EDUCAÇÃO AFRO NO SISTEMA DE EDUCAÇÃO BRASILEIRA

Com a criação da Lei nº 10.639/03 tornou-se obrigatório o ensino da História e Cultura Afro-Brasileira e Africana nas escolas de ensino básico, propiciando dessa forma a contemplação da matriz africana no currículo oficial de ensino. O presente trabalho visa analisar as contribuições do ambiente escolar que motivaram a criação da Lei nº10.639/03. A metodologia utilizada para produção da pesquisa foi baseada em consultas documentais, em literatura referente a livros, artigos científicos, artigos eletrônicos e periódicos. A abordagem feita neste trabalho reconhece como a sociedade brasileira reflete de forma bem expressiva as desigualdades e como a escola, enquanto ambiente de formação cultural da humanidade, representa um espaço de reprodução das desigualdades, através do currículo escolar adotado que atende aos interesses da classe dominante, um material que retrata o negro numa condição de inferioridade e professores que reproduzem as ideologias da classe dominante através da sua prática. A pesquisa retrata o quanto é relevante a conquista da Lei nº 10.639/03 para a construção da dignidade do povo negro, que sempre foi renegado a uma condição de desprestígio social na sociedade brasileira

PROJETO DE INTERVENÇÃO REDUÇÃO DOS CASOS DE SÍFILIS EM INDIVÍDUOS DE 20 A 39 ANOS NO MUNICÍPIO DE ARAGUARI-MG

A sífilis adquirida é transmitida, comumente, por via sexual e pode evoluir para lesões dermatológicas, cardiovasculares e nervosas. O estudo objetivou descrever o perfil epidemiológico da sífilis adquirida em Araguari-MG e desenvolver um projeto de intervenção para reduzir a incidência da doença. Um estudo epidemiológico descritivo foi conduzido com dados do SINAN e TABNET, sobre sífilis adquirida na população de 20 a 39 anos, durante o período de 2012 a 2021, em Araguari-MG. Analisou-se variáveis como diagnóstico, evolução, idade, sexo, raça e escolaridade. A revisão de literatura foi realizada nas plataformas LILACS e PubMed, utilizando-se os indexadores: sífilis, intervenção e prevenção. Avaliou-se artigos originais publicados a partir de 2017. Foram notificados 347 casos no município, especialmente no ano de 2018 (124 casos). O perfil epidemiológico de casos de sífilis adquirida período estudado predominou em indivíduos do sexo masculino, brancos e pardos, que obtiveram diagnóstico laboratorial. A partir dos critérios de inclusão e exclusão, utilizaram-se 4 artigos na confecção da proposta de intervenção. Intervenções sugeridas incluem vídeos educativos, Centros de Triagem anônimos e ferramentas de notificação de parceiros sexuais. As limitações incluem preenchimento deficiente de dados e falta de campo sobre orientação sexual na ficha de notificação

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

The ATLAS fast tracKer system

The ATLAS Fast TracKer (FTK) was designed to provide full tracking for the ATLAS high-level trigger by using pattern recognition based on Associative Memory (AM) chips and fitting in high-speed field programmable gate arrays. The tracks found by the FTK are based on inputs from all modules of the pixel and silicon microstrip trackers. The as-built FTK system and components are described, as is the online software used to control them while running in the ATLAS data acquisition system. Also described is the simulation of the FTK hardware and the optimization of the AM pattern banks. An optimization for long-lived particles with large impact parameter values is included. A test of the FTK system with the data playback facility that allowed the FTK to be commissioned during the shutdown between Run 2 and Run 3 of the LHC is reported. The resulting tracks from part of the FTK system covering a limited η-ϕ region of the detector are compared with the output from the FTK simulation. It is shown that FTK performance is in good agreement with the simulation. © The ATLAS collaboratio

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