1000 resultados para 10071116 TM-25


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Potenciais produtivos distintos têm sido verificados entre talhões, bem como dentro desses, em áreas sob muitos anos de plantio direto (PD). Ferramentas de agricultura de precisão (AP) podem auxiliar a identificar tais diferenças, mas para manejar eficientemente a fertilidade do solo nessas condições a amostragem deve ser representativa. Este trabalho teve como objetivo avaliar a influência de atributos químicos do solo, conforme a camada ou profundidade de amostragem, na produtividade da cultura do trigo, em uma área sob PD de longa duração, utilizando zonas de um talhão com potenciais produtivos distintos. O estudo foi feito em Reserva do Iguaçu, PR, em área com 25 anos de PD e cinco anos de adoção de técnicas de AP. A partir de mapas de colheita anteriores, identificaram-se duas zonas, Z1 (alta produtividade) e Z2 (baixa produtividade), onde se estabeleceram malhas com 16 unidades amostrais. A produtividade do trigo foi estimada em três pontos por unidade, coletando-se amostras de solo de 0,0-0,1 e de 0,1-0,2 m nos mesmos pontos. A produtividade do trigo foi 22 % maior em Z1 do que em Z2, de acordo com os mapas de colheita utilizados. Os teores de carbono orgânico do solo (Corg) foram maiores em Z1, nas duas camadas do solo. Na camada de 0,1-0,2 m, a saturação (m%) e os teores de Al3+ foram significativamente maiores em Z2; nessa camada, Z1 apresentou maiores valores de pH e saturação por bases (V%) e teores de Ca2+, Mg2+ e K+. Houve correlação positiva da produtividade com os teores de Corg nas duas camadas do solo. Considerando somente a camada de 0,1-0,2 m, a correlação foi positiva com os valores de pH e V% e com a disponibilidade de Ca2+, Mg2+ e K+; e negativa, com a disponibilidade de Al3+. As diferenças na fertilidade do solo entre Z1 e Z2 se deram principalmente na camada de 0,1-0,2 m e foram associadas à diferença de produtividade do trigo, indicando ser importante a presença desse estrato na amostragem do solo em áreas de PD de longa duração, visando representar corretamente o estado de fertilidade do solo.

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Weekly newsletter for Center For Acute Disease Epidemiology of Iowa Department of Public Health.

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Bureau of Nutrition and Health Promotion part of the Iowa Department of Public Health produces of weekly newsletter about the Iowa WIC Program for the State of Iowa citizen.

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Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the effect of covariates on the outcome of interest. In this slight, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors. In this manuscript, we present the full Bayesian approach to analyzing traffic safety data and focus on highlighting the differences between the empirical Bayes and the full Bayes approaches. We use an illustrative example to discuss a step-by-step Bayesian analysis of the data and to show some of the types of inferences that are possible within the full Bayesian framework.

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Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the effect of covariates on the outcome of interest. In this light, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors. In this manuscript, we present the full Bayesian approach to analyzing traffic safety data and focus on highlighting the differences between the empirical Bayes and the full Bayes approaches. We use an illustrative example to discuss a step-by-step Bayesian analysis of the data and to show some of the types of inferences that are possible within the full Bayesian framework.

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Executive Order 17, signed by Governor Chester J. Culver on September 25, 2009, emphasizes revitalization of historic properties and cultural and entertainment districts and also supports safe and healthy work places, sustainable design and cost effective use of state resources. Specifically, the Executive Order requires that State entities managing or leasing real estate on behalf of the State shall give priority to the needs of public entities and the populations they serve consistent with the cost effective use of state revenues. It also indicates that existing resources and facilities shall be used where adequate, cost competitive and appropriate for efficient and effective current state operations.

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Iowa Secretary of Agriculture Bill Northey today commented on the Iowa Crops and Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October.

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Iowa Workforce Development's bi-monthly newsletter.

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau. Iowa Secretary of Agriculture Bill Northey today commented on the Iowa Crops and Weather report released by the USDA National Agricultural Statistical Service. The report is released weekly from April through October.

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Crop and livestock summaries for the state of Iowa, produced by the Iowa Department of Agriculture.

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The reintroduction of the Iowa Department on Aging legislative and policy update, now known as “Aging Watch.” The Department is providing this update to better inform you about policy affecting older Iowans. In addition to policy updates from the statehouse and the nation’s capitol, you’ll learn about Department programs and changes affecting the landscape. As you’ll learn reading this and future editions, big changes are coming for the Iowa Aging Network. Over the next year the Department will be reducing the number of local Area Agencies on Aging, as required by legislative action. Not surprisingly, this is a major change for everyone.

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The reintroduction of the Iowa Department on Aging legislative and policy update, now known as “Aging Watch.” The Department is providing this update to better inform you about policy affecting older Iowans. In addition to policy updates from the statehouse and the nation’s capitol, you’ll learn about Department programs and changes affecting the landscape. As you’ll learn reading this and future editions, big changes are coming for the Iowa Aging Network. Over the next year the Department will be reducing the number of local Area Agencies on Aging, as required by legislative action. Not surprisingly, this is a major change for everyone.