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Coarse to Fine: The role of Severe Plastic Deformation in Advancing Titanium-Based Medical Implants - A Comprehensive review

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Journal of wuhan University of Technology(Materials Science) 2025年第1期40卷 295-306页

作者： Dragana r Mihajlović Bojan I Međo Ivana Lj Cvijović-Alagić Veljko r Djokić Faculty of Technology and Metallurgy University of BelgradeKarnegijeva 411120 BelgradeSerbia Vinča Institute of Nuclear Sci-ences-National Institute of the republic of Serbia University of Belgrade11001BeogradSerbia Innovation Centre of the Faculty of Technology and Metallurgy Karnegijeva 411120 BelgradeSerbia

This paper describes severe plastic deformation(SPD)procedures,which are utilized to form an ultrafine-grained structure in metallic *** the SPD process,a solid material sample is subjected to very high loads without a significant change in sample *** the present work,the high-pressure torsion(hPT)process,as one of the SPD techniques,which achieves a high degree of deformation and ensures refinement of the microstructure,will be discussed in more *** that grain size control is accepted as a method to obtain materials with desired characteristics,an overview of the properties of ultrafine-grained titanium-based biomaterials to be used in medicine is ***,particular attention is dedicated to the influences of hPT process parameters,primarily hydrostatic pressure,and number of revolutions during torsion,on the grain size and physical and mechanical characteristics(modulus of elasticity,microhardness,and tensile properties),corrosion resistance,and biocompatibility of the titanium-based biomaterials.A review of the literature indicates that titanium-based materials obtained by the SPD process show improved mechanical and physical properties without losing biocompatibility and corrosion resistance,which suggests that these methods of obtaining implants are something that should be further developed in the future.

关键词： high-pressure torsion process ultrafine-grained titanium-based materials electrochemical anodization physical properties mechanical properties

Neuroinflammation as a therapeutic target in huntington's disease

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Neural regeneration research 2025年第3期20卷 817-818页

作者： Andrea Kwakowsky Thulani h.Palpagama Center for Brain research and Department of Anatomy and Medical Imaging Faculty of Medical and Health SciencesUniversity of AucklandAucklandNew Zealand Pharmacology and Therapeutics School of MedicineGalway Neuroscience CentreUniversity of GalwayGalwayIreland

In 1872, George huntington presented his essay “On Chorea” to the Meigs and Mason Academy of Medicine and, in doing so, detailed a disease that would later bear his name. huntington's disease(hD) is a genetic, neurodegenerative disease that manifests as the loss of motor control,cognitive impairment,and mood and psychiatric changes in paents.

关键词： huntington inflammation Medicine

Glial response in the midcingulate cortex in huntington’s disease

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Neural regeneration research 2025年第1期20卷 207-208页

作者： Thulani h.Palpagama Andrea Kwakowsky Center for Brain research and Department of Anatomy and Medical Imaging Faculty of Medical and Health SciencesUniversity of AucklandAucklandNew Zealand Pharmacology and Therapeutics School of MedicineGalway Neuroscience CenterUniversity of GalwayGalwayIreland

huntington’s disease(hD)is a genetic disease characterized by the progressive degeneration of the striatum and *** can present with a variety of symptoms that can broadly be classified into motor symptoms,inclusive of choreatic movements and rigidity,mood and psychiatric symptoms,such as depression and apathy,and cognitive symptoms,such as cognitive *** causal mutation underlying hD results from an expansion of a CAG repeat sequence on the IT15 gene,resulting in the formation and accumulation of a mutant huntingtin protein.

关键词： huntington degeneration cortex

Emerging potential of progranulin-dependent SorCS2 signaling in healthy and diseased nervous systems

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Neural regeneration research 2025年第9期20卷 2591-2593页

作者： Alena Salasova Anders Nykjær Danish research Institute of Translational Neuroscience DANDrITE-Nordic EMBL Partnership for Molecular Medicine and Centre of Excellence PROMEMODepartment of BiomedicineAarhus UniversityAarhusDenmark

The formation of the mammalian nervous system and its maturation into sensory,motor,cognitive,and behavioral circuits is a complex process that begins during early embryogenesis and lasts until young *** neurodevelopm... 详细信息

关键词： progr jointly CS2

Security Strategy of Digital Medical Contents Based on Blockchain in Generative AI Model

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Computers, Materials & Continua 2025年第1期82卷 259-278页

作者： hoon Ko Marek r.Ogiela Division of Computer Science and Engineering Sunmoon UniversityAsan31460Republic of Korea AGh University of Krakow Cryptography and Cognitive Informatics LaboratoryKrakow30-059Poland

This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain *** combining the strengths of blockchain and generative AI,the research team aimed to address the timely challenge of safeguarding visual medical *** participating researchers conducted a comprehensive analysis,examining the vulnerabilities of medical AI services,personal information protection issues,and overall security *** multi faceted exploration led to an indepth evaluation of the model’s performance and ***,the correlation between accuracy,detection rate,and error rate was *** analysis revealed insights into the model’s strengths and limitations,while the consideration of standard deviation shed light on the model’s stability and performance *** study proposed practical improvements,emphasizing the reduction of false negatives to enhance detection rate and leveraging blockchain technology to ensure visual data integrity in medical *** blockchain to generative AI-created medical content addresses key personal information protection *** utilizing the distributed ledger system of blockchain,the research team aimed to protect the privacy and integrity of medical data especially medical *** approach not only enhances security but also enables transparent and tamperproof ***,the use of generative AI models ensures the creation of novel medical content without compromising personal information,further safeguarding patient *** conclusion,this study showcases the potential of blockchain-based solutions in the medical field,particularly in securing sensitive medical data and protecting patient *** proposed approach,combining blockchain and generative AI,offers a promising direction toward more robust and secure medical content *** research and advancements

关键词： Digitalmedical content medical diagnostic visualization security analysis generativeAI blockchain vulnerability pattern recognition

Comparative chemical sensor for detection of chromium(Ⅵ) in aqueous solution

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Optoelectronics Letters 2025年第1期21卷 21-27页

作者： Sura h.AL-rEKABI A.A.ALwAhIB Electrical Technique Department Al Suwayrah Technical Institute Middle Technical University Laser and Optoelectronics Department University of Technology-Iraq

A process for purifying aqueous solutions containing heavy and toxic metals such as chromium（Cr） has been investigated. One of the extremely harmful pollutants in rivers and seawater is the heavy metal ions due to their direct impacts on human, animals and plants are hexavalent Cr（Ⅵ）. Consequently, highly sensitive sensor to detect Cr is essential. Surface plasmon resonance（SPr） technique has attracted huge research interest in detecting heavy metals specifically. In this study, three types of prism-based SPr sensor, gold（Au）/silver（Ag）, Au/polyaniline（PANI） and Au/titanium dioxide（TiO2） nanostructured films, are investigated as potential sensing material to detect the presence of Cr（Ⅵ） ions in water. The base Au layer with thickness of 48.3 nm is deposited on a glass slide for all sensors. For Au/Ag, Au/PANI nanofibers and Au/TiO2sensor films, the Cr（Ⅵ） concentration is varied from 1 ppm to 15 ppm with sensitivity of 0.270 °ppm-1, 0.082 °ppm-1and 0.039 °ppm-1, respectively. Based on these results, the Au/PANI nanofibers are the most sensitive to Cr（Ⅵ） among the tested sensing materials.

关键词： Titanium dioxide

MODELING,SIMULATION,AND OPTIMIZATION OF SUrFACE ACOUSTIC wAVE DrIVEN MICrOFLUIDIC BIOChIPS

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Journal of Computational Mathematics 2010年第2期28卷 149-169页

作者： harbir Antil roland Glowinski ronald h.w.hoppe Christopher Linsenmann Tsorng-whay Pan Achim wixforth Department of Mathematics University of Houston Institute of Mathematics University of Augsburg Institute of Physics University of Augsburg

we will be concerned with the mathematical modeling, numerical simulation, and shape optimization of micro fluidic biochips that are used for various biomedical applications. A particular feature is that the fluid flow in the fluidic network on top of the biochips is in- duced by surface acoustic waves generated by interdigital transducers. we are thus faced with a multiphysics problem that will be modeled by coupling the equations of piezoelectricity with the compressible Navier-Stokes equations. Moreover, the fluid flow exhibits a multiscale character that will be taken care of by a homogenization approach. we will discuss and analyze the mathematical models and deal with their numerical solution by space-time discretizations featuring appropriate finite element approximations with respect to hierarchies of simplicial triangulations of the underlying computational domains. Simulation results will be given for the propagation of the surface acoustic waves on top of the piezoelectric substrate and for the induced fluid flow in the microchannels of the fluidic network. The performance of the operational behavior of the biochips can be significantly improved by shape optimization. In particular, for such purposes we present a multilevel interior point method relying on a predictor-corrector strategy with an adaptive choice of the continuation steplength along the barrier path. As a specific example, we will consider the shape optimization of pressure driven capillary barriers between microchannels and reservoirs.

关键词： Microfluidic biochips Mathematical modeling Numerical simulation Shape optimization Multiphysics Multiscale problems.

A comprehensive investigation on nonlinear vibration and bending characteristics of bio-inspired helicoidal laminated composite structures

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 81-100页

作者： S.SAUrABh r.KIrAN D.SINGh r.VAISh V.S.ChAUhAN School of Mechanical and Materials Engineering Indian Institute of Technology Mandi

Bio-inspired helicoidal composite laminates, inspired by the intricate helical structures found in nature, present a promising frontier for enhancing the mechanical properties of structural designs. hence, this study provides a comprehensive investigation into the nonlinear free vibration and nonlinear bending behavior of bio-inspired composite plates. The inverse hyperbolic shear deformation theory(IhSDT) of plates is employed to characterize the displacement field, with the incorporation of Green-Lagrange nonlinearity. The problem is modeled using the C0finite element method(FEM), and an in-house code is developed in the MATLAB environment to solve it numerically. Various helicoidal layup configurations including helicoidal recursive(hr), helicoidal exponential(hE), helicoidal semi-circular(hS), linear helicoidal(Lh), and Fibonacci helicoidal(Fh)with different layup sequences and quasi-isotropic configurations are studied. The model is validated, and parametric studies are conducted. These studies investigate the effects of layup configurations, side-to-thickness ratio, modulus ratios, boundary conditions, and loading conditions at different load amplitudes on the nonlinear vibration and nonlinear bending behaviors of bio-inspired composite plates. The results show that the laminate sequence exerts a substantial impact on both nonlinear natural frequencies and nonlinear bending behaviors. Moreover, this influence varies across different side-to-thickness ratios and boundary conditions of the bio-inspired composite plate.

关键词： Inverse problems

Machine Learning Techniques in Predicting hot Deformation Behavior of Metallic Materials

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 713-732页

作者： Petr Opela Josef walek Jaromír Kopecek Department of Metallurgical Technologies Faculty of Materials Science and TechnologyVSB–Technical University of OstravaOstrava70800Czech Republic FZU—Institute of Physics of the Czech Academy of Sciences Prague18200Czech Republic

In engineering practice,it is often necessary to determine functional relationships between dependent and independent *** relationships can be highly nonlinear,and classical regression approaches cannot always provide sufficiently reliable ***,Machine Learning(ML)techniques,which offer advanced regression tools to address complicated engineering issues,have been developed and widely *** study investigates the selected ML techniques to evaluate their suitability for application in the hot deformation behavior of metallic *** ML-based regression methods of Artificial Neural Networks(ANNs),Support Vector Machine(SVM),Decision Tree regression(DTr),and Gaussian Process regression(GPr)are applied to mathematically describe hot flow stress curve datasets acquired experimentally for a medium-carbon *** the GPr method has not been used for such a regression task before,the results showed that its performance is the most favorable and practically unrivaled;neither the ANN method nor the other studied ML techniques provide such precise results of the solved regression analysis.

关键词： Machine learning Gaussian process regression artificial neural networks support vector machine hot deformation behavior