Dublin Core 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/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core 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/. Creator An entity primarily responsible for making the resource Seema; Singhal, Abhinav; Hashim, Hussam E.; Sharma, Alka; Bareja, Umang Title A name given to the resource Analytical and AINN-based investigation of surface wave propagation in dry long bones with initial stress, magnetic field, and rotation effects Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Theory in Biosciences;Volume;145;Issue;2;Article No.;17; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s12064-026-00470-1" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s12064-026-00470-1</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105035818991?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105035818991?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Seema, Christ University, Bengaluru, 560029, India; Singhal A., Christ University, Bengaluru, 560029, India; Hashim H.E., Department of Mathematics, Turabah University College, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia; Sharma A., Department of Mathematics, Faculty of Science and Humanities, Poornima University, Rajasthan, Jaipur, 303905, India; Bareja U., Department of Mathematics, Mukand Lal National College, Haryana, Yamunanagar, 135001, India Description An account of the resource This study presents a comprehensive analytical and artificial intelligence neural network (AINN)-based investigation of wave propagation in dry long bones, modeled as an orthotropic hollow cylindrical structure. The proposed model incorporates the combined effects of initial stress, magnetic field, and rotational motion to capture the complex behavior of bone-like media under coupled physical influences. The governing equations are formulated within a continuum mechanics framework and solved analytically using displacement potential methods, yielding solutions in terms of Bessel functions that satisfy the cylindrical geometry and boundary conditions. Two distinct cases, corresponding to the absence and presence of rotation, are examined to assess the influence of rotational effects on wave dynamics. A detailed parametric analysis is carried out to evaluate the variation of phase velocity and frequency with respect to wave number, initial stress, magnetic parameter, density, and geometric ratios. The analytical results indicate that initial stress enhances wave propagation, while magnetic effects introduce damping and rotation significantly modifies dispersion characteristics. To improve computational efficiency and predictive capability, an AINN model is developed and trained using analytically generated data. The AINN predictions show excellent agreement with the analytical results, as confirmed through parity plots, error analysis, residual distribution, and loss convergence behavior. The novelty of the study lies in the unified analytical-AINN framework that integrates mechanical, electromagnetic, and rotational effects within a single model. The findings provide important insights for wave-based characterization of bone structures and have potential applications in non-destructive evaluation, ultrasonic diagnostics, and advanced biomedical sensing systems. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2026. Subject The topic of the resource AINN; Artificial neural network; Biomedical diagnostics; Continuum mechanics; Dry long bone; Initial stress; Magnetic coupling; Non-destructive evaluation; Orthotropic hollow cylinder; Rotation effect; Surface energy Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 14317613; CODEN: THBIF Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online