Echoes of time. The mobility of Brazilian researchers and students in Portugal

A investigação que apresentamos, de caráter exploratório, recaiu sobre histórias biográficas de brasileiros que escolhem Portugal para prosseguir formação e ou investigação. Procura-se encontrar na sua experiência elos de ligação explicativos sobre as motivações e os processos que os trazem para Portugal, assim como as expetativas e os projetos que comportam para os seus futuros e que incluem, ou não, este país. Temos em conta, especialmente, a forma como essa narrativa transporta sentidos identitários decorrentes das formas de relacionamento intercultural e político entre Portugal e Brasil e formas de cooperação implícitas, assim como mapas representacionais acerca dos lugares de eleição para desenvolvimento de carreiras científicas e académicas. A nossa pesquisa incide sobre as informações recolhidas através de um inquérito por questionário e entrevistas realizadas junto de estudantes e bolseiros brasileiros em Portugal.We present an exploratory study that investigated biographical stories of Brazilians who choose to continue their education or develop research in Portugal. We sought to find in their experiences explanatory links connecting the motivations and processes that bring them to Portugal, as well as the expectations and projects that they hold for the future, which may include, or not, this country. We take into account, particularly, the way this narrative carries senses of identity arising from the forms of intercultural and political relationship between Portugal and Brazil, as well as implicit forms of cooperation and representations about the places chosen for the development of scientific and academic careers. Our research draws on information collected through a survey based on questionnaires and interviews with Brazilian students and scholarship holders in Portugal.(undefined

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

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

Public intervention in food and nutrition in Brazil

En las últimas dos décadas, el gobierno brasileño creó varios programas de transferencia de ingresos para los más pobres con el objetivo de promover la seguridad alimentaria y nutricional, así como para erradicar la pobreza extrema y el hambre. Estos programas proporcionaron algunos resultados satisfactorios, lo que no se puede atribuir exclusivamente a la transferencia de ingresos, sino también a otros sectores gubernamentales y a diversas políticas públicas en las áreas de educación, salud y saneamiento básico. En conjunto, estas políticas están destinadas a romper el patrón de pobreza intergeneracional, contribuyendo con el desarrollo humano del país

Sobrepeso em crianças menores de 6 anos de idade em Florianópolis, SC Overweight in children under 6 years of age in Florianópolis, SC, Brazil

Verificou-se a prevalência de sobrepeso através do índice de peso para altura, classificação expressa em escore-Z, padrão de referência do National Center for Health Statistics, em 3 806 crianças menores de seis anos de idade, residentes no município de Florianópolis, Estado de Santa Catarina, Brasil. Obteve-se uma prevalência de 1,9% de desnutrição e 6,8% de sobrepeso, sendo este predominante em crianças residentes em áreas não carentes, do sexo feminino e menores de dois anos de idade. A prevalência de sobrepeso deste estudo foi comparada com aquelas encontradas em outras regiões do Brasil e em outros países. Aplicou-se o teste chi2 (Mantel-Haenszel), para verificar a associação de casos com sobrepeso entre áreas carentes e não carentes, sexo e faixa etária. Observou-se associação estatisticamente significante (p<0,05) entre as crianças menores de dois anos de idade, resultado semelhante ao encontrado pela Pesquisa Nacional sobre Saúde e Nutrição para o Brasil em 1989.<br>The prevalence of overweight in 3,806 children under six years of age, living in the city of Florianópolis, state of Santa Catarina, Brazil, was determined through weight for height Z-scores (National Center for Health Statistics reference). Results showed an incidence of 1.9% for malnutrition and 6.8% for overweight, and this last one predominated in female children under the age of two, living in not-so-poor areas. The prevalence of overweight in this study was compared to those found in other regions of Brazil and in other countries. The chi2 Mantel-Haenszel test was applied to verify the association of overweight occurrence with poor/not poor areas, sex and age. Statistically significant association (p<0.05) was observed among children under two years of age. This result is similar to the one found by Pesquisa Nacional sobre Saúde e Nutrição for Brazil in 1989