ANÁLISE EPIDEMIOLÓGICA DA TUBERCULOSE NO BRASIL ENTRE 2020 A 2023

It is understood that the disease Tuberculosis (TB) is considered an infectious disease, caused by Mycobacterium tuberculosis. Of course, it is known that transmission occurs via air, from an infected person, who expels aerosols from coughing, talking or sneezing, mainly affecting the lungs. The main symptoms are: cough for 3 weeks or more; afternoon fever; night sweats and weight loss. The study aims to analyze the epidemiology of Tuberculosis (TB) notifications in the last five years in Brazil. The research was carried out through an epidemiological, cross-sectional, descriptive study, carried out between 2020 and 2023, quantitative, with statistical information, being discussed in a qualitative way. In Brazil, 391,365 notifications for Tuberculosis were recorded, and the Southeast and Northeast Regions had the highest incidence rates and the highest amount of mortality. Therefore, it is observed that the most affected profile are men, aged between 20-59, with a significant number of cures and new cases are the ones that predominateCompreende-se que a enfermidade Tuberculose (TB) é considerada uma doença infectocontagiosa, causada pela Mycobacterium tuberculosis.  De certo, sabe-se que a transmissão acontece por via aérea, a partir de uma pessoa contaminada, a qual expele aerossóis advindos da tosse, fala ou espirro, acometendo, principalmente, o pulmão. Os principais sintomas são : tosse por 3 semanas ou mais; febre vespertina; sudorese noturna e  emagrecimento. O estudo tem como escopo analisar a epidemiologia das notificações  da Tuberculose (TB)  nos   últimos   cinco   anos  no   Brasil. Realizou-se  a pesquisa  através  do  estudo epidemiológico, transversal, descritivo, pregressa entre 2020 a 2023, quantitativo, com informações estatísticas, sendo discutidas de maneira qualitativa. No  Brasil  foram  registradas 391.365 notificações por Tuberculose, e as  Regiões  Sudeste e Nordeste  apresentaram  os  maiores  índices  de incidência e  a  maior  quantidade  de  mortalidade. Logo, observa-se que o perfil mais afetado são os homens, de faixa etária entre 20-59, com um número significativo de cura e os casos novos são os que predominam.Compreende-se que a enfermidade Tuberculose (TB) é considerada uma doença infectocontagiosa, causada pela Mycobacterium tuberculosis.  De certo, sabe-se que a transmissão acontece por via aérea, a partir de uma pessoa contaminada, a qual expele aerossóis advindos da tosse, fala ou espirro, acometendo, principalmente, o pulmão. Os principais sintomas são : tosse por 3 semanas ou mais; febre vespertina; sudorese noturna e  emagrecimento. O estudo tem como escopo analisar a epidemiologia das notificações  da Tuberculose (TB)  nos   últimos   cinco   anos  no   Brasil. Realizou-se  a pesquisa  através  do  estudo epidemiológico, transversal, descritivo, pregressa entre 2020 a 2023, quantitativo, com informações estatísticas, sendo discutidas de maneira qualitativa. No  Brasil  foram  registradas 391.365 notificações por Tuberculose, e as  Regiões  Sudeste e Nordeste  apresentaram  os  maiores  índices  de incidência e  a  maior  quantidade  de  mortalidade. Logo, observa-se que o perfil mais afetado são os homens, de faixa etária entre 20-59, com um número significativo de cura e os casos novos são os que predominam

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

Adaptive device with underlying mechanism defined by a programming language

Abstract:- An adaptive device is made up of an underlying mechanism, for instance, an automaton, a grammar, a decision tree, etc., to which is added an adaptive mechanism, responsible for allowing a dynamic modification in the structure of the underlying mechanism. This article aims to investigate if a programming language can be used as an underlying mechanism of an adaptive device, resulting in an adaptive language. Key-Words:- adaptive devices, self-modifying machines, adaptive automaton, functional adaptive programming language, algorithms and computation theory.

A viagem científica de Neiva e Penna: roteiro para os estudos das doenças do sertão The scientific journey taken by Neiva and Penna: a blueprint for studies of diseases from the Brazilian hinterland

Analisa o relatório de Arthur Neiva e Belisario Penna , focalizando a contribuição dos autores ao estudo de uma das doenças endêmicas por eles encontrada ao longo de todo o trajeto percorrido, de longa data conhecida popularmente por 'mal de engasgo'. Observaram e descreveram com minúcia os sintomas apresentados pelos doentes e a associação frequente do mal de engasgo com outro mal endêmico conhecido por 'vexame' ou 'vexame do coração', que consistia em crises de palpitações. Os estudos epidemiológicos e clínicos de Neiva e Penna sobre o mal de engasgo muito contribuíram para o conhecimento dessa afecção e representaram um incentivo para todos os pesquisadores que se dedicaram ao seu estudo, especialmente quanto a sua relação com a doença de Chagas.<br>Analyze the report by Neiva and Penna, focusing on the contribution these authors made to the study of one of the endemic diseases encountered throughout their journey, which had been long known under the popular name of mal de engasgo (choking disease). They recorded their observations and detailed descriptions of the patients' symptoms and the association frequently encountered between mal de engasgo and another endemic disease, known as vexame or vexame do coração, characterized by bouts of palpitations. Neiva and Penna's epidemiological and clinical observations of mal de engasgo were crucial for all the researchers interested in the disease, especially its relationship with Chagas disease