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              <name>Title</name>
              <description>A name given to the resource</description>
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                  <text>Coronavirus</text>
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                  <text>Dominio científico: Coronavirus</text>
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                <text>Detection and Prevalence Patterns of Group I Coronaviruses in Bats, Northern Germany</text>
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                <text>Sung Sup Park, Nadine Petersen, Ana Maria Bispo de Filippis, Marcel A. Müller, Klaus Grywna, Florian Gloza-Rausch, Antje Seebens, Anne Ipsen, Matthias Göttsche, Marcus Panning, Augustina Annan, Susanne Pfefferle</text>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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                <text>We tested 315 bats from 7 different bat species in northern Germany for coronaviruses by reverse transcription–PCR. The overall prevalence was 9.8%. There were 4 lineages of group I coronaviruses in association with 4 different species of verspertilionid bats (Myotis dasycneme, M. daubentonii, Pipistrellus nathusii, P. pygmaeus). The lineages formed a monophyletic clade of bat coronaviruses found in northern Germany. The clade of bat coronaviruses have a sister relationship with a clade of Chinese type I coronaviruses that were also associated with the Myotis genus (M. ricketti). Young age and ongoing lactation, but not sex or existing gravidity, correlated significantly with coronavirus detection. The virus is probably maintained on the population level by amplification and transmission in maternity colonies, rather than being maintained in individual bats.</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="27240">
                <text>2008</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="27241">
                <text>research, Germany, coronavirus, bats, SARS</text>
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          <element elementId="43">
            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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              <elementText elementTextId="27242">
                <text>DOI: 10.3201/eid1404.071439</text>
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          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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                <text>Emerging Infectious Diseases</text>
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          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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                <text>Centers for Disease Control and Prevention</text>
              </elementText>
            </elementTextContainer>
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          <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>
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                <text>Infectious and parasitic diseases, Medicine</text>
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              <name>Title</name>
              <description>A name given to the resource</description>
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                  <text>Coronavirus</text>
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              <name>Description</name>
              <description>An account of the resource</description>
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                  <text>Dominio científico: Coronavirus</text>
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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>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
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              <elementText elementTextId="19845">
                <text>Detection of alpha- and betacoronaviruses in rodents from Yunnan, China</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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              <elementText elementTextId="19846">
                <text>Xingyi Ge, Weihong Yang, Jihua Zhou, Bei Li, Wei Zhang, Zhengli Shi, Yunzhi Zhang</text>
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                <text>Abstract Background Rodents represent the most diverse mammals on the planet and are important reservoirs of human pathogens. Coronaviruses infect various animals, but to date, relatively few coronaviruses have been identified in rodents worldwide. The evolution and ecology of coronaviruses in rodent have not been fully investigated. Results In this study, we collected 177 intestinal samples from thress species of rodents in Jianchuan County, Yunnan Province, China. Alphacoronavirus and betacoronavirus were detected in 23 rodent samples from three species, namely Apodemus chevrieri (21/98), Eothenomys fidelis (1/62), and Apodemus ilex (1/17). We further characterized the full-length genome of an alphacoronavirus from the A. chevrieri rat and named it as AcCoV-JC34. The AcCoV-JC34 genome was 27,649 nucleotides long and showed a structure similar to the HKU2 bat coronavirus. Comparing the normal transcription regulatory sequence (TRS), 3 variant TRS sequences upstream the spike (S), ORF3, and ORF8 genes were found in the genome of AcCoV-JC34. In the conserved replicase domains, AcCoV-JC34 was most closely related to Rattus norvegicus coronavirus LNRV but diverged from other alphacoronaviruses, indicating that AcCoV-JC34 and LNRV may represent a novel alphacoronavirus species. However, the S and nucleocapsid proteins showed low similarity to those of LRNV, with 66.5 and 77.4% identities, respectively. Phylogenetic analysis revealed that the S genes of AcCoV-JC34, LRNV, and HKU2 formed a distinct lineage with all known coronaviruses. Conclusions Both alphacoronaviruses and betacoronaviruses were detected in Apodemus chevrieri in the Yunnan Province of China, indicating that Apodemus chevrieri is an important host for coronavirus. Several new features were identified in the genome of an Apodemus chevrieri coronavirus. The phylogenetic distance to other coronaviruses suggests a variable origin and evolutionary route of the S genes of AcCoV-JC34, LRNV, and HKU2. These results indicate that the diversity of rodent coronaviruses is much higher than previously expected. Further surveillance and functional studies of these coronaviruses will help to better understand the importance of rodent as host for coronaviruses.</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="19848">
                <text>2017</text>
              </elementText>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="19849">
                <text>rodent, coronavirus, genetic diversity</text>
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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="19850">
                <text>DOI: 10.1186/s12985-017-0766-9</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="19851">
                <text>Virology Journal</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="19852">
                <text>BMC</text>
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            </elementTextContainer>
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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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                <text>Infectious and parasitic diseases</text>
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            <name>Language</name>
            <description>A language of the resource</description>
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              <elementText elementTextId="19854">
                <text>EN</text>
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          <name>Dublin Core</name>
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            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
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                  <text>Coronavirus</text>
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            <element elementId="41">
              <name>Description</name>
              <description>An account of the resource</description>
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                <elementText elementTextId="2">
                  <text>Dominio científico: Coronavirus</text>
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              </elementTextContainer>
            </element>
          </elementContainer>
        </elementSet>
      </elementSetContainer>
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    <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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      <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>Detection of Alphacoronavirus vRNA in the Feces of Brazilian Free-Tailed Bats (Tadarida brasiliensis) from a Colony in Florida, USA</text>
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            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="7825">
                <text>Tania S. Bonny, John P. Driver, Taylor Paisie, Marco Salemi, John Glenn Morris, Lisa A. Shender, Lisa Smith, Carolyn Enloe, Kevin Oxenrider, Jeffery A. Gore, Julia C. Loeb, Chang-yu Wu, John A Lednicky</text>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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                <text>Bats are natural reservoirs of coronaviruses and other viruses with zoonotic potential. Florida has indigenous non-migratory populations of Brazilian free-tailed bats (Tadarida brasiliensis) that mostly roost in colonies in artificial structures. Unlike their counterparts in Brazil and Mexico, the viruses harbored by the Florida bats have been underexplored. We report the detection of an alphacoronavirus RNA-dependent RNA polymerase (RdRp) gene sequence in the feces of two of 19 different T. brasiliensis that were capture/release bats that had been evaluated for overall health. The RdRp sequence is similar but not identical to previously detected sequences in the feces of two different species of bats (T. brasiliensis and Molossus molossus) in Brazil. In common with the experience of others doing similar work, attempts to isolate the virus in cell cultures were unsuccessful. We surmise that this and highly related alphacoronavirus are carried by Brazilian free-tailed bats living in a wide eco-spatial region. As various coronaviruses (CoVs) that affect humans emerged from bats, our study raises the question whether CoVs such as the one detected in our work are yet-to-be-detected pathogens of humans and animals other than bats.</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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                <text>2017</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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                <text>Brazilian free-tailed bats, alphacoronavirus, RNA-dependent RNA polymerase (RdRp) gene</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="7829">
                <text>DOI: 10.3390/diseases5010007</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>
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                <text>Diseases</text>
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            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="7831">
                <text>MDPI AG</text>
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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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                <text>Medicine</text>
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            <description>A language of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="7833">
                <text>EN</text>
              </elementText>
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              <name>Title</name>
              <description>A name given to the resource</description>
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                  <text>Coronavirus</text>
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            <element elementId="41">
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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>
      <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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            <description>A name given to the resource</description>
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                <text>Detection of Bovine Leukemia Virus in Brains of Cattle with a Neurological Syndrome: Pathological and Molecular Studies</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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              <elementText elementTextId="5456">
                <text>Rubens Henrique Ramos D’Angelino, Edviges Maristela Pituco, Eliana Monteforte Cassaro Villalobos, Ricardo Harakava, Fabio Gregori, Claudia Del Fava</text>
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            <name>Description</name>
            <description>An account of the resource</description>
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                <text>Bovine leukemia virus (BLV) was investigated in the central nervous system (CNS) of cattle with neurological syndrome. A total of 269 CNS samples were submitted to nested-PCR (BLV env gene gp51), and the viral genotypes were identified. The nested-PCR was positive in 4.8% (13/269) CNS samples, with 2.7% (2/74) presenting at histological examination lesions of nonpurulent meningoencephalitis (NPME), whereas 5.6% (11/195) not presenting NPME (P&gt;0.05). No samples presented lymphosarcoma. The PCR products (437 bp) were sequenced and submitted to phylogenetic analysis by neighbor-joining and maximum composite likelihood methods, and genotypes 1, 5, and 6 were detected, corroborating other South American studies. The genotype 6 barely described in Brazil and Argentina was more frequently detected in this study. The identity matrices showed maximum similarity (100%) among some samples of this study and one from Argentina (FJ808582), recovered from GenBank. There was no association among the genotypes and NPME lesions.</text>
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            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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                <text>2013</text>
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            <name>Identifier</name>
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                <text>DOI: 10.1155/2013/425646</text>
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            <description>A related resource from which the described resource is derived</description>
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                <text>BioMed Research International</text>
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                <text>Hindawi Limited</text>
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                <text>Medicine</text>
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                <text>EN</text>
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                  <text>Coronavirus</text>
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                  <text>Dominio científico: Coronavirus</text>
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          <element elementId="50">
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              <elementText elementTextId="16398">
                <text>Detection of bovine viral diarrhea virus genotype 1 in aerosol by a real time RT-PCR assay</text>
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              <elementText elementTextId="16399">
                <text>Peili Hou, Yaru Xu, Hongmei Wang, Hongbin He</text>
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                <text>Abstract Background As a pestivirus of the Flaviviridae family, bovine viral diarrhea virus (BVDV), has imposed a large burden on animal husbandry worldwide, and such virus can be transmitted mainly through direct contact with other infected animals and probably via aerosols. In the present study, we aimed to develop a real-time RT-PCR method for detection of BVDV-1 in aerosol samples. Methods A pair of primers specific for highly conserved regions of the BVDV-1 5′-UTR was designed. The standard curve and sensitivity of the developed assay were assessed based on 10-fold serial dilutions of RNA molecular standard. The specificity of the assay was evaluated with other pestiviruses and infectious bovine viruses. The clinical performance was examined by testing 169 aerosol samples. Results The results showed that a good linear relationship existed between the standard curve and the concentration of template. The lowest detection limit was 5.2 RNA molecules per reaction. This assay was specific for detection of BVDV-1, and no amplification was found for other pestiviruses such as classical swine fever virus (CSFV), border disease virus (BDV), and common infectious bovine viruses, including BVDV-2, infectious bovine rhinotracheitis virus (IBRV), bovine parainfluenza virus type 3 (BPIV-3), bovine respiratory syncytial virus (BRSV), bovine ephemeral fever virus (BEFV) and bovine coronavirus (BcoV). The assay was highly reproducible with low variation coefficient values (CVs) for intra-assay and inter-assay. A total of 169 aerosol samples collected from six dairy herds were tested using this method. The results showed that the positive detection rate of BVDV-1 was 17.2% (29/169), which was significantly higher compared with the conventional RT-PCR. Additionally, the positive samples (n = 29) detected by real-time RT-PCR were verified by BVDV RPA-LFD, and a concordance rate of 100% was obtained between them. Conclusions Taken together, we developed a real-time RT-PCR assay for quantitative analysis of BVDV-1 in aerosol samples, and our finding provided valuable insights into the risk on aerosol transmission of BVDV-1.</text>
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                <text>2020</text>
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                <text>bovine viral diarrhea virus (BVDV), Real-time RT-PCR, BVDV-1 aerosol, detection</text>
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              <elementText elementTextId="16403">
                <text>DOI: 10.1186/s12917-020-02330-6</text>
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          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="16404">
                <text>BMC Veterinary Research</text>
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                <text>BMC</text>
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                <text>Veterinary medicine</text>
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            <elementTextContainer>
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                <text>EN</text>
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            <element elementId="50">
              <name>Title</name>
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                  <text>Coronavirus</text>
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                  <text>Dominio científico: Coronavirus</text>
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      <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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          <element elementId="50">
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              <elementText elementTextId="4987">
                <text>Detection of canine visceral leishmaniasis by conjunctival swab PCR</text>
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          <element elementId="39">
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              <elementText elementTextId="4988">
                <text>Vanessa Figueredo Pereira, Julia Cristina Benassi, Wilma Aparecida Starke Buzetti, Diogo Tiago Silva, Helena Lage Ferreira, Lara Borges Keid, Rodrigo Martins Soares, Vera Letticie de Azevedo Ruiz, Trícia Maria Ferreira de Sousa Oliveira</text>
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          <element elementId="41">
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            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="4989">
                <text>Abstract:  INTRODUCTION:  Conjunctival swab PCR was evaluated as a tool to diagnose visceral leishmaniasis in dogs.  METHODS:  Conjunctival swab PCR was compared to indirect immunofluorescence antibody test and blood PCR.  RESULTS:  Indirect immunofluorescence was significantly correlated with conjunctival swab PCR (p &lt; 0.05), but not with blood PCR (p &gt; 0.05). In addition, conjunctival swab PCR was significantly associated with presence of clinical symptoms (p &lt; 0.05), whereas blood PCR was associated with absence of clinical symptoms (p &lt; 0.05).  CONCLUSIONS:  Results indicate that conjunctival swab PCR is useful in epidemiological surveys of canine visceral leishmaniasis.</text>
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            <name>Date</name>
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            <elementTextContainer>
              <elementText elementTextId="4990">
                <text>2016</text>
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          <element elementId="49">
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              <elementText elementTextId="4991">
                <text>Canine visceral leishmaniasis, Conjunctival swab, Epidemiological survey</text>
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          <element elementId="43">
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              <elementText elementTextId="4992">
                <text>DOI: 10.1590/0037-8682-0191-2015</text>
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            <elementTextContainer>
              <elementText elementTextId="4993">
                <text>Revista da Sociedade Brasileira de Medicina Tropical</text>
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              <elementText elementTextId="4994">
                <text>Sociedade Brasileira de Medicina Tropical (SBMT)</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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              <elementText elementTextId="4995">
                <text>Arctic medicine. Tropical medicine</text>
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            <description>A language of the resource</description>
            <elementTextContainer>
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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>
      <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>
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          <element elementId="50">
            <name>Title</name>
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              <elementText elementTextId="25856">
                <text>Detection of coronavirus Disease (COVID-19) based on Deep Features and Support Vector Machine</text>
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              <elementText elementTextId="25857">
                <text>Prabira Kumar Sethy, Santi Kumari Behera, Pradyumna Kumar Ratha, Preesat Biswas</text>
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              <elementText elementTextId="25858">
                <text>The detection of coronavirus (COVID-19) is now a critical task for the medical practitioner. The coronavirus spread so quickly between people and approaches 100,000 people worldwide. In this consequence, it is very much essential to identify the infected people so that prevention of spread can be taken. In this paper, the deep feature plus support vector machine (SVM) based methodology is suggested for detection of coronavirus infected patient using X-ray images. For classification, SVM is used instead of deep learning based classifier, as the later one need a large dataset for training and validation. The deep features from the fully connected layer of CNN model are extracted and fed to SVM for classification purpose. The SVM classifies the corona affected X-ray images from others. The methodology consists of three categories of Xray images, i.e., COVID-19, pneumonia and normal. The method is beneficial for the medical practitioner to classify among the COVID-19 patient, pneumonia patient and healthy people. SVM is evaluated for detection of COVID-19 using the deep features of different 13 number of CNN models. The SVM produced the best results using the deep feature of ResNet50. The classification model, i.e. ResNet50 plus SVM achieved accuracy, sensitivity, FPR and F1 score of 95.33%,95.33%,2.33% and 95.34% respectively for detection of COVID-19 (ignoring SARS, MERS and ARDS). Again, the highest accuracy achieved by ResNet50 plus SVM is 98.66%. The result is based on the Xray images available in the repository of GitHub and Kaggle. As the data set is in hundreds, the classification based on SVM is more robust compared to the transfer learning approach. Also, a comparison analysis of other traditional classification method is carried out. The traditional methods are local binary patterns (LBP) plus SVM, histogram of oriented gradients (HOG) plus SVM and Gray Level Co-occurrence Matrix (GLCM) plus SVM. In traditional image classification method, LBP plus SVM achieved 93.4% of accuracy.</text>
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            <name>Date</name>
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              <elementText elementTextId="25859">
                <text>2020</text>
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          <element elementId="49">
            <name>Subject</name>
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            <elementTextContainer>
              <elementText elementTextId="25860">
                <text>diagnosis, SVM, coronavirus, Deep features, COVID-19</text>
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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="25861">
                <text>DOI: 10.33889/IJMEMS.2020.5.4.052</text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="25862">
                <text>International Journal of Mathematical, Engineering and Management Sciences</text>
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            <name>Publisher</name>
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              <elementText elementTextId="25863">
                <text>International Journal of Mathematical, Engineering and Management Sciences</text>
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              <elementText elementTextId="25864">
                <text>Technology, Mathematics</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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                <text>Detection of Coronavirus Disease (COVID-19) using Radiological Examinations</text>
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              <elementText elementTextId="37285">
                <text>Anees Muhammad, Muhammad Shahzeb, Areena Khan</text>
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            <name>Description</name>
            <description>An account of the resource</description>
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              <elementText elementTextId="37286">
                <text>An outbreak of Coronavirus disease 2019 (COVID-19) occurred in China. The causative agent of COVID-19is Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The disease rapidly spreads fromChina to the world by trading and traveling. Until April 24, 2020, approximately 2,544,792 cases wereconfirmed with 175,694 deaths throughout the world. The highest number of cases were identifiedfrom the United States of America (USA) whereas the mortality rate is high in Portugal. The diagnosis ofCOVID-19 is based on Computed Tomography Scanning (CT Scan) and Real-Time Reverse TranscriptionPolymerase Chain Reaction (qRT-PCR). Assessing the extension of pathology, the exact location of thearea involved, and assessment of the disease severity makes CT scan superior to other modalities. Thisreview shows that real-time polymerase chain reaction and imaging technology both play an importantrole in the diagnosis of COVID-19. However, imaging modalities have more importance in diagnosisand screening than qRT-PCR. The qRT-PCR was positive in 81.3% whereas CT scan abnormality wasobserved in 89.8%. Bilateral lobe (51.4%) abnormality was found more than a single lobe (21.5%) inCOVID-19 infected patients. The CT scan reports show a high-level abnormality in right lower lung lobethan others in COVID-19 infected patients. The CT scan evaluates different manifestations such as thepresence of ground-glass opacities, consolidations, crazy paying linear, cavitation, discrete nodules,pleural effusion, and lymphadenopathy. It is concluded that imaging technology especially CT scan andX-rays play an important role in the screening and diagnosis of COVID-19 infected patients in limitedaccess to qRT-PCR regions. The common radiological manifestation was also determined, which willbe helpful for the radiologist to diagnosed COVID-19 infected patients in the early stages. Follow upstudies required regarding the radiological examinations.</text>
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                <text>2020</text>
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          <element elementId="49">
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              <elementText elementTextId="37288">
                <text>consolidation, real-time polymerase chain reaction, Ground glass opacity, Computed tomography scanning, COVID-19</text>
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            <name>Identifier</name>
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              <elementText elementTextId="37289">
                <text>DOI: 10.22207/JPAM.14.SPL1.28</text>
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              <elementText elementTextId="37290">
                <text>Journal of Pure and Applied Microbiology</text>
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              <elementText elementTextId="37291">
                <text>Journal of Pure and Applied Microbiology</text>
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                <text>Microbiology</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="86148">
                <text>Detection of Coronavirus Phishing Emails using Echo State Neural Network</text>
              </elementText>
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          </element>
          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="86149">
                <text>omar younis</text>
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            </elementTextContainer>
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          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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                <text>E-mail is an important and fast  mean of conveying information among  people, banks, companies and organizations, that information is often important, sensitive and secret, this make it worthy to attackers who can use it for harmful purposes. Spread of coronavirus in most countries of the world and the huge amount of media coverage surrounding this virus led to emergence phishing emails by exploiting coronavirus pandemic. Phishing emails are scam messages used by fraudsters to take out secret information from persons by pretending that it is from official sources. In this paper a novel method has been proposed to detect the coronavirus phishing emails and distinguish them from legitimate mails by using Echo state neural network(ESN), after preprocessing the emails, features are selected from the header and body  of it, these features are given as fed to the (ESN) algorithm to classify emails as malicious or legitimate. The results showed the efficiency and accuracy of the algorithm used in the detection of coronavirus phishing emails, where the rate of accuracy, precision, recall and F-measure are 99.392, 98.892, 99888, and 99.387 respectively with low required processing time (0.00092 msec.) for testing and (165.19 msec.) for training.</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="86151">
                <text>2020</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="86152">
                <text>coronavirus, Features, Phishing, E-mail, ESN, legitimate</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="43">
            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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              <elementText elementTextId="86153">
                <text>10.21271/ZJPAS.32.5.7</text>
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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="86154">
                <text>Zanco Journal of Pure and Applied Sciences</text>
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          </element>
          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="86155">
                <text>Salahaddin University-Erbil</text>
              </elementText>
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          <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>
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              <elementText elementTextId="86156">
                <text>Science, Technology</text>
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  <item itemId="625" public="1" featured="0">
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        <src>https://socictopen.socict.org/files/original/498b7c8949a2c6d2014b8542571e1e8b.pdf</src>
        <authentication>402598c2395dc29054d8f928f3de8b38</authentication>
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          <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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                <elementText elementTextId="1">
                  <text>Coronavirus</text>
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              </elementTextContainer>
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            <element elementId="41">
              <name>Description</name>
              <description>An account of the resource</description>
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                <elementText elementTextId="2">
                  <text>Dominio científico: Coronavirus</text>
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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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        <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="5831">
                <text>Detection of Coronaviruses in Bats of Various Species in Italy</text>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="5832">
                <text>Maria B. Boniotti, Enrica Rosti, Ana Moreno, Cristiano Sabelli, Alice Papetti, Davide Lelli</text>
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          </element>
          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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              <elementText elementTextId="5833">
                <text>Bats are natural reservoirs for many mammalian coronaviruses, which have received renewed interest after the discovery of the severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS) CoV in humans. This study describes the identification and molecular characterization of alphacoronaviruses and betacoronaviruses in bats in Italy, from 2010 to 2012. Sixty-nine faecal samples and 126 carcasses were tested using pan-coronavirus RT-PCR. Coronavirus RNAs were detected in seven faecal samples and nine carcasses. A phylogenetic analysis of RNA-dependent RNA polymerase sequence fragments aided in identifying two alphacoronaviruses from Kuhl’s pipistrelle (Pipistrellus kuhlii), three clade 2b betacoronaviruses from lesser horseshoe bats (Rhinolophus hipposideros), and 10 clade 2c betacoronaviruses from Kuhl’s pipistrelle, common noctule (Nyctalus noctula), and Savi’s pipistrelle (Hypsugo savii). This study fills a substantive gap in the knowledge on bat-CoV ecology in Italy, and extends the current knowledge on clade 2c betacoronaviruses with new sequences obtained from bats that have not been previously described as hosts of these viruses.</text>
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          <element elementId="40">
            <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="5834">
                <text>2013</text>
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            </elementTextContainer>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="5835">
                <text>coronavirus, bats, Italy, Molecular characterization, Phylogenetic analysis</text>
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            </elementTextContainer>
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            <name>Identifier</name>
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                <text>DOI: 10.3390/v5112679</text>
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          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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                <text>Viruses</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="5838">
                <text>MDPI AG</text>
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            </elementTextContainer>
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          <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="5839">
                <text>Microbiology</text>
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            </elementTextContainer>
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          <element elementId="44">
            <name>Language</name>
            <description>A language of the resource</description>
            <elementTextContainer>
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                <text>EN</text>
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            </elementTextContainer>
          </element>
        </elementContainer>
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