62 research outputs found

    Genetic Characterization of Melipona subnitida Stingless Bee in Brazilian Northeast

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    The study of M. subnitida, stingless bee well adapted to extreme environmental conditions, is noteworthy once the Northeastern Brazil faces climate changing predictions in which the precipitation rates are expected to decrease, and the average of temperatures to increase. The well-studied populations are limited to the Caatinga biome, where the species was considered endemic. However, the occurrence of this species has been reported in contrasting environments from arid region, such as mangrove and sandbanks in Maranhão state. Our primary goal was to characterize samples from these different environments and compare them with previously studied populations. We identified a unique mitochondrial haplotype per region. The haplotype found in Lençóis Maranhenses National Park was exclusive from this location and differed regarding the amino acid sequence when compared to the literature presented haplotypes from Caatinga, which might be related with different evolutionary processes in the distinct environments, though further studies are needed to confirm. Melipona subnitida is highly adapted to extreme environmental conditions and can survive under long drought periods, since during water and resource scarcity, the bees reduce the colony size to a minimum number of brood and workers. Thus, the species maintains only essential tasks for the nest, being an important mechanism to save the resources stored during the bloom of rainy periods (Maia-Silva et al., 2014; 2015). Assuming the climate change predictions for Northeastern Brazil (Marengo et al., 2011) in the semi-arid region, where average reductions in precipitation rates of up to 40–50% are expected (PBMC, 2013), the study bees resistant to these conditions, such as M. subnitida, is noteworthy. Considering the importance of this species regarding resistance to extreme climatic conditions, distributional modelin

    Corrosion Grade on Anchor Rods of Guyed Transmission Towers Applying Machine Committee / Grau de Corrosão em Hastes de Âncora de Torres de Transmissão Guiadas Comitê de Aplicação de Máquinas

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    The use of guyed structures in electric power transmission lines is a growing practice because of their cost efficiency. However, the anchor systems are subject to corrosion, which can lead to their rupture and loss of tower support. Monitoring the evolution of the corrosion of the anchor rods by visual inspection is a destructive and costly method; therefore, there is considerable interest in developing methods and tools that are capable of generating a maintenance diagnosis of the system. This work aimed to propose a classification tool for guyed towers in terms of the corrosion degree by a machine committee with neural networks and applied it to the Paraiso-Açu line located in Rio Grande do Norte in Brazil. Thirty-eight samples were collected and 33 variables related to the soil corrosion along the line were analyzed. The targets for training the networks were obtained from the inspection of anchor rods taken from the field. A simplification of the problem's dimension was proposed by principal component analysis, describing the phenomenon with 6 variables instead of 33, simplifying the practical application by massively reducing the requirements for data sampling in the field. Several network typologies were trained and the best ones in terms of their generalist and specialist capacities were combined in a machine committee for the final proposal of this work. The classification obtained by the application of the committee for 10 towers was compared with the classification from non-destructive impulse reflectometry tests and showed an 80% correlation

    Resistividade em solos: efeito dos índices físicos e condições de análise / Soil resistivity: phisical indexes and analysis conditions influence

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    A resistividade elétrica é um parâmetro amplamente utilizado na avaliação da corrosividade dos solos. Entretanto, algumas metodologias de análise em laboratório têm divergência nos procedimentos e resultados obtidos, o que pode impactar na correta avaliação da propriedade e sua consequente correlação com a resistência à corrosão. Neste estudo foi realizado uma revisão dos ensaios de resistividade de solo propostos pelos procedimentos adotados pelas normas ABNT NBR 16254-1:2014 (Anexo C), ASTM G-187-15 e ASTM G-187-15 modificada pela adoção de cálculos dos índices físicos para obtenção do grau de saturação da amostra de solo. A avaliação dos resultados indicou que o os procedimentos realizados pela norma ASTM-G187-15 e pelo mesmo procedimento modificado, adotando os índices físicos foram compatíveis. Já o ensaio realizado pela norma ABNT NBR 16254-1:2014 (Anexo C) não teve resultados satisfatórios

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

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    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

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    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

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    Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

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    Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection
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