Statistical modeling of manufacturing uncertainties for microstrip filters

This work presents a technique to characterize the errors that occur in the process of manufacturing into electromagnetic simulations of microwave devices. The procedure combines the unscented transform (UT) with simulations. The use of the UT allows efficient use of computational resources for the characterization of the random variables modeling the uncertainty. The technique was validated with the simulation, construction, and test of several sets of identical microstrip filters with very good results. Although the combination of UT and electromagnetic simulators was presented for microstrip filters, it can also be used for different types of microwave devices

UTILIZAÇÃO DA UNSCENTED TRANSFORM PARA A MODELAGEM E SIMULAÇÃO DE PROBLEMAS DE CUSTOS DE PRODUÇÃO E LUCRO

Este artigo descreve como pode ser feita a aplicação da técnica denominada Unscented Transform (U.T.) em um problema clássico envolvendo custos de produção e lucro. Tradicionalmente, problemas dessa natureza são modelados utilizando a técnica de Simulação de Monte Carlo, que frente à Unscented Transform pode na maioria dos casos demandar maior esforço computacional, por realizar maior número de simulações, além da necessidade de conhecimento de todos os parâmetros relativos ao problema. Isso faz com que nestas situações a U.T. seja uma melhor alternativa

VIVÊNCIAS NO ESTÁGIO SUPERVISIONADO EM SETOR CLÍNICO DE ENDOSCOPIA E COLONOSCOPIA – RELATO DE EXPERIÊNCIA.

Introduction: The study of upper digestive endoscopy (EDA) and colonoscopy are exams that have improved with advances in global technologies. They serve as a basis for diagnosing basic diseases of the digestive system, with high prevalence and mortality in the world. The non-mandatory internship chosen in this area of knowledge aims to learn and develop clinical skills with the aim of improving the medical academic curriculum and exposing the activity as an experience report to the scientific community. Method: descriptive, longitudinal study, carried out in the first half of 2023 in a private clinic in Belém do Pará, where the intern presents its advantages and difficulties when carrying out the procedure. Results: the confluence between the curriculum and practical internship activities proved to be productive, in accordance with the objectives of the study and a new clinical experience for the academic. Conclusion: the active methodology of the medical course was passed on to the scientific community, where placing students in direct contact with care in an uncontrolled environment is essential to their training.  Introdução: O estudo da endoscopia digestiva alta (EDA) e colonoscopia, são exames que se aprimoraram com os avanços das tecnologias mundiais. Servem de base ao diagnóstico de doenças bases do sistema digestório, de alta prevalência e mortalidade no mundo. O estágio não obrigatório escolhido nesta área do conhecimento visa aprender e desenvolver habilidades clínicas com o intuito melhor o currículo acadêmico médico e expor a atividade como relato de experiência a comunidade científica. Método: estudo descritivo, longitudinal, realizado no primeiro semestre de 2023 em uma clínica particular em Belém do Pará, onde o estagiário apresenta suas vantagens e dificuldades ao realiza-lo. Resultados: a confluência entre grade curricular e atividades prática em estágio mostraram-se produtiva, de acordo com os objetivos do estudo e uma nova experiência clínica ao acadêmico. Conclusão: repassado a comunidade científica a metodologia ativa do curso de medicina onde colocar os alunos em contato direto com o atendimento em um ambiente não controlado é essencial a sua formação.   &nbsp

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

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved

Growing knowledge: an overview of Seed Plant diversity in Brazil

Abstract An updated inventory of Brazilian seed plants is presented and offers important insights into the country's biodiversity. This work started in 2010, with the publication of the Plants and Fungi Catalogue, and has been updated since by more than 430 specialists working online. Brazil is home to 32,086 native Angiosperms and 23 native Gymnosperms, showing an increase of 3% in its species richness in relation to 2010. The Amazon Rainforest is the richest Brazilian biome for Gymnosperms, while the Atlantic Rainforest is the richest one for Angiosperms. There was a considerable increment in the number of species and endemism rates for biomes, except for the Amazon that showed a decrease of 2.5% of recorded endemics. However, well over half of Brazillian seed plant species (57.4%) is endemic to this territory. The proportion of life-forms varies among different biomes: trees are more expressive in the Amazon and Atlantic Rainforest biomes while herbs predominate in the Pampa, and lianas are more expressive in the Amazon, Atlantic Rainforest, and Pantanal. This compilation serves not only to quantify Brazilian biodiversity, but also to highlight areas where there information is lacking and to provide a framework for the challenge faced in conserving Brazil's unique and diverse flora