Aços de ductilidade especial em estruturas de betão armado : aplicação ao dimensionamento de ponte rodoviária

Tese de mestrado integrado. Engenharia Civil (especialização em Estruturas). Faculdade de Engenharia. Universidade do Porto. 200

Arbustus unedo essence: morphological and genetic characterization of the strawberry tree of Castelo de Paiva

O medronheiro é um arbusto da região mediterrânica que pode ser encontrada por todo o país. Ao contrário do que verifica na região sul do país, no concelho de Castelo de Paiva é atribuída uma reduzida importância económica a esta espécie. Com o intuito de preservar e potenciar a produção desta espécie e contribuir para a dinamização da economia do concelho, procedeu-se à caracterização morfológica e genética de uma amostra da população de medronheiros de Castelo de Paiva. A caracterização morfológica e genética foi realizada para um total de 10 genótipos. Para tal recolheram-se 70 folhas aleatoriamente em cada árvore. Em 40 folhas mediu-se o comprimento, largura, comprimento do pedúnculo, peso fresco, peso seco e determinou-se a área foliar. Dos caracteres morfológicos analisados, aqueles que se revelaram mais úteis na distinção dos vários genótipos foram: comprimento do pedúnculo, peso fresco e peso seco. As restantes 30 folhas foram utilizadas para a caracterização genética. Esta caracterização foi realizada recorrendo a um marcador de DNA, ISSR. Os 5 primeiros exemplaresutilizados na técnica de ISSR demonstraram-se polimórficos. Os resultados da caracterização genética sugerem que a variabilidade genética na população é média a alta.The strawberry tree is a shrub native in the Mediterranean region and it can be found throughout Portugal. Unlike the case in the southern region of the country, in Castelo de Paiva a minor economic importance is given to this species. In order to preserve, to enhance the production of this species and to contribute to the boosting of the economy of the region, we proceeded to the characterization of a small sample population of this fruit tree of Castelo de Paiva in what concerns to its morphology and genetics. The morphological and genetic characterization was performed for a total of 10 genotypes. For this, 70 leaves were randomly collected from each tree. For 40 leaves, it was measured the length, the width, the peduncle length, the wet weight, the dry weight and determined the leaf area. Of the morphological characteristics analyzed, the ones that proved most useful in distinguishing the various genotypes were: the length peduncle, the wet weight and the dry weight. The remaining 30 leaves were used in the genetic characterization. This characterization was performed using a DNA marker, the ISSR. The 5 primers used in the ISSR technique proved to be polymorphic. The results from the genetic characterization suggest that variability in population genetics is medium to high

SARS-CoV-2 introductions and early dynamics of the epidemic in Portugal

Genomic surveillance of SARS-CoV-2 in Portugal was rapidly implemented by the National Institute of Health in the early stages of the COVID-19 epidemic, in collaboration with more than 50 laboratories distributed nationwide. Methods By applying recent phylodynamic models that allow integration of individual-based travel history, we reconstructed and characterized the spatio-temporal dynamics of SARSCoV-2 introductions and early dissemination in Portugal. Results We detected at least 277 independent SARS-CoV-2 introductions, mostly from European countries (namely the United Kingdom, Spain, France, Italy, and Switzerland), which were consistent with the countries with the highest connectivity with Portugal. Although most introductions were estimated to have occurred during early March 2020, it is likely that SARS-CoV-2 was silently circulating in Portugal throughout February, before the first cases were confirmed. Conclusions Here we conclude that the earlier implementation of measures could have minimized the number of introductions and subsequent virus expansion in Portugal. This study lays the foundation for genomic epidemiology of SARS-CoV-2 in Portugal, and highlights the need for systematic and geographically-representative genomic surveillance.We gratefully acknowledge to Sara Hill and Nuno Faria (University of Oxford) and Joshua Quick and Nick Loman (University of Birmingham) for kindly providing us with the initial sets of Artic Network primers for NGS; Rafael Mamede (MRamirez team, IMM, Lisbon) for developing and sharing a bioinformatics script for sequence curation (https://github.com/rfm-targa/BioinfUtils); Philippe Lemey (KU Leuven) for providing guidance on the implementation of the phylodynamic models; Joshua L. Cherry (National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health) for providing guidance with the subsampling strategies; and all authors, originating and submitting laboratories who have contributed genome data on GISAID (https://www.gisaid.org/) on which part of this research is based. The opinions expressed in this article are those of the authors and do not reflect the view of the National Institutes of Health, the Department of Health and Human Services, or the United States government. This study is co-funded by Fundação para a Ciência e Tecnologia and Agência de Investigação Clínica e Inovação Biomédica (234_596874175) on behalf of the Research 4 COVID-19 call. Some infrastructural resources used in this study come from the GenomePT project (POCI-01-0145-FEDER-022184), supported by COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation (POCI), Lisboa Portugal Regional Operational Programme (Lisboa2020), Algarve Portugal Regional Operational Programme (CRESC Algarve2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and by Fundação para a Ciência e a Tecnologia (FCT).info: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 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

Resumos concluídos - Bioquímica

Resumos concluídos - Bioquímic

Resumos concluídos - Bioquímica

Resumos concluídos - Bioquímic

New content management models: use of digital technologies by Mídia NINJA

O presente artigo reflete acerca da utilização das novas tecnologias de rede pelo meio de comunicação independente e ativista Mídia NINJA (Narrativas Independentes, Jornalismo e Ação) como modelo alternativo de gestão de conteúdos que utiliza o tripé: produção, circulação e distribuição. A pesquisa tem como objetivo compreender como funciona este modelo e de que forma ele atrai o público. Para tanto, o método utilizado foi a netnografia (ramo da Etnografia que analisa o comportamento de indivíduos e grupos sociais na internet e as dinâmicas desses grupos no ambiente online), para observar as dinâmicas de dois grupos do Telegram da Mídia NINJA (NINJASP e NINJADF) e a página do Instagram deste meio alternativo. Complementámos a metodologia com uma entrevista semiestruturada. Constatou-se, através da análise dos conteúdos das ferramentas estudadas, que as novas tecnologias de media digital como modelo de produção e distribuição utilizado pela Mídia NINJA provocam no público o interesse na leitura dos conteúdos deste medium, além de promover a participação e a interação.This article reflects on the use of new network technologies by the independent communication and activist Mídia NINJA (Independent Narratives, Journalism and Action) as an alternative model of content management that uses the tripod: production, circulation and distribution. The research aims to understand how this model works and how it attracts the public. For that, the method used is netnography (a branch of Ethnography that analyzes the behavior of individuals and social groups on the internet and the dynamics of these groups in the online environment), to observe the dynamics of two groups of the Telegram of the Mídia NINJA (NINJASP and NINJADF) and the Instagram page of this alternative medium. We complemented the methodology with a semi-structured interview. It was found, through the analysis of the contents of the studied tools, that the new technologies of digital media as a production and distribution model used by the Mídia NINJA provokes in the public an interest in reading the contents of this medium, in addition to promoting participation and interaction