EIXOS COGNITIVOS, COMPETÊNCIAS E HABILIDADES PRESENTES NAS QUESTÕES DO ENEM QUE ENVOLVEM CONCEITOS QUÍMICOS

..

Desafios e impacto da educação em saúde associada a cinesioterapia laboral para a promoção da saúde em servidores do estado do Paraná

Introdução: A Fisioterapia atua na saúde do trabalhador pela promoção e prevenção a saúde. Diversos recursos podem ser utilizados para tal finalidade, como a educação em saúde e a cinesioterapia laboral. Objetivo: Verificar os desafios e os efeitos da educação em saúde associada a cinesioterapia laboral sobre a qualidade de vida, percepção da saúde e dor musculoesquelética em servidores públicos do Estado do Paraná. Metodologia: Trata-se de um estudo experimental desenvolvido por meio da disciplina de Habilidades Fisioterapêuticas. Foram aplicados questionários para avaliação da qualidade de vida (SF-36), percepção da saúde e dor musculoesquelética (Nórdico). A prática de educação em saúde foi realizada por meio de cartilhas informativas e foi associada a cinesioterapia laboral. As atividades foram realizadas na Procuradoria Geral do Estado do Paraná uma vez por semana, totalizando 12 encontros. A comparação dos momentos pré e pós intervenção foi realizada pelos testes de Wilcoxon e Qui-Quadrado. Resultados: A análise dos dados evidenciou que grande parte dos servidores melhorou os domínios de capacidade funcional e dor da qualidade de vida e a percepção da saúde. A maior queixa de dor lombar e apresentou redução de sua prevalência após o experimento. Conclusão: O grande desafio da atividade proposta foi a aderência e participação dos servidores. Apesar disso, os servidores que participaram ativamente do programa de educação em saúde com a cinesioterapia laboral evidenciaram efeitos positivos sobre a qualidade de vida, percepção da saúde e dores musculoesqueléticas, sendo estas sugeridas como uma ferramenta importante para a promoção da saúde de servidores

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Phase transformations and aging of the Cu72.9Al15.0Mn10.5Ag1.6 alloy

The phase transformations and aging of the Cu72.9Al15.0Mn10.5Ag1.6 alloy were studied in the temperature range from 523 to 723 K using measurement of change in microhardness with variation in quenching temperature and aging time, differential scanning calorimetry (DSC), X-ray diffractometry (XRD), magnetization measurements with temperature and applied field, optical microscopy (MO) and high-resolution transmission electron microscopy (HRTEM). The results indicated that the bainitic precipitation is dominant with increase in microhardness and the activation energy value obtained for this process is lower than that reported in the literature due to the occurrence of a diffusion process disturbed by the presence of Ag dissolved in the alloy. (C) 2016 Elsevier B.V. All rights reserved.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)UNESP, Inst Quim, Dept Fis Quim, Caixa Postal 355, BR-14801970 Araraquara, SP, BrazilUNIFESP, Dept Ciencias Exatas & Terra, BR-09972270 Diadema, SP, BrazilDepartamento de Ciências Exatas e da Terra, Universidade Federal de São Paulo (UNIFESP), 09972-270 Diadema, SP, BrazilFAPESP: 2011/11041-1CNPq: 484135/2012Web of Scienc