Construção de uma bancada didática de performance / Building a performance teaching bench

O presente trabalho tem o propósito de apresentar todo o resultado do desenvolvimento de uma bancada didática com o objetivo de complementar o ensino nos cursos de Engenharia na Universidade do Estado do Rio de Janeiro, Unidade de Resende, junto ao Laboratório de Motores, Hidráulica e Pneumática. No desenvolvimento deste trabalho, é necessário enfatizar a integração e a importância da execução de atividades práticas junto aos recursos audiovisuais no ensino, em continuidade as aulas teóricas durante a graduação. Inicialmente é desenvolvida a demonstração do funcionamento de uma caixa de marchas veicular, que neste propósito foi acionada por um motor elétrico, para explicar o próprio funcionamento interno da transmissão assim como a relação de transferência de torque e potência passando por todo “powertrain” e chegando ao solo através do torque líquido do pneu. Para exemplificar esta relação motor e transmissão, foi desenvolvido em paralelo uma planilha de dados, com base no conceito da dinâmica veicular, relacionando informações a performance do modelo e permitindo que os alunos simulem condições por intermédio de alteração dos dados de entrada a fim de que gere resultados na análise proposta. Desta forma, o presente trabalho foi desenvolvido em uma bancada acadêmica adaptada para receber uma transmissão mecânica veicular, um motor elétrico, uma “Smart TV” e um computador, permitindo a compreensão física do conjunto motor- transmissão, através da interatividade dos alunos com a apresentação de outros dispositivos do “powertrain” e de uma planilha de dados simulando condições da dinâmica veicular, e oferecer condições e um ambiente propício para facilitar que os alunos compreendam as análises de performance, independente dos ciclos serem motores Otto, Diesel ou um circuito Híbrido.

Retorno às aulas presenciais no sistema educacional do estado do Pará-Brasil: Obstáculos e desafios durante a epidemia de Covid-19(Sars-Cov-2) / Return to presential classes in the educational system of the state of Pará-Brazil: obstacles and challenges during the covid-19 epidemic (Sars-Cov-2)

O presente trabalho trata do impacto da Pandemia causada pelo CORONAVÍRUS (SARS-CoV-2), no meio educacional brasileiro, em especial nas cidades do Estado do Pará,  e as normas possíveis necessárias para a retomada segura ao trabalho nestes locais e  os métodos sanitários utilizados pelos Países mais atingidos, China, Coréia do Sul, França, Espanha e Alemanha além das táticas adotadas por estas Nações, na retomada dos trabalhos educacionais, observando seu sucesso ou fracasso, tomando a partir de investigações sugestões para a volta das atividades escolares de uma forma segura e escalonada. Foi implementados sugestões de mudança do ambiente escolar com a adequação da entrada, intervalos, quantidade de alunos em sala e saída dos alunos. O objetivo é investigar e alertar a população e aos órgãos gestores da educação no Estado do Pará dos efeitos ocasionados pela Pandemia COVID-19.Também foi interpretado um modelo matemático da curva de casos no Estado do Pará, cedido pela SESPA, juntamente com os casos recuperados e número de óbitos, tomando a partir daí estratégias para o retorno ao trabalho em função da apropriação e investigação do modelo

Detection and identification of Xanthomonas pathotypes associated with citrus diseases using comparative genomics and multiplex PCR.

Background. In Citrus cultures, three species of Xanthomonas are known to cause distinct diseases. X. citri subsp. citri patothype A, X. fuscans subsp. aurantifolii pathotypes B and C, and X. alfalfae subsp. citrumelonis, are the causative agents of cancrosis A, B, C, and citrus bacterial spots, respectively. Although these species exhibit different levels of virulence and aggressiveness, only limited alternatives are currently available for proper and early detection of these diseases in the fields. The present study aimed to develop a new molecular diagnostic method based on genomic sequences derived from the four species of Xanthomonas. Results. Using comparative genomics approaches, primers were synthesized for the identification of the four causative agents of citrus diseases. These primers were validated for their specificity to their target DNA by both conventional and multiplex PCR. Upon evaluation, their sensitivity was found to be 0.02 ng/?l in vitro and 1.5 ? 104 CFU ml?1 in infected leaves. Additionally, none of the primers were able to generate amplicons in 19 other genomes of Xanthomonas not associated with Citrus and one species of Xylella, the causal agent of citrus variegated chlorosis (CVC). This denotes strong specificity of the primers for the different species of Xanthomonas investigated in this study. Conclusions. We demonstrated that these markers can be used as potential candidates for performing in vivo molecular diagnosis exclusively for citrus-associated Xanthomonas. The bioinformatics pipeline developed in this study to design specific genomic regions is capable of generating specific primers. It is freely available and can be utilized for any other model organism

Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data

Tropical savanna ecosystems play a major role in the seasonality of the global carbon cycle. However, their ability to store and sequester carbon is uncertain due to combined and intermingling effects of anthropogenic activities and climate change, which impact wildfire regimes and vegetation dynamics. Accurate measurements of tropical savanna vegetation aboveground biomass (AGB) over broad spatial scales are crucial to achieve effective carbon emission mitigation strategies. UAV-lidar is a new remote sensing technology that can enable rapid 3-D mapping of structure and related AGB in tropical savanna ecosystems. This study aimed to assess the capability of high-density UAV-lidar to estimate and map total (tree, shrubs, and surface layers) aboveground biomass density (AGBt) in the Brazilian Savanna (Cerrado). Five ordinary least square regression models esti-mating AGBt were adjusted using 50 field sample plots (30 m × 30 m). The best model was selected under Akaike Information Criterion, adjusted coefficient of determination (adj.R2), absolute and relative root mean square error (RMSE), and used to map AGBt from UAV-lidar data collected over 1,854 ha spanning the three major vegetation formations (forest, savanna, and grassland) in Cerrado. The model using vegetation height and cover was the most effective, with an overall model adj-R2 of 0.79 and a leave-one-out cross-validated RMSE of 19.11 Mg/ha (33.40%). The uncertainty and errors of our estimations were assessed for each vegetation formation separately, resulting in RMSEs of 27.08 Mg/ha (25.99%) for forests, 17.76 Mg/ha (43.96%) for savannas, and 7.72 Mg/ha (44.92%) for grasslands. These results prove the feasibility and potential of the UAV-lidar technology in Cerrado but also emphasize the need for further developing the estimation of biomass in grasslands, of high importance in the characterization of the global carbon balance and for supporting integrated fire management activities in tropical savanna ecosystems. Our results serve as a benchmark for future studies aiming to generate accurate biomass maps and provide baseline data for efficient management of fire and predicted climate change impacts on tropical savanna ecosystems

Health-related quality of life in patients with type 1 diabetes mellitus in the different geographical regions of Brazil : data from the Brazilian Type 1 Diabetes Study Group

Background: In type 1 diabetes mellitus (T1DM) management, enhancing health-related quality of life (HRQoL) is as important as good metabolic control and prevention of secondary complications. This study aims to evaluate possible regional differences in HRQoL, demographic features and clinical characteristics of patients with T1DM in Brazil, a country of continental proportions, as well as investigate which variables could influence the HRQoL of these individuals and contribute to these regional disparities. Methods: This was a retrospective, cross-sectional, multicenter study performed by the Brazilian Type 1 Diabetes Study Group (BrazDiab1SG), by analyzing EuroQol scores from 3005 participants with T1DM, in 28 public clinics, among all geographical regions of Brazil. Data on demography, economic status, chronic complications, glycemic control and lipid profile were also collected. Results: We have found that the North-Northeast region presents a higher index in the assessment of the overall health status (EQ-VAS) compared to the Southeast (74.6 ± 30 and 70.4 ± 19, respectively; p < 0.05). In addition, North- Northeast presented a lower frequency of self-reported anxiety-depression compared to all regions of the country (North-Northeast: 1.53 ± 0.6; Southeast: 1.65 ± 0.7; South: 1.72 ± 0.7; Midwest: 1.67 ± 0.7; p < 0.05). These findings could not be entirely explained by the HbA1c levels or the other variables examined. Conclusions: Our study points to the existence of additional factors not yet evaluated that could be determinant in the HRQoL of people with T1DM and contribute to these regional disparities

ATLANTIC-CAMTRAPS: a dataset of medium and large terrestrial mammal communities in the Atlantic Forest of South America

Our understanding of mammal ecology has always been hindered by the difficulties of observing species in closed tropical forests. Camera trapping has become a major advance for monitoring terrestrial mammals in biodiversity rich ecosystems. Here we compiled one of the largest datasets of inventories of terrestrial mammal communities for the Neotropical region based on camera trapping studies. The dataset comprises 170 surveys of medium to large terrestrial mammals using camera traps conducted in 144 areas by 74 studies, covering six vegetation types of tropical and subtropical Atlantic Forest of South America (Brazil and Argentina), and present data on species composition and richness. The complete dataset comprises 53,438 independent records of 83 species of mammals, includes 10 species of marsupials, 15 rodents, 20 carnivores, eight ungulates and six armadillos. Species richness averaged 13 species (±6.07 SD) per site. Only six species occurred in more than 50% of the sites: the domestic dog Canis familiaris, crab-eating fox Cerdocyon thous, tayra Eira barbara, south American coati Nasua nasua, crab-eating raccoon Procyon cancrivorus and the nine-banded armadillo Dasypus novemcinctus. The information contained in this dataset can be used to understand macroecological patterns of biodiversity, community, and population structure, but also to evaluate the ecological consequences of fragmentation, defaunation, and trophic interactions. © 2017 by 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 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