Modelo de Rede Social Virtual para Inclusão Digital e Social

O rápido avanço da tecnologia na sociedade não só proporciona o auxílio de diversas ferramentas para comunicação e inclusão social, como também cria maior necessidade de presença na mesma, um grande exemplo disso são as redes sociais virtuais que se tornaram parte da rotina de grande parcela da população. Neste contexto, tivemos como objetivo encontrar e apresentar um modelo com interface e usabilidade de forma mais clara, permitindo assim que pessoas com deficiência intelectual se incluam em meios sociais digitais. A metodologia constou da análise das dificuldades, testando a usabilidade de outras redes sociais e posteriormente, a iteração com um modelo de rede social acessível gerada do estudo com um grupo de jovens e adultos deficientes intelectuais, frequentadores de um programa de educação especial. Este estudo, por fim, fornece resultados que comprovam a eficácia de uma interface mais adequada para uso daqueles que não estão acostumados com a quantidade excessiva de informação presente em diversos meios de comunicação hoje em dia

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

Signaling through retinoic acid receptors in cardiac development: Doing the right things at the right times

Retinoic acid (RA) is a terpenoid that is synthesized from vitamin A/retinol (ROL) and binds to the nuclear receptors retinoic acid receptor (RAR)/retinoid X receptor (RXR) to control multiple developmental processes in vertebrates. The available clinical and experimental data provide uncontested evidence for the pleiotropic roles of RA signaling in development of multiple embryonic structures and organs such eyes, central nervous system, gonads, lungs and heart. The development of any of these above-mentioned embryonic organ systems can be effectively utilized to showcase the many strategies utilized by RA signaling. However, it is very likely that the strategies employed to transfer RA signals during cardiac development comprise the majority of the relevant and sophisticated ways through which retinoid signals can be conveyed in a complex biological system. Here, we provide the reader with arguments indicating that RA signaling is exquisitely regulated according to specific phases of cardiac development and that RA signaling itself is one of the major regulators of the timing of cardiac morphogenesis and differentiation. We will focus on the role of signaling by RA receptors (RARs) in early phases of heart development1849294111CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP481983/2013-92011/15273-7; 2012/14859-0; 2013/12008-

Dismantling Brazil's science threatens global biodiversity heritage

In the middle of a political and fiscal crisis, the Brazilian government is applying successive budget cuts, including in science funding. Recent cuts radically affect research programs on biodiversity that are crucial components for the design and monitoring of public policies for nature conservation and sustainable development. We analyze the consequences of such cuts on the Research Program on Biodiversity (PPBio), the largest biodiversity research network in Brazil (626 researchers, nine networks in all Brazilian biomes). Brazil holds a substantial part of the world's biodiversity and of tropical forests that play a significant role for regional and global climate stability. If underfunding is maintained, the dismantling of the Brazilian PPBio will have consequences that go beyond biodiversity knowledge itself but affect society as a whole. Brazil will likely fail to reach the National Targets for Biodiversity 2011–2020, and it will be difficult to fulfill the restoration target of the Brazilian NDC and to advance with the sustainable development goals. © 2017 Associação Brasileira de Ciência Ecológica e Conservaçã