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                  <text>Coronavirus</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Occupational Stress, Burnout, and Depression in Women in Healthcare During COVID-19 Pandemic: Rapid Scoping Review</text>
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                <text>Abi Sriharan, Abi Sriharan, Savithiri Ratnapalan, Savithiri Ratnapalan, Savithiri Ratnapalan, Andrea C. Tricco, Andrea C. Tricco, Doina Lupea, Ana Patricia Ayala, Hilary Pang, Hilary Pang, Dongjoo Daniel Lee, Dongjoo Daniel Lee</text>
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                <text>Objectives: The overall objectives of this rapid scoping review are to (a) identify the common triggers of stress, burnout, and depression faced by women in health care during the COVID-19 pandemic, and (b) explore individual-, organizational-, and systems-level interventions that can support the well-being of women HCWs during a pandemic.Design: This scoping review is registered on Open Science Framework (OSF) and was guided by the JBI guide to scoping reviews and reported using the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) extension to scoping reviews. A systematic search of literature databases (Medline, EMBASE, CINAHL, PsycInfo and ERIC) was conducted from inception until June 12, 2020. Two reviewers independently assessed full-text articles according to predefined criteria.Interventions: We included review articles and primary studies that reported on stress, burnout, and depression in HCWs; that primarily focused on women; and that included the percentage or number of women included. All English language studies from any geographical setting where COVID-19 has affected the population were reviewed.Primary and secondary outcome measures: Studies reporting on mental health outcomes (e.g., stress, burnout, and depression in HCWs), interventions to support mental health well-being were included.Results: Of the 2,803 papers found, 28 were included. The triggers of stress, burnout and depression are grouped under individual-, organizational-, and systems-level factors. There is a limited amount of evidence on effective interventions that prevents anxiety, stress, burnout and depression during a pandemic.Conclusions: Our preliminary findings show that women HCWs are at increased risk for stress, burnout, and depression during the COVID-19 pandemic. These negative outcomes are triggered by individual level factors such as lack of social support; family status; organizational factors such as access to personal protective equipment or high workload; and systems-level factors such as prevalence of COVID-19, rapidly changing public health guidelines, and a lack of recognition at work.</text>
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                <text>2020</text>
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                <text>mental health, Pandemic, health care, Women, Burnout, Occupational stress</text>
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            <name>Identifier</name>
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                <text>10.3389/fgwh.2020.596690</text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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                <text>Epidemiology and Health</text>
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                <text>Korean Society of Epidemiology</text>
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            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>Gynecology and obstetrics, Women. Feminism</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Beyond Muamalah Principles in Digital Payment Education and its Impacts on Corruption Prevention in Indonesian Public Sectors</text>
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                <text>Abidin Abidin, Tulus Suryanto, Pertiwi Utami</text>
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                <text>Covid-19 global pandemic has extensively affected various dimensions in life and changed socioeconomic behavior in society.  In line with this, the tremendous growthof digital technology has brought about a positive influence on social education and muamalah (literally ”transaction”) activities due to, indirectly, the enactment of large-scale social restriction policy (LSSR) in the capital city of Indonesia: Jakarta. Consequently,digital transaction has increased immensely as digital technology ensures more safety and effectiveness. Furthermore, the policy has created new perspectives in social education towards the use of digital technology and society are prompted to learn how to use it. Learning from the background, the authors employ the risk-need-responsive model (RNR model) and conditional approach in this study as a conceptual framework to reveal the impact of Muamalah social education on digital payments for corruption prevention for public services in Indonesia. In addition, quantitative research design is also applied in this study by distributing questionnaires to as many as 300 respondents in Jakarta randomly chosen as a sample.  This study revealed that they were influenced by LSSR. Data collection techniques are questionnaires combined with literature studies. This research has a novelty as it attempts to fill the impact of Muamalah social education on digital payments for corruption prevention and is derived from people’s responsiveness affected by Covid-19. The results revealed that although people were forced to use digital payments due to emergency conditions, in fact, social education has brought about major changes in social dynamics. The impact of Muamalah social education on digital payments has improved individual cognitive learning abilities,demonstrated more wise actions and changed social behavior for better life. Furthermore, the impact of Muamalah social education on the use of digital payments in preventing corruption or digital anti-corruption likely minimizes corrupt practices in the public service sector. This research is likely a useful reference  for stakeholders, especially the government, as a blueprint for preventing corruption by considering aspects of social education and the growing Muamalah principle of digital payments  in society.</text>
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                <text>2020</text>
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                <text>education, public service, muamalah, digital payment, corupption</text>
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                <text>Journal of Social Studies Education Research</text>
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                <text>Journal of Social Studies Education Research</text>
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                <text>Education (General), Social Sciences</text>
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                <text>Lessons of the month: Co-infection with SARS-CoV-2 and influenza B virus in a patient with community-acquired pneumonia.</text>
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                <text>Abigail Coutinho, Afrah Riaz, Annabel Makan, Emma Crawford, Devapriya Dev, Koottalai Srinivasan, Nawaid Ahmad, Harmesh Moudgil</text>
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                <text>Why we only infrequently detect or report two or more respiratory viruses co-infecting an adult host is poorly understood. We report a rare case where influenza B and SARS-CoV-2 caused viral pneumonia in a 74-year-old man diagnosed during the UK winter epidemic/pandemic for these organisms and discuss concepts of co-infection.</text>
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                <text>2020</text>
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                <text>covid-19, SARS-CoV-2, Co-infection, Viral co-infection, influenza B</text>
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                <text>10.7861/clinmed.2020-0598</text>
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                <text>Clinical medicine (London, England)</text>
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                  <text>Agricultura sostenible</text>
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                  <text>Dominio científico: Agricultura sostenible</text>
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                <text>SISTEMAS AGROFLORESTAIS NO MUNICÍPIO DE PARAGOMINAS, PARÁ.</text>
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                <text>Abimael Oliveira dos Santos, Rosana Cardoso Rodrigues da Silva</text>
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            <description>An account of the resource</description>
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                <text>Este trabalho que teve como objetivo identificar e analisar os sistemas agroflorestais em Paragominas, gerando informações para subsidiar ações públicas de implantação de novos arranjos de SAF’s no referido município. Foi realizada através de pesquisa de campo com a coleta de dados e aplicação de questionário semiestruturado, com questões relacionadas à temática da produção em SAF. Das 31 comunidades pesquisadas 21 foram identificadas com sistemas agroflorestais. As dificuldades citadas pelos   agricultores com sistemas agroflorestais foram: ausência de assistência técnica adequada e com frequência periódica; o baixo nível de escolaridade dos agricultores; a falta de documentação da terra por parte da maioria dos agricultores; a falta de verticalização da produção; a falta de diversificação da comercialização; estradas ruins e; o baixo acesso a crédito. Porém, apesar das dificuldades foram encontrados inúmeros resultados positivos, principalmente na esfera social e ambiental, tais quais: boa participação em organizações sociais; participação em algum tipo de capacitação técnica; a maior parte da produção é comercializada em feiras e na comunidade local, baixo índice de frequência de uso de produtos químicos e; diversificação da produção, o que traz renda durante o ano todo para as famílias envolvidas.</text>
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                <text>2020</text>
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                <text>Agricultura Familiar, Comunidades rurais, diagnóstico</text>
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                <text>10.15628/holos.2020.9548</text>
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                <text>Holos</text>
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                <text>Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Norte</text>
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                <text>General Works</text>
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                <text>&lt;a href="http://www2.ifrn.edu.br/ojs/index.php/HOLOS/article/view/9548" target="_blank" rel="noreferrer noopener"&gt;http://www2.ifrn.edu.br/ojs/index.php/HOLOS/article/view/9548&lt;/a&gt;</text>
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                <text>Abolfazl Jafari-Sales, Homeira Khaneshpour, Mehrdad Pashazadeh, Rozita Nasiri</text>
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                <text>On December 31, 2019, the Wuhan-China Health Commission reported a case of pneumonia in the city. The first symptoms began in mid-December 2019. Clinically isolated specimens identified the coronavirus as the cause of the disease. It was first shown as 2019-nCoV, and as the number of victims of the coronavirus crossed the border of thousands of people, the World Health Organization chose the official name COVID-19 for its illness. Although it appears to be of animal origin, it is rapidly transmitting from person to person around the world. The World Health Organization released a statement calling the outbreak of the new Corona virus a Public Health Emergency Situations that poses a threat to the whole world, not just China. In this study highlights how the virus is transmitted, the clinical signs, the laboratory characteristics, the pathogenicity of the virus, Vaccines, and the prevention and control of the spread of the virus.</text>
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                <text>MERS-CoV, SARS-CoV, covid-19, Pandemic</text>
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                <text>Biotemas</text>
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                <text>Universidade Federal de Santa Catarina</text>
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                <text>Biology (General), Medicine</text>
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                  <text>Dominio científico: Coronavirus</text>
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      <name>Text</name>
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                <text>Artificial Neural Network Modeling of Novel Coronavirus (COVID-19) Incidence Rates across the Continental United States</text>
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                <text>Abolfazl Mollalo, Kiara M. Rivera, Behzad Vahedi</text>
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                <text>Prediction of the COVID-19 incidence rate is a matter of global importance, particularly in the United States. As of 4 June 2020, more than 1.8 million confirmed cases and over 108 thousand deaths have been reported in this country. Few studies have examined nationwide modeling of COVID-19 incidence in the United States particularly using machine-learning algorithms. Thus, we collected and prepared a database of 57 candidate explanatory variables to examine the performance of multilayer perceptron (MLP) neural network in predicting the cumulative COVID-19 incidence rates across the continental United States. Our results indicated that a single-hidden-layer MLP could explain almost 65% of the correlation with ground truth for the holdout samples. Sensitivity analysis conducted on this model showed that the age-adjusted mortality rates of ischemic heart disease, pancreatic cancer, and leukemia, together with two socioeconomic and environmental factors (median household income and total precipitation), are among the most substantial factors for predicting COVID-19 incidence rates. Moreover, results of the logistic regression model indicated that these variables could explain the presence/absence of the hotspots of disease incidence that were identified by Getis-Ord Gi* (p &lt; 0.05) in a geographic information system environment. The findings may provide useful insights for public health decision makers regarding the influence of potential risk factors associated with the COVID-19 incidence at the county level.</text>
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                <text>2020</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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                <text>GIS, artificial neural networks, United States, Multi-layer perceptron, covid-19 coronavirus</text>
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                <text>DOI: 10.3390/ijerph17124204</text>
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              <elementText elementTextId="34482">
                <text>International Journal of Environmental Research and Public Health</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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                <text>MDPI AG</text>
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                <text>Medicine</text>
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              <name>Title</name>
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                  <text>Coronavirus</text>
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              <description>An account of the resource</description>
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                  <text>Dominio científico: Coronavirus</text>
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      <name>Text</name>
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      <elementSet elementSetId="1">
        <name>Dublin Core</name>
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          <element elementId="50">
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                <text>Concerns and confidences expressed by teaching staff about the shift of medical education to online mode in South India during the COVID 19 pandemic</text>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
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                <text>Aboobacker Mohammed Rafi, Pulikkottil Raphael Varghese, Praveenlal Kuttichira</text>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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                <text>Background: Online education is prevalent in the country since the beginning of the 21st century. The outbreak of COVID-19, the government declared lockdown, and subsequent closing of institutions was unexpected, and it forced medical colleges to launch online programs for undergraduate courses. Due to the sudden shifting to online mode, most teaching staff members face the challenges of lacking online teaching experience, early preparation, or support from educational technology teams. This institution was in touch with the teachers and students through online mode, enquiring about their welfare and wellness. The present study focuses on concerns and confidences presented by the medical teaching staff on online medical education.   Method: This study was conducted at Jubilee Mission Medical College &amp; Research Institute, a medical college in central Kerala in south India. This institution conducted online classes for undergraduate (UG) medical students through Google classroom and YouTube platforms. There was 186 teaching staff from 21 departments involved in undergraduate (MBBS) teaching in this Institute. In this study, we collected information from the teaching staff about the online classes that they handled. A 27-point survey form was designed using a Google survey and mailed to them. The responses were collected in a week. The data collected was analyzed.  Result: Fifty-one members responded. All responding teachers preferred regular classroom teaching due to the provision for better teacher-student interaction. However, one-third of respondents wanted the continuation of online classes, even after resuming classroom teaching. Out of 51 responses, 24 teachers graded the success of the programs more than 90%. The major suggestions received for further improvement of the program were that the departments provided their hardware and software, centralized online sessions for practical purposes, and collected regular feedback from students.  Conclusion: The successes of our online teaching programs were limited to didactic teaching only. It could not replace the actual patient examination in a clinical setting, which involves communication skills and emotional relationships. This adversary must be converted into an opportunity to develop e-learning programs. This pandemic should open our eyes, so we learn from it and be better prepared for the future.</text>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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              <elementText elementTextId="50921">
                <text>2020</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="50922">
                <text>India, covid-19, Pandemic, Concerns, Kerala, teaching staff, Online medical education</text>
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            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
            <elementTextContainer>
              <elementText elementTextId="50923">
                <text>10.47108/jidhealth.Vol3.IssSpecial2.81</text>
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            </elementTextContainer>
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          <element elementId="48">
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            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="50924">
                <text>Epidemiology and Health</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="50925">
                <text>Korean Society of Epidemiology</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="38">
            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
            <elementTextContainer>
              <elementText elementTextId="50926">
                <text>Medicine, Medicine (General)</text>
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            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
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              <name>Description</name>
              <description>An account of the resource</description>
              <elementTextContainer>
                <elementText elementTextId="2">
                  <text>Dominio científico: Coronavirus</text>
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              </elementTextContainer>
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          </elementContainer>
        </elementSet>
      </elementSetContainer>
    </collection>
    <itemType itemTypeId="1">
      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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    <elementSetContainer>
      <elementSet elementSetId="1">
        <name>Dublin Core</name>
        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
        <elementContainer>
          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
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                <text>Cyclin dependent kinase inhibitors as a new potential therapeutic option in management of COVID-19.</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="70696">
                <text>Aboubaker Alzwi, Mohamed Gargouri, Anis Abobaker</text>
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            </elementTextContainer>
          </element>
          <element elementId="40">
            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="70697">
                <text>2021</text>
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            </elementTextContainer>
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          <element elementId="43">
            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
            <elementTextContainer>
              <elementText elementTextId="70698">
                <text>10.1016/j.mehy.2020.110380</text>
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            </elementTextContainer>
          </element>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="70699">
                <text>Medical hypotheses</text>
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            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
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                <elementText elementTextId="1">
                  <text>Coronavirus</text>
                </elementText>
              </elementTextContainer>
            </element>
            <element elementId="41">
              <name>Description</name>
              <description>An account of the resource</description>
              <elementTextContainer>
                <elementText elementTextId="2">
                  <text>Dominio científico: Coronavirus</text>
                </elementText>
              </elementTextContainer>
            </element>
          </elementContainer>
        </elementSet>
      </elementSetContainer>
    </collection>
    <itemType itemTypeId="1">
      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
    </itemType>
    <elementSetContainer>
      <elementSet elementSetId="1">
        <name>Dublin Core</name>
        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>فعالية استخدام تطبيقات الذكاء الاصطناعي الحديثة في مواجهة فيروس كورونا (COVID-19): تجربة كوريا الجنوبية نموذجا</text>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="35256">
                <text>Aboubaker Khoualed, Khayreddine Bouzerb</text>
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            </elementTextContainer>
          </element>
          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="35257">
                <text>يعد فيرس كورونا (COVID-19) من التحديات الصحية الصعبة التي تواجهها دول العالم اليوم، وتأتي هذه الدراسة في محاولة لتوضيح الدور الذي تلعبه تطبيقات الذكاء الاصطناعي في مواجهة فيروس كورونا وذلك من خلال دراسة تجربة كوريا الجنوبية في هذا المجال، ولتحقيق الهدف السابق الذكر تم الاعتماد على المنهج الوصفي التحليلي، وقد قسمت هذه الدراسة إلى جزأين: جزء نظري يتناول الأطر النظرية والتطبيقات الحديثة للذكاء الاصطناعي في المجال الطبي، وقسم تحليلي يتناول عرض وتحليل التجربة الكورية، وقد خلصت هذه الدراسة في الأخير إلى فعالية تجربة كوريا الجنوبية في مواجهة فيروس كورونا من خلال تطبيقات الذكاء الاصطناعي الحديثة وعلى رأسها: الكشف عن المرض باستخدام الخوارزميات، أنظمة تتبع للمصابين بالفيروس عبر (GPS)، نظام معلومات ذكي للحجر الصحي، التشخيص والتطبيب عن بعد، تطوير منصة رقمية للوقاية من الأوبئة، استخدامات الروبوت في المساعدة على التشخيص وقياس الحرارة وتوزيع المعقمات، استخدام الطائرات بدون طيار للتعقيم.  تصنيف جال: I18، O3.</text>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="35258">
                <text>2020</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="35259">
                <text>كوريا الجنوبية, الذكاء الاصطناعي, تطبيقات, الطب والصحة, فيروس (covid-19)</text>
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            </elementTextContainer>
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            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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              <elementText elementTextId="35260">
                <text>DOI: </text>
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            </elementTextContainer>
          </element>
          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="35261">
                <text>مجلة بحوث الإدارة والاقتصاد</text>
              </elementText>
            </elementTextContainer>
          </element>
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                <text>faculty of Economics, Commercial and Management Sciences</text>
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                  <text>Coronavirus</text>
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                <text>The impact of Covid-19 on the port environment: The case of Tanger Med container port, Morocco</text>
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                <text>Abous Hajar, Hamiche Mhamed, El Merouani Mohamed</text>
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                <text>The appearance of the COVID-19 virus has a huge impact on the economy, where many factories and logistics flows are affected. With global supply chains severely disrupted, production and consumption centers around the world are beginning to be affected by the situation. our study tried to measure the impact of this pandemic on the containers transport in Morocco, our work targeted the Tanger Med port due to its geographic position as the most important link between Africa and Europe, Autoregressive Distributed Lag (ARDL) cointegration technique was applied, this model integrates the term of lag and difference in the modeling of linear series. To verify the existence of long-term relationships, F-bond test was applied. The model was estimated on short and long term. the results were significant and has shown that the activity within Tanger Med port, experienced a shock during the pandemic period.</text>
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                <text>10.1051/e3sconf/202123400025</text>
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                <text>Epidemiology and Health</text>
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                <text>Korean Society of Epidemiology</text>
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                <text>Environmental sciences</text>
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