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arXiv 2023年

作者： Luo, Renjie Legvold, Tanner J. Chen, Liyang Navarro, Henry Basaran, Ali C. Hong, Deshun Liu, Changjiang Bhattacharya, Anand Schuller, Ivan K. Natelson, Douglas Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Graduate Program Rice Quantum Institute Rice University HoustonTX77005 United States Department of Physics Center for Advanced Nanoscience University of California La Jolla San DiegoCA92093 United States Materials Science Division Argonne National Laboratory LemontIL60439 United States Department of Electrical and Computer Engineering Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

The spin Seebeck effect (SSE) is sensitive to thermally driven magnetic excitations in magnetic insulators. Vanadium dioxide in its insulating low temperature phase is expected to lack magnetic degrees of freedom, as vanadium atoms are thought to form singlets upon dimerization of the vanadium chains. Instead, we find a paramagnetic SSE response in VO2 films that grows as the temperature decreases below 50 K. The field and temperature dependent SSE voltage is qualitatively consistent with a general model of paramagnetic SSE response and inconsistent with triplet spin transport. Quantitative estimates find a spin Seebeck coefficient comparable in magnitude to that observed in strongly magnetic materials. The microscopic nature of the magnetic excitations in VO2 requires further examination. Copyright © 2023, The Authors. All rights reserved.

关键词： Paramagnetism

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A Platform for Monitoring Student Commuting in the Use of School Transport in Smart Cities - A Facial Recognition Based Approach

A Platform for Monitoring Student Commuting in the Use of Sc...

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International Conference on Smart Communications and Networking (SmartNets)

作者： Jessé Da Costa Rocha Marcela Alves de Souza Evelin Helena Silva Cardoso Nandamudi Vijaykumar Jasmine Priscyla Leite de Araújo Renato Lisboa Francês Graduate Program in Electrical Engineering Institute of Technology Federal University of Pará (UFPA) Belém Pará Brazil Information and Communication Technology Center Federal University of the South and Southeast of Para (Unifesspa) Marabá Pará Brazil Department of Computer Science Federal Rural University of the Amazon (UFRA) Capitão Poço Pará Brazil Coordination of Applied Research and Technological Development National Institute for Space Research (INPE) São Paulo Brazil

This article proposes an intelligent platform for monitoring students' steps on their way to school until they leave the school to their homes. This platform can identify students and notify those responsible and competent authorities in various situations of school life, such as: entering and leaving the school bus, entering and leaving school, entering the school cafeteria, etc. The first application aims to control access to the school bus through facial recognition. In the tests carried out, the recognition system achieved excellent results in all metrics.

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Miniaturized Microarray-Format Digital ELISA Enabled by Lithographic Protein Patterning

SSRN

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SSRN 2023年

作者： Stephens, Andrew D. Song, Yujing McClellan, Brandon L. Su, Shiuan-Haur Xu, Sonnet Chen, Kevin Castro, Maria G. Singer, Benjamin H. Kurabayashi, Katsuo Department of Mechanical Engineering University of Michigan Ann ArborMI48109 United States Department of Neurosurgery University of Michigan Medical School Ann ArborMI48109 United States Department of Cell and Developmental Biology University of Michigan Medical School Ann ArborMI48109 United States Graduate Program in Immunology University of Michigan Medical School Ann ArborMI48109 United States Department of Biomedical Engineering University of Michigan Ann ArborMI48109 United States Rogel Cancer Center University of Michigan Ann ArborMI48109 United States Department of Internal Medicine Division of Pulmonary and Critical Care Medicine University of Michigan Ann ArborMI48109 United States Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States Weil Institute for Critical Care Research and Innovation University of Michigan Ann ArborMI48109 United States

The search for reliable protein biomarker candidates is critical for early disease detection and treatment. However, current immunoassay technologies are failing to meet increasing demands for sensitivity and multiplexing. Here, the authors have created a highly sensitive protein microarray using the principle of single-molecule counting for signal amplification, capable of simultaneously detecting a panel of cancer biomarkers at sub-pg/mL levels. To enable this amplification strategy, the authors introduce a novel method of protein patterning using photolithography to subdivide addressable arrays of capture antibody spots into hundreds of thousands of individual microwells. This allows for the total sensor area to be miniaturized, increasing the total possible multiplex capacity. With the immunoassay realized on a standard 75x25 mm form factor glass substrate, sample volume consumption is minimized to © 2023, The Authors. All rights reserved.

关键词： Biomarkers

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A Framework for Interpretability in Machine Learning for Medical Imaging

arXiv

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arXiv 2023年

作者： Wang, Alan Q. Karaman, Batuhan K. Kim, Heejong Rosenthal, Jacob Saluja, Rachit Young, Sean I. Sabuncu, Mert R. School of Electrical and Computer Engineering Cornell University Cornell Tech New YorkNY10044 United States Department of Radiology Weill Cornell Medical School New YorkNY10065 United States Weill Cornell/Rockefeller/Sloan Kettering Tri-Institutional MD-PhD Program New YorkNY10065 United States Martinos Center for Biomedical Imaging Harvard Medical School BostonMA02129 United States Computer Science and Artificial Intelligence Laboratory MIT CambridgeMA02139 United States

Interpretability for machine learning models in medical imaging (MLMI) is an important direction of research. However, there is a general sense of murkiness in what interpretability means. Why does the need for interpretability in MLMI arise? What goals does one actually seek to address when interpretability is needed? To answer these questions, we identify a need to formalize the goals and elements of interpretability in MLMI. By reasoning about real-world tasks and goals common in both medical image analysis and its intersection with machine learning, we identify five core elements of interpretability: localization, visual recognizability, physical attribution, model transparency, and actionability. From this, we arrive at a framework for interpretability in MLMI, which serves as a step-by-step guide to approaching interpretability in this context. Overall, this paper formalizes interpretability needs in the context of medical imaging, and our applied perspective clarifies concrete MLMI-specific goals and considerations in order to guide method design and improve real-world usage. Our goal is to provide practical and didactic information for model designers and practitioners, inspire developers of models in the medical imaging field to reason more deeply about what interpretability is achieving, and suggest future directions of interpretability research. © 2023, CC0.

关键词： Machine learning

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Effect of alginate and chitosan addition in the fabrication of polyvinyl alcohol-based matrix for tissue engineering applications

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AIP Conference Proceedings 2024年第1期3215卷

作者： Retno Wahyu Nurhayati Fatimah Azzahra Nuzli Fahdia Mazfufah Siti Fauziyah Rahman Wildan Mubarok Department of Chemical Engineering Faculty of Engineering Universitas Indonesia 16464 Depok Indonesia Research Center for Biomedical Engineering Faculty of Engineering Universitas Indonesia 16464 Depok Indonesia Stem Cells & Tissue Engineering Cluster Indonesian Medical Education and Research Institute Faculty of Medicine Universitas Indonesia Jakarta 10430 Indonesia Doctoral Program in Biomedical Sciences Faculty of Medicine Universitas Indonesia Jakarta 10430 Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Indonesia 16464 Depok Indonesia Division of Chemical Engineering Department of Materials Engineering Science Graduate School of Engineering Science Osaka University 560-0031 Toyonaka Japan

Recently, there has been a growing interest in artificial skin on hydrogels as a potential alternative for animal testing to evaluate the efficacy and safety of new drugs or cosmetics. Synthetic polymers have been widely used due to their superior physicochemical properties. However, synthetic polymers such as polyvinyl alcohol (PVA) are limited by their poor biocompatibility and cell adhesion. Combining synthetic and natural polymers can improve these properties. Therefore, in this study, we aimed to investigate the effect of alginate and chitosan addition to PVA-based hydrogels on protein adsorption, cell viability and cell attachment. The addition of chitosan decreased protein adsorption, which was caused by the changes in electrostatic charge by PVA-chitosan interaction and changes in surface roughness. Primary human fibroblast cells cultured on PVA, PVA-alginate and PVA-chitosan had >80% viability which indicates the cytocompatibility of the hydrogels. More importantly, alginate and chitosan also improved the cell attachment on the PVA-based hydrogels. Taken together, the addition of both alginate and chitosan has the potential to improve PVA-based hydrogels for artificial skin application.

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A review of fluid-structure interaction: blood flow in arteries

Biomedical Engineering Advances

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biomedical engineering Advances 2025年 9卷

作者： Zubeir Allum Saib Farid Abed Mergen H. Ghayesh Marco Amabili Biomedical Engineering Graduate Program American University of Sharjah Sharjah United Arab Emirates Department of Bioengineering New York University Abu Dhabi Abu Dhabi United Arab Emirates Department of Civil Engineering American University of Sharjah Sharjah United Arab Emirates School of Electrical and Mechanical Engineering University of Adelaide South Australia Australia School of Engineering Westlake University Hangzhou Zhejiang province China

Over the past decade, Fluid-Structure Interaction studies related to blood vessels have been an active area of research, as they adequately capture the multiphysics of blood flow within the circulatory system. Despite the growing interest, only few state-of-the-art reviews have been published in the literature, each focusing individually on the coronary artery, carotid artery, aorta, heart valves and peripheral arteries. This systematic review assesses the current research and implications of Fluid-Structure Interaction implementation strategies in relation to human arteries. It is meant to comprehensively amalgamate research studies on an array of arteries coupled with cardiovascular complications such as atherosclerosis, plaque calcification, aneurysms, aortic dissections and valve dysfunction. It additionally covers computational finite element and finite volume solver demands, coupling schemes, inlet and outlet boundary conditions specifications, Newtonian and non-Newtonian blood rheological properties, laminar and turbulent flow types, as well as the modelling of the vessel wall’s hyperelastic and viscoelastic mechanical behavior. The research information is retrieved from the last ten years and summarized in a tabulated format, to help researchers in easily extracting useful information for future investigations and reviews.

关键词： Fluid-structure interaction Computational fluid dynamics Finite element analysis Blood flow Hemodynamics Biomechanics Atherosclerosis Aneurysm Calcification Artery Plaque Valve

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Structural and performance comparison between SU-8 microfabricated and 3D-printed microneedle electrodes

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Journal of 3D Printing in Medicine 2020年第1期4卷 29-44页

作者： Soltanzadeh, Ramin Afsharipour, Elnaz Anssari, Neda Mansouri, Behzad Shafai, Cyrus Biomedical Graduate Studies Program University of Manitoba Winnipeg R3T 5V6 MB Canada Electrical and Computer Engineering Department University of Manitoba Winnipeg R3T 5V6 MB Canada Department of Internal Medicine (Neurology) University of Manitoba Winnipeg R3A 1R9 MB Canada

Aim: This study is aimed to compare the structure and performance of 3D-printed and microfabricated microneedle arrays (MNAs). Materials & methods: MNAs were produced using either stereolithography printing or were micro-fabricated using SU-8 polymer. The structure of both MNA types were tested and compared through scanning electron microscopy. MNA performance was also evaluated through electrical impedence spectroscopy and nerve conduction velocity testing. Results & conclusion: The 3D-printed MNAs were shown to have higher gain than microfabricated MNAs at high frequencies. However, the selectivity of the microfabricated MNAs is more than 3D-printed MNAs. Scanning electron microscopy image comparison also showed significant differences between the output of the 3D-printed MNAs and the microfabricated MNAs. It was understood that the microfabricated MNAs' geometries are closer to the primary design than the 3D-printed MNAs. © 2020 Future Medicine Ltd.

关键词： 3D printing microfabrication microneedle array performance difference strucutral difference

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Graph Laplacian Learning with Exponential Family Noise

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IEEE Transactions on Signal and Information Processing over Networks 2025年

作者： Shi, Changhao Mishne, Gal UC San Diego Electrical and Computer Engineering Department CA92093 United States UC San Diego Hal.c.o.glu Data Science Institute and the Neurosciences Graduate Program CA92093 United States

Graph signal processing (GSP) is a prominent framework for analyzing signals on non-Euclidean domains. The graph Fourier transform (GFT) uses the combinatorial graph Laplacian matrix to reveal the spectral decomposition of signals in the graph frequency domain. However, a common challenge in applying GSP methods is that in many scenarios the underlying graph of a system is unknown. A solution in such cases is to construct the unobserved graph from available data, which is commonly referred to as graph or network inference. Although different graph inference methods exist, they are restricted to learning from either smooth graph signals or simple additive Gaussian noise. Other types of noisy data, such as discrete counts or binary digits, are rather common in real-world applications, yet are underexplored in graph inference. In this paper, we propose a versatile graph inference framework for learning from graph signals corrupted by exponential family noise. Our framework generalizes previous methods from continuous smooth graph signals to various data types. We propose an alternating algorithm that jointly estimates the graph Laplacian and the unobserved smooth representation from the noisy signals. We also extend our approach to include an offset variable which models different levels of variation of the nodes. Since real-world graph signals are frequently non-independent and temporally correlated, we further adapt our original setting to a timevertex formulation. We demonstrate on synthetic and real-world data that our new algorithms outperform competing Laplacian estimation methods that suffer from noise model mismatch. © 2025 IEEE.

关键词： Laplace transforms

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Functional neuroplasticity of facilitation and interference effects on inhibitory control following 3-month physical exercise in aging

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Scientific Reports 2024年第1期14卷 1-13页

作者： Wu, Hong-Yi Huang, Chih-Mao Hsu, Ai-Ling Chen, Chiao-Nan Wu, Changwei W. Chen, Jyh-Horng Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Bachelor Program in Artificial Intelligence Chang Gung University Taoyuan Taiwan Department of Psychiatry Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan Department of Physical Therapy and Assistive Technology National Yang Ming Chiao Tung University Taipei Taiwan Graduate Institute of Mind Brain and Consciousness Taipei Medical University New Taipei Taiwan Research Center of Sleep Medicine Taipei Medical University Hospital Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan

Preservation of executive function, like inhibition, closely links to the quality of life in senior adults. Although neuroimaging literature has shown enhanced inhibitory function followed by aerobic exercise, current evidence implies inconsistent neuroplasticity patterns along different time durations of exercise. Hence, we conducted a 12-week exercise intervention on 12 young and 14 senior volunteers and repeatedly measured the inhibitory functionality of distinct aspects (facilitation and interference effects) using the numerical Stroop task and functional Magnetic Resonance Imaging. Results showcased improved accuracy and reduced reaction times (RT) after 12-week exercise, attributed to frontoparietal and default mode network effects. In young adults, the first phase (0 to six weeks) exercise increased the activation of the right superior medial frontal gyrus, associated with reduced RT in interference, but in the second intervention phase (six to twelve weeks), the decreased activation of the left superior medial frontal gyrus positively correlated with reduced RT in facilitation. In senior adults, the first six-week intervention led to reduced activations of the inferior frontal gyrus, inferior parietal gyrus, and default mode network regions, associated with the reduced RT in interference. Still, in the second intervention phase, only the visual area exhibited increased activity, associated with reduced RT in interference. Except for the distinctive brain plasticity between the two phases of exercise intervention, the between-group comparison also presented that the old group gained more cognitive benefits within the first six weeks of exercise intervention;however, the cognitive improvements in the young group occurred after six weeks of intervention. Limited by the sample size, these preliminary findings corroborated the benefits of aerobic exercise on the inhibitory functions, implying an age × exercise interaction on the brain plasticity for both facilita

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Spin Seebeck effect at low temperatures in the nominally paramagnetic insulating state of vanadium dioxide

arXiv

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arXiv 2022年

作者： Luo, Renjie Zhao, Xuanhan Chen, Liyang Legvold, Tanner J. Navarro, Henry Schuller, Ivan K. Natelson, Douglas Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Graduate Program Rice University HoustonTX77005 United States Department of Physics Center for Advanced Nanoscience University of California-San Diego La Jolla CA92093 United States Department of Electrical and Computer Engineering Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States

The low temperature monoclinic, insulating phase of vanadium dioxide is ordinarily considered nonmagnetic, with dimerized vanadium atoms forming spin singlets, though paramagnetic response is seen at low temperatures. We find a nonlocal spin Seebeck signal in VO2 films that appears below 30 K and which increases with decreasing temperature. The spin Seebeck response has a non-hysteretic dependence on in-plane external magnetic field. This paramagnetic spin Seebeck response is discussed in terms of prior findings on paramagnetic spin Seebeck effects and expected magnetic excitations of the monoclinic ground state. Copyright © 2022, The Authors. All rights reserved.

关键词： Vanadium dioxide

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