GERENCIAMENTO DE RISCOS NOS MAIORES BANCOS BRASILEIROS E O COMPONENTE ESTRATÉGICO DA PROVISÃO PARA RISCO DE CRÉDITO

O presente estudo buscou analisar as estruturas e os processos de gestão de riscos e o comportamento dos principais indicadores relacionados nas maiores instituições financeiras do Brasil, visando avaliar a eficácia do gerenciamento e a resiliência de tais indicadores frente a cenário adverso (COVID-19). A metodologia adotada foi a da pesquisa descritiva com técnicas padronizadas para coleta de dados em fontes públicas, para os procedimentos utilizou-se a pesquisa documental e na abordagem do problema adotou-se os métodos comparativo e estatístico, portanto abordagem quantitativa. Foram analisados os principais riscos incorridos, que guardam relação direta com a atividade bancária, quais sejam, risco de crédito, de mercado, de liquidez e operacional, além de uma avaliação sobre o cenário macroeconômico, interno e externo, e sobre o ambiente de riscos. Concluiu-se que os maiores bancos brasileiros estão adequadamente preparados para suportar cenários de maior adversidade, no tocante ao gerenciamento de seus riscos, com seus indicadores se demonstrando resilientes, mesmo em cenário estressado e de maior volatilidade. O estudo realizado é útil para os profissionais do mercado bancário e gestores de riscos

Proposta de Regulação para classificação de Fundos de Investimento sob a temática ASG / ESG (Ambiental, Social e Governança)

A presente proposta contempla a regulação de regras e critérios para que os Gestores de Ativos de Terceiros possam atribuir a classificação “ASG ou ESG” para Fundos de Investimento. Sequencialmente, serão apresentadas informações contextuais, o cenário atual e as justificativas que embasam a proposta de regulação do tema, denotando a crescente relevância do assunto para investidores e gestores de ativos no Brasil

Comparison of force variables and dynamic strength index between age groups in elite young Brazilian football goalkeepers

Introduction: The application of muscle force is a determinant of football success as it is inherent to the motor control and sport. The aims of this study are: (1) to describe force variables Isometric Maximal Force (IMF), Concentric Peak Force (CPPF), and Dynamic Strength Index (DSI) in football goalkeepers from different age groups; (2) to compare these variables’ behavior between those groups. Methods: The sample was formed by 19 youth players (15.97 ± 1.55 years old) from a first-division Brazilian football team. The CPPF and IMF variables were obtained through the Countermovement jump and isometric squat tests, respectively. For data collection, a force plate (Cefise, Brazil) was used with an acquisition frequency of 600 Hz and mono-axial. The DSI was calculated using the ratio between CPPF and IMF. For data analysis, the sample was separated into clusters by age. After the grouping, a descriptive analysis of the data and a comparison between the groups with p < 0.05. Results: The sample was grouped into three groups (GA, GB, and GC) and one of the individuals did not enter the group, totaling 18 individuals in the analyzed sample. The comparison between the ages of the groups showed a significant difference and small and moderate effect size (ES), validating the cluster strategy. The CPPF and IMF variables showed increased values according to chronological age. CPPF showed a significant difference between GA-GB, (ES = very large) GA-GC (ES = very large), and GB-GC (ES = moderate). The IMF variable had significant differences between GA-GB (ES = moderate) and GA-GC (ES = very large). However, DSI showed significant differences only between GA GB (ES = small) and GB-GC (ES = very large). Conclusions: The CPPF and IMF variables had constant increases and distinct values with an increase according to age, and this did not occur for DSI. The difference between CPPF and IMF compared to DSI bring to light the variability in dynamics and proportionality between muscular force in the concentric phase and maximal force in the isometric regime during the developmental process over chronological age in soccer goalkeepers.info:eu-repo/semantics/publishedVersio

Selection of reference genes for expression Study in pulp and seeds of Theobroma grandiflorum (Willd. ex Spreng.) Schum

Cupuassu (Theobroma grandiflorum [Willd. ex Spreng.] Schum) is a species of high economic importance in Brazil with great potential at international level due to the multiple uses of both its seeds and pulp in the industry of sweets and cosmetics. For this reason, the cupuassu breeding program focused on the selection of genotypes with high pulp and seed quality—selection associated with the understanding of the mechanisms involved in fruit formation. Gene expression is one of the most used approaches related to such understanding. In this sense, quantitative real-time PCR (qPCR) is a powerful tool, since it rapidly and reliably quantifies gene expression levels across different experimental conditions. The analysis by qPCR and the correct interpretation of data depend on signal normalization using reference genes, i.e. genes presenting a uniform pattern of expression in the analyzed samples. Here, we selected and analyzed the expression of five genes from cupuassu (ACP, ACT, GAPDH, MDH, TUB) to be used as candidates for reference genes on pulp and seed of young, maturing and mature cupuassu fruits. The evaluation of the gene expression stability was obtained using the NormFinder, geNorm and BestKeeper programs. In general, our results indicated that the GAPDH and MDH genes constituted the best combination as reference genes to analyze the expression of cupuassu samples. To our knowledge, this is the first report of reference gene definition in cupuassu, and these results will support subsequent analysis related to gene expression studies in cupuassu plants subjected to different biotic or abiotic conditions as well as serve as a tool for diversity analysis based on pulp and seed quality. (Résumé d'auteur

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

ATLANTIC-PRIMATES: a dataset of communities and occurrences of primates in the Atlantic Forests of South America

Primates play an important role in ecosystem functioning and offer critical insights into human evolution, biology, behavior, and emerging infectious diseases. There are 26 primate species in the Atlantic Forests of South America, 19 of them endemic. We compiled a dataset of 5,472 georeferenced locations of 26 native and 1 introduced primate species, as hybrids in the genera Callithrix and Alouatta. The dataset includes 700 primate communities, 8,121 single species occurrences and 714 estimates of primate population sizes, covering most natural forest types of the tropical and subtropical Atlantic Forest of Brazil, Paraguay and Argentina and some other biomes. On average, primate communities of the Atlantic Forest harbor 2 ± 1 species (range = 1–6). However, about 40% of primate communities contain only one species. Alouatta guariba (N = 2,188 records) and Sapajus nigritus (N = 1,127) were the species with the most records. Callicebus barbarabrownae (N = 35), Leontopithecus caissara (N = 38), and Sapajus libidinosus (N = 41) were the species with the least records. Recorded primate densities varied from 0.004 individuals/km 2 (Alouatta guariba at Fragmento do Bugre, Paraná, Brazil) to 400 individuals/km 2 (Alouatta caraya in Santiago, Rio Grande do Sul, Brazil). Our dataset reflects disparity between the numerous primate census conducted in the Atlantic Forest, in contrast to the scarcity of estimates of population sizes and densities. With these data, researchers can develop different macroecological and regional level studies, focusing on communities, populations, species co-occurrence and distribution patterns. Moreover, the data can also be used to assess the consequences of fragmentation, defaunation, and disease outbreaks on different ecological processes, such as trophic cascades, species invasion or extinction, and community dynamics. There are no copyright restrictions. Please cite this Data Paper when the data are used in publications. We also request that researchers and teachers inform us of how they are using the data. © 2018 by the The Authors. Ecology © 2018 The Ecological Society of Americ

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