PMC:7796058 / 47296-48361 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"328","span":{"begin":583,"end":589},"obj":"Gene"},{"id":"329","span":{"begin":437,"end":443},"obj":"Gene"},{"id":"330","span":{"begin":856,"end":864},"obj":"Disease"},{"id":"331","span":{"begin":1040,"end":1048},"obj":"Disease"}],"attributes":[{"id":"A328","pred":"tao:has_database_id","subj":"328","obj":"Gene:59286"},{"id":"A329","pred":"tao:has_database_id","subj":"329","obj":"Gene:59286"},{"id":"A330","pred":"tao:has_database_id","subj":"330","obj":"MESH:C000657245"},{"id":"A331","pred":"tao:has_database_id","subj":"331","obj":"MESH:C000657245"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"Depending on the size of the data, type of beacons, and network bandwidth, mobile proximity detection performance may differ. In our experiment, various beacons such as Estimote (https://estimote.com/), Accent Systems (https://accent-systems.com/) and Radius Networks (https://www.radiusnetworks.com/) have been evaluated using the developed app on the Samsung Galaxy S9 smartphone. Our results demonstrated that the app could capture a beacon’s proximity of fewer than 60 milliseconds, which is enough for our case study. The complexity of the position determination depends on the beacon software development kit; however, the complexity is O(n) in the worst-case scenario. Concerning the duration spent in a room, we detected and recorded durations of less than five seconds when walking past beacons in a corridor. Significance of time for the sake of COVID-19 risk was not considered important for durations less than 15 min, which was standard practice. So, our sampling and recording intervals were much better than was required for COVID-19 risk evaluation."}

{"project":"LitCovid-sentences","denotations":[{"id":"T330","span":{"begin":0,"end":125},"obj":"Sentence"},{"id":"T331","span":{"begin":126,"end":382},"obj":"Sentence"},{"id":"T332","span":{"begin":383,"end":522},"obj":"Sentence"},{"id":"T333","span":{"begin":523,"end":675},"obj":"Sentence"},{"id":"T334","span":{"begin":676,"end":818},"obj":"Sentence"},{"id":"T335","span":{"begin":819,"end":959},"obj":"Sentence"},{"id":"T336","span":{"begin":960,"end":1065},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Depending on the size of the data, type of beacons, and network bandwidth, mobile proximity detection performance may differ. In our experiment, various beacons such as Estimote (https://estimote.com/), Accent Systems (https://accent-systems.com/) and Radius Networks (https://www.radiusnetworks.com/) have been evaluated using the developed app on the Samsung Galaxy S9 smartphone. Our results demonstrated that the app could capture a beacon’s proximity of fewer than 60 milliseconds, which is enough for our case study. The complexity of the position determination depends on the beacon software development kit; however, the complexity is O(n) in the worst-case scenario. Concerning the duration spent in a room, we detected and recorded durations of less than five seconds when walking past beacons in a corridor. Significance of time for the sake of COVID-19 risk was not considered important for durations less than 15 min, which was standard practice. So, our sampling and recording intervals were much better than was required for COVID-19 risk evaluation."}