MONITORIA GERAL DA DISCIPLINA ELEMENTOS DE INFORMÁTICA PARA DISCENTES DO CURSO DE AGRONOMIA

Atualmente, no mundo onde a informação e conhecimento circulam através de recursos e tecnologiascada vez mais modernos, pode-se declarar que o panorama atual é configurado como uma Revolução Digital.O uso da informática no dia-a-dia dos indivíduos se teve crescimento exponencial a partir do surgimento dainternet e com a popularização dos computadores pessoais (PC), hoje sendo ferramenta essencial para o idealdesenvolvimento e manutenção de diversas áreas da sociedade moderna. Isso posto, o objetivo com estetrabalho é expor as experiências de ensino como monitor de classe presenciadas durante um período letivoemergencial (PLE). Este trabalho foi realizado durante o período de Setembro de 2020 a Dezembro de 2020,atividades desenvolvidas na disciplina “Elementos de Informática” para uma turma de ingressantes no Cursode Bacharelado em Agronomia pela Universidade Federal do Sul e Sudeste do Pará. Inicialmente, os alunosapresentaram algumas dificuldades de adaptação para com as ferramentas apresentadas e utilizadas, pois boaparte dos discentes, até o momento, se tinham tido contato com as ferramentas, era pouco. Um dos problemasenfrentados por grande parte dos estudantes durante o decorrer da disciplina, foi a indisponibilidade de umaboa conexão de internet. Fato que prejudicou a experiência de aprendizagem para muitos, visto que alguns nãoestavam em áreas urbanas e assim tinham menor qualidade do serviço de internet. Pôde-se ter significativosresultados na disciplina, visto que grande parte dos estudantes iniciaram com pouco (ou nenhum)conhecimento das ferramentas digitais trabalhadas e concluíram a disciplina demonstrando significativodomínio sobre as mesmas. Diante disso, pôde-se observar bons resultados no decorrer da experiência comomonitor, sobretudo num contexto de distanciamento social onde a utilização de ferramentas de ensino digitaisforam essenciais para a manutenção das atividades acadêmicas

Does the facial pattern give individuals a profile of a crime suspect?

To evaluate the influence of mesofacial, brachyfacial and dolichofacial facial patterns on giving an individual the profile of a crime suspect in the eyes of public security agents. This study had a cross-sectional design, conducted with public security agents of both sexes (n=100), where images of facial composites (police sketches) of individuals with different facial patterns (mesofacial, brachyfacial and dolichofacial) were used. With these images in hand, a questionnaire was created, divided into three parts: the first in which all the images were presented together, allowing comparison among them; the second, in which each image was evaluated separately followed by questions and the third that consisted on a visual analog scale that presented a bar with marks going from 0 to 100, where 0 represented the untrustworthy individual, 50 the individual who could be trusted, and 100 a very trustworthy individual. When all the data had been obtained statistical analyses were performed using the Chi-square and Friedman tests. The level of significance adopted was 5% (α=0.05). The dolichofacial individual was associated with security agents as the most prone to commit crimes and became more insecure and distrustful when compared to the mesofacial and brachyfacial individuals (p <0.001). The dolichofacial profile had a negative influence on the judgment of security agents who attributed to it, a character suspected of a crime and a low level of trustworthiness

Ways to Measuring Quality of Life in Mental Health

As quality is of life considered as a measure of clinical outcome that prioritizes client assessment itself and the effects of a disease, a life change or a treatment has on their daily life and their level of satisfaction and well-being, their evaluation allows obtain a safe parameter for implementing clinical interventions that may have more positive impact on the lives of these people. It is believed that investigate the QoL of a given population is a strategy that will enable to broaden the understanding of the problems experienced by patients in order to facilitate effective future interventions, improving the quality of lived days. This information can also be used to identify patients at higher risk of problems and thus anticipate interventions, contributing to health promotion thereof. Nevertheless, there is currently a growing interest in transforming the QoL in a quantitative measure. To this end, the measurement of quality of life through the perception of the patient has been recommended. Some studies indicate that the measurement of quality of life the mental patient is an indicator of the care he receives and that this issue should be included in the assessment and care planning. There are few studies witch accessed the influence of health intervention on patients ‘quality of life, anxiety, and depressive symptom levels. With this brief contribution, we hope can deepen discussion regards public health and mental wellbeing, as well as the options of measurement instruments to assess mental health interventions and thus able to gather more arguments to answer the following question: What`s the best way for measuring quality of life in Mental health

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

Estimulação cerebral profunda na Doença de Parkinson: evidências de estudos de longa duração

A Doença de Parkinson (DP) é uma condição neurodegenerativa crônica que afeta principalmente idosos, mas pode ocorrer em adultos jovens. É a segunda doença neurodegenerativa mais comum, após o Alzheimer. A DP afeta 1% dos indivíduos acima de 60 anos em países industrializados. Sua causa envolve fatores genéticos e ambientais, como exposição a pesticidas e envelhecimento. A Estimulação Cerebral Profunda (DBS) é um tratamento que simula lesões cerebrais, melhorando sintomas motores e não motores. O presente estudo tem como objetivo analisar evidências de estudos sobre a eficácia da DBS no tratamento da DP. Trata-se de uma revisão sistemática de estudos quantitativos que utiliza as bases de dados PubMed (Medline), Cochrane Library e Scientific Electronic Library Online (SciELO) para selecionar artigos científicos. Os estudos incluídos abrangem o período de 2013 a 2023 e estão em inglês, abordando a DBS no tratamento da DP. A DBS melhora diversos sintomas motores e não motores, resultando em uma melhor qualidade de vida para os pacientes. Tais benefícios são sustentados mesmo em estágios avançados da Doença de Parkinson, a qual consiste em fornecer pulsos de corrente elétrica a áreas cerebrais profundas através de eletrodos implantados cirurgicamente, geralmente quando a terapia medicamentosa já não é eficaz. Em um estudo com 82 pacientes, a terapia com DBS resultou em uma redução de ± 52% nos sintomas motores do UPDRS sob medicação antes da cirurgia. A melhora nos sintomas motores com a estimulação, em comparação com a ausência de estimulação e medicação, foi de ± 61% no primeiro ano e ± 39% de 8 a 15 anos após a cirurgia (antes da reprogramação). A medicação foi reduzida em ± 55% após 1 ano e ± 44% após 8 a 15 anos, com a maioria dos pacientes mostrando melhorias após a reprogramação. De acordo com as literaturas analisadas, a DBS é uma terapia eficaz para a DP. Enfatiza-se a importância da inovação contínua e dos novos estudos para explorar as facetas não investigadas desse campo. Com a abordagem dos aspectos clínicos, cirúrgicos, tecnológicos e científicos, destacam-se os benefícios, limitações e desafios a serem superados. Ademais, inovações tecnológicas na DBS, como a estimulação direcional, adaptativa e a telemedicina estão sendo exploradas. Em suma, este artigo fornece evidências sobre os benefícios da DBS na DP, ressaltando a necessidade de pesquisas adicionais para otimizar tal intervenção terapêutica e melhorar a qualidade de vida dos pacientes

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

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ