Study and Application of a Recurrence Relationship / Estudo e Aplicação de uma Relação de Recorrência

Recurrence relationships allow us to accurately determine logarithms, square roots, factorials, several sequences (like Fibonacci), roots of equations and more. This paper aims to describe a recurrence relationship and present some applications. It presents the concept of reciprocal matrix and allowed the approximation of non perfect square roots of positive integers and their representation in continuous fraction. In addition, there was a correspondence between this study and the so-called Fibonacci polynomials. As it is a new job, more studies are needed to expand its concepts and applications

Funções afins elucidadas no software geogebra / Related functions elucidated in the geogebra software

Este artigo tem como objetivo relatar a montagem e aplicação da oficina “Funções Afins elucidadas no software GeoGebra” apresentada por discentes de Licenciatura Plena em Matemática do IFPA. A oficina fora direcionada aos alunos de uma determinada escola pública na periferia de Belém - PA, com o intuito de preparar os alunos, com dificuldade de aprendizado da matemática na educação básica, para novas tecnologias, utilizando como ferramenta o software livre GeoGebra. Desta maneira, a utilização do referido software contribuiu na interação entre o mundo tecnológico e o ensino da Matemática, através das aulas práticas, nas quais os participantes desenvolveram atividades em equipe

Inclusão escolar de alunos portadores de Transtorno do Espectro Autista na educação infantil: uma revisão sistemática: School inclusion of students with Autistic Spectrum Disorder in early childhood education: a systematic review

Este artigo debate o problema da inclusão escolar de crianças com transtorno do espectro autista (TEA). Para estabelecer o debate, foi feito um levantamento bibliográfico e referencial para uma revisão sistemática do tema. O objetivo é clarificar os conceitos de inclusão escolar e TEA para debater como é feito o processo educacional de crianças com TEA. Sendo assim, a partir da pesquisa científica de descritores como “inclusão escolar”, “transtorno do espectro autista”, foi observado, pelos diversos autores trabalhados, que ainda há muito o que se debater e trabalhar para que ocorra a inclusão escolar de crianças com TEA. Apesar das muitas tentativas, erros e acertos, o tema ainda é pouco trabalhado e divulgado, visto que há poucos profissionais capacitados na área

Os aspectos semiológicos do acidente vascular encefálico: uma abordagem neurológica

O Acidente Vascular Encefálico (AVC) é um evento neurológico súbito, com um foco de isquemia ou hemorragia. Ambos, qualificados pelo déficit neurológico focal abrupto. Ressaltando, que estes déficits podem ocorrer, sendo a ocorrência espontânea, perduração de 15 minutos, autoresolutiva é denominada como Ataque Isquêmico Transitório (AIT), no entanto, toda insuficiência neural que não melhorar pós esse período deve ser manejado como AVC. O artigo objetivou descrever os principais aspectos clínicos do AVC. O AVC é uma emergência para a saúde pública, em razão de ser um potencial em gerar morbimortalidades para os portadores e prejuízos para os sistemas de saúde. O AVC do tipo isquêmico representa a maioria das ocorrências, o quadro clínico do paciente é correspondente ao tecido neural afetado, inicialmente a tomografia computadorizada sem contraste é o primeiro exame, por ser crucial para descartar a etiologia hemorrágica, a condução terapêutica se baseia em medidas neuroprotetoras através da estabilização da glicemia, temperatura e sódio, adequar os níveis pressóricos, mediante o prazo estipulado impor terapia antitrombótica. A manifestação hemorrágica, pode ocorrer por torção de aneurisma sacular originando o sangramento subaracnóideo ou por hipertensão gerando o sangramento intraparenquimatoso. A partir da análise das informações coletadas, elucida-se que o diagnóstico precoce e o período transcorrido até o manejo terapêutico são cruciais para o desfecho clínico do portador, ou seja, é possível a normalização ou ocorrer sequelas neurais e óbito

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

Panoramic snapshot of serum soluble mediator interplay in pregnant women with convalescent COVID-19: an exploratory study

IntroductionSARS-CoV-2 infection during pregnancy can induce changes in the maternal immune response, with effects on pregnancy outcome and offspring. This is a cross-sectional observational study designed to characterize the immunological status of pregnant women with convalescent COVID-19 at distinct pregnancy trimesters. The study focused on providing a clear snapshot of the interplay among serum soluble mediators.MethodsA sample of 141 pregnant women from all prenatal periods (1st, 2nd and 3rd trimesters) comprised patients with convalescent SARS-CoV-2 infection at 3-20 weeks after symptoms onset (COVID, n=89) and a control group of pre-pandemic non-infected pregnant women (HC, n=52). Chemokine, pro-inflammatory/regulatory cytokine and growth factor levels were quantified by a high-throughput microbeads array.ResultsIn the HC group, most serum soluble mediators progressively decreased towards the 2nd and 3rd trimesters of pregnancy, while higher chemokine, cytokine and growth factor levels were observed in the COVID patient group. Serum soluble mediator signatures and heatmap analysis pointed out that the major increase observed in the COVID group related to pro-inflammatory cytokines (IL-6, TNF-α, IL-12, IFN-γ and IL-17). A larger set of biomarkers displayed an increased COVID/HC ratio towards the 2nd (3x increase) and the 3rd (3x to 15x increase) trimesters. Integrative network analysis demonstrated that HC pregnancy evolves with decreasing connectivity between pairs of serum soluble mediators towards the 3rd trimester. Although the COVID group exhibited a similar profile, the number of connections was remarkably lower throughout the pregnancy. Meanwhile, IL-1Ra, IL-10 and GM-CSF presented a preserved number of correlations (≥5 strong correlations in HC and COVID), IL-17, FGF-basic and VEGF lost connectivity throughout the pregnancy. IL-6 and CXCL8 were included in a set of acquired attributes, named COVID-selective (≥5 strong correlations in COVID and <5 in HC) observed at the 3rd pregnancy trimester.Discussion and conclusionFrom an overall perspective, a pronounced increase in serum levels of soluble mediators with decreased network interplay between them demonstrated an imbalanced immune response in convalescent COVID-19 infection during pregnancy that may contribute to the management of, or indeed recovery from, late complications in the post-symptomatic phase of the SARS-CoV-2 infection in pregnant women

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

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others