On Quantum Nonlocality and the Device-independent Paradigm

Ph.DDOCTOR OF PHILOSOPH

Avanços da cirurgia robotica no tratamento do Câncer

A cirurgia robótica tem sido almejada por profissionais cirurgiões, visto que, é um procedimento considerado de alta eficácia, assim como, apresenta reduzidos níveis de riscos ao paciente, o que configura significativamente a qualidade elevada do procedimento médico. Logo, tem sido utilizada no tratamento cirúrgico de diversos tipos de câncer, o qual tem demonstrado melhores resultados quando comparados com procedimentos mais invasivas ou tradicionais O principal objetivo do é discutir por meio de uma revisão sistematizada da literatura acerca dos avanços da cirurgia robótica no tratamento dos demais tipos de cânceres. O presente estudo trata-se de uma revisão sistemática da literatura, de modo que, realizou-se buscas de na Scielo, Periódico Capes e na Biblioteca Virtual em Saúde (BVS), através de termos específicos do Decs, o qual resultou-se em: “Neoplasias” AND “Procedimentos Cirúrgicos Robóticos” AND “Terapêutica”. Foram elegíveis um total de 8 estudos na presente revisão sistemática. Este procedimento é devidamente realizado com menores danos de incisão possível no paciente, de modo que, possibilitou a diminuição de dores pós-operatórios, além da redução de sangramentos, traumas, respostas inflamatórias, tempo de internação e até mesmo melhores resultados estéticos nos pacientes, quando comparados com os métodos mais tradicionais e invasivos

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

A list of land plants of Parque Nacional do Caparaó, Brazil, highlights the presence of sampling gaps within this protected area

Brazilian protected areas are essential for plant conservation in the Atlantic Forest domain, one of the 36 global biodiversity hotspots. A major challenge for improving conservation actions is to know the plant richness, protected by these areas. Online databases offer an accessible way to build plant species lists and to provide relevant information about biodiversity. A list of land plants of “Parque Nacional do Caparaó” (PNC) was previously built using online databases and published on the website "Catálogo de Plantas das Unidades de Conservação do Brasil." Here, we provide and discuss additional information about plant species richness, endemism and conservation in the PNC that could not be included in the List. We documented 1,791 species of land plants as occurring in PNC, of which 63 are cited as threatened (CR, EN or VU) by the Brazilian National Red List, seven as data deficient (DD) and five as priorities for conservation. Fifity-one species were possible new ocurrences for ES and MG states

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

Análise de Feeds de Inteligência de Ataques DDoS sob a Ótica da Qualidade da Informação

<p>A segurança de servidores web é uma preocupação crítica para organizações diante de ameaças cibernéticas, entre elas os ataques de negação de serviço distribuídos (DDoS). Em um ambiente onde a disponibilidade online é vital, informações confiáveis desempenham um papel crucial na proteção contra ataques cibernéticos. Nesse sentido, o uso de feeds de inteligência desempenha um papel preventivo crucial no reforço da segurança cibernética. Este estudo elaborou métricas para avaliar a qualidade de feeds de inteligência e utilizou essas métricas para analisar relatórios de empresas de segurança cibernética, focando em ataques DDoS recentes, buscando aprimorar critérios de avaliação da qualidade desses relatórios com o objetivo de auxiliar equipes de TI na tomada de decisão sobre sua utilidade na modelagem de ameaças e estratégia de defesa contra ataques DDoS. A análise revelou deficiências em completude, oportunidade e capacidade de ação, variando entre as fontes de informação. Essas descobertas têm implicações significativas para equipes de TI ao considerar a utilidade desses relatórios na modelagem de ameaças e estratégias de defesa contra DDoS. </p&gt