Vulnerabilidade das microrregiões da Região Sul do Brasil à pandemia do novo coronavírus (SARS-CoV-2)

This is the first report of the ‘Observatório COVID191 - Grupo: Redes de Contágio – Laboratório de Estudos de Defesa’ for the South region of Brazil. We have combined data of confirmed cases of the new coronavirus (SARS-CoV-2) for the South available up to 17/04/2020, with structural analyses of road networks, from within and between states, to estimate the vulnerability and potential influence of the South micro-regions to propagate the disease.Este é o primeiro relatório do Observatório COVID19 - Grupo: Redes de Contágio – Laboratório de Estudos de Defesa para a região Sul do Brasil. Combinamos dados de casos confirmados do novo coronavírus (SARS-CoV-2) para o Sul, disponíveis até o dia 17/04/2020, com análises estruturais da rede de rotas rodoviárias intra e interestaduais para estimarmos a vulnerabilidade e potencial influência das microrregiões sulinas na propagação da doença

Vulnerabilidade estrutural dos hospitais e cemitérios e crematórios da cidade de São Paulo à COVID-19

This is the first report by the COVID19 Observatory - Group: Contagion Networks analyzing mortality data from the city of São Paulo. In this report, we integrated mortality data for the city of São Paulo between 04/02/2020 and 04/28/2020, with information on the flow of victims between hospitals and cemeteries/crematoriums. We included in our analyzes both confirmed and suspected deaths from COVID-19. The main objectives of this report were: (1) to describe the structure of the flow of victims between locations and (2) to suggest changes in the current flow based on geographical distances in order to avoid a potential overload of the mortuary system. We suggest that the city of São Paulo should plan for a potential overload of the mortuary system (that is, the number of burials), based on the presented results. Thus, our results reinforce the need to adopt specific planning for the management of the extraordinary number of victims of this pandemic. Our predictions are based on the structural analysis of the COVID-19 victim flow network, which shows several hotspots with high vulnerability to system overload. These hotspots concentrate with either the greatest number of deaths (hospital) or of burials (cemetery or crematorium), and therefore have high potential to become overwhelmed by receiving many bodies due to the increase in victims of the pandemic. We recommend special attention to be given to localities on the east side of São Paulo, which has both the most vulnerable hospitals in the city, and also houses cemeteries and crematoriums that have a central role in the network and / or are vulnerable. Based on our optimization analysis, we suggest logistical changes in the current flow of bodies from hospitals to cemeteries/crematoriums so as not to overload the funeral system and minimize transportation costs. In this sense, our results are potentially useful for improving the operational planning of the Municipality of São Paulo, ratifying or rectifying actions underway at the municipal level.Este é o primeiro relatório do Observatório COVID19 - Grupo: Redes de Contágio analisando os dados de óbitos da cidade de São Paulo. Neste relatório, integramos os dados de óbitos da cidade de São Paulo entre os dias 02/04/2020 e 28/04/2020 com informações sobre o fluxo de vítimas entre os hospitais e os cemitérios e crematórios da cidade de São Paulo. Incluímos em nossas análises óbitos confirmados e óbitos suspeitos de COVID-19. Os principais objetivos deste relatório são: (1) descrever a estrutura do fluxo de vítimas entre localidades e (2) sugerir mudanças no fluxo com base em distâncias geográficas de maneira a evitar uma potencial sobrecarga do sistema funerário. Sugere-se à prefeitura da cidade de São Paulo que seja realizado um planejamento para uma potencial sobrecarga do sistema funerário (isto é, número de sepultamentos) da cidade de São Paulo com base nos resultados apresentados. Desta forma, nossos resultados reforçam a necessidade de ser adotado planejamento específico para a gestão dos casos extraordinários visualizados no contexto da pandemia. Esta previsão está baseada na análise estrutural da rede de fluxos de vítimas da COVID-19, que indica a concentração de vários locais com alta vulnerabilidade à sobrecarga do sistema. Tais locais concentram a maior quantidade de óbitos (hospitais) ou a maior concentração de sepultamentos (cemitérios ou crematórios) e tem portanto alto potencial de tornarem-se sobrecarregados por receberem muitos corpos devido ao aumento de vítimas da pandemia. Recomenda-se especial atenção à localidades da zona leste de São Paulo, que apresenta os hospitais mais vulneráveis da cidade e abriga cemitérios e crematórios que possuem papel central na rede e/ou encontram-se vulneráveis. Com base em nossa análise de otimização, sugerimos mudanças logísticas no atual fluxo de corpos de hospitais para cemitérios/crematórios de modo a não sobrecarregar o sistema funerário e minimizar os custos de transporte. Neste sentido, nossos resultados são potencialmente úteis ao aperfeiçoamento do planejamento operacional da Prefeitura Municipal de São Paulo, ratificando ou retificando ações em curso no âmbito municipal

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

Electron impact ionization and fragmentation of biofuels

We present in this article, a review of our recent experimental and theoretical studies published in the literature on electron impact ionization and fragmentation of the primary alcohols methanol, ethanol, 1-propanol and 1-butanol (C1–C4). We discuss the mass spectra (MS) of these alcohols, measured for the electron impact energy of 70 eV and also, total (TICS) and partial (PICS) ionization cross sections in the energy range from 10 to 100 eV, which revealed the probability of forming different cations, by either direct or dissociative ionization. These experimental TICS are summarized together with theoretical values, calculated using the Binary-encounter Bethe (BEB) and the independent atom model with the screening corrected additivity rule (IAM-SCAR) methods. Additionally, we compared data of appearance energies – AE and discussed the application of the extended Wannier theory to PICS in order to produce the ionization and ionic fragmentation thresholds for the electron impact of these alcohols