ABORDAGEM INTERDISCIPLINAR NO PROEJA

Em se tratando de educação, além do chamado “êxito escolar”, temas como os que envolvem “evasão” e “permanência” são alguns dos quais mais geram apreensão na sociedade. Tal inquietação tende a se aprofundar quando o debate abrange discentes da educação direcionada para jovens e adultos (EJA), uma vez que os mesmos já são pessoas que não puderam estudar no período que foi convencionado como o mais adequado e, portanto, estão buscando, em outra faixa etária, uma nova chance na rede formal de ensino. Diante disso, encontrar maneiras para mitigar a evasão, elevando a permanência na modalidade EJA, é de grande relevância. Assim, o presente trabalho objetiva: 1-apontar alguns dos motivos que podem levar ao abandono; e 2-promover uma proposta de execução interdisciplinar em curso EJA, da Educação Profissional e Tecnológica, com o intuito de despertar no alunado o sentimento de importância individual e coletiva da sua formação. Os resultados esperados são: maior integração entre as disciplinas do curso escolhido; elevação da motivação do alunado; e redução da evasão escolar

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

Tendências de consumo de leite de cabra: enfoque para a melhoria da qualidade

The goat milk is defined as product originating from complete, uninterrupted, under hygiene conditions of milking from animals of the goat specie, well fed and rested. The goat milk is considered a high nutritional value food, differentiated of the cow milk for the digestibility, alkalinity and buffer capacity and it became great feeding option for allergic people to the cow milk and for people that look for a feeding nutrient and healthy and with high joined value. This work was accomplished with the intention of evaluating the tendencies of consumption of the goat milk, describing the characteristics of the product, the importance of being consumed by the man and the market perspectives e to analyze as the measures to improve the quality of goat milk have led to an increase of consumption of the product.O leite de cabra é definido como, produto oriundo da ordenha completa, ininterrupta, em condições de higiene, de animais da espécie caprina sadios, bem alimentados e descansados. É considerado um alimento de alto valor nutritivo, diferenciado do leite de vaca pela alta digestibilidade, alcalinidade e capacidade tamponante, se tornou ótima opção de alimentação para pessoas alérgicas ao leite de vaca e para pessoas que buscam uma alimentação nutricional saudável e com alto valor agregado. Este trabalho foi realizado com o intuito de avaliar as tendências de consumo do leite de cabra, descrevendo as características do produto, as perspectivas de mercado e analisar como as medidas para melhorar a qualidade de leite de cabra têm levado a um aumento de consumo do produto