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                  <text>Dominio científico: Coronavirus</text>
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                <text>Technology to Address Food Deserts: Low Energy Corner Store Groceries with Integrated Agriculture Greenhouse</text>
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                <text>Kevin  P. Hallinan, Fahad  Awjah Almehmadi, Rydge  B. Mulford, Saeed  A. Alqaed</text>
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                <text>Food deserts have emerged as sources of urban crises around the world. The lack of access to healthy food has rendered health inequities that have been made more visible by the devastating effects of COVID-19 on the populations experiencing food insecurity and healthy food access. Research is posed to fight food deserts through innovation and technology; specifically, through the development of corner store grocery markets with integrated agricultural greenhouses in such a way as to both provide access to healthy foods at reasonable cost to better meet nutritional needs, and significantly reduce operating costs. The posed technology includes a combined heat and power (CHP) system to reduce overall energy costs by meeting the partial electric and thermal loads required within the store and the connected greenhouse. A mathematical model is developed to control the operation of the CHP system and to dispatch the generated electric power to the store and the thermal energy to the greenhouse to minimize overall energy requirements. The model is applied to an ambient environment representing a heating-dominant climate. Results indicate the potential to reduce operating costs by 55% in a heating-dominant climate.</text>
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                <text>optimization, sustainable development goals, food deserts, efficient energy management</text>
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                <text>Biotemas</text>
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                <text>Universidade Federal de Santa Catarina</text>
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                <text>Environmental effects of industries and plants, Renewable energy sources, Environmental sciences</text>
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                <text>Focal seizures with impaired awareness as long-term neurological complication of COVID-19: a case report.</text>
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                <text>Marco Bozzali, Alberto Grassini, Giovanni Morana, Michela Zotta, Sara Cabras, Alberto Romagnolo, Carlo Alberto Artusi, Elisa Montalenti, Mario Giorgio Rizzone, Diego Garbossa, Elisa Montanaro, Mara Cercignani, Leonardo Lopiano</text>
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                <text>We report here the first case of a young individual otherwise healthy, who presented with frequent focal seizures with impaired awareness as a possible long-term complication of severe acute respiratory syndrome coronavirus-2 infection. Seizures were documented by electroencephalography and responded clinically and neuro-physiologically to antiseizure therapy. The patient underwent an extensive investigation including cerebrospinal fluid examination, conventional and quantitative brain magnetic resonance imaging, and 18-FDG positron emission tomography. Beyond the clinical interest, this case contributes to clarify the possible pathways by which SARS-CoV-2 may enter the central nervous system and cause long-term neurological complications.</text>
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                <text>2021</text>
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                <text>covid-19, encephalitis, epilepsy, Focal seizures with impaired awareness</text>
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                <text>10.1007/s10072-021-05233-y</text>
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                <text>Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Pemantauan Perhatian Publik terhadap Pandemi COVID-19 melalui Klasifikasi Teks dengan Deep Learning</text>
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                <text>Novrindah Alvi Hasanah, Nanik Suciati, Diana Purwitasari</text>
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                <text>Monitoring public concern in the surrounding environment to certain events is done to address changes in public behavior individually and socially. The results of monitoring public attention can be used as a benchmark for related parties in making the right policies and strategies to deal with changes in public behavior as a result of the COVID-19 pandemic. Monitoring public attention can be done using Twitter social media data because the users of the media are quite high, so that they can represent the aspirations of the general public. However, Twitter data contains varied topics, so a classification process is required to obtain data related to COVID-19. Classification is done by using word embedding variations (Word2Vec and fastText) and deep learning variations (CNN, RNN, and LSTM) to get the classification results with the best accuracy. The percentage of COVID-19 data based on the best accuracy is calculated to determine how high the public's attention is to the COVID-19 pandemic. Experiments were carried out with three scenarios, which were differentiated by the number of data trains. The classification results with the best accuracy are obtained by the combination of fasText and LSTM which shows the highest accuracy of 97.86% and the lowest of 93.63%. The results of monitoring public attention to the time vulnerability between June and October show that the highest public attention to COVID-19 is in June.</text>
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                <text>2021</text>
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                <text>covid-19, deep learning, twitter, Word Embedding, monitoring public concern</text>
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                <text>10.29207/resti.v5i1.2927</text>
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                <text>Korean Society of Epidemiology</text>
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                <text>Information technology, Systems engineering</text>
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                <text>Synthesis and systematic review of reported neonatal SARS-CoV-2 infections</text>
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                <text>Daniele De Luca, Roberto Raschetti, Alexandre J. Vivanti, Christelle Vauloup-Fellous, Barbara Loi, Alexandra Benachi</text>
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                <text>There are a growing number of reports of neonatal SARS-CoV-2 infections. Here, De Luca and colleagues systematically analyse 176 published cases to better understand the route of transmission, as well as the clinical features and outcomes of neonatal COVID-19.</text>
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                <text>10.1038/s41467-020-18982-9</text>
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                <text>Korean Society of Epidemiology</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Conceptualizing the Nexus of Migration and Food Security during COVID-19</text>
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                <text>Manoj Sharma</text>
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                <text>Migration has been a part of the livelihood strategy and risk diversification to relieve crises. Food insecu­rity as a consequence as well as a cause of migration demands review during the COVID-19 pandemic. This paper is an attempt to explore the dynamics and vulnerabilities that ensue from the nexus of migra­tion, food security, and COVID-19, as the economic crisis of COVID-19 seems more intensive when viewed through a migration lens. The vulnerability of the economy based on food imports and remit­tances is heightened by COVID-19. The whole nexus of migration and food security has shifted; even the positive aspects of migration are predisposed to vulnerabilities.</text>
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                <text>2020</text>
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                <text>covid-19, Pandemic, Migration, vulnerability, food security</text>
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                <text>Çin'in Wuhan kentinde 2019 Aralık ayının sonlarında ortaya çıkan yeni koronavirüs salgını tüm dünyayı etkisi altına almış ve salgının giderek yayılmasıyla uluslararası ticaret yavaşlama eğilimine girmiştir. Covid-19 salgını tüm dünyada ekonomik anlamda etkisini hissettirirken bu sürecin ne kadar süreceği belirsizliğini koruyor. Dünya Sağlık Örgütü'nün talimatları doğrultusunda ülkeler kısmen sokağa çıkma yasağı uygulaması ile kişilerin yaşam şeklini değiştirmiş ve tüketicinin mobil hizmet veren uygulamalara geçişini teşvik etmiştir. Ayrıca ülkeler taşımacılık türlerini ülkeler arasında kısıtlamış daha sonra tamamen kaldırmıştır. Böylece taşımacılık sektörü gelirlerinin azalmasına sebep olmuştur. Bu çalışmada, 2020 yılında dünyada etkisini gösterdiği Covid-19'un küresel ekonomi üzerindeki etkisini tespit etmek amaçlanmaktadır. Bu amaçla havayolu yolcu sayısı ve yük trafiğinin 2018-2020 yılları arasındaki değişimi analiz edilmiş ve bu salgın hastalığın lojistik sektörünü nasıl etkilediği ortaya konulmuştur.</text>
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                <text>2020</text>
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                <text>ekonomi, Ticaret, e-Ticaret, Lojistik, yeni koronavirüs (covid-19)</text>
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                <text>Korean Society of Epidemiology</text>
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                <text>Covid-19’un En Etkili Olduğu Ülkelerde Salgın-Borsa İlişkisi</text>
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                <text>Nuri Hacıevli̇yagi̇l, Arif Gümüş</text>
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                <text>Covid-19 salgın hastalığı 2019 Aralık ayında Çin’in Wuhan eyaletinde ilk kez görülerek kısa süre içerisinde dünya genelinde milyonlarca kişiye bulaşmış ve binlerce insanın ölümüne yol açmıştır. Elbette bu salgında en çok etki alanlarından biri de ülke borsalarında yaşanmaktadır. Bu çalışmada Covid-19’un en fazla vaka sayısının görüldüğü 10 ülkedeki (Türkiye, Brezilya, Fransa, Almanya, İngiltere, İtalya, İspanya, Rusya, Çin, ABD) ölüm ve vaka sayıları ile bu ülkelere ait borsa endeksleri arasındaki ilişki incelenmiştir. Çalışmanın ekonometrik uygulama kısmında, uzun dönemli ilişkiyi test etmek için Maki (2012) Çoklu Kırılmalı Eşbütünleşme Testi kullanılmıştır. Çalışmanın ekonometrik sonuçlarının ülkeden ülkeye fark ettiği, hatta bazı ülkelerde Covid-19 ölüm ve vaka sayılarının ayrı ayrı etkileşim sergilediği sonucu görülmektedir. Vaka sayılarının ölüm sayılarına göre daha az etkin olduğu yorumu yapılabilmektedir.</text>
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            <name>Date</name>
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              <elementText elementTextId="41533">
                <text>2020</text>
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              <elementText elementTextId="41534">
                <text>COVID-19 epidemic, covid-19 salgını, stock exchange indices, maki eşbütünleşme analizi, borsa endeksleri, maki cointegration analysis</text>
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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="41535">
                <text>10.21547/jss.742893</text>
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            </elementTextContainer>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="41536">
                <text>Epidemiology and Health</text>
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            <name>Publisher</name>
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              <elementText elementTextId="41537">
                <text>Korean Society of Epidemiology</text>
              </elementText>
            </elementTextContainer>
          </element>
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            <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>
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              <elementText elementTextId="41538">
                <text>Social sciences (General), Social Sciences</text>
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              <name>Title</name>
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                  <text>Coronavirus</text>
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                  <text>Dominio científico: Coronavirus</text>
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      <name>Text</name>
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                <text>Lockdown during COVID-19 pandemic: impact on road traffic noise and on the perception of sound environment in France</text>
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                <text>Munoz Patricio, Vincent Bruno, Domergue Céline, Gissinger Vincent, Guillot Sébastien, Halbwachs Yann, Janillon Valérie</text>
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                <text>Acoucité¹, centre of expertise in environmental acoustics and observatory of the sound environment, has investigated the changes in sound environment and its perception during the French lockdown period. The approach adopted is multidimensional, since it combines long-term acoustic measurements, large area noise mapping, as well as the study of sound perception self-reported by population sample through an on-line structured questionnaire. Data from 21 continuous sound monitoring stations² were analysed for the entire lockdown period in five conurbations in the south of France and compared to typical values in the “normal” situation (before lockdown) in order to quantify the reduction in terms of sound levels. Reductions from 4 dB to 6 dB (Lden) were observed for monitoring stations with highly dominant road noise. These results were used to obtain new Strategic Noise Maps for road noise (corresponding to the lockdown situation) for the conurbations of Lyon and Grenoble. The impact of such reductions in terms of noise exposure of their inhabitants was thus assessed. An estimation of the impact on health effects in comparison with the “normal” situation (Strategic Noise Maps “Round 3 CE-DE-2002”) was also carried out. This estimation considers a scenario where the above level reductions (4 to 6 dB) would take place in the long-term. An on-line perception questionnaire was available during the lockdown period with the aim of gathering information on the way that the changes in sound environment were perceived by people all over France and ended up with more than 3000 respondents. This paper reports the main findings of the study in terms of acoustics and sound perception.</text>
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              <elementText elementTextId="41524">
                <text>2020</text>
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                <text>coronavirus outbreak, Survey, Mapping, measurement, Acoustics</text>
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                <text>10.1515/noise-2020-0024</text>
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              <elementText elementTextId="41528">
                <text>Korean Society of Epidemiology</text>
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                <text>Environmental technology. Sanitary engineering</text>
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                <text>Addendum: Early triage of critically ill COVID-19 patients using deep learning</text>
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              <elementText elementTextId="41515">
                <text>Wenhua Liang, Jianhua Yao, Ailan Chen, Qingquan Lv, Mark Zanin, Jun Liu, SookSan Wong, Yimin Li, Jiatao Lu, Hengrui Liang, Guoqiang Chen, Haiyan Guo, Jun Guo, Rong Zhou, Limin Ou, Niyun Zhou, Hanbo Chen, Fan Yang, Xiao Han, Wenjing Huan, Weimin Tang, Weijie Guan, Zisheng Chen, Yi Zhao, Ling Sang, Yuanda Xu, Wei Wang, Shiyue Li, Ligong Lu, Nuofu Zhang, Nanshan Zhong, Junzhou Huang, Jianxing He</text>
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            <name>Date</name>
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              <elementText elementTextId="41516">
                <text>2021</text>
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              <elementText elementTextId="41517">
                <text>10.1038/s41467-021-21044-3</text>
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            <elementTextContainer>
              <elementText elementTextId="41518">
                <text>Epidemiology and Health</text>
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            <name>Publisher</name>
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              <elementText elementTextId="41519">
                <text>Korean Society of Epidemiology</text>
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            <name>Coverage</name>
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                <text>Science</text>
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              <name>Title</name>
              <description>A name given to the resource</description>
              <elementTextContainer>
                <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>
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      </elementSetContainer>
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      <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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      <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>
              <elementText elementTextId="41507">
                <text>On a new conceptual mathematical model dealing the current novel coronavirus-19 infectious disease.</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="41508">
                <text>Kamal Shah, Anwarud Din, Dumitru Baleanu, Aly Seadawy, Hussam Alrabaiah</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="41509">
                <text>The present paper describes a three compartment mathematical model to study the transmission of the current infection due to the novel coronavirus (2019-nCoV or COVID-19). We investigate the aforesaid dynamical model by using Atangana, Baleanu and Caputo (ABC) derivative with arbitrary order. We derive some existence results together with stability of Hyers-Ulam type. Further for numerical simulations, we use Adams-Bashforth (AB) method with fractional differentiation. The mentioned method is a powerful tool to investigate nonlinear problems for their respective simulation. Some discussion and future remarks are also given.</text>
              </elementText>
            </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="41510">
                <text>2020</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="41511">
                <text>numerical simulations, qualitative results, Three compartments model, Adams–Bashforth (AB) method</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="43">
            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
            <elementTextContainer>
              <elementText elementTextId="41512">
                <text>10.1016/j.rinp.2020.103510</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="41513">
                <text>Results in physics</text>
              </elementText>
            </elementTextContainer>
          </element>
        </elementContainer>
      </elementSet>
    </elementSetContainer>
  </item>
</itemContainer>
