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Von Mises stress analysis of CoCrMo-on-CoCrMo hip prosthesis based on body mass index: 2D FEM estimation

AIP Conference Proceedings 2023年第1期2714卷

作者： Muhammad Imam Ammarullah Ilham Yustar Afif Mohamad Izzur Maula Mohammad Tauviqirrahman Athanasius Priharyoto Bayuseno Jamari Tri Indah Winarni Hasan Basri Ardiyansyah Syahrom Amir Putra Md Saad Department of Mechanical Engineering Faculty of Engineering Diponegoro University Tembalang 50275 Semarang Central Java Indonesia Department of Anatomy Faculty of Medicine Diponegoro University Tembalang 50275 Semarang Central Java Indonesia Center for Biomedical Research (CEBIOR) Faculty of Medicine Diponegoro University Tembalang 50275 Semarang Central Java Indonesia Department of Mechanical Engineering Faculty of Engineering Sriwijaya University Indralaya 30662 Ogan Ilir South Sumatra Indonesia Applied Mechanics and Design School of Mechanical Engineering Faculty of Mechanical Engineering Universiti Teknologi Malaysia Skudai 81310 Johor Bahru Malaysia Medical Device and Technology Center (MEDiTEC) Institute of Human-Centered and Engineering (iHumEn) Universiti Teknologi Malaysia Skudai 81310 Johor Bahru Malaysia

Various studies of total hip arthroplasty from many existing researchers have examined implant user external factors from implant user. Unfortunately, internal factor of implant user is not profoundly discussed. Our current study aims to understand von mises stress in CoCrMo-on-CoCrMo of total hip arthroplasty based on body mass index of implant user. Numerical estimation using 2D finite element model is presented for this purpose with varying loads based on various body mass index categories, consisting of underweight, normal, overweight, obese class I, obese class II, and obese class III. Gait loading under normal walking conditions is carried out per actual conditions of human hip joint. The result describes that von mises stress increased with a greater body mass index.

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FAIR Convergence Matrix:Optimizing the Reuse of Existing FAIR-Related Resources

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Data Intelligence 2020年第1期2卷 158-170,313页

作者： Hana Pergl Sustkova Kristina Maria Hettne Peter Wittenburg Annika Jacobsen Tobias Kuhn Robert Pergl Jan Slifka Peter McQuilton Barbara Magagna Susanna-Assunta Sansone Markus Stocker Melanie Imming Larry Lannom Mark Musen Erik Schultes GO FAIR International Support and Coordination Office LeidenThe Netherlands Centre for Digital Scholarship Leiden University LibrariesLeidenThe Netherlands Max Planck Computing and Data Facility Gießenbachstraße 285748 GarchingGermany Leiden University Medical Center Leiden2333 ZAThe Netherlands Department of Computer Science Vrije Universiteit AmsterdamDe Boelelaan 11051081 HV AmsterdamThe Netherlands Czech Technical University in Prague Faculty of Information Technology(FIT CTU)16000 Prague 6Czech Republic Oxford e-Research Centre Department of Engineering SciencesUniversity of OxfordOxford OX13PJUK Environment Agency Austria A-1090 ViennaAustria TIB Leibniz Information Centre for Science and Technology HannoverGermany SURF Utrecht 3511 EPThe Netherlands Corporation for National Research Initiatives(CNRI) RestonVirginia 20191USA Stanford Center for Biomedical Informatics Research StanfordCA 94305USA

The FAIR principles articulate the behaviors expected from digital artifacts that are Findable,Accessible,Interoperable and Reusable by machines and by *** by now widely accepted,the FAIR Principles by design do not explicitly consider actual implementation choices enabling FAIR *** different communities have their own,often well-established implementation preferences and priorities for data reuse,coordinating a broadly accepted,widely used FAIR implementation approach remains a global *** an effort to accelerate broad community convergence on FAIR implementation options,the GO FAIR community has launched the development of the FAIR Convergence *** Matrix is a platform that compiles for any community of practice,an inventory of their self-declared FAIR implementation choices and *** Convergence Matrix is itself a FAIR resource,openly available,and encourages voluntary participation by any self-identified community of practice(not only the GO FAIR Implementation Networks).Based on patterns of use and reuse of existing resources,the Convergence Matrix supports the transparent derivation of strategies that optimally coordinate convergence on standards and technologies in the emerging Internet of FAIR Data and Services.

关键词： FAIR Implementation Choices and Challenges Convergence FAIR Communities

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2D finite element deformation investigation on CoCrMo-on-CoCrMo bearing of total hip implant under normal walking condition

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AIP Conference Proceedings 2023年第1期2580卷

作者： Muhammad Imam Ammarullah Ilham Yustar Afif Mohamad Izzur Maula Tri Indah Winarni Mohammad Tauviqirrahman Athanasius Priharyoto Bayuseno Hasan Basri Ardiyansyah Syahrom Amir Putra Md Saad J. Jamari Department of Mechanical Engineering Faculty of Engineering Diponegoro University Tembalang 50275 Semarang Central Java Indonesia Department of Anatomy Faculty of Medicine Diponegoro University Tembalang 50275 Semarang Central Java Indonesia Center for Biomedical Research (CEBIOR) Faculty of Medicine Diponegoro University Tembalang 50275 Semarang Central Java Indonesia Department of Mechanical Engineering Facultyof Engineering Sriwijaya University Indralaya 30662 Ogan Ilir South Sumatera Indonesia Applied Mechanics and Design School of Mechanical Engineering Faculty of Mechanical Engineering Universiti Teknologi Malaysia Skudai 81310 Johor Bahru Malaysia Medical Device and Technology Center (MEDiTEC) Institute of Human-Centered and Engineering (IHumEn) Universiti Teknologi Malaysia Skudai 81310 Johor Bahru Malaysia

In daily human activity, normal walking becomes the most common performed activity. For this reason, many researchers have been adopted normal walking condition to giving actual loading on many hip implants studies. Our recent article intends to conducting deformation study in hip joint bearing during normal walking activity using numerical analysis. 2D model has been established to pursuing deformation analysis on CoCrMo-on-CoCrMo beraring under normal walking condition. Selected phase has been considered to represent whole of normal walking cycle as parameter input in loading. Deformation larger along acted loading with proportional correlation. Distribution of deformation also wider in case of larger deformation.

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Cancer nanotechnology: Enhancing tumor cell response to chemotherapy for hepatocellular carcinoma therapy

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Asian Journal of Pharmaceutical Sciences 2019年第6期14卷 581-594页

作者： Yongbing Sun Wen Ma Yuanyuan Yang Mengxue He Aimin Li Lei Bai Bin Yu Zhiqiang Yu National Engineering Research Center for solid preparation technology of Chinese Medicines Jiangxi University of Traditional Chinese MedicinesNanchang 330006China School of Pharmaceutical Sciences Southern Medical UniversityGuangzhou 510515China Integrated Hospital of Traditional Chinese Medicine Southern Medical UniversityGuangzhou 510315China Department of Chemical and Biomedical Engineering West Virginia UniversityMorgantown 26506USA School of Pharmaceutical Sciences Zhengzhou UniversityZhengzhou 450001China

Hepatocellular carcinoma(HCC)is one of the deadliest cancers due to its complexities,reoccurrence after surgical resection,metastasis and *** addition to sorafenib and lenvatinib for the treatment of HCC approved by FDA,various strategies including transarterial chemoembolization,radiotherapy,locoregional therapy and chemotherapy have been investigated in ***,cancer nanotechnology has got great attention for the treatment of various cancers including *** passive and active targetings are progressing at a steady ***,we describe the lessons learned from pathogenesis of HCC and the understanding of targeted and non-targeted nanoparticles used for the delivery of small molecules,monoclonal antibodies,miRNAs and *** current efficacy is to enhance tumor cell response of *** highlights the opportunities and challenges faced by nanotechnologies in contemporary hepatocellular carcinoma therapy,where personalized medicine is increasingly becoming the *** objective of this review is to enhance our understanding in the design and development of nanotechnology for treatment of HCC.

关键词： Hepatocellular carcinoma Cancer nanotechnology Cell response Chemotherapy

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Corrigendum to "Defect-engineered dual Z-scheme core-shell MoS2/WO3-x/AgBiS2 for antibiotic and dyes degradation in photo and night catalysis: Mechanism and pathways" [Environ. Pollut. 356 (2024) 124375]

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Environmental pollution (Barking, Essex : 1987) 2024年 357卷 124419页

作者： Muhammad Abbas Mubashar Ilyas Kashif Hussain Tariq Ali Muhammad Afzal Nazia Batool Navid Hussain Shah Muhammad Qasim Yaling Wang Yanyan Cui Beijing Engineering Research Center of Mixed Reality and Advanced Display School of Optics and Photonics Beijing Institute of Technology Beijing 100081 China. Key Laboratory of Clusters Science of Ministry of Education School of Chemistry Beijing Institute of Technology Beijing 100081 China. THz Technical Research Center Shenzhen Key Laboratory of Micro-Nano Photonic Information Technology Key Laboratory of Optoelectronic Devices and Systems College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen 518060 China. Department of Physics COMSATS University Islamabad Lahore Campus Lahore Pakistan. University of Agriculture Faisalabad Sub-campus Burewala Pakistan. School of Natural Science Department of Physics National University of Science and Technology (NUST) Islamabad Pakistan. CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety National Center for Nanoscience and Technology of China Beijing 100190 China. Beijing Engineering Research Center of Mixed Reality and Advanced Display School of Optics and Photonics Beijing Institute of Technology Beijing 100081 China. Electronic address: cuiyanyan@***.

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Bioelectronics for targeted pain management

Nature Reviews Electrical Engineering

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Nature Reviews Electrical engineering 2025年 1-18页

作者： Matthew T. Flavin Jose A. Foppiani Angelica H. Alvarez Lacey Foster Haobo Ma Samuel J. Lin Marek A. Paul Dominika Gavlasova John A. Rogers School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Division of Plastic and Reconstructive Surgery Beth Israel Deaconess Medical Center Harvard Medical School Boston MA USA Department of Anesthesiology and Pain Management Beth Israel Deaconess Medical Center Harvard Medical School Boston MA USA Plastic and Reconstructive Surgery Doc Paul Klinika Bytom Poland Jan Dlugosz University Czestochowa Poland Institute of Clinical and Experimental Medicine Prague Czech Republic Querrey-Simpson Institute for Bioelectronics Northwestern University Evanston IL USA Department of Mechanical Engineering Northwestern University Evanston IL USA Department of Biomedical Engineering Northwestern University Evanston IL USA Department of Materials Science and Engineering Northwestern University Evanston IL USA Department of Neurological Surgery Feinberg School of Medicine Northwestern University Chicago IL USA

Pain management in humans is an unresolved problem with substantial medical, societal and economic implications. Traditional strategies such as opioid-based medications are highly effective but pose many long-term risks, including addiction and overdose. In this Review, we discuss these persistent challenges in medical care along with advances in bioelectronics that enable safer and more effective alternative treatments. Emerging approaches leverage wireless embedded networks and machine learning to accurately detect and quantify the symptoms of pain, establishing a foundation for targeted, on-demand treatment. These platforms offer a powerful complement to wearable and implantable neural interfaces that can control these symptoms with unprecedented spatiotemporal and functional selectivity. Now, emotional and cognitive aspects of pain can be addressed through immersive multisensory engagement with systems for augmented and virtual reality. Trends in diagnostic and interventional technologies show how their integration is well suited to addressing some of the most intractable problems in pain management.

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Multipole engineering by displacement resonance: a new degree of freedom of Mie resonance

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Nature Communications 2023年第1期14卷 7213页

作者： Tang, Yu-Lung Yen, Te-Hsin Nishida, Kentaro Li, Chien-Hsuan Chen, Yu-Chieh Zhang, Tianyue Pai, Chi-Kang Chen, Kuo-Ping Li, Xiangping Takahara, Junichi Chu, Shi-Wei Department of Physics National Taiwan University 1 Sec 4 Roosevelt Rd. Taipei 10617 Taiwan Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications Institute of Photonics Technology Jinan University Guangzhou 510632 China Institute of Imaging and Biomedical Photonics National Yang Ming Chiao Tung University 301 Gaofa 3rd Road Tainan 711 Taiwan Institute of Photonics Technologies National Tsing Hua University 301 Gaofa 3rd Road Hsinchu Taiwan Graduate School of Engineering Osaka University 2-1 Yamadaoka Suita Osaka 565-0871 Japan Photonics Center Graduate School of Engineering Osaka University 2-1 Yamadaoka Suita Osaka 565-0871 Japan Molecular Imaging Center National Taiwan University 1 Sec 4 Roosevelt Rd. Taipei 10617 Taiwan Brain Research Center National Tsing Hua University 101 Sec 2 Guangfu Road Hsinchu 30013 Taiwan

The canonical studies on Mie scattering unravel strong electric/magnetic optical responses in nanostructures, laying foundation for emerging meta-photonic applications. Conventionally, the morphology-sensitive resonances hinge on the normalized frequency, i.e. particle size over wavelength, but non-paraxial incidence symmetry is overlooked. Here, through confocal reflection microscopy with a tight focus scanning over silicon nanostructures, the scattering point spread functions unveil distinctive spatial patterns featuring that linear scattering efficiency is maximal when the focus is misaligned. The underlying physical mechanism is the excitation of higher-order multipolar modes, not accessible by plane wave irradiation, via displacement resonance, which showcases a significant reduction of nonlinear response threshold, sign flip in all-optical switching, and spatial resolution enhancement. Our result fundamentally extends the century-old light scattering theory, and suggests new dimensions to tailor Mie resonances. © 2023, The Author(s).

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Bistable scattering of nano-silicon for super-linear super-resolution imaging

arXiv

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arXiv 2023年

作者： Tseng, Po-Hsueh Nishida, Kentaro Wu, Pang-Han Tang, Yu-Lung Chen, Yu-Chieh Yang, Chi-Yin Yang, Jhen-Hong Chen, Wei-Ruei Pashina, Olesiya Petrov, Mihail Chen, Kuo-Ping Chu, Shi-Wei Graduate Institute of Applied Physics National Taiwan University 1 Sec 4 Roosevelt Rd. Taipei10617 Taiwan Department of Physics National Taiwan University 1 Sec 4 Roosevelt Rd. Taipei10617 Taiwan Institute of Imaging and Biomedical Photonics National Yang Ming Chiao Tung University 301 Gaofa 3rd Road Tainan711 Taiwan Institute of Photonic System National Yang Ming Chiao Tung University 301 Gaofa 3rd Road Tainan711 Taiwan Physics and Engineering Department ITMO University St. Petersburg197101 Russia Institute of Photonics Technology National Tsing Hua University 101 Section 2 Kuang-Fu Road Hsinchu30013 Taiwan Molecular Imaging Center National Taiwan University 1 Sec 4 Roosevelt Rd. Taipei10617 Taiwan Brain Research Center National Tsing Hua University 101 Sec 2 Guangfu Road Hsinchu30013 Taiwan

Optical bistability is fundamental for all-optical switches, but typically requires high-Q cavities with micrometer sizes. Through boosting nonlinearity with photo-thermo-optical effects, we achieve bistability in a s... 详细信息

关键词： Q factor measurement

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Roadmap for Animate Matter

arXiv

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arXiv 2024年

作者： Volpe, Giorgio Araújo, Nuno A.M. Guix, Maria Miodownik, Mark Martin, Nicolas Alvarez, Laura Simmchen, Juliane Leonardo, Roberto Di Pellicciotta, Nicola Martinet, Quentin Palacci, Jérémie Ng, Wai Kit Saxena, Dhruv Sapienza, Riccardo Nadine, Sara Mano, João F. Mahdavi, Reza Adiels, Caroline Beck Forth, Joe Santangelo, Christian Palagi, Stefano Seok, Ji Min Webster-Wood, Victoria A. Wang, Shuhong Yao, Lining Aghakhani, Amirreza Barois, Thomas Kellay, Hamid Coulais, Corentin van Hecke, Martin Pierce, Christopher J. Wang, Tianyu Chong, Baxi Goldman, Daniel I. Reina, Andreagiovanni Trianni, Vito Volpe, Giovanni Beckett, Richard Nair, Sean P. Armstrong, Rachel Department of Chemistry University College London 20 Gordon Street LondonWC1H 0AJ United Kingdom Departamento de Física Faculdade de Ciências Universidade de Lisboa Lisboa1749-016 Portugal Centro de Física Teórica e Computacional Faculdade de Ciências Universidade de Lisboa Lisboa1749-016 Portugal Department of Materials Science and Physical Chemistry Institute of Theoretical and Computational Chemistry University of Barcelona Barcelona Catalonia08028 Spain Department of Mechanical Engineering University College London London United Kingdom University of Bordeaux CNRS Centre de Recherche Paul Pascal UMR 5031 115 Avenue du Dr. Albert Schweitzer Pessac33600 France Pure and Applied Chemistry University of Strathclyde United Kingdom Department of Physics "Sapienza" University of Rome Rome00185 Italy NANOTEC-CNR Institute of Nanotechnology Soft and Living Matter Laboratory Rome00185 Italy Klosterneuburg Austria Blackett Laboratory Department of Physics Imperial College London London United Kingdom CICECO - Aveiro Institute of Materials Department of Chemistry University of Aveiro Campus Universitário de Santiago Aveiro3810-193 Portugal Department of Physics University of Gothenburg GothenburgSE-41296 Sweden Department of Physics University of Liverpool Crown Street LiverpoolL69 7ZD United Kingdom Department of Chemistry University of Liverpool Oxford Street LiverpoolL69 7ZE United Kingdom Physics Department Syracuse University SyracuseNY13244 United States The BioRobotics Institute Department of Excellence in Robotics & AI Sant'Anna School of Advanced Studies Tuscany Pisa56025 Italy Department of Mechanical Engineering Carnegie Mellon University United States Department of Mechanical Engineering Department of Biomedical Engineering The Robotics Institute Carnegie Mellon University United States Morphing Matter Lab Mechanical Engineering UC Berkeley United States Zhejiang University China Institute of Biomaterials and Biomolecular

Humanity has long sought inspiration from nature to innovate materials and devices. As science advances, nature-inspired materials are becoming part of our lives. Animate materials, characterized by their activity, adaptability, and autonomy, emulate properties of living systems. While only biological materials fully embody these principles, artificial versions are advancing rapidly, promising transformative impacts across various sectors. This roadmap presents authoritative perspectives on animate materials across different disciplines and scales, highlighting their interdisciplinary nature and potential applications in diverse fields including nanotechnology, robotics and the built environment. It underscores the need for concerted efforts to address shared challenges such as complexity management, scalability, evolvability, interdisciplinary collaboration, and ethical and environmental considerations. The framework defined by classifying materials based on their level of animacy can guide this emerging field encouraging cooperation and responsible development. By unravelling the mysteries of living matter and leveraging its principles, we can design materials and systems that will transform our world in a more sustainable manner. Copyright © 2024, The Authors. All rights reserved.

关键词： Biotic

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Transfer learning with deep Convolutional Neural Network (CNN) for pneumonia detection using chest X-ray

arXiv

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arXiv 2020年

作者： Rahman, Tawsifur Chowdhury, Muhammad E.H. Khandakar, Amith Islam, Khandaker R. Islam, Khandaker F. Mahbub, Zaid B. Kadir, Muhammad A. Kashem, Saad Department of Biomedical Physics & Technology University of Dhaka Dhaka1000 Bangladesh Department of Electrical Engineering Qatar University Doha2713 Qatar Department of Orthodentics Bangabandhu Sheikh Mujib Medical University Dhaka1000 Bangladesh Department of Mathematics and Physics North South University Dhaka1229 Bangladesh Faculty of Robotics and Advanced Computing Qatar Armed Forces-Academic Bridge Program Qatar Foundation Doha24404 Qatar

Pneumonia is a life threatening disease, which occurs in the lungs caused by either bacterial or viral infection. It can be life endangering if not acted upon in the right time and thus early diagnosis of pneumonia is vital. The aim of this paper is to automatically detect bacterial and viral pneumonia using the digital x-ray images. It provides a detailed report on advances made in making accurate detection of pneumonia and then presents the methodology adopted by the authors. Four different pre-trained deep Convolutional Neural Network (CNN): AlexNet, ResNet18, DenseNet201 and SqueezeNet were used for transfer learning. 5247 chest x-ray images consisting of bacterial, viral and normal chest x-rays were used and through preprocessing techniques, the modified images were trained for the transfer learning based classification task. In this work, the authors have reported three schemes of classifications: normal vs pneumonia, bacterial vs viral pneumonia and normal, bacterial and viral pneumonia. The classification accuracy of normal and pneumonia images, bacterial and viral pneumonia images, and normal, bacterial and viral pneumonia were 98%, 95% and 93.3% respectively. This is the highest accuracy in any scheme than the accuracies reported in the literature. Therefore, the proposed study can be useful in faster diagnosing pneumonia by the radiologist and can help in the fast airports screening of the pneumonia patients. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

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