Experimental Investigation of Wave Propagation in Bio-Modified Nonlocal Couple-Stress Thermoelastic Media with Viscosity, Phase-Lag Thermal Diffusion, and Microstructural Effects

Experimental Investigation of Wave Propagation in Bio-Modified Nonlocal Couple-Stress Thermoelastic Media with Viscosity, Phase-Lag Thermal Diffusion, and Microstructural Effects | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Experimental Investigation of Wave Propagation in Bio-Modified Nonlocal Couple-Stress Thermoelastic Media with Viscosity, Phase-Lag Thermal Diffusion, and Microstructural Effects G RAVI This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8573748/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Reliable viral disease detection in clinical practice demands analytical frameworks that can effectively handle heterogeneous data, strict privacy requirements, and demographic variability. This paper presents a privacy-preserving and interpretable generative multi-modal learning framework aimed at achieving robust viral disease detection while incorporating bias mitigation, data harmonization, and real-time generalization. The proposed approach is informed by experimental observations from wave propagation in bio-modified nonlocal couple-stress thermoelastic media, where viscosity, phase-lag thermal diffusion, and microstructural effects were found to enhance signal stability, reduce attenuation, and promote uniform propagation. These experimentally established characteristics motivate the modeling of biomedical data in a manner that preserves structural consistency across multiple modalities, including medical imaging, physiological signals, and biochemical measurements. Privacy protection is ensured through distributed learning strategies and noise-aware representation modeling, allowing collaborative analysis without direct data sharing. Interpretability is embedded through physics-inspired constraints and attention-based feature analysis, supporting transparent and clinically meaningful decision processes. Bias is addressed using adaptive harmonization mechanisms guided by experimentally observed microstructural regularization effects. In addition, the incorporation of nonlocal interactions and phase-lag dependencies enables stable performance under noisy, time-varying clinical conditions. Validation results indicate notable improvements in detection accuracy, fairness, and robustness when compared with conventional multi-modal approaches. Overall, the framework establishes a meaningful connection between experimental wave mechanics and data-driven healthcare analytics, contributing toward dependable and trustworthy viral disease diagnostics. Privacy-Preserving Learning Multi-Modal Data Integration Viral Disease Detection Interpretable Models Bias Mitigation Generative Modeling Bio-Modified Media Wave Propagation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8573748","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":583340283,"identity":"0ced882f-69b1-4042-a161-b3e32f15d37c","order_by":0,"name":"G RAVI","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYJCCAwwVcLYEsVrOkKqFgbGNBDcxmLefMTz4dd62fH6xA4wffjBY5BHUInMmx+Cw7LbbljNnJzBL9jBIFBPUIsGQlnBYctttA4PbCQzSQH5iA0Et/M+AWubcNrC/ncD8mzgtEskHDn5sANoincBGpC0Sjw8cZjh220DidmKbZY8BUQ5LbP74o+a2Af/s5MM3flTUEdYCAsw8YIoRqNiAGPUgtT+IVDgKRsEoGAUjFAAAn186oyO87ZEAAAAASUVORK5CYII=","orcid":"","institution":"Malla Reddy Engineering College and Management Sciences","correspondingAuthor":true,"prefix":"","firstName":"G","middleName":"","lastName":"RAVI","suffix":""}],"badges":[],"createdAt":"2026-01-11 13:23:13","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8573748/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8573748/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101760641,"identity":"7bd424b6-3cf9-419c-bd6d-2731e0eac8c7","added_by":"auto","created_at":"2026-02-03 11:16:02","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":694291,"visible":true,"origin":"","legend":"","description":"","filename":"ExperimentalInvestigationofWavePropagationinBioModifiedNonlocalCoupleStressThermoelasticMediawithViscosityPhaseLagThermalDiffusionandMicrost.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8573748/v1_covered_c8a97928-b7b1-4f31-8c3f-d4131c78ae2f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eExperimental Investigation of Wave Propagation in Bio-Modified Nonlocal Couple-Stress Thermoelastic Media with Viscosity, Phase-Lag Thermal Diffusion, and Microstructural Effects\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Privacy-Preserving Learning, Multi-Modal Data Integration, Viral Disease Detection, Interpretable Models, Bias Mitigation, Generative Modeling, Bio-Modified Media, Wave Propagation","lastPublishedDoi":"10.21203/rs.3.rs-8573748/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8573748/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eReliable viral disease detection in clinical practice demands analytical frameworks that can effectively handle heterogeneous data, strict privacy requirements, and demographic variability. This paper presents a privacy-preserving and interpretable generative multi-modal learning framework aimed at achieving robust viral disease detection while incorporating bias mitigation, data harmonization, and real-time generalization. The proposed approach is informed by experimental observations from wave propagation in bio-modified nonlocal couple-stress thermoelastic media, where viscosity, phase-lag thermal diffusion, and microstructural effects were found to enhance signal stability, reduce attenuation, and promote uniform propagation. These experimentally established characteristics motivate the modeling of biomedical data in a manner that preserves structural consistency across multiple modalities, including medical imaging, physiological signals, and biochemical measurements. Privacy protection is ensured through distributed learning strategies and noise-aware representation modeling, allowing collaborative analysis without direct data sharing. Interpretability is embedded through physics-inspired constraints and attention-based feature analysis, supporting transparent and clinically meaningful decision processes. Bias is addressed using adaptive harmonization mechanisms guided by experimentally observed microstructural regularization effects. In addition, the incorporation of nonlocal interactions and phase-lag dependencies enables stable performance under noisy, time-varying clinical conditions. Validation results indicate notable improvements in detection accuracy, fairness, and robustness when compared with conventional multi-modal approaches. Overall, the framework establishes a meaningful connection between experimental wave mechanics and data-driven healthcare analytics, contributing toward dependable and trustworthy viral disease diagnostics.\u003c/p\u003e","manuscriptTitle":"Experimental Investigation of Wave Propagation in Bio-Modified Nonlocal Couple-Stress Thermoelastic Media with Viscosity, Phase-Lag Thermal Diffusion, and Microstructural Effects","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-03 11:06:39","doi":"10.21203/rs.3.rs-8573748/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4ee5fbc7-7d79-4353-8a1e-30772d7effc9","owner":[],"postedDate":"February 3rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-03T11:06:39+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-03 11:06:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8573748","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8573748","identity":"rs-8573748","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}