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A machine learning-guided design and manufacturing of wearable nanofibrous acoustic energy harvesters

Nano research 2024年第10期17卷 9181-9192页

作者： Negar Hosseinzadeh Kouchehbaghi Maryam Yousefzadeh Aliakbar Gharehaghaji Safoora Khosravi Danial Khorsandi Reihaneh Haghniaz Ke Cao Mehmet R.Dokmeci Mohammad Rostami Ali Khademhosseini Yangzhi Zhu Terasaki Institute for Biomedical Innovation Los AngelesCA 91367USA Department of Textile Engineering Amirkabir University of Technology(Tehran Polytechnic)Hafez Avenue*** TehranIran Department of Electrical and Computer Engineering University of British ColumbiaVancouverBC V6T1Z4Canada Chemical Sciences Division Oak Ridge National LaboratoryOak RidgeTN 37831USA Department of Computer Science University of Southern CaliforniaLos AngelesCA 90007USA

Nanofibrous acoustic energy harvesters(NAEHs)have emerged as promising wearable platforms for efficient noise-to-electricity conversion in distributed power energy systems and wearable sound amplifiers for assistive listening ***,their reallife efficacy is hampered by low power output,particularly in the low-frequency range(<1 kHz).This study introduces a novel approach to enhance the performance of NAEHs by applying machine learning(ML)techniques to guide the synthesis of electrospun polyvinylidene fluoride(PVDF)/polyurethane(PU)nanofibers,optimizing their application in wearable *** use a feed-forward neural network along with solving an optimization problem to find the optimal input values of the electrospinning(applied voltage,nozzle-collector distance,electrospinning time,and drum rotation speed)to generate maximum output performance(acoustic-to-electricity conversion efficiency).We first prepared a dataset to train the network to predict the output power given the input variables with high *** introducing the neural network,we fix the network and then solve an optimization problem using a genetic algorithm to search for the input values that lead to the maximum energy harvesting *** ML-guided wearable PVDF/PU NAEH platform can deliver a maximal acoustoelectric power density output of 829μW/cm^(3) within the surrounding noise *** addition,our system can function stably in a broad frequency(0.1-2 kHz)with a high energy conversion efficiency of 66%.Sound recognition analysis reveals a robust correlation exceeding 0.85 among lexically akin terms with varying sound intensities,contrasting with a diminished correlation below 0.27 for words with disparate semantic ***,this work provides a previously unexplored route to utilize ML in advancing wearable NAEHs with excellent practicability.

关键词： wearable electronics acoustic energy harvester machine learning piezoelectric nanogenerator electrospun nanofiber

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Direct ink writing of gradient shear-stiffening elastomer for enhanced toughness and impact resistance

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Journal of Industrial and engineering Chemistry 2025年 149卷 593-603页

作者： Gong, Liping Zhao, Chunyu Lu, Hongda Zhang, Qingtian Chen, Zexin Yang, Junjie Yang, Jinyu Sun, Shuaishuai Du, Haiping Li, Weihua School of Mechanical Materials Mechatronic and Biomedical Engineering University of Wollongong Wollongong2522 Australia CAS Key Laboratory of Mechanical Behaviour and Design of Materials Department of Modern Mechanics University of Science and Technology of China Hefei230027 China School of Electrical Computer and Telecommunication Engineering University of Wollongong Wollongong2522 Australia

Shear-stiffening materials have garnered significant attention due to their inherent ability to rapidly respond to changes in strain rate. However, conventional studies on these materials exhibit limited mechanical performance and insufficient structural design, hindering applications in material science and smart mechatronics. Inspired by the gradient structure of a squid beak, this study uses a direct-ink-writing (DIW) technology to develop a novel gradient shear-stiffening elastomer (GSSE). Comprehensive characterizations were conducted to optimize the printability of the shear-stiffening elastomer under various testing conditions, including rheology, compression, and tension. Additionally, the toughness and impact resistance of the elastomer were systematically investigated. It is demonstrated that the biomimetic GSSE exhibits enhanced flexibility, efficient energy dissipation, and outstanding impact resistance. Consequently, this work advances the field of shear-stiffening elastomers for diverse applications by leveraging the gradient structure design strategy to achieve superior mechanical performance under complex loading conditions. © 2025 The Author(s)

关键词： Strain rate

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Topology entropy: Enhancing graph partitioning for TAD identification and single-cell clustering

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Computational and Structural Biotechnology Journal 2025年 27卷 1864-1886页

作者： Liang, Qiushi Zhao, Shengjie Chen, Lingxi Li, Shuai Cheng School of Computer Science and Technology Tongji University Shanghai201804 China Department of Computer Science City University of Hong Kong 999077 Hong Kong Department of Biomedical Sciences City University of Hong Kong 999077 Hong Kong Engineering Research Center of Key Software Technologies for Smart City Perception and Planning Ministry of Education China

Entropy quantifies the limits of information compression and provides a theoretical foundation for exploring complex structures in large-scale graphs. However, effective metrics are needed to capture the intricate structural details in biological graphs. In this paper, we introduce the topology entropy encoding tree to quantify the complexity of biological graphs and show that minimizing the associated entropy is equivalent to optimal graph partitioning. We develop two methods, TEC-O and TEC-U, for partitioning ordered and unordered biological graphs. TEC-O is applied to identify Topologically Associated Domains (TADs) in Hi-C contact maps, while TEC-U is used for cell clustering in single-cell sequencing data. Results from simulated datasets demonstrate that topology entropy is robust to noise and effectively captures structural information, outperforming existing methods. Experiments on Hi-C data from five cell lines and ten single-cell sequencing datasets show that TEC-O and TEC-U achieve the highest accuracy in TAD detection and cell clustering, respectively, providing biologically meaningful insights. © 2025 The Authors

关键词： Cell culture

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Highly robust soft-rigid connections via mechanical interlocking for assembling ultra-stretchable displays

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npj Flexible Electronics 2024年第1期8卷 387-396页

作者： Lixue Tang Huayi Wang Jifeng Ren Xingyu Jiang Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application School of Biomedical EngineeringCapital Medical UniversityNo.10 XitoutiaoYou An Men Wai100069 BeijingChina Shenzhen Key Laboratory of Smart Healthcare Engineering Guangdong Provincial Key Laboratory of Advanced BiomaterialsDepartment of Biomedical EngineeringSouthern University of Science and TechnologyNo.1088Xueyuan Rd.Nanshan District518055 ShenzhenGuangdongP.R.China

Stretchable electronic circuits can seamlessly conform to irregular and dynamic surfaces with high ***,current stretchable configurations typically have limited stretchability due to the lack of robust connections between soft interconnects and rigid ***,we printed highly stretchable metal–polymer conductors on thermoplastic elastomers as *** developed electronic vests with porous surfaces for rigid electronics and introduced polyester hot-melt adhesives to strengthen connections between soft interconnects and rigid *** thermal bonding,the adhesive penetrates the porous surface of electronic vests,creating a mechanical interlock and providing an adhesion force of 8.34 N/cm for the connection(3×higher than conductive adhesives).Thus,rigid electronics of different sizes and different pin counts can form strong connections to soft interconnects,achieving a maximum strain tolerance of~700%(10×higher than conductive adhesives).We achieved highly integrated ultra-stretchable displays that can withstand stretching up to 220%without dead pixels.

关键词： rigid stretching polyester

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Optimizing Smart Home Energy Forecasting: Unveiling Superiority among RBFNN, ESN, and LSTM 4

Optimizing Smart Home Energy Forecasting: Unveiling Superior...

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4th International Conference on Innovative research in Applied science, engineering and Technology, IRASET 2024

作者： Bhih, Mouad Abou Elassad, Zouhair Elamrani Ameksa, Mohammed Boustani, Abdelhakim El El Meslouhi, Othmane Abou Elassad, Dauha Elamrani Cadi Ayyad University Sars Research Team Ensas Computer Science Department Safi Morocco Fssm Cadi Ayyad University Lisi Laboratory Computer Science Department Morocco Moroccan School Of Engineering Sciences Emsi Lamigep Laboratory Marrakech Morocco

ISBN: (纸本)9798350309508

In response to the accelerating integration of IoT devices for monitoring residential energy consumption, this study focuses on identifying robust predictive models aligned with global sustainability goals. Investigating three advanced models-Radial Basis Function Neural Networks (RBFNN), Echo State Networks (ESN), and Long Short-Term Memory (LSTM)-reveals distinct performance metrics. RBFNN demonstrates solid performance, while after meticulous tuning, ESN exhibits superior predictive capabilities, outperforming traditional techniques and even LSTM. Employing Recursive Feature Elimination (RFE) identifies key predictors, emphasizing ESN's heightened predictive accuracy. This research provides empirical insights, highlighting ESN's potential in enabling sustainable energy management within smart homes. © 2024 IEEE.

关键词： Long short-term memory

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A GPGPU-Based Algorithm Acceleration System for ECG Signal Processing 7

A GPGPU-Based Algorithm Acceleration System for ECG Signal P...

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7th International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2024

作者： Huang, Tianyu Wang, Zhijiong Hu, Guannan Pun, Sio Hang Li, Hung Chun Vai, Mang I Science and Technology Research Institute Lingyange Semiconductor Incorporated University of Macau Joint Laboratory of Zhuhai UM Department of Electrical and Computer Engineering China Science and Technology Research Institute Lingyange Semiconductor Incorporated University of Macau Joint Laboratory of Zhuhai UM Lingyange Semiconductor Incorporated Department of Electrical and Computer Engineering China Science and Technology Research Institute Lingyange Semiconductor Incorporated Joint Laboratory of Zhuhai UM Lingyange Semiconductor Incorporated Zhuhai China Institute of Microelectronics Science and Technology Research Institute Lingyange Semiconductor Incorporated University of Macau Joint Laboratory of Zhuhai UM Department of Electrical and Computer Engineering China

ISBN: (纸本)9798331529314

Electrocardiogram (ECG) is an important non-invasive technique for diagnosing cardiovascular diseases (CVD). After acquiring the patients' raw ECG signal data, signal processing is essential for the diagnosis. Conventional ECG signal processing is usually performed serially, which takes a long time to process signals with large amounts of data. In this study, we have proposed a GPGPU-based algorithm acceleration system to improve the efficiency of ECG signal processing. This system utilizes OpenCL for parallel algorithm development on GPGPU. GPGPU executes certain steps in the QRS complex detection algorithm via parallel computing, thereby accelerating the algorithmic process. Experimental results showed that the system achieved a speedup of 1.279 compared to serial computing when processing 39 ECG signal sequences in parallel. In addition, our system has been equipped with a progressive transmission mechanism and a function that intelligently determines whether an algorithm can be accelerated. These features make this system practical not only in biomedical signal processing but also in engineering and research fields with large amounts of data. © 2024 IEEE.

关键词： Noninvasive medical procedures

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The Mechanics of Tumor Cells Dictate Malignancy via Cytoskeleton-Mediated APC/Wnt/β-Catenin Signaling

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research 2024年第2期2023卷 659-673页

作者： Xi Chen Zichen Xu Kai Tang Guanshuo Hu Pengyu Du Junfang Wang Cunyu Zhang Ying Xin Keming Li Qiantang Zhang Jianjun Hu Zhuxue Zhang Mo Yang Guixue Wang Youhua Tan The Hong Kong Polytechnic University Shenzhen Research Institute Shenzhen518057China Key Laboratory for Biorheological Science and Technology of Ministry of Education State and Local Joint Engineering Laboratory for Vascular ImplantsBioengineering College of Chongqing UniversityChongqing400030China Research Institute of Smart Ageing The Hong Kong Polytechnic UniversityHong KongChina Department of Biomedical Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Pathology Guizhou Provincial People's HospitalGuiyangGuizhou550002China

Tumor cells progressively remodel cytoskeletal structures and reduce cellular stiffness during tumor progression,implicating the correlation between cell mechanics and ***,the roles of tumor cell cytoskeleton and the mechanics in tumor progression remain incompletely *** report that softening/stiffening tumor cells by targeting actomyosin promotes/suppresses self-renewal in vitro and tumorigenic potential in ***/strengthening actin cytoskeleton impairs/reinforces the interaction between adenomatous polyposis coli(APC)andβ-catenin,which facilitatesβ-catenin nuclear/cytoplasmic ***β-catenin binds to the promoter of Oct4,which enhances its transcription that is crucial in sustaining self-renewal and *** results demonstrate that the mechanics of tumor cells dictate self-renewal through cytoskeleton-APC-Wnt/β-catenin-Oct4 signaling,which are correlated with tumor differentiation and patient *** study unveils an uncovered regulatory role of cell mechanics in self-renewal and malignancy,and identifies tumor cell mechanics as a hallmark not only for cancer diagnosis but also for mechanotargeting.

关键词： diagnosis skeleton APC

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An interfacial robust and entire self-healing ionogel-elastomer hybrid for elastic electronics enables discretionary assembly and reconfiguration

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science China Chemistry 2024年第4期67卷 1316-1323页

作者： Lei Yang Lijie Sun Hongfei Huang Rasoul Esmaeely Neisiany Zhengwei You State Key Laboratory for Modification of Chemical Fibers and Polymer Materials Institute of Functional MaterialsCollege of Materials Science and EngineeringDonghua UniversityResearch Base of Textile Materials for Flexible Electronics and Biomedical Applications(China Textile Engineering Society)Shanghai Engineering Research Center of Nano-Biomaterials and Regenerative MedicineShanghai 201620China Department of Polymer Engineering Hakim Sabzevari UniversitySabzevar ***Iran Biotechnology Centre Silesian University of TechnologyGliwice 44-100Poland

Inspired by the multi-layer architecture of mammal skins,interfacial robust,stretchable,and entirely healable gel-elastomer hybrids hold great potential in diverse fields including biomedical devices,wearable electrical devices,and soft ***,existing gel-elastomer hybrids have numerous limitations including low interfacial bonding toughness,complex and time-consuming preparation process,unhealable,and ***,we propose a simple and general chemical strategy through the interfacial dynamic bonding between gel and elastomer to simultaneously address the abovementioned *** covalent bonds readily and repeatably covalent bonding ionogel and elastomer(interfacial toughness:390 J m^(-2)),endowed the hybrids with entire self-healing features like skin and enabled discretionary assembly and ***,this strategy resolved the troublesome contradiction between interfacial stability and *** advantage of the aforementioned features,we readily constructed a multi-module,self-healing,self-powered,and realtime monitoring of personal status integrated elastic electronics,which could simply reconfigure the output signal of elastic electronics into an input signal of the devices-braille keyboard.

关键词： ionogel elastomer interface bonding self-healing dynamic covalent bond

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Pulsed Electromagnetic Field Interaction With a Transmission Line: An Analytical Traveling-Wave Approach Based on Reciprocity

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IEEE Transactions on Antennas and Propagation 2025年第6期73卷 3783-3791页

作者： Stumpf, Martin Antonini, Giulio Lager, Ioan E. Ekman, Jonas The Czech Republic Lerch Laboratory of em Research Department of Radio Electronics Feec Brno University of Technology Technická Brno3082/12 616 00 Czech Republic Luleå University of Technology Department of Computer Science Electrical and Space Engineering Eislab Luleå971 87 Sweden University of l'Aquila UAq Emc Laboratory Department of Industrial and Information Engineering and Economics L'Aquila671 00 Italy Delft University of Technology Terahertz Sensing Group Faculty of Electrical Engineering Mathematics and Computer Science Delft2628 CD Netherlands

Pulsed electromagnetic (EM) field signal transfer from a general EM source distribution to a transmission line (TL) is analyzed with the aid of Lorentz's reciprocity theorem. In this fashion, the transient voltage induced by the impulsive EM source is expressed through the EM fields as radiated by the TL. These transmitted EM fields are expressed in closed form using an analytical procedure that resembles the Cagniard-DeHoop (CdH) technique. The validity of the proposed reciprocity-based methodology is verified with the aid of an alternative analytical solution describing the EM field signal transfer excited by an impulsive vertical electric dipole (VED). Illustrative numerical examples are presented. © 1963-2012 IEEE.

关键词： Time domain analysis

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A Composite Decomposition Method for Large-Scale Global Optimization

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6304-6319页

作者： Tian, Maojiang Chen, Minyang Du, Wei Tang, Yang Jin, Yaochu Yen, Gary G. Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen518055 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China East China University of Science and Technology Engineering Research Center of Process System Engineering Ministry of Education Shanghai200237 China Westlake University School of Engineering Hangzhou310030 China Oklahoma State University School of Electrical and Computer Engineering StillwaterOK74048 United States

Cooperative coevolution (CC) algorithms, based on the divide-and-conquer strategy, have emerged as the predominant approach to solving large-scale global optimization (LSGO) problems. The efficiency and accuracy of the grouping stage significantly impact the performance of the optimization process. While the general separability grouping (GSG) method has overcome the limitation of previous differential grouping (DG) methods by enabling the decomposition of nonadditively separable functions, it suffers from high computational complexity. To address this challenge, this article proposes a composite separability grouping (CSG) method, seamlessly integrating DG and GSG into a problem decomposition framework to utilize the strengths of both approaches. CSG introduces a step-by-step decomposition framework that accurately decomposes various problem types using fewer computational resources. By sequentially identifying additively, multiplicatively and generally separable variables, CSG progressively groups nonseparable variables by recursively considering the interactions between each nonseparable variable and the formed nonseparable groups. Furthermore, to enhance the efficiency and accuracy of CSG, we introduce two innovative methods: a multiplicatively separable variable detection method and a nonseparable variable grouping method. These two methods are designed to effectively detect multiplicatively separable variables and efficiently group nonseparable variables, respectively. Extensive experimental results demonstrate that CSG achieves more accurate variable grouping with lower computational complexity compared to GSG and state-of-the-art DG-series designs. © 2024 IEEE.

关键词： Computational efficiency

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