PROPOSTA DE (RE)DESIGN DO AMBIENTE EDUCATIVO FORMAL UNIVERSITÁRIO PARA ESTIMULAR UMA APRENDIZAGEM PROTAGONISTA, CRIATIVA E INOVADORA

Para atender às novas demandas sociais de uma educação inovadora, é fundamental reformular o ambiente educacional tradicional. Nesta pesquisa, objetiva-se projetar uma sala de aula que colabore com o protagonismo do aluno na construção do seu conhecimento tendo como premissa favorecer métodos de aprendizagem que estimulem a criatividade, comunicação, inovação, autonomia e a troca de conhecimentos entre alunos e professores. Com resultado: Um referencial da evolução histórica dos ambientes educacionais universitários e suas novas perspectivas; Um projeto arquitetônico de um Laboratório Aberto de Fabricação Digital: ambiente compartilhado para pesquisadores com o foco em criatividade e inovação

Architectural design of classroom to stimulate learning in higher education: an approach connected with neuroeducation and neuroarchitecture

The architectural design of learning spaces in higher education has undergone profound changes with the new educational perspectives that break with traditional pedagogical practice supported by control, hierarchy, and information dissemination. Educational institutions are gradually seeking disruptive models that enhance new learning experiences. This article presents references of innovative projects of learning and interaction spaces, that have been added to the principles of Neuroeducation and Neuroarchitecture for the development of architectural strategies for a new classroom proposal for the Bahia State University. As a result, the project brings preliminary studies to the Learning Environment Model for Higher Education (LEMHE). A flexible model, divided into three learning areas: flexible zone (active); introspection zone, and relaxing zone. This zoning aims to provide diverse experiences of pedagogical practices, added to respect the physiological needs of its users to enhance well-being and learning in higher education.info:eu-repo/semantics/publishedVersio

Zika Brazilian Cohorts (ZBC) Consortium: Protocol for an Individual Participant Data Meta-Analysis of Congenital Zika Syndrome after Maternal Exposure during Pregnancy.

Despite great advances in our knowledge of the consequences of Zika virus to human health, many questions remain unanswered, and results are often inconsistent. The small sample size of individual studies has limited inference about the spectrum of congenital Zika manifestations and the prognosis of affected children. The Brazilian Zika Cohorts Consortium addresses these limitations by bringing together and harmonizing epidemiological data from a series of prospective cohort studies of pregnant women with rash and of children with microcephaly and/or other manifestations of congenital Zika. The objective is to estimate the absolute risk of congenital Zika manifestations and to characterize the full spectrum and natural history of the manifestations of congenital Zika in children with and without microcephaly. This protocol describes the assembly of the Consortium and protocol for the Individual Participant Data Meta-analyses (IPD Meta-analyses). The findings will address knowledge gaps and inform public policies related to Zika virus. The large harmonized dataset and joint analyses will facilitate more precise estimates of the absolute risk of congenital Zika manifestations among Zika virus-infected pregnancies and more complete descriptions of its full spectrum, including rare manifestations. It will enable sensitivity analyses using different definitions of exposure and outcomes, and the investigation of the sources of heterogeneity between studies and regions

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

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

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

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

Determination of Total Carotenoids and β-Carotene in Germplasm of Pumpkin Caboclo (<i>Cucurbita maxima</i>)

The genus Cucurbita has been mentioned as a good source of carotenoids, including β-carotene, which is a precursor of vitamin A. However, the variability observed for the genus denotes the individual need to invest in the species. An experiment was carried out with the aim of evaluating the content of total carotenoids and β-carotene in C. maxima germplasm. Treatments consisted of 23 accessions and two commercial cultivars of C. maxima. The content of total carotenoids, β-carotene, and the pulp color of the accessions were evaluated. Clustering was performed, and the components of genotypic variance, mean heritability, and accuracy were calculated. The grouping led to the formation of four groups where the total carotenoid content influenced the formation the most. There was no difference in color parameters. High variability was observed for total carotenoids in the studied genotypes (22.28 µg/g to 49.58 µg/g) and β-carotene (7.81 µg/g to 13.75 µg/g). Accessions CMAX-09, CMAX-10, CMAX-12, CMAX-13, and CMAX-14 showed the highest levels of total carotenoids and β-carotene