Random Map Model
Mostrando 1-12 de 36 artigos, teses e dissertações.
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1. Efficacy and safety of dexmedetomidine in maintaining hemodynamic stability in pediatric cardiac surgery: a systematic review and meta-analysis
Abstract Objectives: Dexmedetomidine (DEX) is a highly selective alpha-2 adrenergic receptor agonist, which is the main sedative in the intensive care unit. This study aims to investigate the effectiveness and adverse events of DEX in maintaining hemodynamic stability in pediatric cardiac surgery. Sources: Databases such as PubMed, Cochrane, Web of Science,
Jornal de Pediatria. Publicado em: 2022
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2. Prediction of soil classes in a complex landscape in Southern Brazil
Resumo: O objetivo deste trabalho foi avaliar o uso da seleção de covariáveis por conhecimento especializado no desempenho de modelos de predição de classes de solos em uma paisagem complexa, para identificar o melhor modelo preditivo para o mapeamento digital de solos na região Sul do Brasil. Um total de 164 pontos foram amostrados em campo, com uso d
Pesq. agropec. bras.. Publicado em: 11/11/2019
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3. Potential and Future Geographical Distribution of Eremanthus erythropappus (DC.) MacLeish: a Tree Threatened by Climate Change
ABSTRACT Eremanthus erythropappus is a commercially-important tree which has a long history of exploitation in the Brazilian State of Minas Gerais. The knowledge on the potential geographical distribution of E. erythropappus is therefore critical for the species sustainability. Thus, the aim of this study was to estimate and map current and future ecological
Floresta Ambient.. Publicado em: 16/09/2019
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4. Prevalence and factors associated with chronic neuropathic pain in workers of a Brazilian public university
RESUMO JUSTIFICATIVA E OBJETIVOS: Embora seja um problema de saúde pública, a prevalência de dor crônica, especialmente em trabalhadores, é subestimada. O presente estudo teve o objetivo de estimar a prevalência de dor crônica e de dor neuropática crônica em trabalhadores de uma instituição pública federal e identificar os fatores associados. M
BrJP. Publicado em: 19/06/2019
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5. Soil type spatial prediction from Random Forest: different training datasets, transferability, accuracy and uncertainty assessment
ABSTRACT: Different uses of soil legacy data such as training dataset as well as the selection of soil environmental covariables could drive the accuracy of machine learning techniques. Thus, this study evaluated the ability of the Random Forest algorithm to predict soil classes from different training datasets and extrapolate such information to a similar a
Sci. agric. (Piracicaba, Braz.). Publicado em: 2019-05
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6. Mapping Soil Cation Exchange Capacity in a Semiarid Region through Predictive Models and Covariates from Remote Sensing Data
ABSTRACT: Planning sustainable use of land resources requires reliable information about spatial distribution of soil physical and chemical properties related to environmental processes and ecosystemic functions. In this context, cation exchange capacity (CEC) is a fundamental soil quality indicator; however, it takes money and time to obtain this data. Alth
Rev. Bras. Ciênc. Solo. Publicado em: 18/10/2018
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7. Mapping the global geographic potential of Zika virus spread
The Americas are presently experiencing the most serious known outbreak of Zika virus (ZIKV). Here, we present a novel set of analyses using environmental characteristics, vector mosquito distributions, and socioeconomic risk factors to develop the first map to detail global ZIKV transmission risk in multiple dimensions based on ecological niche models. Our
Mem. Inst. Oswaldo Cruz. Publicado em: 2016-09
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8. Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia
The objective of this research was to identify environmental risk factors for cutaneous leishmaniasis (CL) in Colombia and map high-risk municipalities. The study area was the Colombian Andean region, comprising 715 rural and urban municipalities. We used 10 years of CL surveillance: 2000-2009. We used spatial-temporal analysis - conditional autoregressive P
Mem. Inst. Oswaldo Cruz. Publicado em: 27/06/2016
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9. Prevalence and conditions associated with chronic pelvic pain in women from São Luís, Brazil
The objective of the present study was to estimate the prevalence of chronic pelvic pain in the community of São Luís, capital of the State of Maranhão, Northeastern Brazil, and to identify independent conditions associated with it. A cross-sectional study was conducted, including a sample of 1470 women older than 14 years predominantly served by the publ
Braz J Med Biol Res. Publicado em: 25/07/2014
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10. Modelo de simulação operacional do manuseio de matérias-primas de uma usina siderúrgica integrada
The main goal of this dissertation is to design and implementation of an Operational Simulation Model (OSM) of the handling of raw material in an Integrated Steelmaking Plant, considering operations of receiving, unloading, stocking, handling and supplying the different raw materials related to the production process with an operational perspective. The aim
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 15/08/2011
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11. Digital soilscape mapping of tropical hillslope areas by neural networks
Geomorphometric variables are applied in digital soil mapping because of their strong correlation with the disposition and distribution of pedological components of the landscapes. In this research, the relationship between environmental components of tropical hillslope areas in the Rio de Janeiro State, Brazil, artificial neural networks (ANN), and maximum
Scientia Agricola. Publicado em: 2011-12
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12. Combinação de modelos de campos aleatórios markovianos para classificação contextual de imagens multiespectrais / Combining markov random field models for multispectral image contextual classification
This work presents a novel MAP-MRF approach for multispectral image contextual classification by combining higher-order Markov Random Field models. The statistical modeling follows the Bayesian paradigm, with the definition of a multispectral Gaussian Markov Random Field model for the observations and a Potts MRF model to represent the a priori knowledge. In
Publicado em: 2010