Numerical Simulation in Biomechanics and Biomedical Engineering-II
This reprint presents a collection of significant contributions to advancement of the application of the mathematical modeling to biomechanics and the biomedical engineering. This publication contains a particularly diverse set of contributions. For instance, Latif and co-authors review the specific...
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Format: | Electronic Book Chapter |
Language: | English |
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Basel
MDPI - Multidisciplinary Digital Publishing Institute
2023
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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100 | 1 | |a Malvè, Mauro |4 edt | |
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245 | 1 | 0 | |a Numerical Simulation in Biomechanics and Biomedical Engineering-II |
260 | |a Basel |b MDPI - Multidisciplinary Digital Publishing Institute |c 2023 | ||
300 | |a 1 electronic resource (248 p.) | ||
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338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a This reprint presents a collection of significant contributions to advancement of the application of the mathematical modeling to biomechanics and the biomedical engineering. This publication contains a particularly diverse set of contributions. For instance, Latif and co-authors review the specifications to model the upper airways before mandibular advancement surgery. Calvo-Gallego et al. propose local stress and strain tensors-derived variables as candidates for bone mechanical stimuli. Sohail et al. present a methodology for total knee arthroplasty. Latorre et al. propose the use of estimated strains to develop a methodology for plaque segmentation in arterial vessels. Lertxundi et al. simulate the blood flow and the microsphere transport during radioembolization for liver cancer treatment. Mañosas et al. combine tissue clarification, advanced microscopy and image analysis to develop a one-dimensional computational model of murine microvasculature hemodynamics. Talygin et al. obtain new quantitative parameters that characterize the normal and pathological aorta. Nježić et al. analyze the motion of nanoparticles in a ferrofluid environment. Hernández-López and co-workers study the parameter influence on lesion growth using a mechanobiological model of atherosclerosis. Jerbi et al present an adaptive learning tracking controller of a wearable robotic knee system. Gahima et al. introduce a novel formulation for a linear elastic model of a heterogeneous arterial section. Urdeitx et al. develop a novel hybrid 3D agent-based model to study multiple myeloma cell growth. Finally, Bayod et al. evaluate the stress generated by medializing calcaneal osteotomyin in hindfoot and forefoot bones. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Technology: general issues |2 bicssc | |
650 | 7 | |a Biotechnology |2 bicssc | |
653 | |a bone remodelling | ||
653 | |a mechanical stimulus | ||
653 | |a correlation | ||
653 | |a bone density distribution | ||
653 | |a strain energy density | ||
653 | |a absolute maximum principal stress | ||
653 | |a fluctuation of stresses | ||
653 | |a imageless navigator | ||
653 | |a knee alignment device | ||
653 | |a total knee arthroplasty | ||
653 | |a repeatable transepicondylar axis | ||
653 | |a femoral coordinate system | ||
653 | |a modified Whiteside's line | ||
653 | |a atherosclerosis | ||
653 | |a fibrous cap thickness | ||
653 | |a finite element model | ||
653 | |a intravascular ultrasound | ||
653 | |a segmentation method | ||
653 | |a strain gradient | ||
653 | |a computational fluid dynamics | ||
653 | |a hemodynamics | ||
653 | |a liver cancer | ||
653 | |a dosimetry | ||
653 | |a drug delivery | ||
653 | |a tumor targeting | ||
653 | |a patient-specific | ||
653 | |a treatment planning | ||
653 | |a blood-brain barrier microvasculature | ||
653 | |a cortical capillary network | ||
653 | |a tissue clarification | ||
653 | |a imaging technique | ||
653 | |a numerical model | ||
653 | |a microvascular hemodynamics | ||
653 | |a potential swirling flow | ||
653 | |a navier-stokes equations | ||
653 | |a unsteady swirling flow | ||
653 | |a tornado-like jets | ||
653 | |a Brownian motion | ||
653 | |a chaotic model | ||
653 | |a ferrofluid | ||
653 | |a targeted drug delivery | ||
653 | |a exogenous power propulsion strategy | ||
653 | |a OSA | ||
653 | |a mandibular advancement | ||
653 | |a CFD | ||
653 | |a sleep apnea | ||
653 | |a mechanobiological model | ||
653 | |a parameter analysis | ||
653 | |a carotid artery | ||
653 | |a wearable robotic knee | ||
653 | |a tracking controller | ||
653 | |a radial basis function neural network | ||
653 | |a L2 gain | ||
653 | |a Hamilton-Jacobi Inequality | ||
653 | |a robust control | ||
653 | |a adaptive control | ||
653 | |a elastic bed boundary condition | ||
653 | |a robin boundary condition | ||
653 | |a immersed boundary method | ||
653 | |a level set | ||
653 | |a arterial biomechanics | ||
653 | |a unfitted method | ||
653 | |a in silico | ||
653 | |a 3D model | ||
653 | |a multiple myeloma | ||
653 | |a tumor aggregate | ||
653 | |a dense discrete particle model | ||
653 | |a finite elements | ||
653 | |a flatfoot | ||
653 | |a stress redistribution | ||
653 | |a osteotomy | ||
653 | |a pes planus | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/7571 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/112458 |7 0 |z DOAB: description of the publication |