22 research outputs found

    A AUTORREPRESENTAÇÃO COMO PRÁTICA DE SI

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    Este artigo é uma pesquisa em arte sobre a produção de um autorretrato que parte da questão: como a autorrepresentação feminina pode colaborar para contrapor os enunciados normativos sobre a mulher? Para isso, objetivo pesquisar o discurso artístico como estratégia feminista de criação de subjetividades não dominadas pelo poder patriarcal; conceituar práticas de si como possibilidade que as artistas feministas tem recorrido para discutir relações de poder na esfera privada; analisar o processo criativo de um autorretrato pictórico como prática de si na construção de discursos que contrapõe narrativas cristalizadas sobre a mulher. Palavras-chave: Feminismo. Processo Criativo. Pintura

    Editorial

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    Editorial da Revista Palíndromo n. 37: Publicações de artista: espaço e tempo do impresso ao virtual&nbsp

    SISTEMA HÍBRIDO DE ENERGIA: FUNCIONAMENTO E UTILIZAÇÃO RESIDENCIA

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    Sabendo da escassez de fontes de energia ecologicamente sustentável, foi estudada uma alternativa para as fontes de energia elétrica comuns em nosso país, para que em meio à escassez de recursos hídricos, termelétricos e nucleares, possa haver um melhor aproveitamento da energia elétrica consumida pelo usuário final. A proposta apresenta uma alternativa através de uma fonte híbrida de geração, composta por um sistema que concilia energia eólica e fotovoltaica. O projeto apresenta um conceito inovador em âmbito nacional, mas comumente utilizado na Europa, chamado Sistema Smart Grid, que possibilita a junção da energia gerada pela concessionária e pela fonte híbrida para o consumo. A partir da estimativa de geração das fontes e de dados coletados de sistemas já implantados, estipulou-se que o sistema proposto, seria capaz de atender a demanda desejada.   Palavras-chave: Energia Eólica. Energia Solar. Sistema híbrido de energia. Sistema Smart Grid

    Atendimento psicoeducacional a crianças com problemas de escolarização e TDAH

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    Anais do 35º Seminário de Extensão Universitária da Região Sul - Área temática: EducaçãoO presente trabalho consiste em um relato de experiência oriundo das intervenções em projeto de extensão, pautado nos pressupostos teóricos da Psicologia Histórico-Cultural sobre queixas escolares relacionadas ao diagnóstico TDAH. A referida abordagem compreende o desenvolvimento humano como um processo histórico que necessita de condições materiais para a apropriação de signos e produções humanas. Dessa perspectiva, as queixas são compreendidas para além do biologicismo, parte-se da zona de desenvolvimento real a qual a criança se encontra, vislumbrando a zona de desenvolvimento proximal, a qual as intervenções são direcionadas visando por meio de atividades mediadas e intencionais promover o desenvolvimento das funções psicológicas superiores. As queixas são recebidas pela Unidade de Psicologia Aplicada (UPA) e encaminhadas para entrevista, em que são selecionados os casos pertinentes aos objetivos do projeto. Neste ano recebemos uma variedade grande de queixas, incluindo diagnósticos de TDAH, dificuldades de alfabetização e desenvolvimento da linguagem oral e escrita. Como objetivos, buscamos trabalhar as questões diferenciais do trabalho com grupo e conhecer as relações que permeiam a construção da queixa escolar. Como fim, buscamos a superação da patologização do não aprender e da medicalização desnecessária, mas recorrente em contexto escolar. Por meio de espaços como este de intervenção, acreditamos ser possível o desenvolvimento de potencialidades, para que as crianças sejam capazes de resignifcar suas histórias e ser autoras de suas próprias vida

    Pervasive gaps in Amazonian ecological research

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    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

    Pervasive gaps in Amazonian ecological research

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    Pervasive gaps in Amazonian ecological research

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    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

    Get PDF
    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

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    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
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