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Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomography

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光：科学与应用（英文版） 2025年第2期14卷 490-508页

作者： Shiyi Cheng Shuaibin Chang Yunzhe Li Anna Novoseltseva Sunni Lin Yicun Wu Jiahui Zhu Ann C.McKee Douglas L.Rosene Hui Wang Irving J.Bigio David A.Boas Lei Tian Department of Electrical and Computer Engineering Boston UniversityBostonMA 02215USA Department of Electrical Engineering and Computer Sciences University of CaliforniaBerkeleyCA 94720USA Department of Biomedical Engineering Boston UniversityBostonMA 02215USA Department of Electrical and Computer Engineering Boston UniversityBostonMA 02215USA Department of Biomedical Engineering Boston UniversityBostonMA 02215USA Department of Computer Science Boston UniversityBostonMA 02215USA Boston University Alzheimer's Disease Research Center and CTE Center Boston University School of MedicineBostonMA 02118USA Department of Neurology Boston University School of MedicineBostonMA 02118USA VA Boston Healthcare System U.S.Department of Veteran AffairsBostonMA 02130USA Department of Pathology and Laboratory Medicine Boston University School of MedicineBostonMA 02118USA Department of Anatomy & Neurobiology Boston University School of MedicineBostonMAUSA Department of Radiology Athinoula A.Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMA 02129USA Department of Electrical and Computer Engineering Boston UniversityBostonMA 02215USA Department of Biomedical Engineering Boston UniversityBostonMA 02215USA Neurophotonics Center Boston UniversityBostonMA 02215USA

A major challenge in neuroscience is visualizing the structure of the human brain at different *** histology reveals micro-and meso-scale brain features but suffers from staining variability,tissue damage,and distortion,which impedes accurate 3D *** emerging label-free serial sectioning optical coherence tomography(S-OCT)technique offers uniform 3D imaging capability across samples but has poor histological interpretability despite its sensitivity to cortical ***,we present a novel 3D imaging framework that combines S-OCT with a deep-learning digital staining(DS)*** enhanced imaging modality integrates high-throughput 3D imaging,low sample variability and high interpretability,making it suitable for 3D histology *** develop a novel semi-supervised learning technique to facilitate DS model training on weakly paired images for translating S-OCT to Gallyas silver *** demonstrate DS on various human cerebral cortex samples,achieving consistent staining quality and enhancing contrast across cortical layer ***,we show that DS preserves geometry in 3D on cubic-centimeter tissue blocks,allowing for visualization of meso-scale vessel networks in the white *** believe that our technique has the potential for high-throughput,multiscale imaging of brain tissues and may facilitate studies of brain structures.

关键词： tomography serial imaging digital human brain coherence enhanced multiscale optical

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Steps Toward Industry 5.0:Building“6S”Parallel Industries With Cyber-Physical-Social Intelligence

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1692-1703页

作者： Xingxia Wang Jing Yang Yutong Wang Qinghai Miao Fei-Yue Wang Aijun Zhao Jian-Ling Deng Lingxi Li Xiaoxiang Na Ljubo Vlacic School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE Macao University of Science and Technology Macao 999078China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100098 State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China North Automatic Control Technology Institute Taiyuan 030006China China Huaneng Group Co. Ltd.Beijing 100031China Department of Electrical and Computer Engineering Indiana University-Purdue University Indianapolis(IUPUI)IndianapolisIN 46202 USA Department of Engineering University of CambridgeCambridgeCB21PZUK School of Engineering and Built Environment Griffith UniversityGold CoastQLD 4222Australia

Very recently,intensive discussions and studies on Industry 5.0 have sprung up and caused the attention of researchers,entrepreneurs,and policymakers from various sectors around the ***,there is no consensus on why and what is Industry 5.0 *** this paper,we define Industry 5.0from its philosophical and historical origin and evolution,emphasize its new thinking on virtual-real duality and human-machine interaction,and introduce its new theory and technology based on parallel intelligence(PI),artificial societies,computational experiments,and parallel execution(the ACP method),and cyber-physical-social systems(CPSS).Case studies and applications of Industry 5.0 over the last decade have been briefly summarized and analyzed with suggestions for its future *** believe that Industry 5.0 of virtual-real interactive parallel industries has great potentials and is critical for building smart *** are outlined to ensure a roadmap that would lead to a smooth transition from CPS-based Industry 4.0 to CPSS-based Industry 5.0 for a better world which is Safe in physical spaces,S ecure in cyberspaces,Sustainable in ecology,Sensitive in individual privacy and rights,Service for all,and Smartness of all.

关键词： ACP artificial intelligence CPS CPSS Industry 4.0 Industry 5.0 parallel industries parallel intelligence

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System- and Sample-agnostic Isotropic 3D Microscopy by Weakly Physics-informed, Domain-shift-resistant Axial Deblurring

arXiv

引用

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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Rethinking the visual cues in audio-visual speaker extraction

arXiv

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arXiv 2023年

作者： Li, Junjie Ge, Meng Pan, Zexu Cao, Rui Wang, Longbiao Dang, Jianwu Zhang, Shiliang Tianjin Key Laboratory of Cognitive Computing and Application College of Intelligence and Computing Tianjin University Tianjin China Department of Electrical and Computer Engineering National University of Singapore Singapore Institute of Data Science National University of Singapore Singapore Shenzhen Research Institute of Big Data Shenzhen China

The Audio-Visual Speaker Extraction (AVSE) algorithm employs parallel video recording to leverage two visual cues, namely speaker identity and synchronization, to enhance performance compared to audio-only algorithms. However, the visual front-end in AVSE is often derived from a pre-trained model or end-to-end trained, making it unclear which visual cue contributes more to the speaker extraction performance. This raises the question of how to better utilize visual cues. To address this issue, we propose two training strategies that decouple the learning of the two visual cues. Our experimental results demonstrate that both visual cues are useful, with the synchronization cue having a higher impact. We introduce a more explainable model, the Decoupled Audio-Visual Speaker Extraction (DAVSE) model, which leverages both visual cues. Copyright © 2023, The Authors. All rights reserved.

关键词： Extraction

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Human-Guided Artificial Intelligence (HGAI), a Framework for Overcoming AI's Blind Spots

Human-Guided Artificial Intelligence (HGAI), a Framework for...

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2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Chen, Ziyu Kelil, Selam B. Naser, Mohammad Y. M. Metcalfe, Jason S. Bhattacharya, Sylvia Kennesaw State University Electrical & Computer Engineering Department Marietta United States Kennesaw State University Computer Science Department Marietta United States Us Devcom Army Research Laboratory Aberdeen Proving Ground Aberdeen United States Kennesaw State University Engineering Technology Department Marietta United States

ISBN: (纸本)9798331504847

Artificial Intelligence (AI) systems frequently exhibit systematic blind spots, often referred to as hallucinations in Large Language Models (LLMs), posing risks in high-stakes applications such as autonomous systems, security, and military operations. This paper explores how human intuitive responses, along with conscious reasoning processes, can be integrated to mitigate AI blind spots and enhance decision-making effectiveness within Human-AI teams. We introduce Human-Guided Artificial Intelligence (HGAI) as a framework for achieving this goal. Specifically, we examine the role of System-1 intuitive processing, as captured through physiological signals such as electroencephalography (EEG) and electrocardiography (ECG), System-2 reasoning-based decision-making, and Multi-Modal Fusion (MMF) mechanisms while assessing the knowledge required to develop more reliable, context-aware, and ethically aligned intelligent decision-making systems for highly complex environments. © 2025 IEEE.

关键词： Artificial Intelligence (AI) Human-AI Teams Multi-Modal Fusion (MMF) Physiological Signals

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Adaptive Frequency Hopping for 5G New Radio mMTC Security

Adaptive Frequency Hopping for 5G New Radio mMTC Security

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IEEE International Conference on Industrial Technology (ICIT)

作者： Wai Ming Chan Hyuck M. Kwon Rémi A. Chou David J. Love Sonia Fahmy Syed Rafiul Hussain Sang Wu Kim Chris Vander Valk Christopher G. Brinton Vuk Marojevic Khanh D. Pham Taejoon Kim Department of Electrical Engineering and Computer Science The University of Kansas Lawrence KS USA Department of Electrical and Computer Engineering Wichita State University Wichita KS USA School of Computing Wichita State University Wichita KS USA Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Computer Science Purdue University West Lafayette IN USA Department of Computer Science and Engineering The Pennsylvania State University State College PA USA Department of Electrical and Computer Engineering Iowa State University Ames IA USA Raytheon BBN Cambridge MA USA Department of ECE Mississippi State University Starkville MS USA Air Force Research Laboratory Albuquerque NM USA

3GPP standards (e.g., LTE and 5G New Radio (NR)) have revolutionized commercial broadband access. Unfortunately, the openness of $\mathbf{3GPP}$ specifications and high-level of adaptability make fifth-generation (5G) networks increasingly sensitive to unsophisticated attacks in the network. While 5G NR has introduced frequency hopping (FH) for massive machine-type communications $(\mathbf{mMTC})$ , there has not been a unified approach to designing the FH patterns in practical 5G systems. In this paper, we investigate the multi-user FH design problem at the physical resource grid of the 5G communication networks. We present various criteria for FH pattern design and propose two algorithms that are implementable with low complexity. The first scheme utilizes known interference patterns to design a set of user equipment (UE) FH patterns that are immune to interfering attacks. The second scheme leverages interference statistics and minimizes the expected number of hits by the interferer. Through numerical simulations and analytical modeling, we demonstrate the efficacy of the proposed schemes, which outperform the uniform FH pattern and achieve near-optimal performance.

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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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GSLB: The Graph Structure Learning Benchmark 37

GSLB: The Graph Structure Learning Benchmark

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37th Conference on Neural Information Processing Systems, NeurIPS 2023

作者： Li, Zhixun Wang, Liang Sun, Xin Luo, Yifan Zhu, Yanqiao Chen, Dingshuo Luo, Yingtao Zhou, Xiangxin Liu, Qiang Wu, Shu Yu, Jeffrey Xu Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Center for Research on Intelligent Perception and Computing State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China Department of Automation University of Science and Technology of China China School of Cyberspace Security Beijing University of Posts and Telecommunications China Department of Computer Science University of California Los Angeles United States Heinz College of Information Systems and Public Policy Machine Learning Department School of Computer Science Carnegie Mellon University United States

ISBN: (纸本)9781713899921

Graph Structure Learning (GSL) has recently garnered considerable attention due to its ability to optimize both the parameters of Graph Neural Networks (GNNs) and the computation graph structure simultaneously. Despite the proliferation of GSL methods developed in recent years, there is no standard experimental setting or fair comparison for performance evaluation, which creates a great obstacle to understanding the progress in this field. To fill this gap, we systematically analyze the performance of GSL in different scenarios and develop a comprehensive Graph Structure Learning Benchmark (GSLB) curated from 20 diverse graph datasets and 16 distinct GSL algorithms. Specifically, GSLB systematically investigates the characteristics of GSL in terms of three dimensions: effectiveness, robustness, and complexity. We comprehensively evaluate state-of-the-art GSL algorithms in node- and graph-level tasks, and analyze their performance in robust learning and model complexity. Further, to facilitate reproducible research, we have developed an easy-to-use library for training, evaluating, and visualizing different GSL methods. Empirical results of our extensive experiments demonstrate the ability of GSL and reveal its potential benefits on various downstream tasks, offering insights and opportunities for future research. The code of GSLB is available at: https://***/GSL-Benchmark/GSLB. © 2023 Neural information processing systems foundation. All rights reserved.

关键词： Graphic methods

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Visualization of relative cochlear motions using high resolution optical coherence microscopy

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Hearing research 2025年 464卷 109311页

作者： Page, Scott Ghaffari, Roozbeh Freeman, Dennis M. Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge MA United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA United States

Despite enormous progress in understanding the electro-mechanical properties of outer hair cells and the molecular basis of these properties, less is known about the relative motion of the organ of Corti and accessory structures that shape cochlear responses to acoustic stimulation. Here, we characterize absolute and relative motions of apical regions of the excised gerbil cochleae using a custom Doppler optical coherence microscopy (DOCM) system. Responses to sinusoidal stimuli show nanometer-scale motions of the tectorial membrane (TM), organ of Corti structures (e.g. outer hair cells, pillar cells), and basilar membrane in the apical turn of the cochlea. Motion-magnified analysis reveals rotations about the inner pillar cells at nearly constant phase, whereas TM motion lags that of the underlying cells by as much as 0.1 radians. Our DOCM results demonstrate a new technique capable of concurrent high resolution anatomical imaging and nanometer-scale motion analysis of cellular and acellular structures in response to stapes stimulation, enabling investigations of relative cochlear motions and feedback mechanisms. © 2025

关键词： Cochlea Cochlea movies Differential motion Gerbil Cochlea Mammalian Cochlea Organ of Corti animation Relative motion Spectral domain Time-domain

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Genetic and phenotypic relationships between coronary atherosclerotic heart disease and electrocardiographic traits

Genetic and phenotypic relationships between coronary athero...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Wang, Xinfeng Zhang, Haoyang Xiu, Xuehao Qi, Mengling Yang, Yuedong Zhao, Huiying Sun Yat-sen University Key Laboratory of Machine Intelligence and Advanced Computing of Moe School of Computer Science and Engineering Guangzhou China Sun Yat-sen Memorial Hospital Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation Department of Medical Research Center Guangzhou China

ISBN: (纸本)9781665468190

Observational studies have revealed that Coronary Atherosclerotic Heart Disease (CAHD) is associated with abnormal electrocardiogram (ECG) traits. However, it remains unclear whether there are genetic correlations between ECG and CAHD. Here, we explored genetic correlations and putative causal relationships between CAHD and ECG by performing Mendelian randomization (MR) and Polygenic risk score (PRS) analyses on the summary statistics from a large-scale genome-wide association study (GWAS) for CAHD (FinnGen: Ncase 23363, Ncontrol 187840) and ECG traits (UK Biobank: Ncase=1137, Ncontrol=40823). Results showed a causal genetic relationship between CAHD and six ECG traits in the lead V6. These ECG traits combining with age and gender have predicted CAHD risk with an AUC of 0.76. Further summary data-based Mendelian randomization (SMR) analysis identified 11 risk genes associated with the causality between CAHD and ECG. Thus, the revealed putative causal effects of CAHD on ECG traits provide genetic evidence to support the importance of monitoring CAHD risk through the ECG. © 2022 IEEE.

关键词： Electrocardiograms

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