Qualidade do jogo de “faz-de-conta” em crianças na idade pré-escolar: relação com o Scaffolding paterno

Dissertação de mestrado integrado em Psicologia (área de especialização em Psicologia Clínica e da Saúde)As crianças desenvolvem as competências cognitivas, primeiramente, como resultado da interação social com os mais experientes, até serem capazes de agir com competência independentemente (Vygotsky, 1978). O scaffolding paterno assume, portanto, um papel importante no desenvolvimento das capacidades da criança. Com base neste pressuposto, o principal objetivo deste trabalho é compreender como é que as figuras paternas promovem o jogo do “faz-de-conta” nos seus filhos, em idade pré-escolar. Participaram no estudo 46 crianças (27 do sexo masculino, 58.7%) com 3 anos de idade, e respetivas figuras paternas. O estudo foi realizado tendo por base uma tarefa semiestruturada de jogo de “faz-de-conta”, com a orientação para recriar um piquenique no campo. As interações foram vídeo-gravadas e, posteriormente, analisadas e codificadas segundo o sistema de codificação desenvolvido no âmbito da presente investigação. De acordo com os resultados obtidos, figuras paternas mais sensíveis são mais cooperantes, e menos intrusivos. Por outro lado, pais mais intrusivos são menos cooperantes e mais controladores. Por fim, estas duas últimas estão negativamente correlacionadas. Maior sensibilidade paterna está, também, associada a maior qualidade no jogo simbólico, maior QI verbal, de realização, e total; e menor controlo paterno está associada a maior QI de realização.Children develop cognitive skills, primarily, as a result of social interaction with more experienced people, until being able to act with competence independently (Vygotsky, 1978). Paternal scaffolding assumes an important role in the development of children's abilities. Based on this assumption, the main objetive of this work is to understand how fathers promote pretense play in their preschool children. Forty-six children 3-years-old participated in the study (27 male, 58.7%) with their parents. The study was based on a semisstructured task, under the orientation to recreate a picnic in the countryside. The interactions were videotaped and then analyzed and coded according to the coding system developed under this research. According to the results, fathers more sensitive are more cooperating, and less obtrusive. On the other hand, fathers more intrusive are less cooperative and more controllers. Finally, the last two are negatively correlated. Higher paternal sensitivity is also associated with a higher quality of symbolic play, higher verbal IQ, performance IQ, and full scale IQ; and less parental guidance is associated with higher performance IQ

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

The Genome of Anopheles darlingi, the main neotropical malaria vector

Anopheles darlingi is the principal neotropical malaria vector, responsible for more than a million cases of malaria per year on the American continent. Anopheles darlingi diverged from the African and Asian malaria vectors ∼100 million years ago (mya) and successfully adapted to the New World environment. Here we present an annotated reference A. darlingi genome, sequenced from a wild population of males and females collected in the Brazilian Amazon. A total of 10 481 predicted protein-coding genes were annotated, 72% of which have their closest counterpart in Anopheles gambiae and 21% have highest similarity with other mosquito species. In spite of a long period of divergent evolution, conserved gene synteny was observed between A. darlingi and A. gambiae. More than 10 million single nucleotide polymorphisms and short indels with potential use as genetic markers were identified. Transposable elements correspond to 2.3% of the A. darlingi genome. Genes associated with hematophagy, immunity and insecticide resistance, directly involved in vectorhuman and vectorparasite interactions, were identified and discussed. This study represents the first effort to sequence the genome of a neotropical malaria vector, and opens a new window through which we can contemplate the evolutionary history of anopheline mosquitoes. It also provides valuable information that may lead to novel strategies to reduce malaria transmission on the South American continent. The A. darlingi genome is accessible at www.labinfo.lncc.br/index.php/anopheles- darlingi. © 2013 The Author(s)

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