corresponding macroscopic and continuous model. We apply it to various movement classes, from drifters that simply go with the flow to navigators that respond to environmental orienteering cues. The utility of the model is demonstrated via its application to 'homing' problems and, in particular, the navigation of the marine green turtle Chelonia mydas to Ascension Island. © 2015 The Author(s).

  20. Caregiver Insightfulness and Young Children’s Violence Exposure: Testing a Relational Model of Risk and Resilience

    Science.gov (United States)

    Gray, Sarah A. O.; Forbes, Danielle; Briggs-Gowan, Margaret; Carter, Alice S.

    2016-01-01

    This study employed a relational post-traumatic stress frame to explore the co-contribution of young children’s exposure to violence and caregiver insightfulness on child behavioral outcomes in a high-risk, non-referred sample of caregivers and preschoolers (n = 64; mean age 3.83 years, SD = .77). Caregiver insightfulness did not have a main effect on child outcomes but did moderate the relation between violence exposure and child behavior across all observed outcomes. Violence-exposed children with non-insightful caregivers demonstrated higher caregiver-rated internalizing and externalizing behaviors and observer-rated negative affect than all other groups. Among children not exposed to violence, insightfulness was not related to children’s behavior problems or negative affect, suggesting violence-specific processes. Though cross-sectional, results suggest that the effects of violence and caregiver insightfulness on child outcomes are contingent on one another and that caregiver insightfulness may play a protective role in contexts of violence. PMID:26503175