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                  <text>Coronavirus</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>A study on the effects of COVID–19 pandemic on Nigerian seafarers</text>
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                <text>Uka John Okeleke, Moses Olatunde Aponjolosun</text>
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                <text>There is no doubt that Coronavirus disease 2019 (COVID-19) pandemic has impacted negatively on global shipping and the effects are also being felt in the Nigerian shipping industry. Through review of extant literature, the effects of COVID-19 on Nigerian shipping industry with specific focus on port operations and Nigerian seafarers were examined. The findings revealed that lock down of the economy  and restriction of movements in Nigeria presented a challenging situation for stakeholders in the shipping industry to fulfill their contractual obligations, import and export operations are hampered , Nigerian seafarers are mentally and psychologically disturbed as a result of lack of social support and extension of contract beyond the agreed contractual term with exhausting workload onboard with little or no support from the management who are more concerned about contract execution than the welfare of the crew onboard. However, it was recommended that living and working conditions of Nigerian seafarers onboard in this pandemic era should be given utmost attention by applying practical and pragmatic approach on issues bordering on facilitation of crew change, resupply, repairs, survey and certification and licensing of seafarers.</text>
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                <text>2020</text>
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                <text>covid-19, Pandemic, welfare, Seafarers</text>
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                <text>Biotemas</text>
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                <text>Universidade Federal de Santa Catarina</text>
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                <text>Transportation engineering</text>
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                  <text>Agricultura sostenible</text>
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                <text>A sucessão em propriedades rurais familiares de Frederico Westphalen/RS: influências e direcionamentos decisórios dos atores</text>
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                <text>Fernando Panno, João Armando Dessimon Machado</text>
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            <description>An account of the resource</description>
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                <text>O presente artigo objetiva discutir a sucessão hereditária em pequenas propriedades rurais familiares, sob a ótica da teoria da decisão, considerando especialmente o processo decisório, aos quais passam potenciais sucessores (filhos) e sucedidos (pais), considerando os diferentes fatores que os influenciam neste processo. Para a análise empírica, considerou-se uma amostra de agricultores familiares do município de Frederico Westphalen/RS, uma vez que o meio rural do município é predominantemente formado por pequenas propriedades familiares e, ao longo do tempo, tem passado por constantes transformações em função do êxodo jovem, fato que vem acarretando uma série de problemas sociais e econômicos ao desenvolvimento rural local.</text>
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            <name>Date</name>
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                <text>2016</text>
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            <description>The topic of the resource</description>
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                <text>Agricultura Familiar. Sucessão Hereditária. Tomada de Decisão. Desenvolvimento Rural</text>
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                <text>10.17058/redes.v21i3.7634</text>
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                <text>Universidade de Santa Cruz do Sul</text>
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                <text>Social Sciences, Social sciences (General), Human ecology. Anthropogeography</text>
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                <text>&lt;a href="https://online.unisc.br/seer/index.php/redes/article/view/7634" target="_blank" rel="noreferrer noopener"&gt;https://online.unisc.br/seer/index.php/redes/article/view/7634&lt;/a&gt;</text>
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                  <text>Agricultura sostenible</text>
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                <text>A sucessão geracional no meio rural em cinco estados brasileiros: possibilidades e limites (Generational succession in rural environment in five brazilian states: possibilities and limits)</text>
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                <text>Eliziário Noé Boeira Toledo, Valdecir José Zonin</text>
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                <text>O presente artigo analisa os aspectos relacionados à sucessão rural, que ocorrem nos estabelecimentos da agricultura familiar. As informações foram levantadas, utilizando a metodologia de estudo de caso, por meio de 219 entrevistas, compostas por questionários fechados. As mesmas foram realizadas nos municípios de Francisco Beltrão, Itapejara D’Oeste e Verê, no estado do Paraná (PR); Concórdia, em Santa Catarina (SC); Augusto Corrêa, Tomé-Açú e Viseu, no Pará (PA); Petrolina, em Pernambuco (PE); e nos municípios de Uauá e Cruz das Almas, na Bahia (BA), um total de dez municípios, nos cinco estados brasileiros. Essa investigação tem o propósito de buscar evidências sobre as relações sociais, econômicas e culturais que regem e influenciam a sucessão geracional nos estabelecimentos rurais. O estudo possibilitou comprovar que, quase metade dos agricultores familiares, não possuem garantia de possíveis sucessores, na medida em que, parte expressiva deles, almejam outras formas de renda monetária, fora dos estabelecimentos, inclusive, por meio da emigração. </text>
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                <text>2021</text>
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                <text>Agricultura familiar. Sucessão rural. Renda</text>
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                <text>10.5212/Emancipacao.v.21.2114643.001</text>
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                <text>Emancipação</text>
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                <text>Universidade Estadual de Ponta Grossa</text>
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                <text>Sociology (General), Social Sciences</text>
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                <text>&lt;a href="https://revistas2.uepg.br/index.php/emancipacao/article/view/14643" target="_blank" rel="noreferrer noopener"&gt;https://revistas2.uepg.br/index.php/emancipacao/article/view/14643&lt;/a&gt;</text>
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                <text>A suinocultura ante a atual legislação ambiental</text>
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            <name>Creator</name>
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              <elementText elementTextId="226526">
                <text>Eloi Erhard Scherer</text>
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            <name>Date</name>
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                <text>2020</text>
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            <name>Source</name>
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                <text>Revista Agropecuária Catarinense</text>
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                <text>Empresa de Pesquisa Agropecuária e Extensão Rural de Santa Catarina - Epagri</text>
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            <name>Coverage</name>
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                <text>Agriculture (General)</text>
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                <text>&lt;a href="https://publicacoes.epagri.sc.gov.br/RAC/article/view/772" target="_blank" rel="noreferrer noopener"&gt;https://publicacoes.epagri.sc.gov.br/RAC/article/view/772&lt;/a&gt;</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>The expansion of Covid-19 has severely hit the community’s health all over the world, killing hundreds of thousands of people, subjecting health systems to an enormous stress (besides derailing economic activities and altering personal and social behavior). Two elements are essential to monitor the evolution of the pandemic as well as to analyze the effectiveness of the response measures: reliable data and useful indicators. We present an indicator that helps to assess the impact of Covid-19 on the community’s health, combining two different components: the extent of the pandemics (i.e. the share of the population affected) and its severity (the intensity of the disease on those affected). The severity measure derives from the application of an evaluation protocol that allows comparing population distributions based on the proportions of those affected with different health conditions. We illustrate the functioning of this indicator over a case study regarding the situation of the Italian regions on March 9 (the beginning of the confinement) and April 8, 2020, one month later.</text>
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                <text>Coronavirus disease 2019 (Covid-19) has been identified as being transmitted among humans with droplets from breath, cough, and sneezes. Understanding the droplets’ behavior can be critical information to avoid disease transmission, especially while designing a device deals with human air respiratory. Although various studies have provided enormous computational fluid simulations, most cases are too specific and quite challenging to combine with other similar studies directly. Therefore, this paper proposes a systematic approach to predict the droplet behavior for coughing cases using machine learning. The approach consists of three models, which are droplet generator, mask model, and free droplet model modeled using feedforward neural network (FFNN). The evaluation has shown that the three FFNNs models’ accuracies are relatively high, with R-values of more than 0.990. The model has successfully predicted the evaporation effect on the diameter reduction and the completely evaporated state, which can be considered unlearned cases for machine learning models. The predicted horizontal distance pattern also agrees with the data in the literature. In summary, the proposed approach has demonstrated the capability to predict the diameter pattern according to the experimental or previous work data at various mask face types.</text>
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