PERFIL EPIDEMIOLÓGICO DA MORTALIDADE POR PNEUMONIA EM IDOSOS NO BRASIL E EM ANÁPOLIS

A pneumonia é uma doença inflamatória aguda que acomete principalmente a população idosa do país. Assim, o desenvolvimento deste trabalho motivou-se pelo paradoxo existente entre os avanços da medicina como um todo e o aumento do número de casos de morte por pneumonia em idosos. E, tem como objetivo comparar o perfil epidemiológico de casos de mortes por pneumonia entre idosos no Brasil e na cidade de Anápolis no ano de 2013. Este estudo consiste em um artigo de revisão de abordagem quantitativa, com os dados coletados do Departamento de Informática do Sistema Único de Saúde (DATASUS), constituindo, portanto, um estudo transversal com o objetivo de averiguar os índices relacionados à mortalidade da pneumonia na população idosa brasileira comparando sexo e faixa etária da população Anapolina. Os dados afirmam que a prevalência da enfermidade é maior em mulheres idosas, sendo que na medida em que a idade aumenta o índice de mortalidade também sobe. Tais dados são verdadeiros para o Brasil, bem como para a cidade de Anápolis em uma análise absoluta. Já em relação a mortes por cem mil, Anápolis não apresenta números expressivos de mortes por pneumonia por provavelmente dois motivos: o intenso incentivo a vacinação e a sua população não tão significante quando relacionada a cem mil. Trançando o perfil epidemiológico da pneumonia, é possível concluir que uma doença tão antiga não precisa fazer parte de uma atualidade tão avançada e tecnológica.  A conscientização e vacinação da população é um início viável de um futuro menos doente

COMPETÊNCIAS DA PSICOPEDAGOGIA NOS PROCESSOS DE ENSINO-APRENDIZAGEM NAS ESCOLAS: UMA REVISÃO DA LITERATURA

Psychopedagogy is a science dedicated to understanding learning difficulties, reflecting and intervening on issues related to cognitive, psychomotor and affective development. For this reason, this integrative literature review aims to highlight the positive impacts that psychopedagogy can provide to the individual. A search was carried out in the electronic virtual databases Google Academic and Scielo, adopting the descriptor: “Learning” associated with the terms “Psychopedagogy” and “Teaching”. As inclusion criteria, studies that cover the topic were included. (Competences of Psychopedagogy in the lives of students) or related topics, published in Portuguese or English, in the period between 2014 and 2024 (last 10 years). As an exclusion criterion, studies that were repeated in the databases and those that were not presented in the format of a scientific article. Therefore, it is concluded that the school needs to look not only at theoretical, methodological and technical training, but also focus on development and value training, with transversal skills and attitudes that preserve life.A psicopedagogia é uma ciência que se dedica a compreender as dificuldades na aprendizagem, refletir e intervir sobre questões relacionadas ao desenvolvimento cognitivo, psicomotor e afetivo. Por esse motivo, a presente revisão integrativa da literatura tem por objetivo destacar quais são os impactos positivos que a psicopedagogia pode proporcionar ao indivíduo. Foi realizada uma pesquisa nas bases de dados virtual eletrônicas Google acadêmico e Scielo, adotando-se o descritor: “Aprendizagem” associando-se aos termos “Psicopedagogia” e “Ensino". Como critérios de inclusão, incluíram-se estudos que contemplem o tema (Competências da Psicopedagogia na vida dos escolares) ou temas afins, publicados nos idiomas português ou inglês, no período compreendido entre 2014 e 2024 (últimos 10 anos). Como critério de exclusão, foram excluídos estudos repetidos nas bases de dados e os que não se apresentem em formato de artigo científico. Portanto, conclui-se que a escola precisa olhar não apenas para a formação teórica, metodológica e técnica, mas também focar no desenvolvimento e formação valorativa, com habilidades e atitudes transversais que preservem a vida

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

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

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