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14th International Conference on Technology of Plasticity, ICTP 2023

作者： Ren, Mengyuan Xie, Haibo Lin, Fei Jia, Fanghui Huo, Mingshuai Wu, Hui Yuan, Shengnan Yang, Ming Manabe, Ken-ichi Jiang, Zhengyi School of Mechanical Materials Mechatronic and Biomedical Engineering University of Wollongong WollongongNSW2522 Australia Graduate School of System Design Tokyo Metropolitan University Tokyo Hino-Shi191-0065 Japan Department of Mechanical Engineering Tokyo Metropolitan University Tokyo Hachioji192-0397 Japan

ISBN: (纸本)9783031409196

Microchannels on metallic substrates are essential parts of microreactors, micro heat exchangers, micro heat sinks, and fuel cell bipolar plates. Because of superior properties, such as good corrosion resistance, excellent thermal conductivity, high strength, excellent ductility and structural stability, composite metal foils are gaining popularity as substrates for microchannels. With the increasing demands of low cost, high efficiency and accuracy, novel micro forming technologies must be capable of creating intricate and precise micro features of microchannels at a low cost. An ultra-thin metal foil rolling for the fabrication of micro composite channels is proposed in this study, which can improve product function and reduce operational costs. Copper/ stainless steel 304L (SS304L) composite foils with a thickness of 0.41 mm after annealing treatment at 800 ℃ and holding for 0.5 h, 1.0 h and 2.0 h are used to fabricate microchannels under the rolling reduction of 60.9%. The hardness of composite foils has been characterised before and after different annealing processes, in which the hardness decreases due to the synergistic effects of decreased dislocation density, grain coarsening and phase transformation. Further, the formability of composite foils after annealing is discussed. In addition, the processing characteristics, material deformation behaviours and mechanisms during micro rolling are also investigated. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fabrication

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Digitally-defined ultrathin transparent wireless sensor network for room-scale imperceptible ambient intelligence

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npj Flexible Electronics 2024年第1期8卷 869-878页

作者： Yunxia Jin Mengxia Yu Dat T.Nguyen Xin Yang Zhipeng Li Ze Xiong Chenhui Li Yuxin Liu Yong Lin Kong John S.Ho Institute for Health Innovation and Technology National University of SingaporeSingapore 117599Singapore Department of Biomedical Engineering National University of SingaporeSingapore 119276Singapore Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Integrative Sciences and Engineering Programme National University of Singapore Graduate SchoolSingapore 119077Singapore The N.1 Institute for Health National University of SingaporeSingapore 117456Singapore Institute of Materials Research and Engineering Agency for Science Technology and ResearchSingapore 138634Singapore Department of Mechanical Engineering University of UtahSalt Lake CityUT 84112USA

Wireless and battery-free radio-frequency(RF)sensors can be used to create physical spaces that ambiently sense and respond to human *** such sensors ultra-flexible and transparent is important to preserve the aesthetics of living environments,accommodate daily activities,and functionally integrate with ***,existing RF sensors are unable to simultaneously achieve high transparency,flexibility,and the electrical conductivity required for remote room-scale ***,we report 4.5μm RF tag sensors achieving transparency exceeding 90%that provide capabilities in room-scale ambient wireless *** develop a laser-assisted water-based adhesion-reversion process to digitally realize computer-aided RF design at *** individually tagging multiple objects and regions of the human body,we demonstrate multiplexed wireless tracking of humanenvironment interactions and physiological signals at a range of up to *** radio-frequency identification sensors open opportunities for non-intrusive wireless sensing of daily living spaces for applications in health monitoring and elderly care.

关键词： network ambient transparent

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Analysis of the Migration of Neutrophil-Like Cells under a pH Gradient using a Microfluidic Device 16

Analysis of the Migration of Neutrophil-Like Cells under a p...

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16th IEEE International Conference on Nano/Molecular Medicine and engineering, NANOMED 2023

作者： Tomita, Masashi Hirose, Satomi Funamoto, Kenichi Tohoku University Graduate School of Biomedical Engineering Sendai Japan Massachusetts Institute of Technology Department of Mechanical Engineering CambridgeMA United States Tohoku University Institute of Fluid Science Sendai Japan

ISBN: (纸本)9798350343700

Neutrophils are known to accumulate in an acidified inflammatory microenvironment, but the effects of environmental factors on neutrophils are not fully understood. Here, we investigated the response of neutrophil-like differentiated human promyelocytic leukemia cells (HL-60) to pH changes. A previously developed microfluidic device that enables control of the oxygen concentration was used to control the pH in a microenvironment. The CO2 concentration in the cell culture medium was controlled by gas exchange between the media and gas channels, thereby establishing certain pH gradients based on chemical equilibrium. The device enabled the generation of a pH 8.5 to 7.1 gradient when gas mixtures of 1% and 50% CO2 were supplied to the left and right gas channels, respectively. Neutrophil-like differentiated HL-60 cells were then seeded into the media channels to observe their cellular dynamics under the pH gradient. Quantitative evaluation showed that cell migration was suppressed in the low-pH (high CO2 concentration) region compared to the high-pH (low CO2 concentration) region, whereas no clear chemotactic migration in response to pH was observed. © 2023 IEEE.

关键词： Carbon dioxide

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How Fast Can a Robotic Drummer Beat Using Dielectric Elastomer Actuators?

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IEEE Robotics and Automation Letters 2024年第3期9卷 2638-2645页

作者： Wakle, Sudhir Lin, Tse-Han Huang, Shu Basu, Sumit Lau, Gih-Keong National Yang Ming Chiao Tung University International College of Semiconductor Technology Hsinchu30010 Taiwan Indian Institute of Technology Kanpur Mechanical Engineering Department Kanpur208016 India National Yang Ming Chiao Tung University Department of Graduate Degree Program of Robotics Hsinchu30010 Taiwan Industrial Technology Research Institute Mechanical and Mechatronics System Research Labs Zhudong 31057 Taiwan National Yang Ming Chiao Tung University Department of Mechanical Engineering International College of Semiconductor Technology Hsinchu30010 Taiwan

Fast drumming presents a speed challenge to many robotic arms. To simultaneously meet the needs for speed, stroke, and force, we proposed and tested a new double-saddle dielectric elastomer actuator (DEA) as the artificial biceps for driving a lightweight robotic drummer. This work finds that fast force induction is instrumental to the fast drumming by a DEA-driven drumstick. While a pure-shear series of DEA under a large pre-stretch and lateral reinforcement can generate a large isotonic stroke, it is not fast in isometric force induction. Instead, this work found a double-saddle DEA, which is a degenerated two-segment pure-shear DEA with a middle laterally buckled beam, managed to induce a faster isometric force at a 0.5 s down time constant when its ultimate actuation tapered due to substantial strain stiffening effect. As such, this double-saddle DEA-driven drummer suffered less from the dynamic stroke decrement than the 8-segment DEA did. A 4.4 g DEA managed to swing freely a 7.8 g drumstick up to nearly 60° at 6 kV and a maximum tip speed of up to 0.45 m/s. The drumming frequency upon 5.5 kV activation was up to 2-2.5 Hz. In comparison, an 8-segment pure-shear DEA-driven drummer failed to reach the drum when pulsed at 2 Hz. Interestingly, a slower stroke excited multiple drumbeats due to secondary bounces. To achieve a faster drumming to match a human drummer, it is foreseen that a harder dielectric elastomer material will help drive a faster soft robot. © 2016 IEEE.

关键词： Dielectric materials

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Coevolution of Myoelectric Hand Control under the Tactile Interaction among Fingers and Objects

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Cyborg and Bionic Systems 2022年第1期2022卷 285-302页

作者： Yuki Kuroda Yusuke Yamanoi Shunta Togo Yinlai Jiang Hiroshi Yokoi Joint Doctoral Program for Sustainability Research Graduate School of Informatics and Engineering The University of Electro-CommunicationsTokyoJapan Department of Mechan ical and Intelligent System Engineering Graduate School of Informatics and Engineering The University of Electro Communications TokyoJapan Center for Neuroscience and Biomedical Engineering The University of Electro Communications TokyoJapan Bejing Innovation Center for Inelligent Robots and Systems BeijingChina

The usability of a prosthetic hand difers significantly from that of a real ***,the complexity of manipulation increases as the number of degrees of freedom to be controlled increases,making manipulation with biological signals extremely *** overcome this problem,users need to select a grasping posture that is adaptive to the object and a stable grasping method that prevents the object from *** previous studies,these have been left to the operating skills of the user,which is extremely difficult to *** this study,we demonstrate how stable and adaptive grasping can be achieved according to the object regardless of the user's operation *** required grasping technique is achieved by determining the correlation bet ween the motor output and each sensor through the interaction between the prosthetic hand and the surrounding stimuli,such as myoelectricity,sense of touch,and grasping *** agents of the 16 DOF robot hand were trained with the myoelectric signals of six participants,including one child with a congenital forearm ***,each agent could open and close the hand in response to the myoeletric stimuli and could accomplish the object pickup *** the tasks,the agents successfully identified grasping patterns suitable for practical and stable positioning of the *** addition,the agents were able to pick up the object in a similar posture regardless of the partiipant,suggesting that the hand was optimized by evolutionary computation to a posture that prevents the object from being dropped.

关键词： robot Objects overcome

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A Physical-Based Artificial Neural Networks Compact Modeling Framework for Emerging FETs

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IEEE Transactions on Electron Devices 2024年第1期71卷 223-230页

作者： Yang, Ya-Shu Li, Yiming Kola, Sekhar Reddy Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory The Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan

We report a compact modeling framework based on the Grove-Frohman (GF) model and artificial neural networks (ANNs) for emerging gate-all-around (GAA) MOSFETs. The framework consists of two ANNs;the first ANN constructed with the drain current model not only can capture the main trend of device I - V characteristics but also can predict its variation even when the amount of training data for the ANN is insufficient or outside the range of applied biases. The second one is then designed to improve the model accuracy by further minimizing the errors between the target and the model outputs. We implement the proposed framework to accurately model emerging GAA nanosheet (NS) MOSFETs and complementary FETs (CFETs) without suffering from divergent issues in circuit simulation. In addition, nonphysical behaviors, such as nonzero current at zero bias, do not occur in the modeling framework. Compared to recently reported machine-learning (ML) models, our approach can achieve a similar level of model accuracy with merely 20% amount of the training data. © 1963-2012 IEEE.

关键词： Neural networks

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A biogenesis construction of CuO@MWCNT via Chenopodium album extract: an effective electrocatalyst for synaptic plasticity neurodegenerative drug pollutant detection

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Environmental Science and Pollution Research 2023年第33期30卷 79744-79757页

作者： Pandiyarajan, Sabarison Velayutham, Gurunathan Liao, Ai-Ho Manickaraj, Shobana Sebastin Mary Ramachandran, Balaji Lee, Kuo-Yu Chuang, Ho-Chiao Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei Taiwan Department of Mechanical Engineering National Taipei University of Technology Taipei Taiwan PG & Research Department of Chemistry Bishop Heber College Tamil Nadu Tiruchirappalli India Graduate Institute of Biomedical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan SV Probe Technology Taiwan Co. Ltd Taipei10453 Taiwan

Clioquinol (CLQ) is one of the most toxic halogenated neurodegenerative drugs, and its synaptic plasticity effect directly affects human health and the environment. Cupric oxide (CuO) is an ideal electrocatalyst owing to its earth-abundance, non-toxic nature, and cost-effectiveness. Since phenolate oxygen and pyridine nitrogen in CLQ act as an electron donor and pave the way for detection with Cu2+ ions in the CuO. Designing the architecture of CuO with a multi-walled carbon nanotube (MWCNT) is a sensible strategy to improve the electrochemical activity of the developed sensor. Inspired by the bio-synthesis and green processing, we have demonstrated the in-situ synthesis of CuO nanosphere-decorated MWCNT by Chenopodium album leaf extract through a sonochemical approach and explored its electrochemical sensing performance toward CLQ. The physical comprehensive characterization of prepared nanocomposite was investigated by various microscopic and spectroscopic techniques. For comparison studies, the CuO nanosphere was prepared by the same preparation process without MWCNT. Based on the physical characterization outcomes, the morphological nature of CuO was observed to be a sphere-like structure, which was decorated on the MWCNT with an average crystallite size of 16 nm (± 1 nm). Based on the electrochemical studies, the fabricated nanocomposite exhibits a wider linear range of 0.025–1375 μM, with a minimum detection limit of 4.59 nM L–1 toward CLQ. The viability examination on the biological matrix obtained considerable spike recoveries. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Nanospheres

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Spectral Learning of Shared Dynamics Between Generalized-Linear Processes 38

Spectral Learning of Shared Dynamics Between Generalized-Lin...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Oganesian, Lucine L. Sani, Omid G. Shanechi, Maryam M. Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA United States Ming Hsieh Department of Electrical and Computer Engineering Thomas Lord Department of Computer Science Alfred E. Mann Department of Biomedical Engineering Neuroscience Graduate Program University of Southern California Los AngelesCA United States

Generalized-linear dynamical models (GLDMs) remain a widely-used framework within neuroscience for modeling time-series data, such as neural spiking activity or categorical decision outcomes. Whereas the standard usage of GLDMs is to model a single data source, certain applications require jointly modeling two generalized-linear time-series sources while also dissociating their shared and private dynamics. Most existing GLDM variants and their associated learning algorithms do not support this capability. Here we address this challenge by developing a multi-step analytical subspace identification algorithm for learning a GLDM that explicitly models shared vs. private dynamics within two generalized-linear time-series. In simulations, we demonstrate our algorithm's ability to dissociate and model the dynamics within two time-series sources while being agnostic to their respective observation distributions. In neural data, we consider two specific applications of our algorithm for modeling discrete population spiking activity with respect to a secondary time-series. In both synthetic and real data, GLDMs learned with our algorithm more accurately decoded one time-series from the other using lower-dimensional latent states, as compared to models identified using existing GLDM learning algorithms. © 2024 Neural information processing systems foundation. All rights reserved.

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Clinical Biomarkers to Evaluate Next Generation Inhaled Tobacco Products’ Effect in the Oral Cavity: a Narrative Review

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Current Oral Health Reports 2024年第1期11卷 30-39页

作者： Sarles, S. Emma Hensel, Edward C. Rahman, Irfan Robinson, Risa J. Biomedical and Chemical Engineering PhD Program Rochester Institute of Technology Rochester NY United States Department of Mechanical Engineering Respiratory Technologies Lab Rochester Institute of Technology Rochester NY United States Department of Environmental Medicine Rahman Lab University of Rochester Medical Center Rochester NY United States

Purpose of Review: Biomarkers in the oral cavity of users of next generation tobacco products, such as electronic cigarettes (EC), provide data about effects on oral and systemic health and help predict long-term health effects, such as cardiovascular, respiratory, and periodontal disease. Despite oral cavity health provides, translation of findings to regulatory outcomes around EC is lacking. A review of the current state of the art in use of clinical biomarkers of the oral cavity was conducted. This identified inconsistencies and gaps in tobacco regulatory science to address how to improve clinical studies for screening tobacco products and studying disease. Recent Findings: The review identified that saliva and buccal biopsies provide dependable biomarkers of oral and systemic health when several parameters of health are standardized and considered. Inflammatory cytokines in oral tissue and biofluids of EC users are conflicting due to differences in sample collection and analysis techniques. Salivary C-reactive protein levels provide information about systemic inflammation and risk of cardiovascular disease, but analysis of this biomarker in the oral cavity does not appear in the current literature. The oral microbiome plays a significant role in human health and may be a useful tool to study systemic effects of tobacco products non-invasively, yet inconsistencies in reporting metrics make studies difficult to compare or translate into tangible outcomes. Effects of tobacco product use on hard dental tissue are not widely investigated despite correlations observed between e-cigarette use and broken teeth. Summary: This review provides a comprehensive update on clinical biomarkers in systemic and oral diseases associated with emerging nicotine products. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Biomarkers Electronic cigarette Oral health Tobacco regulatory science Vaping

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Motion Detection Method of Electrostatic MEMS Resonators Operating in Aqueous Media 6

Motion Detection Method of Electrostatic MEMS Resonators Ope...

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6th International Youth Conference on Radio Electronics, Electrical and Power engineering, REEPE 2024

作者： Hemid, Mohamed Alattar, Basil Ghommem, Mehdi Ahmed, Alaaeldin Abdel-Rahman, Eihab Sabouni, Rana Mechatronics Graduate Program American University of Sharjah Sharjah United Arab Emirates American University of Sharjah Mechanical Engineering Department Sharjah United Arab Emirates Systems Design Engineering University of Waterloo Ontario Canada American University of Sharjah Chemical Engineering Department Sharjah United Arab Emirates

ISBN: (纸本)9798350382891

This paper introduces an experimental method to detect the motion of an electrostatic Micro-Electro-mechanical Systems (MEMS) resonator in aqueous media. The resonator comprises a micro cantilever beam subject to electrostatic actuation through a side electrode. A Finite Element Method (FEM) model of the resonator is developed to determine the in-plane mode shapes and their natural frequencies in order to facilitate the experimental study. The motion of the resonator lead to variations in its capacitance and induce a current. The developed experiments demonstrate that motion-induced current can be measured and analyzed to detect the motion of the resonator's higher-order modes and can be used in chemical sensing. © 2024 IEEE.

关键词： Electrostatics

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