Sistema de orientação automática de espelhos para painéis fotovoltaicos

Trabalho de Conclusão de Curso (graduação)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2018.Estudo para verificar a possibilidade do aumento da produção de energia elétrica de módulos solares por intermédio do uso de espelhos. Para isso, confeccionou-se um protótipo, que utiliza motores de passo para movimentar espelhos, visando redirecionar, de forma controlada, os raios solares para um painel fotovoltaico. Diante disso, tem-se uma análise empírica para averiguar a eficiência do painel com o uso de espelhos.This research presents a study to verify the possibility of increasing the production of electricity through solar modules by using mirrors. In this regard, a prototype was made, which one uses motors to move the mirrors aiming for redirect, in a controlled way, the sun's rays to a photovoltaic panel. In addition, there are an empirical analysis in order to check the efficiency of the panel using mirrors

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

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

Anos potenciais de vida perdidos nos últimos cinco anos em decorrência do câncer em Minas Gerais

O câncer é um problema crescente de saúde pública no Brasil e no mundo. Sendo uma doença multifatorial, que no ano de 2015 foi responsável por 209.780 mortes no Brasil e 8,8 milhões de mortes no mundo. Em vista disso, enfatiza-se a importância da mortalidade prematura como expressão social do valor da morte. O presente estudo tem como objetivo caracterizar o impacto de óbitos na população economicamente ativa do estado de Minas Gerais em decorrência do câncer nos últimos cinco anos, através do indicador "Anos Potenciais de Vida Perdidos (APVP)”. O número de óbitos notificados no Sistema de Informações sobre Mortalidade, de indivíduos com idade até 74 anos, em decorrência do câncer nos anos de 2014 a 2018, foi de 75.203 o que totaliza 1.263.919 APVP. Do total geral de óbitos, 54,86% eram do sexo masculino e 45,14% do feminino. Em relação aos óbitos na faixa etária economicamente ativa (15 a 64 anos), estes representam 80,95%. Portanto, é imprescindível realizar novas pesquisas nessa área, para que seja possível planejar e estruturar medidas com potencial para conter a elevação de indicadores, promover qualidade de vida e oferecer saúde à população