A ANGÚSTIA E O DESESPERO EM TEMPOS DE PANDEMIA: UMA ABORDAGEM A PARTIR DA FILOSOFIA EXISTENCIALISTA

O texto objetiva refletir o momento pandêmico na perspectiva da filosofia existencialista, com recorte em dois conceitos, a saber, o desespero e a angústia. Não há a intenção de aprofundamento nos sentidos filosóficos que esses conceitos foram tratados ao longo da contemporaneidade, mas em pensá-los como lentes para ver alguns sentimentos vividos durante o distanciamento social decretado em função da Pandemia de COVID-19. A argumentação tem por base uma pesquisa qualitativa bibliográfica, centrada nos autores da filosofia como Kierkegaard, Nietzsche e Heidegger e alguns interlocutores. O horizonte do percurso reflexivo é uma possível colaboração na compreensão das tarefas humanas de ser em seus momentos históricos, mais especificamente do ano 2020

OS BENEFÍCIOS DA ATIVIDADE FÍSICA PARA O TRATAMENTO DO TRANSTORNO DE ANSIEDADE GENERALIZADA E DEPRESSÃO EM PACIENTES ADULTOS: UMA REVISÃO INTEGRATIVA

Identificar na literatura científica as características benefícas dos impactos da atividade física para o processo de controle e tratamento do Transtorno de Ansiedade Generalizada em pacientes adultos. Método: revisão integrativa, cujos critérios de elegibilidade dos artigos foram: corresponder aos descritores “Transtorno de ansiedade”; “Ansiedade” e “Atividade física”, ser artigo de pesquisa; estar nos idioma português, inglês e espanhol; estar disponível eletronicamente nas bases de dados BVS (Biblioteca Virtual em Saúde) e as fontes de dados Scientific Eletronic Library onLine (SciELO) e Brazilian Journal of Health Review (BJHR), ano de publicação referente ao período de 2013 a 2023. Resultados: encontraram-se 08 publicações expressivas. A análise ocorreu mediante leituras analíticas e interpretativas. Considerações finais: A importância da atividade física para o tratamento da TAB são promissoras e acenam para a utilização de exercícios físicos aeróbios como auxiliares das terapêuticas tradicionais.https://revistaft.com.br/os-beneficios-da-atividade-fisica-para-o-tratamento-do-transtorno-de-ansiedade-generalizada-e-depressao-em-pacientes-adultos-uma-revisao-integrativa

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