A new framework for warehouse assessment using a Genetic-Algorithm driven analytic network process
A novel way of integrating the genetic algorithm (GA) and the analytic network process (ANP) is presented in this paper in order to develop a new warehouse assessment scheme, which is developed through various stages. First, we define the main criteria that influence a warehouse performance. The pro...
Gespeichert in:
| Veröffentlicht in: | PloS one 2021-09, Vol.16 (9), p.e0256999-e0256999 |
|---|---|
| Hauptverfasser: | , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | e0256999 |
|---|---|
| container_issue | 9 |
| container_start_page | e0256999 |
| container_title | PloS one |
| container_volume | 16 |
| creator | AlAlaween, Wafa' H AlAlawin, Abdallah H Mahfouf, Mahdi Abdallah, Omar H Shbool, Mohammad A Mustafa, Mahmoud F |
| description | A novel way of integrating the genetic algorithm (GA) and the analytic network process (ANP) is presented in this paper in order to develop a new warehouse assessment scheme, which is developed through various stages. First, we define the main criteria that influence a warehouse performance. The proposed algorithm that integrates the GA with the ANP is then utilized to determine the relative importance values of the defined criteria and sub-criteria by considering the interrelationships among them, and assign strength values for such interrelationships. Such an algorithm is also employed to linguistically present the relative importance and the strength of the interrelationships in a way that can circumvent the use of pairwise comparisons. Finally, the audit checklist that consists of questions related to the criteria is integrated with the proposed algorithm for the development of the warehouse assessment scheme. Validated on 45 warehouses, the proposed scheme has been shown to be able to identify the warehouse competitive advantages and the areas where more improvements can be achieved. |
| doi_str_mv | 10.1371/journal.pone.0256999 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2570021373</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A674600426</galeid><doaj_id>oai_doaj_org_article_34e3849eb1e1420a940e2087a39c89e4</doaj_id><sourcerecordid>A674600426</sourcerecordid><originalsourceid>FETCH-LOGICAL-c669t-7a61a7e7638f721710dce199dda667d226d85c2e23c9a942e8c7f7322f0a7d3</originalsourceid><addsrcrecordid>eNqNk11rFDEUhgdRbK3-A8EBQfRi13xtMrkpLEXrQqFgxduQzZyZzTqTrEmmtf_e7O4oHemF5CLh5DnvOXnJKYrXGM0xFfjj1g_B6W6-8w7miCy4lPJJcYolJTNOEH364HxSvIhxi9CCVpw_L04oY5Igzk-L9bJ0cFc2Qfdw58OPsvGhvNMBNn6IUOoYIcYeXCqHaF1b6vISHCRrZsuu9cGmTV_Wwd6CK3Xu5j7fZMF0kNoFb3L2y-JZo7sIr8b9rLj5_OnbxZfZ1fXl6mJ5NTOcyzQTmmMtQHBaNYJggVFtAEtZ15pzURPC62phCBBqpJaMQGVEIyghDdKipmfFm6PqrvNRjeZERRYCIZINo5lYHYna663aBdvrcK-8tuoQ8KFVOuT-O1CUAa2YhDUGzAjK5RAQVAlNpakksKx1PlYb1j3kRl0KupuITm-c3ajW36qKEUqqvcD7USD4nwPEpHobDXSddpCdP_RNxYJRmdG3_6CPv26kWp0fYF3jc12zF1VLLhhHiBGeqfkjVF419Nbkn9TYHJ8kfJgkZCbBr9TqIUa1uvn6_-z19yn77gG7Ad2lTfTdkKx3cQqyI2iCjzFA89dkjNR-EP64ofaDoMZBoL8B54T5HA</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2570021373</pqid></control><display><type>article</type><title>A new framework for warehouse assessment using a Genetic-Algorithm driven analytic network process</title><source>DOAJ Directory of Open Access Journals</source><source>Public Library of Science (PLoS) Journals Open Access</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>AlAlaween, Wafa' H ; AlAlawin, Abdallah H ; Mahfouf, Mahdi ; Abdallah, Omar H ; Shbool, Mohammad A ; Mustafa, Mahmoud F</creator><contributor>Keshavarz-Ghorabaee, Mehdi</contributor><creatorcontrib>AlAlaween, Wafa' H ; AlAlawin, Abdallah H ; Mahfouf, Mahdi ; Abdallah, Omar H ; Shbool, Mohammad A ; Mustafa, Mahmoud F ; Keshavarz-Ghorabaee, Mehdi</creatorcontrib><description>A novel way of integrating the genetic algorithm (GA) and the analytic network process (ANP) is presented in this paper in order to develop a new warehouse assessment scheme, which is developed through various stages. First, we define the main criteria that influence a warehouse performance. The proposed algorithm that integrates the GA with the ANP is then utilized to determine the relative importance values of the defined criteria and sub-criteria by considering the interrelationships among them, and assign strength values for such interrelationships. Such an algorithm is also employed to linguistically present the relative importance and the strength of the interrelationships in a way that can circumvent the use of pairwise comparisons. Finally, the audit checklist that consists of questions related to the criteria is integrated with the proposed algorithm for the development of the warehouse assessment scheme. Validated on 45 warehouses, the proposed scheme has been shown to be able to identify the warehouse competitive advantages and the areas where more improvements can be achieved.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0256999</identifier><identifier>PMID: 34492066</identifier><language>eng</language><publisher>San Francisco: Public Library of Science</publisher><subject>Algorithms ; Analysis ; Biology and Life Sciences ; Computer and Information Sciences ; Corporate image ; Criteria ; Data envelopment analysis ; Decision analysis ; Engineering and Technology ; Evaluation ; Fuzzy sets ; Genetic algorithms ; Industrial engineering ; Logistics ; Medicine and Health Sciences ; Physical Sciences ; R&D ; Research & development ; Research and Analysis Methods ; Social Sciences ; Supply chains ; Warehouse stores ; Warehouses</subject><ispartof>PloS one, 2021-09, Vol.16 (9), p.e0256999-e0256999</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 AlAlaween et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 AlAlaween et al 2021 AlAlaween et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c669t-7a61a7e7638f721710dce199dda667d226d85c2e23c9a942e8c7f7322f0a7d3</citedby><cites>FETCH-LOGICAL-c669t-7a61a7e7638f721710dce199dda667d226d85c2e23c9a942e8c7f7322f0a7d3</cites><orcidid>0000-0002-1823-7490 ; 0000-0002-9413-7985</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423284/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423284/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793</link.rule.ids></links><search><contributor>Keshavarz-Ghorabaee, Mehdi</contributor><creatorcontrib>AlAlaween, Wafa' H</creatorcontrib><creatorcontrib>AlAlawin, Abdallah H</creatorcontrib><creatorcontrib>Mahfouf, Mahdi</creatorcontrib><creatorcontrib>Abdallah, Omar H</creatorcontrib><creatorcontrib>Shbool, Mohammad A</creatorcontrib><creatorcontrib>Mustafa, Mahmoud F</creatorcontrib><title>A new framework for warehouse assessment using a Genetic-Algorithm driven analytic network process</title><title>PloS one</title><description>A novel way of integrating the genetic algorithm (GA) and the analytic network process (ANP) is presented in this paper in order to develop a new warehouse assessment scheme, which is developed through various stages. First, we define the main criteria that influence a warehouse performance. The proposed algorithm that integrates the GA with the ANP is then utilized to determine the relative importance values of the defined criteria and sub-criteria by considering the interrelationships among them, and assign strength values for such interrelationships. Such an algorithm is also employed to linguistically present the relative importance and the strength of the interrelationships in a way that can circumvent the use of pairwise comparisons. Finally, the audit checklist that consists of questions related to the criteria is integrated with the proposed algorithm for the development of the warehouse assessment scheme. Validated on 45 warehouses, the proposed scheme has been shown to be able to identify the warehouse competitive advantages and the areas where more improvements can be achieved.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Biology and Life Sciences</subject><subject>Computer and Information Sciences</subject><subject>Corporate image</subject><subject>Criteria</subject><subject>Data envelopment analysis</subject><subject>Decision analysis</subject><subject>Engineering and Technology</subject><subject>Evaluation</subject><subject>Fuzzy sets</subject><subject>Genetic algorithms</subject><subject>Industrial engineering</subject><subject>Logistics</subject><subject>Medicine and Health Sciences</subject><subject>Physical Sciences</subject><subject>R&D</subject><subject>Research & development</subject><subject>Research and Analysis Methods</subject><subject>Social Sciences</subject><subject>Supply chains</subject><subject>Warehouse stores</subject><subject>Warehouses</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNk11rFDEUhgdRbK3-A8EBQfRi13xtMrkpLEXrQqFgxduQzZyZzTqTrEmmtf_e7O4oHemF5CLh5DnvOXnJKYrXGM0xFfjj1g_B6W6-8w7miCy4lPJJcYolJTNOEH364HxSvIhxi9CCVpw_L04oY5Igzk-L9bJ0cFc2Qfdw58OPsvGhvNMBNn6IUOoYIcYeXCqHaF1b6vISHCRrZsuu9cGmTV_Wwd6CK3Xu5j7fZMF0kNoFb3L2y-JZo7sIr8b9rLj5_OnbxZfZ1fXl6mJ5NTOcyzQTmmMtQHBaNYJggVFtAEtZ15pzURPC62phCBBqpJaMQGVEIyghDdKipmfFm6PqrvNRjeZERRYCIZINo5lYHYna663aBdvrcK-8tuoQ8KFVOuT-O1CUAa2YhDUGzAjK5RAQVAlNpakksKx1PlYb1j3kRl0KupuITm-c3ajW36qKEUqqvcD7USD4nwPEpHobDXSddpCdP_RNxYJRmdG3_6CPv26kWp0fYF3jc12zF1VLLhhHiBGeqfkjVF419Nbkn9TYHJ8kfJgkZCbBr9TqIUa1uvn6_-z19yn77gG7Ad2lTfTdkKx3cQqyI2iCjzFA89dkjNR-EP64ofaDoMZBoL8B54T5HA</recordid><startdate>20210907</startdate><enddate>20210907</enddate><creator>AlAlaween, Wafa' H</creator><creator>AlAlawin, Abdallah H</creator><creator>Mahfouf, Mahdi</creator><creator>Abdallah, Omar H</creator><creator>Shbool, Mohammad A</creator><creator>Mustafa, Mahmoud F</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-1823-7490</orcidid><orcidid>https://orcid.org/0000-0002-9413-7985</orcidid></search><sort><creationdate>20210907</creationdate><title>A new framework for warehouse assessment using a Genetic-Algorithm driven analytic network process</title><author>AlAlaween, Wafa' H ; AlAlawin, Abdallah H ; Mahfouf, Mahdi ; Abdallah, Omar H ; Shbool, Mohammad A ; Mustafa, Mahmoud F</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c669t-7a61a7e7638f721710dce199dda667d226d85c2e23c9a942e8c7f7322f0a7d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Analysis</topic><topic>Biology and Life Sciences</topic><topic>Computer and Information Sciences</topic><topic>Corporate image</topic><topic>Criteria</topic><topic>Data envelopment analysis</topic><topic>Decision analysis</topic><topic>Engineering and Technology</topic><topic>Evaluation</topic><topic>Fuzzy sets</topic><topic>Genetic algorithms</topic><topic>Industrial engineering</topic><topic>Logistics</topic><topic>Medicine and Health Sciences</topic><topic>Physical Sciences</topic><topic>R&D</topic><topic>Research & development</topic><topic>Research and Analysis Methods</topic><topic>Social Sciences</topic><topic>Supply chains</topic><topic>Warehouse stores</topic><topic>Warehouses</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>AlAlaween, Wafa' H</creatorcontrib><creatorcontrib>AlAlawin, Abdallah H</creatorcontrib><creatorcontrib>Mahfouf, Mahdi</creatorcontrib><creatorcontrib>Abdallah, Omar H</creatorcontrib><creatorcontrib>Shbool, Mohammad A</creatorcontrib><creatorcontrib>Mustafa, Mahmoud F</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>AlAlaween, Wafa' H</au><au>AlAlawin, Abdallah H</au><au>Mahfouf, Mahdi</au><au>Abdallah, Omar H</au><au>Shbool, Mohammad A</au><au>Mustafa, Mahmoud F</au><au>Keshavarz-Ghorabaee, Mehdi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new framework for warehouse assessment using a Genetic-Algorithm driven analytic network process</atitle><jtitle>PloS one</jtitle><date>2021-09-07</date><risdate>2021</risdate><volume>16</volume><issue>9</issue><spage>e0256999</spage><epage>e0256999</epage><pages>e0256999-e0256999</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>A novel way of integrating the genetic algorithm (GA) and the analytic network process (ANP) is presented in this paper in order to develop a new warehouse assessment scheme, which is developed through various stages. First, we define the main criteria that influence a warehouse performance. The proposed algorithm that integrates the GA with the ANP is then utilized to determine the relative importance values of the defined criteria and sub-criteria by considering the interrelationships among them, and assign strength values for such interrelationships. Such an algorithm is also employed to linguistically present the relative importance and the strength of the interrelationships in a way that can circumvent the use of pairwise comparisons. Finally, the audit checklist that consists of questions related to the criteria is integrated with the proposed algorithm for the development of the warehouse assessment scheme. Validated on 45 warehouses, the proposed scheme has been shown to be able to identify the warehouse competitive advantages and the areas where more improvements can be achieved.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>34492066</pmid><doi>10.1371/journal.pone.0256999</doi><tpages>e0256999</tpages><orcidid>https://orcid.org/0000-0002-1823-7490</orcidid><orcidid>https://orcid.org/0000-0002-9413-7985</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2021-09, Vol.16 (9), p.e0256999-e0256999 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2570021373 |
| source | DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Algorithms Analysis Biology and Life Sciences Computer and Information Sciences Corporate image Criteria Data envelopment analysis Decision analysis Engineering and Technology Evaluation Fuzzy sets Genetic algorithms Industrial engineering Logistics Medicine and Health Sciences Physical Sciences R&D Research & development Research and Analysis Methods Social Sciences Supply chains Warehouse stores Warehouses |
| title | A new framework for warehouse assessment using a Genetic-Algorithm driven analytic network process |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T13%3A55%3A20IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20new%20framework%20for%20warehouse%20assessment%20using%20a%20Genetic-Algorithm%20driven%20analytic%20network%20process&rft.jtitle=PloS%20one&rft.au=AlAlaween,%20Wafa'%20H&rft.date=2021-09-07&rft.volume=16&rft.issue=9&rft.spage=e0256999&rft.epage=e0256999&rft.pages=e0256999-e0256999&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0256999&rft_dat=%3Cgale_plos_%3EA674600426%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2570021373&rft_id=info:pmid/34492066&rft_galeid=A674600426&rft_doaj_id=oai_doaj_org_article_34e3849eb1e1420a940e2087a39c89e4&rfr_iscdi=true |