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arXiv 2024年

作者： Han, Jiashu Liu, Kunzan Isaacson, Keith B. Monakhova, Kristina Griffith, Linda G. You, Sixian Research Laboratory of Electronics MIT United States Department of Electrical Engineering and Computer Science MIT United States Newton-Wellesley Hospital Mass General Brigham United States Department of Biological Engineering MIT United States Department of Mechanical Engineering MIT United States

Three-dimensional (3D) subcellular imaging is essential for biomedical research, but the diffraction limit of optical microscopy compromises axial resolution, hindering accurate 3D structural analysis. This challenge is particularly pronounced in label-free imaging of thick, heterogeneous tissues, where assumptions about data distribution (e.g. sparsity, label-specific distribution, and lateral-axial similarity) and system priors (e.g. independent and identically distributed (i.i.d.) noise and linear shift-invariant (LSI) point-spread functions (PSFs)) are often invalid. Here, we introduce SSAI-3D, a weakly physics-informed, domain-shift-resistant framework for robust isotropic 3D imaging. SSAI-3D enables robust axial deblurring by generating a PSF-flexible, noise-resilient, sample-informed training dataset and sparsely fine-tuning a large pre-trained blind deblurring network. SSAI-3D was applied to label-free nonlinear imaging of living organoids, freshly excised human endometrium tissue, and mouse whisker pads, and further validated in publicly available ground-truth-paired experimental datasets of 3D heterogeneous biological tissues with unknown blurring and noise across different microscopy systems. © 2024, CC BY.

关键词： Optical transfer function

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On the design and fabrication of nanoliter-volume hanging drop networks

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Microsystems & Nanoengineering 2024年第5期10卷 435-447页

作者： Matthew Wester Jongwon Lim Liliana Khaertdinova Sriya Darsi Neel Donthamsetti Glennys Mensing George Vasmatzis Panos Anastasiadis Enrique Valera Rashid Bashir Department of Bioengineering University of linois Urbana-ChampaignUrbanaIL 61801USA Nick Holonyak Jr.Micro and Nanotechnology Laboratory University of Ilinois Urbana-ChampaignUrbanaIL 61801USA Center for Individualized Medicine Mayo ClinicRochesterMN 55905USA Mayo-Illinois Alliance for Technology-Based Healthcare UrbanaIL 61801USA Department of Cancer Biology Mayo ClinicJacksonvilleFL 32224USA Carl R.Woese Institute for Genomic Biology University of Illinois at Urbana-ChampaignUrbanaIL 61801USA Biomedical Research Center Carle Foundation HospitalUrbanaIL 61801USA Cancer Center at Illinois University of Illinois at Urbana-ChampaignUrbanaIL 61801USA Department of Biomedical and Translation Science Carle Illinois College of MedicineUniversity of Illinois at Urbana-ChampaignUrbanaIL 61801USA Chan Zuckerberg Biohub Chicago ChicagoIL 60642USA Department of Electrical and Computer Engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA Department of Mechanical Science and Engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA Department of Materials Science and Engineering University of Illinois at Urbana-ChampaignUrbanaIL 61801USA

Hanging drop cultures provide a favorable environment for the gentle,gel-free formation of highly uniform three-dimensional cell cultures often used in drug screening *** cell numbers can be limited,as with primary cells provided by minimally invasive ***,it can be beneficial to divide cells into miniaturized arrays of hanging drops to supply a larger number of ***,we present a framework for the miniaturization of hanging drop networks to nanoliter *** principles of a single hanging drop are described and used to construct the fundamental equations for a microfluidic system composed of multiple connected *** equations for the hanging drop as a nonlinear capacitive element are derived for application in the electronic-hydraulic analogy,forming the basis for more complex,time-dependent numerical modeling of hanging drop *** is supplemented by traditional computational fluid dynamics simulation to provide further information about flow conditions within the wells.A fabrication protocol is presented and demonstrated for creating transparent,microscale arrays of pinned hanging drops.A custom interface,pressure-based fluidic system,and environmental chamber have been developed to support the ***,fluid flow on the chip is demonstrated to align with expected behavior based on the principles derived for hanging drop *** with the system and potential areas for improvement are *** paper expands on the limited body of hanging drop network literature and provides a framework for designing,fabricating,and operating these systems at the microscale.

关键词： networks system hanging

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Development and Validation of a Prognostic Risk Score System for COVID-19 Inpatients:A Multi-Center Retrospective Study in China

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engineering 2022年第1期8卷 116-121页

作者： Ye Yuan Chuan Sun Xiuchuan Tang Cheng Cheng Laurent Mombaerts Maolin Wang Tao Hu Chenyu Sun Yuqi Guo Xiuting Li Hui Xu Tongxin Ren Yang Xiao Yaru Xiao Hongling Zhu Honghan Wu Kezhi Li Chuming Chen Yingxia Liu Zhichao Liang Zhiguo Cao Hai-Tao Zhang Ioannis Ch.Paschaldis Quanying Liu Jorge Goncalves Qiang Zhong Li Yan School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China Luxembourg Centre for Systems Biomedicine University of LuxembourgBelval L-4367Luxembourg Department of Plant Sciences University of CambridgeCambridge CB21TNUK Department of Emergency Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030China AMITA Health Saint Joseph Hospital Chicago ChicagoIL 60657USA Department of Anesthesiology Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030China Huazhong University of Science and Technology-Wuxi Research Institute Wuxi 214174China Division of Cardiology Department of Internal MedicineTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030China Institute of Health Informatics University College LondonLondon NW12DAUK Department of Biomedical Engineering Southern University of Science and TechnologyShenzhen 518055China Department of Infectious Diseases Shenzhen Key Laboratory of Pathogenic Microbiology and ImmunologyNational Clinical Research Center for Infectious DiseaseThe Third People’s Hospital of Shenzhen(Second Hospital Affiliated with the Southern University of Science and Technology)Shenzhen 518055China Department of Electrical and Computer Engineering&Division of Systems Engineering&Department of Biomedical Engineering Boston UniversityBostonMA 02215USA

Coronavirus disease 2019(COVID-19)has become a worldwide *** patients of COVID-19 suffer from a high mortality rate,motivating the development of convenient and practical methods that allow clinicians to promptly identify high-risk ***,we have developed a risk score using clinical data from 1479 inpatients admitted to Tongji Hospital,Wuhan,China(development cohort)and externally validated with data from two other centers:141 inpatients from Jinyintan Hospital,Wuhan,China(validation cohort 1)and 432 inpatients from The Third People’s Hospital of Shenzhen,Shenzhen,China(validation cohort 2).The risk score is based on three biomarkers that are readily available in routine blood samples and can easily be translated into a probability of *** risk score can predict the mortality of individual patients more than 12 d in advance with more than 90%accuracy across all ***,the Kaplan-Meier score shows that patients can be clearly differentiated upon admission as low,intermediate,or high risk,with an area under the curve(AUC)score of *** summary,a simple risk score has been validated to predict death in patients infected with severe acute respiratory syndrome coronavirus 2(SARS-CoV-2);it has also been validated in independent cohorts.

关键词： COVID-19 Risk score Mortality risk prediction

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An ab initio framework for understanding and controlling quantum fluctuations in complex light-matter systems

An ab initio framework for understanding and controlling qua...

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CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Rivera, Nicholas Uddin, Shiekh Zia Seyler, Devin Salamin, Yannick Sloan, Jamison Roques-Carmes, Charles Xu, Shutao Sander, Michelle Soljacic, Marin Department of Physics Harvard University CambridgeMA02138 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States E.L. Ginzton Laboratory Stanford University StanfordCA94305 United States Department of Electrical and Computer Engineering BU Photonics Center Boston University BostonMA02215 United States Division of Materials Science and Engineering Boston University BrooklineMA02446 United States Department of Biomedical Engineering Boston University BostonMA02215 United States

We develop a new general theory of quantum noise in photonics. As an example, we demonstrate strong quantum correlations and squeezing in supercontinuum generation. Our results enable overcoming quantum noise limits i... 详细信息

ISBN: (纸本)9781957171395

关键词： Supercontinuum generation

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High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System

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Journal of Bionic engineering 2022年第2期19卷 299-313页

作者： Yinlong Zhang Wei Liang Sichao Zhang Xudong Yuan Xiaofang Xia Jindong Tan Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China The School of Computer Science and Technology Xidian UniversityXi’an 710071China Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeKonxville 37996USA Department of Automation Technology ABB Corporate Research Sweden72178 VästerasSweden

Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured *** robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical *** paper introduces a novel calibration ***,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint ***,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent *** calibration has been evaluated on our collected visual inertial-manipulator *** systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method.

关键词： Bio-inspired robotic system Monocular camera IMU Manipulator Calibration

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Optimization and evaluation of motion sequences of an averaged human motion model by using kinematic techniques and new evaluation methods

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Current Directions in Biomedical engineering 2021年第2期7卷 566-569页

作者： Kitzig, Andreas Demmer, Julia Naroska, Edwin Stockmanns, Gudrun Viga, Reinhard Grabmaier, Anton Niederrhein University of Applied Sciences Faculty of Electrical Engineering and Computer Science Ambient Intelligence Laboratory Reinarzstr. 49 Krefeld 47805 Germany Niederrhein University of Applied Sciences Krefeld Germany University of Duisburg- Essen Department of Electronic Components and Circuits Duisburg Germany Duisburg Germany

Signal processing, pattern recognition as well as modelling and simulation require a large amount of reference data, both for the development of new methods and for their evaluation. Depending on the application, the availability of databases is rather low. In the field of biosignal processing with a focus on the functionalization of furniture for nursing and hospital facilities, a database from a motion capturing system (MoCap), and a method to generate averaged human motion sequences was presented in subsequent works by our research group. Evaluations revealed that the averaged motion sequences partly contain artifacts caused by the averaging and thus are not directly usable. To use the averaged motion sequences e.g., in simulation tasks, this paper presents an extension with kinematic methods to combine averaged motion sequences and to suppress and thus optimize inappropriate motion artifacts by error correction. To check whether the results are usable after the processing steps, four evaluation criteria are proposed. The evaluation of the resulting motion sequences shows that sequences are generated which do not fully correspond to human motion sequences but are well suited for simulation tasks. © 2021 by Walter de Gruyter Berlin/Boston.

关键词： Kinematics

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Multi-label advertising image classification using traditional deep neural networks and vision language models: dataset and annotation agreement method

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Multimedia Tools and Applications 2025年 1-30页

作者： Mir, Tatheer Hussain Wei, Jui-Cheng Simanjuntak, Mutiara Cheng, Wan-Shu Lee, Yi-Hsun Zhang, You-Chen Chen, Jia-Bin Dai, Hong-Jie Intelligent System Laboratory Department of Electrical Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Computer Science and Information Management Providence University Taichung Taiwan Research and Development Department Linker AI Co. Ltd Taipei Taiwan School of Post-Baccalaureate Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan National Institute of Cancer Research National Health Research Institutes Tainan Taiwan

Effectively classifying advertising images is crucial in targeting the right audience and maximizing marketing performance. To address this problem, this paper presents a multi-label advertising image classification study using popular deep-learning architectures. First, we compile a dedicated dataset for this task and evaluate the performance of traditional deep learning-based models based on the convolutional neural network (CNN) and vision transformer architectures. To ensure the quality of dataset annotations, we introduce an extended Krippendorf’s Alpha (α) method based on the Jaccard index to provide a reliable measure of inter-annotation agreement which can address the missing annotations and multiple labels to establish the dataset’s annotation consistency. Our results demonstrate that transformer-based architectures like ViT and Swin outperform the CNN-based model’s baseline and differential learning rate settings. Through the visualization analysis of saliency maps, we gain insights into the model’s decision-making processes and identify the factors influencing their predictions. Furthermore, we assess the impact of annotation quality on model performance, comparing models trained on different annotation reliability levels. Our results indicate that higher annotation consistency, as quantified by α-Jaccard, leads to improved model performance, emphasizing the importance of high-quality datasets in advertising image classification. Beyond traditional deep learning models, we explore the effectiveness of vision language models (VLMs) in this task by employing prompt engineering and comparing their performance with fine-tuned deep learning models. Our findings indicate that while VLMs provide richer contextual annotations, they suffer from over-classification tendencies, subjective biases, and significantly higher computational costs. In contrast, deep learning models remain a more efficient and scalable solution for structured, large-scale advertising classi

关键词： Advertising image Convolution neural network Krippendorf’s Alpha Learning rate configuration Marketing effectiveness Multi-label classification Vision Language Models Vision transformer

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Advances of wearable silicone rubber-based triboelectric nanogenerators:from manufacturing to application

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International Journal of Extreme Manufacturing 2025年第3期7卷 126-158页

作者： Dianlong Shen Taili Du Fangyang Dong Hu Cai Aziz Noor Xiannan Du Yongjiu Zou Chengkuo Lee Minyi Xu Dalian Key Laboratory of Marine Micro/Nano Energy and Self-Powered Systems Marine Engineering CollegeDalian Maritime UniversityDalian 116026People’s Republic of China State Key Laboratory of Maritime Technology and Safety Dalian 116026People’s Republic of China Collaborative Innovation Research Institute of Autonomous Ship Dalian Maritime UniversityDalian 116026People’s Republic of China Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117576Singapore

Wearable bioelectronic devices are rapidly evolving towards miniaturization and multifunctionality,with remarkable features such as flexibility and ***,achieving a sustainable power supply for wearable bioelectronic devices is still a great *** nanogenerators(TENGs)provide an efficient solution by converting irregular,low-frequency bioenergy from the human body into electrical *** sustainably powering wearable bioelectronics,the harvested electrical energy also carries rich information for human body *** this conversion process,the choice of material plays a crucial role in affecting the output performance of the *** various materials,silicone rubber(SR)stands out due to its exceptional plasticity,flexibility,comfortability and other favorable ***,with appropriate treatment,SR can achieve extreme functionalities such as high robustness,good stability,self-healing capabilities,rapid response,and *** this review,recent advances in wearable SR-based TENGs(SR-TENGs)are systematically reviewed with a focus on their application in different parts of the human *** that the manufacturing method of SR-TENGs largely determines its output performance and sensitivity,this paper introduces the design of SR-TENGs,including material selection,process modulation,and structure ***,this article discusses the current challenges in the SR-TENG fabrication technology and potential future directions,aiming to promote the effective development of SR-TENGs in biomechanical energy harvesting and self-powered sensing applications.

关键词： extreme function silicone rubber triboelectric nanogenerators wearable bioelectronics energy harvesting self-powered sensing fabrication methods

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Multi-Criteria Fuzzy-Based Decision Making Algorithm to Optimize the VHO Performance in Hetnets

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computers, Materials & Continua 2022年第1期70卷 323-341页

作者： A.Prithiviraj A.Maheswari D.Balamurugan Vinayakumar Ravi Moez Krichen Roobaea Alroobaea Saeed Rubaiee Sankar Sennan Department of CSE Sona College of TechnologySalem636005India Department of CSE Dr.M.G.R.Educational and Research InstituteChennai600095India Center for Artificial Intelligence PrinceMohammad Bin Fahd UniversityKhobarSaudi Arabia Faculty of CSIT Al-Baha UniversitySaudi Arabia ReDCAD laboratory University of SfaxTunisia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Industrial and Systems Engineering College of EngineeringUniversity of JeddahJaddahSaudi Arabia

Despite the seemingly exponential growth of mobile and wireless communication,this same technology aims to offer uninterrupted access to different wireless systems like Radio Communication,Bluetooth,and Wi-Fi to achieve better network connection which in turn gives the best quality of service(QoS).Many analysts have established many handover decision systems(HDS)to enable assured continuous mobility between various radio access *** is one of themost significant problems considered in wireless communication *** application needs a distinct QoS,so the network choice may shift *** achieve this objective and to choose the finest networks,it is important to select a best decision making algorithm that chooses the most effective network for every application that the user requires,dependent on QoS ***,the main goal of the proposed system is to provide an enhanced vertical handover(VHO)decision making programby using aMulti-CriteriaFuzzy-Based algorithm to choose the best *** Multi-Criteria algorithms and a Fuzzy-Based algorithm is implemented successfully for optimal network selection and also to minimize the probability of false ***,a double packet buffer is utilized to decrease the packet loss by 1.5%and to reduce the number of handovers up to 50%compared to the existing *** addition,the network setup has an optimized mobilitymanagement system to supervise the movement of the mobile nodes.

关键词： Vertical handover mobility management handover decision systems multi-criteria fuzzy logic QoS false handover

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CCT5: A Code-Change-Oriented Pre-Trained Model

arXiv

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arXiv 2023年

作者： Lin, Bo Liu, Yepang Wang, Shangwen Xia, Xin Liu, Zhongxin Mao, Xiaoguang College of Computer Science National University of Defense Technology Changsha China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Zhejiang University Hangzhou China Key Laboratory of Software Engineering for Complex Systems China Research Institute of Trustworthy Autonoumous Systems United Kingdom

Software is constantly changing, requiring developers to perform several derived tasks in a timely manner, such as writing a description for the intention of the code change, or identifying the defect-prone code changes. Considering that the cost of dealing with these tasks can account for a large proportion (typically around 70 percent) of the total development expenditure, automating such processes will significantly lighten the burdens of developers. To achieve such a target, existing approaches mainly rely on training deep learning models from scratch or fine-tuning existing pre-trained models on such tasks, both of which have weaknesses. Specifically, the former uses comparatively small-scale labelled data for training, making it difficult to learn and exploit the domain knowledge of programming language hidden in the large-amount unlabelled code in the wild;the latter is hard to fully leverage the learned knowledge of the pre-trained model, as existing pre-trained models are designed to encode a single code snippet rather than a code change (i.e., the difference between two code snippets). We propose to pre-train a model specially designed for code changes to better support developers in software maintenance. To this end, we first collect a large-scale dataset containing 1.5M+ pairwise data of code changes and commit messages. Based on these data, we curate five different tasks for pre-training, which equip the model with diverse domain knowledge about code changes. We fine-tune the pre-trained model, CCT5, on three widely-studied tasks incurred by code changes and two tasks specific to the code review process. Results show that CCT5 outperforms both conventional deep learning approaches and existing pre-trained models on these tasks. Copyright © 2023, The Authors. All rights reserved.

关键词： Domain Knowledge

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