Estudo da influência da transferência de calor por convecção na soldagem de uma junta de fechamento de um transformador de potência através de simulação numérica / Study of the influence of heat transfer by convection in the welding of a cover power transformer through numerical simulation

A soldagem é o processo de fabricação de equipamentos na indústria metal mecânica, comumente utilizada. A soldagem da tampa de fechamento do tanque dos transformadores de potência com nível de tensão entre 69 kV e 138 kV, possui algumas implicações em relação a itens de segurança. Este trabalho tem como objetivo avaliar a influência do coeficiente de transferência de calor por convecção, ao ar livre e ao óleo isolante, durante a soldagem de uma junta de fechamento, utilizando-se o processo GMAW. Será utilizado o software Sysweld®, para simular numericamente a transferência de calor na soldagem. Foram soldados quatro corpos de prova, com metal de base ASTM A36 e consumível arame sólido ER-70S6. Os ciclos térmicos foram obtidos no regime quase estacionário, na região de vedação (RV) e na região interna (RI). Após a simulação, foram comparadas temperaturas máximas nas regiões de interesse. Com essa metodologia foi possível verificar a influência do coeficiente de transferência de calor da convecção, entre o óleo isolante e a superfície interna do tanque. Na região interna em contato direto com o óleo, houve uma diferença em torno de 66% entre as temperaturas máximas obtidas a partir das condições de convecção implementadas

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

Sepsis expands a CD39+ plasmablast population that promotes immunosuppression via adenosine-mediated inhibition of macrophage antimicrobial activity

Sepsis results in elevated adenosine in circulation. Extracellular adenosine triggers immunosuppressive signaling via the A2a receptor (A2aR). Sepsis survivors develop persistent immunosuppression with increased risk of recurrent infections. We utilized the cecal ligation and puncture (CLP) model of sepsis and subsequent infection to assess the role of adenosine in post-sepsis immune suppression. A2aR-deficient mice showed improved resistance to post-sepsis infections. Sepsis expanded a subset of CD39hi B cells and elevated extracellular adenosine, which was absent in mice lacking CD39-expressing B cells. Sepsis-surviving B cell-deficient mice were more resistant to secondary infections. Mechanistically, metabolic reprogramming of septic B cells increased production of ATP, which was converted into adenosine by CD39 on plasmablasts. Adenosine signaling via A2aR impaired macrophage bactericidal activity and enhanced interleukin-10 production. Septic individuals exhibited expanded CD39hi plasmablasts and adenosine accumulation. Our study reveals CD39hi plasmablasts and adenosine as important drivers of sepsis-induced immunosuppression with relevance in human disease