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Enhancing Strategy of Triboelectric Nanogenerator via Origami Pattern by Harvesting Mechanical Motion and Wind Flow

International Journal of Energy Research 2024年第1期2024卷 2120442-2120442页

作者： Chung, Seh-Hoon Kim, Minsoo Lin, Zong-Hong Koo, Bonwook Choi, Dongwhi Kim, Dongseob Lee, Sangmin School of Mechanical Engineering Chung-ang University 84 Heukseok-ro Dongjak-gu Seoul06974 Korea Republic of Department of Biomedical Engineering National Taiwan University Taipei10167 Taiwan Major in Wood Science and Technology Kyungpook National University 80 Daehakro Daegu41566 Korea Republic of Department of Mechanical Engineering Integrated Engineering Program Kyung Hee University Yongin Gyeonggi17104 Korea Republic of 57 Yangho-gil Gyeongsangbuk-do Yeongcheon-si38822 Korea Republic of

Triboelectric nanogenerators (TENGs) are promising energy-harvesting devices that generate electricity from mechanical energy. However, the electrical outputs of typical TENGs are limited because of the fundamental mechanism by which TENGs require a certain amount of space for contact-separation motion. Therefore, we developed an origami-based vertical/fluttering hybrid TENG (OVFH-TENG), which is the innovative structure that can generate electricity from both vertical movement and wind flow which is generated by vertical movement. It consists of a vertical TENG and a fluttering TENG where vertical TENGs can generate electricity and wind flow from mechanical input and the fluttering TENGs can generate electricity from the wind flow which is generated by its own operation process. Thus, OVFH-TENG can effectively harvest energy from vertical contact and fluttering motions with a single input. The optimized OVFH-TENG generated a 34.7% higher output than the general contact-separation TENG. Finally, the OVFH-TENG was able to light 180 LEDs, which was not possible with a general contact-separation TENG. © 2024 Seh-Hoon Chung et al.

关键词： Nanogenerators

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PD-1 blockade-unresponsive human tumor-infiltrating CD8^(+)T cells are marked by loss of CD28 expression and rescued by IL-15

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Cellular & Molecular Immunology 2021年第2期18卷 385-397页

作者： Kyung Hwan Kim Hong Kwan Kim Hyung-Don Kim Chang Gon Kim Hoyoung Lee Ji Won Han Seong Jin Choi Seongju Jeong Minwoo Jeon Hyunglae Kim Jiae Koh Bo Mi Ku Su-Hyung Park Myung-Ju Ahn Eui-Cheol Shin Graduate School of Medical Science and Engineering Korea Advanced Institute of Science and TechnologyDaejeonRepublic of Korea Department of Thoracic and Cardiovascular Surgery Samsung Medical CenterSungkyunkwan University School of MedicineSeoulRepublic of Korea Biomedical Science and Engineering Interdisciplinary Program Korea Advanced Institute of Science and TechnologyDaejeonRepublic of Korea Research Institute for Future Medicine Samsung Medical CenterSungkyunkwan University School of MedicineSeoulRepublic of Korea Department of Radiation Oncology Yonsei Cancer CenterYonsei University College of MedicineSeoulRepublic of Korea Division of Hematology-Oncology Department of MedicineSamsung Medical CenterSungkyunkwan University School of MedicineSeoulRepublic of Korea

Blockade of programmed death-1(PD-1)reinvigorates exhausted CD8^(+)T cells,resulting in tumor regression in cancer ***,reinvigoration of exhausted CD8^(+)T cells following PD-1 blockade was shown to be CD28-dependent in mouse ***,we examined the role of CD28 in anti-PD-1 antibody-induced human T cell reinvigoration using tumor-infiltrating CD8^(+)T cells(CD8^(+)TILs)obtained from non-small-cell lung cancer ***-cell analysis demonstrated a distinct expression pattern of CD28 between mouse and human CD8^(+)***,we found that human CD28^(+)CD8^(+)but not CD28^(–)CD8^(+)TILs responded to PD-1 blockade irrespective of B7/CD28 blockade,indicating that CD28 costimulation in human CD8^(+)TILs is dispensable for PD-1 blockade-induced reinvigoration and that loss of CD28 expression serves as a marker of anti-PD-1 antibody-unresponsive CD8^(+)*** and phenotypically,PD-1 blockade-unresponsive human CD28^(–)PD-1^(+)CD8^(+)TILs exhibited characteristics of terminally exhausted CD8^(+)T cells with low TCF1 ***,CD28^(–)PD-1^(+)CD8^(+)TILs had preserved machinery to respond to IL-15,and IL-15 treatment enhanced the proliferation of CD28^(–)PD-1^(+)CD8^(+)TILs as well as CD28^(+)PD-1^(+)CD8^(+)*** together,these results show that loss of CD28 expression is a marker of PD-1 blockade-unresponsive human CD8^(+)TILs with a TCF1–signature and provide mechanistic insights into combining IL-15 with anti-PD-1 antibodies.

关键词： anti-PD-1 T cells TCF1 CD28 IL-15

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Microengineered platforms for characterizing the contractile function of in vitro cardiac models

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Microsystems & Nanoengineering 2022年第1期8卷 29-50页

作者： Wenkun Dou Manpreet Malhi Qili Zhao Li Wang Zongjie Huang Junhui Law Na Liu Craig A.Simmons Jason T.Maynes Yu Sun Department of Mechanical and Industrial Engineering University of TorontoTorontoON M5S 3G8Canada Program in Molecular Medicine The Hospital for Sick ChildrenTorontoON M5G 1X8Canada Department of Biochemistry University of TorontoTorontoON M5S 1A8Canada Institute of Robotics and Automatic Information System and the Tianjin Key Laboratory of Intelligent Robotics Nankai UniversityTianjin 300350China School of Mechanical&Automotive Engineering Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Mechatronics Engineering and Automation Shanghai UniversityShanghai 200444China Institute of Biomedical Engineering University of TorontoTorontoON M5S 3G9Canada Translational Biology&Engineering Program Ted Rogers Centre for Heart ResearchTorontoON M5G 1M1Canada Department of Anesthesiology and Pain Medicine University of TorontoTorontoON M5S 1A8Canada Department of Anesthesia and Pain Medicine The Hospital for Sick ChildrenTorontoON M5G 1X8Canada Department of Electrical and Computer Engineering University of TorontoTorontoON M5S 3G4Canada Department of Computer Science University of TorontoTorontoON M5T 3A1Canada

Emerging heart-on-a-chip platforms are promising approaches to establish cardiac cell/tissue models in vitro for research on cardiac physiology,disease modeling and drug cardiotoxicity as well as for therapeutic *** still exist in obtaining the complete capability of in situ sensing to fully evaluate the complex functional properties of cardiac cell/tissue *** to contractile strength(contractility)and beating regularity(rhythm)are particularly important to generate accurate,predictive *** new platforms and technologies to assess the contractile functions of in vitro cardiac models is essential to provide information on cell/tissue physiologies,drug-induced inotropic responses,and the mechanisms of cardiac *** this review,we discuss recent advances in biosensing platforms for the measurement of contractile functions of in vitro cardiac models,including single cardiomyocytes,2D monolayers of cardiomyocytes,and 3D cardiac *** characteristics and performance of current platforms are reviewed in terms of sensing principles,measured parameters,performance,cell sources,cell/tissue model configurations,advantages,and *** addition,we highlight applications of these platforms and relevant discoveries in fundamental investigations,drug testing,and disease ***,challenges and future outlooks of heart-on-a-chip platforms for in vitro measurement of cardiac functional properties are discussed.

关键词： cardiac contractile regularity

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A Comparative Study of Machine Learning Classifiers for Enhancing Knee Osteoarthritis Diagnosis

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Information (Switzerland) 2024年第4期15卷 183页

作者： Raza, Aquib Phan, Thien-Luan Li, Hung-Chung Hieu, Nguyen Van Nghia, Tran Trung Ching, Congo Tak Shing Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung402 Taiwan Department of Physics and Electronic Engineering University of Science Vietnam National University of Ho Chi Minh City Ho Chi Minh City70000 Viet Nam Undergraduate Program of Intellectual Creativity Engineering National Chung Hsing University Taichung402 Taiwan VNU-HCM Ho Chi Minh City72409 Viet Nam Department of Electrical Engineering National Chi Nan University Puli Township545 Taiwan International Doctoral Program in Agriculture National Chung Hsing University Taichung402 Taiwan

Knee osteoarthritis (KOA) is a leading cause of disability, particularly affecting older adults due to the deterioration of articular cartilage within the knee joint. This condition is characterized by pain, stiffness, and impaired movement, posing a significant challenge in medical diagnostics and treatment planning, especially due to the current inability for early and accurate detection or monitoring of disease progression. This research introduces a multifaceted approach employing feature extraction and machine learning (ML) to improve the accuracy of diagnosing and classifying KOA stages from radiographic images. Utilizing a dataset of 3154 knee X-ray images, this study implemented feature extraction methods such as Histogram of Oriented Gradients (HOG) with Linear Discriminant Analysis (LDA) and Min–Max scaling to prepare the data for classification. The study evaluates six ML classifiers—K Nearest Neighbors classifier, Support Vector Machine (SVM), Gaussian Naive Bayes, Decision Tree, Random Forest, and XGBoost—optimized via GridSearchCV for hyperparameter tuning within a 10-fold Stratified K-Fold cross-validation framework. An ensemble model has also been made for the already high-accuracy models to explore the possibility of enhancing the accuracy and reducing the risk of overfitting. The XGBoost classifier and the ensemble model emerged as the most efficient for multiclass classification, with an accuracy of 98.90%, distinguishing between healthy and unhealthy knees. These results underscore the potential of integrating advanced ML methodologies for the nuanced and accurate diagnosis and classification of KOA, offering new avenues for clinical application and future research in medical imaging diagnostics. © 2024 by the authors.

关键词： Extraction

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Generalization is not a universal guarantee: Estimating similarity to training data with an ensemble out-of-distribution metric

arXiv

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arXiv 2025年

作者： Schreyer, W. Max Anderson, Christopher Thompson, Reid F. Computational Biology Program Oregon Health & Science University PortlandOR United States Department of Biomedical Engineering Oregon Health & Science University PortlandOR United States Portland VA Research Foundation PortlandOR United States Department of Radiation Medicine Oregon Health & Science University PortlandOR United States Department of Medical Informatics and Clinical Epidemiology Oregon Health & Science University PortlandOR United States Division of Hospital and Specialty Medicine VA Portland Healthcare System PortlandOR United States

Failure of machine learning models to generalize to new data is a core problem limiting the reliability of AI systems, partly due to the lack of simple and robust methods for comparing new data to the original training dataset. We propose a standardized approach for assessing data similarity in a model-agnostic manner by constructing a supervised autoencoder for generalizability estimation (SAGE). We compare points in a low-dimensional embedded latent space, defining empirical probability measures for k-Nearest Neighbors (kNN) distance, reconstruction of inputs and task-based performance. As proof of concept for classification tasks, we use MNIST and CIFAR-10 to demonstrate how an ensemble output probability score can separate deformed images from a mixture of typical test examples, and how this SAGE score is robust to transformations of increasing severity. As further proof of concept, we extend this approach to a regression task using non-imaging data (UCI Abalone). In all cases, we show that out-of-the-box model performance increases after SAGE score filtering, even when applied to data from the model’s own training and test datasets. Our out-of-distribution scoring method can be introduced during several steps of model construction and assessment, leading to future improvements in responsible deep learning implementation. Copyright © 2025, The Authors. All rights reserved.

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Cerebral Oxygenation Dynamics in Awake Behaving Mice

Cerebral Oxygenation Dynamics in Awake Behaving Mice

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Clinical and Translational Biophotonics, Translational 2022

作者： Zhang, Qingguang Roche, Morgane Gheres, Kyle W. Chaigneau, Emmanuelle Haselden, William D. Kedarasetti, Ravi T. Charpak, Serge Drew, Patrick J. Department of Engineering Science and Mechanics The Pennsylvania State University University ParkPA United States Institut National de la Santé et de la Recherche Médicale ParisU1128 France Laboratory of Neurophysiology and New Microscopies Université Paris Descartes Paris France Graduate Program in Molecular Cellular and Integrative Biosciences The Pennsylvania State University University ParkPA United States Medical Scientist Training Program and Neuroscience Graduate Program The Pennsylvania State University University ParkPA United States Department of Neurosurgery Department of Biomedical Engineering The Pennsylvania State University University ParkPA United States

We investigated (1) how and by what mechanisms voluntary exercise impacts brain tissue oxygenation, and (2) what is the origin of the 1/f-like oxygen fluctuations, in awake behaving mice. © 2022 The Author(s).

ISBN: (纸本)9781557528209

关键词： Mammals

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A physical picture of liquid–liquid phase separation of proteins

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Journal of Molecular Liquids 2025年 424卷

作者： Kinoshita, Masahiro Hayashi, Tomohiko Nakamura, Yuka Yoshimori, Akira Katahira, Masato Nagata, Takashi Department of Chemistry of Science Chiba University 1-33 Yayoi-cho Inage Chiba263-8522 Japan Institute of Advanced Energy Kyoto University Kyoto Uji611-0011 Japan Interdisciplinary Program of Biomedical Engineering Assistive Technology and Art and Sports Sciences Faculty of Engineering Niigata University 8050 Ikarashi 2-no-cho Nishi-ku Niigata950-2181 Japan Department of Physics Niigata University Niigata950-2181 Japan

Liquid-liquid phase separation (LLPS) of proteins, by which they assemble and partition into a protein-dense phase and a protein-dilute phase, has caught much attention due to its essential roles in a variety of biological processes. Nevertheless, its mechanism remains to be unveiled. Here we develop a physical picture covering almost all the aspects of LLPSs of diverse systems. In our view, when only the proteins are looked at, one of the two phases is liquid-like and the other is gas-like. We relate LLPS to gas–liquid phase separation (GLPS) of simple fluids wherein the pivotal quantity is kBT (kB is the Boltzmann constant and T is the absolute temperature) divided by the absolute value of the minimum of interaction potential between fluid particles. GLPS occurs only if the pivotal quantity is sufficiently small. For LLPS, the interaction potential must be replaced by the potential of mean force (PMF) between protein molecules in aqueous solution. We do not explicitly consider aqueous solution, and its influence on properties of protein molecules is incorporated in PMF. PMF can reach its deep minimum when the two protein molecules associate. A physical interpretation is given for GLPS from a statistical-mechanics point of view, and it is extended to LLPS. In the extension, we discuss not only the similarities between the two phase separations but also the physical factors to be taken into account only in LLPS due to the fact that proteins are large molecules possessing polyatomic structures and they are immersed in aqueous solution. LLPS can be categorized as a biological self-assembly process. By reconsidering the results obtained in our earlier studies on biological self-assembly processes, we specify the entropic and energetic factors driving or opposing coacervation (association) of protein molecules followed by LLPS. We clarify the differences between LLPSs of folded proteins (i.e., proteins in the native states) and intrinsically disordered proteins. There c

关键词： Alkali halides

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Polarized Superradiance from CsPbBr3 Quantum Dot Superlattice with Controlled Inter-dot Electronic Coupling

arXiv

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arXiv 2024年

作者： Luo, Lanyin Tang, Xueting Park, Junhee Wang, Chih-Wei Park, Mansoo Khurana, Mohit Singh, Ashutosh Cheon, Jinwoo Belyanin, Alexey Sokolov, Alexei V. Son, Dong Hee Department of Physics and Astronomy Texas A&M University College StationTX77843 United States Institute of Quantum Science and Engineering Texas A&M University College StationTX77843 United States Department of Chemistry Texas A&M University College StationTX77843 United States Center for Nanomedicine Institute for Basic Science and Graduate Program of Nano Biomedical Engineering Advanced Science Institute Yonsei University Seoul03722 Korea Republic of

Cooperative emission of photons from an ensemble of quantum dots (QDs) as superradiance can arise from the electronically coupled QDs with a coherent emitting excited state. This contrasts with superfluorescence (Dicke superradiance), where the cooperative photon emission occurs via a spontaneous buildup of coherence in an ensemble of incoherently excited QDs via their coupling to a common radiation mode. While superfluorescence has been observed in perovskite QD systems, reports of superradiance from the electronically coupled ensemble of perovskite QDs are rare. Here, we demonstrate the generation of polarized superradiance with a very narrow linewidth ( © 2024, CC BY-NC-ND.

关键词： Perovskite

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A deep learning approach to Lung Nodule Growth Prediction using CT image combined with Demographic and image features 23

A deep learning approach to Lung Nodule Growth Prediction us...

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7th International Conference on Medical and Health Informatics, ICMHI 2023

作者： Li, Ai-Hsien Adams Nguyen, Duc-Khanh Lai, Yen-Jun Chien, Ting-Ying Chiu, Yen-Ling Chan, Chien-Lung Yang, Pan-Chyr Division of Cardiology Far Eastern Memorial Hospital Taipei220 Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Department of Information Management Yuan Ze University Taoyuan320 Taiwan Department of Radiology Far Eastern Memorial Hospital Taipei220 Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Medical Research Far Eastern Memorial Hospital Taipei Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan320 Taiwan Institute of Biomedical Sciences Academia Sinica Taipei106 Taiwan Department of Internal Medicine College of Medicine National Taiwan University Taipei100 Taiwan Center of Genomic Medicine National Taiwan University Taipei100 Taiwan

ISBN: (纸本)9798400700712

Lung cancer remains a significant global public health concern, being the leading cause of cancer-related deaths worldwide. Despite recent medical advancements, the disease still has a high mortality rate, making early detection and treatment critical for improving patient outcomes. Accurate prediction of nodule growth is key to early lung cancer treatment, but current assessments offer unclear indications of future growth, leading physicians to recommend costly and anxiety-provoking follow-up appointments every 3 to 12 months. To address this need, this study develops an ensemble deep learning approach that combines demographic data with existing CT images to predict whether lung nodules will grow, potentially reducing unnecessary examinations and easing the burden on patients. Our study, conducted on 862 patients with 1004 nodules, produced promising preliminary results with Accuracy, Sensitivity, Precision, F1 Score, and AUC of 0.66, 0.66, 0.67, 0.66, and 0.71, respectively. The proposed method provides a promising support system to empower patients to make informed decisions about seeking medical attention and helps physicians facilitate early treatment regimens, leading to improved patient outcomes and potentially saving lives. © 2023 ACM.

关键词： Forecasting

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Biosynthesis of silver nanoparticles as a reliable alternative for the catalytic degradation of organic dyes and antibacterial applications

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Current Research in Green and Sustainable Chemistry 2024年 8卷

作者： Hijazi, Baraa U. Faraj, Marwa Mhanna, Rami El-Dakdouki, Mohammad H. Department of Chemistry Faculty of Science Beirut Arab University P.O. Box 11-5020 Riad El Solh Beirut 11072809 Lebanon Biomedical Engineering Program Maroun Semaan Faculty of Engineering and Architecture American University of Beirut Beirut 1107 2020 Lebanon

Water bodies are being threatened continuously by various anthropogenic pollutants such as organic dyes and bacteria which led to scarcity of fresh water suitable for drinking and irrigation. Therefore, different water treatment methods have been implemented before the discharge of contaminated wastewater into water bodies. In this report, green-synthesized silver nanoparticles (AgNPs) were evaluated in the degradation of organic dyes and bacterial decontamination. The S. costus root aqueous extract was used as an environmentally benign reducing agent in the biosynthesis of AgNPs. The synthetic procedure was optimized in terms of different parameters, and several analytical techniques were used to thoroughly characterize the prepared nanocomposites including TEM, SEM, EDX, DLS, XRD, FTIR, UV/Vis, photoluminescence, and TGA. The nanoparticles were spherical, monodisperse, colloidally and thermally stable, and crystalline in nature. The efficiency of the biogenic AgNPs as catalysts for the degradation of organic dyes was evaluated against six structurally diverse dyes. These included methylene blue, phenol red, methyl orange, Congo red, orange G and safranin O. Moreover, the applicability of AgNPs as antibacterial agents was tested against K. pneumoniae, S. aureus, S. haemolyticus and E. faecalis where the zones of growth inhibition, MIC and MBC values were determined for each bacterium. Overall, the biosynthesized nanoparticles were remarkable catalysts in the discoloration of hazardous dyes and displayed notable antibacterial potency against Gram-positive and Gram-negative bacteria. © 2024

关键词： Antimicrobial activity Catalytic activity Green synthesis Hazardous dyes Saussurea costus

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