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dc.contributor.authorNieto-Chaupis, Huber
dc.date.accessioned2022-04-29T17:12:25Z
dc.date.available2022-04-29T17:12:25Z
dc.date.issued2021-10-18
dc.identifier.citationNieto-Chaupis, H. (2021). Proteins-Based Circuits in an Intelligent Internet of Bio-Nano Things Network for Molecular Diagnostic of Renal Damage. In 2021 Third International Conference on Transdisciplinary AI (TransAI) (pp. 68-71). IEEE.es_PE
dc.identifier.isbn978-1-6654-3412-6
dc.identifier.urihttps://hdl.handle.net/20.500.13067/1812
dc.description.abstractIt is shown that the accumulation of albumin proteins around the locations of podocytes is rather similar to a R-C (Resistance-Capacitor) circuit. While the electric shielding is not enough to detain the pass of albumin, more than a diffusion phenomenon, it is a problem that is entirely treated as one belonging to the classical electrodynamics. In this manner it was identified that the diffusion constant plays a role as the electrical parameters. The permanent aggregation of albumin proteins creates a capacitance. Therefore the expended power by the R-C circuit is interpreted as the loss of energy of renal glomerulus with implications on the performance and homeostasis of kidney. Thus, the identification of electric unbalance is translated as a signal of Kidney disease. The fact of having a physics-based scenario demands us to propose schemes inside the framework of the Internet of Bio-Nano Things.es_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherInstitute of Electrical and Electronics Engineerses_PE
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_PE
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/es_PE
dc.sourceAUTONOMAes_PE
dc.subjectProteinses_PE
dc.subjectNanoparticleses_PE
dc.subjectElectrodynamicses_PE
dc.subjectTemperaturees_PE
dc.subjectBiological system modelinges_PE
dc.subjectIonses_PE
dc.subjectMathematical modelses_PE
dc.titleProteins-Based Circuits in an Intelligent Internet of Bio-Nano Things Network for Molecular Diagnostic of Renal Damagees_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.identifier.journal2021 Third International Conference on Transdisciplinary AI (TransAI)es_PE
dc.identifier.doihttps://doi.org/10.1109/TransAI51903.2021.00020
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.02.04es_PE
dc.publisher.countryPEes_PE
dc.relation.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85126208917&doi=10.1109%2fTransAI51903.2021.00020&partnerID=40es_PE
dc.source.beginpage68es_PE
dc.source.endpage71es_PE


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