Diseño de un seguro de ingresos de toda la granja para cultivos agrícolas en la provincia de Zanjan de Irán

[EN] The purpose of this article is to design and empirically evaluate the Whole Farm Insurance (WFI) over the conventional insurance programs in Zanjan province of Iran. Historical farm-level and county-level data were used to estimate yield and price density functions. Both parametric and non-parametric methods were applied for predicting the future values and the PQH simulation method was utilized to calculate premium rates. Results revealed that loss ratios of the WFI are lower for farmers who insured more than one crop. Additionally, utilizing WFI reduces premiums. Moreover, premiums obtained from nonparametric method are relatively lower compared to the parametric approach.[ES] El propósito de este artículo es diseñar y evaluar empíricamente el Seguro Agrario Integral (SAI) con respecto a los programas de seguros convencionales en la provincia de Zanjan de Irán. Se usaron datos históricos a nivel de explotación y de comarca para estimar las funciones de rendimiento y de densidad de precios. Se aplicaron métodos paramétricos y no paramétricos para predecir los valores futuros y se utilizó el método de simulación SAI para calcular las tasas de primas. Los resultados revelaron que los índices de pérdida del SAI son más bajos para los agricultores que aseguraron más de un cultivo. Además, la utilización del SAI reduce las primas. Las primas obtenidas del método no paramétrico son relativamente más bajas en comparación con el enfoque paramétrico.Ghahremanzadeh, M.; Mohammadrezaei, R.; Dashti, G.; Ainollahi, M. (2018). Designing a whole-farm revenue insurance for agricultural crops in Zanjan province of Iran. Economía Agraria y Recursos Naturales - Agricultural and Resource Economics. 17(2):29-53. doi:10.7201/earn.2017.02.02SWORD295317

Development of Optimized Phenomic Predictors for Efficient Plant Breeding Decisions Using Phenomic-Assisted Selection in Soybean

The rate of advancement made in phenomic-assisted breeding methodologies has lagged those of genomic-assisted techniques, which is now a critical component of mainstream cultivar development pipelines. However, advancements made in phenotyping technologies have empowered plant scientists with affordable high-dimensional datasets to optimize the operational efficiencies of breeding programs. Phenomic and seed yield data was collected across six environments for a panel of 292 soybean accessions with varying genetic improvements. Random forest, a machine learning (ML) algorithm, was used to map complex relationships between phenomic traits and seed yield and prediction performance assessed using two cross-validation (CV) scenarios consistent with breeding challenges. To develop a prescriptive sensor package for future high-throughput phenotyping deployment to meet breeding objectives, feature importance in tandem with a genetic algorithm (GA) technique allowed selection of a subset of phenotypic traits, specifically optimal wavebands. The results illuminated the capability of fusing ML and optimization techniques to identify a suite of in-season phenomic traits that will allow breeding programs to decrease the dependence on resource-intensive end-season phenotyping (e.g., seed yield harvest). While we illustrate with soybean, this study establishes a template for deploying multitrait phenomic prediction that is easily amendable to any crop species and any breeding objective

Issues on Mechanical Properties of 3D Prints

This project studied variation of material properties, particularly the Young’s modulus, under different 3D prints orientation using three different approaches. Experimentally, we created a testing apparatus that would hold cantilever beam test specimens. For numerical analysis, we remade the model with the printing pattern in Solidworks and used finite element analysis to compare experimental results to the theoretical results. We also researched microstructures for justification of variance in 3D prints due to certain print settings. The results have shown that mechanical properties of 3D prints varies with the manufacturing setting, for example, print orientation has an effect on the Young’s modulus of 3D prints under print orientation

2021 IMSAloquium

Welcome to IMSAloquium 2021. This is IMSA’s 34th year of leading in educational innovation, and the 33rd year of the IMSA Student Inquiry and Research (SIR) Program.https://digitalcommons.imsa.edu/archives_sir/1031/thumbnail.jp

Occupational Health Interventions: Evaluating the Effectiveness of Workplace Wellness Programs

This exploration completely looks at the impacts of work environment Wellness programs on word related Wellness and representative prosperity in different hierarchical settings, utilizing an exhaustive methodology. Through a far reaching survey of writing from the beyond a decade, we have blended proof based rehearses that exhibit the positive effect of these projects on physical and psychological well-being. Thus, efficiency and occupation fulfillment are eventually improved. Our review centers around different intercessions, including Wellness screenings, work out schedules, stress the executives procedures, and ergonomic measures. Besides, we analyze the effect of authoritative culture, administration backing, and worker commitment on the aftereffects of the program. We utilize a blend of quantitative and subjective exploration techniques, for example, overviews, center gatherings, and objective Wellness measurements, to assess the viability of intercessions. Our review looks at an extensive variety of working environment health drives, offering nitty gritty bits of knowledge into their viability and distinguishing key factors that add to program achievement. This examination adds to the scholarly world and gives commonsense direction to industry, educating the turn of events and execution regarding proof based working environment health programs. Our examination gives associations a thorough comprehension that empowers them to tweak intercessions as per their labor force's particular requirements, consequently advancing a better and more useful workplace

Wizard building in an abstract portal framework

This report investigates a particular way in which enterprise portals can support the working life of their users. Through monitoring a user's behaviour and observing archetypal sequences of actions, the system constructs abstract templates of tools that assist him to carry out such sequences efficiently and easily in the future. We call these new tools "wizards" after the utilities introduced by Microsoft into their applications and operating systems, designed to guide users through potentially complex tasks such as constructing graphs in Excel or setting up the computer to access the Internet. At the heart of the process lies a re-programmable rule-base that encodes the principles by which action records are to be assembled into intelligible generic patterns of working practice, and thence converted into templates of new wizard tools that provide direct support for those patterns

Chapter Operationalizing Heterogeneous Data-Driven Process Models for Various Industrial Sectors through Microservice-Oriented Cloud-Based Architecture

Industrial performance optimization increasingly makes the use of various analytical data-driven models. In this context, modern machine learning capabilities to predict future production quality outcomes, model predictive control to better account for complex multivariable environments of process industry, Bayesian Networks enabling improved decision support systems for diagnostics and fault detection are some of the main examples to be named. The key challenge is to integrate these highly heterogeneous models in a holistic system, which would also be suitable for applications from the most different industries. Core elements of the underlying solution architecture constitute highly decoupled model microservices, ensuring the creation of largely customizable model runtime environments. Deployment of isolated user-space instances, called containers, further extends the overall possibilities to integrate heterogeneous models. Strong requirements on high availability, scalability, and security are satisfied through the application of cloud-based services. Tieto successfully applied the outlined approach during the participation in FUture DIrections for Process industry Optimization (FUDIPO), a project funded by the European Commission under the H2020 program, SPIRE-02-2016

Improving the forecast for biodiversity under climate change

Acknowledgments: This paper originates from the “Ecological Interactions and Range Evolution Under Environmental Change” and “RangeShifter” working groups, supported by the Synthesis Centre of the German Centre for Integrative Biodiversity Research (DFG-FZT-118), DIVERSITAS, and its core projects bioDISCOVERY and bioGENESIS. Supported by the Canada Research Chair, Natural Sciences and Engineering Research Council of Canada, and Quebec Centre for Biodiversity Science (A.G.); the University of Florida Foundation (R.D.H.); KU Leuven Research Fund grant PF/2010/07, ERA-Net BiodivERsA TIPPINGPOND, and Belspo IAP SPEEDY (L.D.M.); European Union Biodiversity Observation Network grant EU-BON-FP7-308454 (J.-B.M. and G.P.); KU Leuven Research Fund (J.P.); and NSF grants DEB-1119877 and PLR-1417754 and the McDonnell Foundation (M.C.U.).Peer reviewedPostprin