VISITAS ORIENTADAS: UMA CONTRIBUIÇÃO PARA A DIVULGAÇÃO E INGRESSO DE NOVOS ALUNOS NO IFC CAMPUS SANTA ROSA DO SUL

O projeto teve como objetivo acolher as escolas da região litoral sul de Santa Catarina e norte do Rio Grande do Sul, apresentando as estruturas de ensino, biblioteca, refeitório, alojamentos, áreas esportivas e parte agrícola, esclarecendosobre o processo seletivo para ingresso de alunos nos cursos de Técnico em Agropecuária ou para o superior de Engenharia Agronômica. O agendamento das visitas é realizado pelo site da instituição, através do preenchimento de um formulárioon-line. Foram atendidas 526 pessoas pelo projeto, sendo recebidas 15 escolas totalizando 502 alunos e mais 7 famílias que realizaram visitas individuais totalizando 24 pessoas

CDJUR-BR -- A Golden Collection of Legal Document from Brazilian Justice with Fine-Grained Named Entities

A basic task for most Legal Artificial Intelligence (Legal AI) applications is Named Entity Recognition (NER). However, texts produced in the context of legal practice make references to entities that are not trivially recognized by the currently available NERs. There is a lack of categorization of legislation, jurisprudence, evidence, penalties, the roles of people in a legal process (judge, lawyer, victim, defendant, witness), types of locations (crime location, defendant's address), etc. In this sense, there is still a need for a robust golden collection, annotated with fine-grained entities of the legal domain, and which covers various documents of a legal process, such as petitions, inquiries, complaints, decisions and sentences. In this article, we describe the development of the Golden Collection of the Brazilian Judiciary (CDJUR-BR) contemplating a set of fine-grained named entities that have been annotated by experts in legal documents. The creation of CDJUR-BR followed its own methodology that aimed to attribute a character of comprehensiveness and robustness. Together with the CDJUR-BR repository we provided a NER based on the BERT model and trained with the CDJUR-BR, whose results indicated the prevalence of the CDJUR-BR.Comment: 15 pages, in Portuguese language, 3 figures, 5 table

Connectome hubs at resting state in children and adolescents:reproducibility and psychopathological correlation

AbstractFunctional brain hubs are key integrative regions in brain networks. Recently, brain hubs identified through resting-state fMRI have emerged as interesting targets to increase understanding of the relationships between large-scale functional networks and psychopathology. However, few studies have directly addressed the replicability and consistency of the hub regions identified and their association with symptoms. Here, we used the eigenvector centrality (EVC) measure obtained from graph analysis of two large, independent population-based samples of children and adolescents (7–15 years old; total N=652; 341 subjects for site 1 and 311 for site 2) to evaluate the replicability of hub identification. Subsequently, we tested the association between replicable hub regions and psychiatric symptoms. We identified a set of hubs consisting of the anterior medial prefrontal cortex and inferior parietal lobule/intraparietal sulcus (IPL/IPS). Moreover, lower EVC values in the right IPS were associated with psychiatric symptoms in both samples. Thus, low centrality of the IPS was a replicable sign of potential vulnerability to mental disorders in children. The identification of critical and replicable hubs in functional cortical networks in children and adolescents can foster understanding of the mechanisms underlying mental disorders

Effect of High vs Low Doses of Chloroquine Diphosphate as Adjunctive Therapy for Patients Hospitalized With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection: A Randomized Clinical Trial.

There is no specific antiviral therapy recommended for coronavirus disease 2019 (COVID-19). In vitro studies indicate that the antiviral effect of chloroquine diphosphate (CQ) requires a high concentration of the drug.To evaluate the safety and efficacy of 2 CQ dosages in patients with severe COVID-19. This parallel, double-masked, randomized, phase IIb clinical trial with 81 adult patients who were hospitalized with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection was conducted from March 23 to April 5, 2020, at a tertiary care facility in Manaus, Brazilian Amazon. - Patients were allocated to receive high-dosage CQ (ie, 600 mg CQ twice daily for 10 days) or low-dosage CQ (ie, 450 mg twice daily on day 1 and once daily for 4 days). - Label: Main Outcomes and Measures Primary outcome was reduction in lethality by at least 50% in the high-dosage group compared with the low-dosage group. Data presented here refer primarily to safety and lethality outcomes during treatment on day 13. Secondary end points included participant clinical status, laboratory examinations, and electrocardiogram results. Outcomes will be presented to day 28. Viral respiratory secretion RNA detection was performed on days 0 and 4. Out of a predefined sample size of 440 patients, 81 were enrolled (41 [50.6%] to high-dosage group and 40 [49.4%] to low-dosage group). Enrolled patients had a mean (SD) age of 51.1 (13.9) years, and most (60 [75.3%]) were men. Older age (mean [SD] age, 54.7 [13.7] years vs 47.4 [13.3] years) and more heart disease (5 of 28 [17.9%] vs 0) were seen in the high-dose group. Viral RNA was detected in 31 of 40 (77.5%) and 31 of 41 (75.6%) patients in the low-dosage and high-dosage groups, respectively. Lethality until day 13 was 39.0% in the high-dosage group (16 of 41) and 15.0% in the low-dosage group (6 of 40). The high-dosage group presented more instance of QTc interval greater than 500 milliseconds (7 of 37 [18.9%]) compared with the low-dosage group (4 of 36 [11.1%]). Respiratory secretion at day 4 was negative in only 6 of 27 patients (22.2%). - Label: Conclusions and Relevance The preliminary findings of this study suggest that the higher CQ dosage should not be recommended for critically ill patients with COVID-19 because of its potential safety hazards, especially when taken concurrently with azithromycin and oseltamivir. These findings cannot be extrapolated to patients with nonsevere COVID-19

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

Mundos mesclados, espaços segregados: cultura material, mestiçagem e segmentação no sítio Aldeia em Santarém (PA)

This article discusses the processes of cultural exchange between Portuguese, Portuguese-Brazilian, Amerindians, and mestizos based on the analysis of the material culture from households of Santarém (PA), occupied during the eighteenth and nineteenth centuries,. Although these social groups manipulated material culture aiming to express different values, related to hierarchy, social segmentation, and affirmation of identities, ambiguity also characterizes these assemblages. This material ambiguity informs about the mixtures of both practices and cultural references that brought about the building of a mestizo society.Com base na análise da cultura material proveniente de unidades domésticas do núcleo urbano de Santarém (PA), ocupadas nos séculos XVIII e XIX, o presente artigo discute os processos de trocas culturais entre portugueses, luso-brasileiros, indígenas e mestiços. Embora esses grupos sociais tenham manipulado a cultura material visando expressar diferentes valores, relacionados à hierarquia, segmentação social e afirmação de identidades, a ambigüidade é uma característica das amostras analisadas, informando sobre as misturas de práticas e de referenciais culturais que levaram à construção de uma sociedade mestiça

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