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arXiv 2024年

作者： Ota, Rikuto Kobayashi, Keito Hayakawa, Keisuke Kanai, Shun Çamsarı, Kerem Y. Ohno, Hideo Fukami, Shunsuke Laboratory for Nanoelectronics and Spintronics Research Institute of Electrical Communication Tohoku University Sendai980-8577 Japan Graduate School of Engineering Tohoku University Sendai980-0845 Japan Center for Science and Innovation in Spintronics Tohoku University Sendai980-8577 Japan WPI-Advanced Institute for Materials Research Tohoku University Sendai980-8577 Japan PRESTO Japan Science and Technology Agency Kawaguchi332-0012 Japan Division for the Establishment of Frontier Sciences Tohoku University Sendai980-8577 Japan National Institutes for Quantum Science and Technology Takasaki370-1207 Japan Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States Center for Innovative Integrated Electronic Systems Tohoku University Sendai980-0845 Japan Inamori Research Institute for Science Kyoto600-8411 Japan

Stochastic magnetic tunnel junctions (s-MTJ) is a promising component of probabilistic bit (p-bit), which plays a pivotal role in probabilistic computers. For a standard cell structure of the p-bit, s-MTJ is desired to be insensitive to voltage across the junction over several hundred millivolts. In conventional s-MTJs with a reference layer having a fixed magnetization direction, however, the stochastic output significantly varies with the voltage due to spin-transfer torque (STT) acting on the stochastic free layer. In this work, we study a s-MTJ with a "double-free-layer" design theoretically proposed earlier, in which the fixed reference layer of the conventional structure is replaced by another stochastic free layer, effectively mitigating the influence of STT on the stochastic output. We show that the key device property characterized by the ratio of relaxation times between the high- and low-resistance states is one to two orders of magnitude less sensitive to bias voltage variations compared to conventional s-MTJs when the top and bottom free layers are designed to possess the same effective thickness. This work opens a pathway for reliable, nanosecond-operation, high-output, and scalable spintronics-based p-bits. © 2024, CC BY.

关键词： Tunnel junctions

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Diphlorethohydroxycarmalol inhibits Müller cell gliosis by disrupting CXCR4/CXCL12 interaction in violet-blue light-induced retinal phototoxicity

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Heliyon 2025年第4期11卷 e42475页

作者： Son, Myeongjoo Nagahawatta, Dineth Pramuditha Jo, Hang-Chan Jeon, You-Jin Ryu, Bomi Kim, Dae Yu Department of Anatomy & Cell Biology School of Medicine Kangwon National University Chuncheon 24341 South Korea Brain Health Research Laboratory Institute of Medical Science Kangwon National University College of Medicine Chuncheon 24341 South Korea Department of Marine Life Sciences Jeju National University Jeju 63243 South Korea Center for Sensor Systems Inha University Incheon 22212 South Korea Department of Electrical and Computer Engineering College of Engineering Inha University Incheon 22212 South Korea Marine Science Institute Jeju National University Jeju 63333 South Korea Major of Food Science and Nutrition Pukyong National University Busan 48513 South Korea Inha Research Institute for Aerospace Medicine Inha University Incheon 22212 South Korea

Müller gliosis is a complex process that impairs the ability of retinal Müller glial cells to respond to various forms of retinal injury or disease, leading to retinal damage. Blue light (BL) exposure is a known cause of retinal damage. In this study, we aimed to investigate the potential of DPHC in inhibiting Müller gliosis in models of BL-exposure. We conducted in silico binding analysis to evaluate the binding of DPHC to CXCR4. Then, we developed in vitro and in vivo experimental models to assess the effects of DPHC and BL exposure on Müller gliosis using MIO-M1 cells and zebrafish. Our findings show that DPHC can suppress the Müller gliosis process in BL-exposed MIO-M1 cells in vitro and in BL-exposed zebrafish in vivo. In silico molecular docking, we identified CXCR4 as the target of active site 1 of DPHC. In BL-exposed MIO-M1 cells, DPHC inhibited CXCR4 activity and altered the expression of Müller gliosis markers and NF-κB-related ERK and AKT signaling. In BL-exposed zebrafish, DPHC prevented retinal thickness reduction and inhibited CXCR4 expression and retinal cell apoptosis. This study suggests that DPHC could be a potential therapeutic agent for retinal diseases involving Müller gliosis. By inhibiting CXCR4 activity, DPHC downregulates the ERK/AKT/NF-κB pathway, reducing retinal cell apoptosis and altered expression of Müller gliosis markers. These findings highlight the potential of natural bioactive compounds for treating various diseases, and further research should investigate the therapeutic potential of DPHC and its derivatives. © 2025

关键词： CXCR4 signaling Diphlorethohydroxycarmalol (DPHC) Müller gliosis Retinal Müller glial cells Retinal phototoxicity Violet-blue 405 nm light

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A RIS-Based Vehicle DOA Estimation Method With Integrated Sensing and Communication System

arXiv

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arXiv 2022年

作者： Chen, Zhimin Chen, Peng Guo, Ziyu Zhang, Yudong Wang, Xianbin The School of Electronic and Information Shanghai Dianji University Shanghai201306 China State Key Laboratory of Integrated Services Networks Xidian University Xi’an710071 China The State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China The School of Information Science and Technology Fudan University Shanghai200433 China The State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai200433 China The School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom School of Computer Science and Engineering Southeast University Nanjing210096 China The Department of Electrical and Computer Engineering Western University LondonONN6A 5B9 Canada

With the development of intelligent transportation, growing attention has been received to integrated sensing and communication (ISAC) systems. In this paper, we formulate a novel passive sensing technique to obtain information on the vehicle’s direction of arrival (DOA) using reconfigurable intelligent surfaces (RIS). A novel estimation method is proposed in the scenario with a receiver using only one full-functional channel, where multiple measurements for the DOA estimation are achieved by controlling the reflection matrix (measurement matrix) in the RIS. Moreover, different from the existing estimation methods, we also consider the interference signals introduced by wireless communication in the ISAC system. Then, we propose a novel atomic norm-based method to remove the interference signals and reconstruct the sparse signal. Additionally, a novel Hankel-based multiple signal classification (MUSIC) method is formulated to obtain the DOA information after the interference removal. To reduce the interference signals more efficiently and improve the performance of the sparse reconstruction, we optimize the measurement matrix to improve the signal-to-interference-plus-noise ratio (SINR). Finally, the theoretical Cram’er-Rao lower bound (CRLB) is derived for the ISAC system on the vehicle DOA estimation. Simulation results show that the proposed method can achieve better performance in the DOA estimation, and the corresponding CRLB with different distributions of the sensing nodes are shown. The code for the proposed method is available online https://***/chenpengseu/***. Copyright © 2022, The Authors. All rights reserved.

关键词： Vehicles

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Identification of switched linear systems: Persistence of excitation and numerical algorithms

arXiv

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arXiv 2021年

作者： Mu, Biqiang Chen, Tianshi Cheng, Changming Bai, Er-Wei Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China State Key Laboratory of Mechanical Systems and Vibration Shanghai Jiaotong University Shanghai China Department of Electrical and Computer Engineering University of Iowa Iowa CityIA52242 United States

This paper investigates two issues on identification of switched linear systems: persistence of excitation and numerical algorithms. The main contribution is a much weaker condition on the regressor to be persistently exciting that guarantees the uniqueness of the parameter sets and also provides new insights in understanding the relation among different subsystems. It is found that for uniquely determining the parameters of switched linear systems, the minimum number of samples needed derived from our condition is much smaller than that reported in the literature. The secondary contribution of the paper concerns the numerical algorithm. Though the algorithm is not new, we show that our surrogate problem, relaxed from an integer optimization to a continuous minimization, has exactly the same solution as the original integer optimization, which is effectively solved by a block-coordinate descent algorithm. Moreover, an algorithm for handling unknown number of subsystems is proposed. Several numerical examples are illustrated to support theoretical analysis. Copyright © 2021, The Authors. All rights reserved.

关键词： Integer programming

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Robust Internal Model Control Boosts PMSM Performance with Fractional Order Vector Control

Robust Internal Model Control Boosts PMSM Performance with F...

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International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Tassadit Chekari Arezki Fekik Ahmad Taher Azar Saim Ahmed Abdelghani Djeddi Nashwa Ahmad Kamal Chakib Ben Njima L2CSP Laboratory Mouloud MAMMERI University of Tizi-Ouzou Algeria Mhamed Bougara University of Boumerdes Algeria Department of Electrical Engineering University Akli Mohand Oulhadj-Bouria Algeria Nantes Université École Centrale Nantes CNRS LS2N Nantes France College of Computer and Information Sciences Prince Sultan University Riyadh Saudi Arabia Automated Systems and Soft Computing Lab (ASSCL) Prince Sultan University Riyadh Saudi Arabia Faculty of Computers and Artificial Intelligence Benha University Benha Egypt Faculty of Sciences and Technology Echahid Cheikh Larbi Tebessi University Tebessa Algeria Faculty of Engineering Cairo University Giza Egypt University of Sousse Tunisia

ISBN: (数字)9798350361025

ISBN: (纸本)9798350361032

In this paper, a combination of fractional order control and a classical vector control scheme is proposed to drive the PMSM speed. The new proposed control scheme with fractional order property is based on IMC structure which is known for its robustness to modelling error and Bode’s ideal transfer function chosen as the reference model which exhibits iso-damping property. Simulation results show that the proposed control scheme tracks the PMSM speed at specified values and compensates the effect of load torque. Moreover, the time constant and fractional order of the Bode’s ideal transfer function can be used as tuning parameters to improve the PMSM speed and current responses.

关键词： Resistance Torque Simulation Transfer functions Stators Robustness Inverters

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Triangle counting accelerations: From algorithm to in-memory computing architecture

arXiv

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arXiv 2021年

作者： Wang, Xueyan Yang, Jianlei Zhao, Yinglin Jia, Xiaotao Yin, Rong Chen, Xuhang Qu, Gang Zhao, Weisheng MIIT Key Laboratory of Spintronics School of Integrated Circuit Science and Engineering Beihang University Beijing100191 China Beihang University Beijing100191 China The Institute of Information Engineering Chinese Academy of Sciences Beijing China The Department of Electrical and Computer Engineering Institute for Systems Research University of Maryland College ParkMD20742 United States

Triangles are the basic substructure of networks and triangle counting (TC) has been a fundamental graph computing problem in numerous fields such as social network analysis. Nevertheless, like other graph computing problems, due to the high memory-computation ratio and random memory access pattern, TC involves a large amount of data transfers thus suffers from the bandwidth bottleneck in the traditional Von-Neumann architecture. To overcome this challenge, in this paper, we propose to accelerate TC with the emerging processing-in-memory (PIM) architecture through an algorithm-architecture co-optimization manner. To enable the efficient in-memory implementations, we come up to reformulate TC with bitwise logic operations (such as AND), and develop customized graph compression and mapping techniques for efficient data flow management. With the emerging computational Spin-Transfer Torque Magnetic RAM (STT-MRAM) array, which is one of the most promising PIM enabling techniques, the device-to-architecture co-simulation results demonstrate that the proposed TC in-memory accelerator outperforms the state-of-the-art GPU and FPGA accelerations by 12.2× and 31.8×, respectively, and achieves a 34× energy efficiency improvement over the FPGA accelerator. Copyright © 2021, The Authors. All rights reserved.

关键词： Data transfer

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ReBoc: Accelerating Block-Circulant Neural Networks in ReRAM

ReBoc: Accelerating Block-Circulant Neural Networks in ReRAM

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Design, Automation and Test in Europe Conference and Exhibition

作者： Yitu Wang Fan Chen Linghao Song C. -J. Richard Shi Hai Helen Li Yiran Chen State Key Laboratory of ASIC and Systems Fudan University Shanghai China Department of Electrical and Computer Engineering Duke University Durham NC U.S.A.

ISBN: (数字)9783981926347

ISBN: (纸本)9781728144689

Deep neural networks (DNNs) emerge as a key component in various applications. However, the ever-growing DNN size hinders efficient processing on hardware. To tackle this problem, on the algorithmic side, compressed DNN models are explored, of which block-circulant DNN models are memory efficient and hardware-friendly; on the hardware side, resistive random-access memory (ReRAM) based accelerators are promising for in-situ processing of DNNs. In this work, we design an accelerator named ReBoc for accelerating block-circulant DNNs in ReRAM to reap the benefits of light-weight models and efficient in-situ processing simultaneously. We propose a novel mapping scheme which utilizes Horizontal Weight Slicing and Intra-Crossbar Weight Duplication to map block-circulant DNN models onto ReRAM crossbars with significant improved crossbar utilization. Moreover, two specific techniques, namely Input Slice Reusing and Input Tile Sharing are introduced to take advantage of the circulant calculation feature in block- circulant DNNs to reduce data access and buffer size. In REBOC, a DNN model is executed within an intra-layer processing pipeline and achieves respectively 96× and 8.86× power efficiency improvement compared to the state-of-the-art FPGA and ASIC accelerators for block-circulant neural networks. Compared to ReRAM-based DNN accelerators, REBOC achieves averagely 4.1× speedup and 2.6× energy reduction.

关键词： Computational modeling Hardware Matrix converters Biological neural networks Field programmable gate arrays Memory management

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Pre-Chirper Free Nonlinear Fiber Amplifier Generating Tunable Picosecond Pulses for Coherent Anti-Stokes Raman Imaging

Pre-Chirper Free Nonlinear Fiber Amplifier Generating Tunabl...

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Jiaying Li Jiamei Wu Kangwen Yang Qiang Hao Minbiao Ji Ming Yan Kun Huang Heping Zeng Shanghai Key Laboratory of Modern Optical System and Engineering Research Center of Optical Instrument and System Ministry of Education School of Optical Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China State Key Laboratory of Surface Physics and Department of Physics Human Phenome Institute Multiscale Research Institute of Complex Systems Academy for Engineering and Technology Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education) Fudan University Shanghai China State Key Laboratory of Precision Spectroscopy East China Normal University Shanghai China Chongqing Institute of East China Normal University Chongqing China Jinan Institute of Quantum Technology Jinan China

A pre-chirper free, core-pumped nonlinear fiber amplifier was demonstrated to generate parabolic pulse with spectral bandwidth of 53 nm, these pulses were filtered and passively synchronized for conducting coherent an...

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A scalable deep attention mechanism of instance segmentation for the investigation of chromosome

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SLAS Technology 2025年 33卷 100306页

作者： Umbreen, Neelam Ali, Sara Sajid, Hasan Ayaz, Yasar Alsenan, Shrooq Nam, Yunyoung Kim, So Yeon Sial, Muhammad Baber Islamabad Pakistan Suzhou Industrial Park Monash Research Institute of Science and Technology Suzhou215000 China Laboratory Islamabad Pakistan Islamabad Pakistan Information Systems Department College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Computer Science and Engineering Soonchunhyang University Asan31538 Korea Republic of School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China Department of Artificial Intelligence Ajou University Suwon Korea Republic of Department of Software and Computer Engineering Ajou University Suwon Korea Republic of

Chromosome segmentation in metaphase images is a critical yet challenging task in cytogenetics and genomics due to the inherent complexity, variability in chromosome shapes, and the scarcity of high-quality annotated datasets. This study proposes a robust instance segmentation framework that integrates an automated annotation pipeline with an enhanced deep learning architecture to address these challenges. A novel dataset is introduced, comprising metaphase images and corresponding karyograms, annotated with precise instance segmentation information across 24 chromosome classes in COCO format. To overcome the labor-intensive manual annotation process, a feature-based image registration technique leveraging SIFT and homography is employed, enabling the accurate mapping of chromosomes from karyograms to metaphase images and significantly improving annotation quality and segmentation performance. The proposed framework includes a custom Mask R-CNN model enhanced with an Attention-based Feature Pyramid Network (AttFPN), spatial attention mechanisms, and a LastLevelMaxPool block for superior multi-scale feature extraction and focused attention on critical regions of the image. Experimental evaluations demonstrate the model's efficacy, achieving a mean average precision (mAP) of 0.579 at IoU = 0.50:0.95, surpassing the baseline Mask R-CNN and Mask R-CNN with AttFPN by 3.94% and 5.97% improvements in mAP and AP50, respectively. Notably, the proposed architecture excels in segmenting small and medium-sized chromosomes, addressing key limitations of existing methods. This research not only introduces a state-of-the-art segmentation framework but also provides a benchmark dataset, setting a new standard for chromosome instance segmentation in biomedical imaging. The integration of automated dataset creation with advanced model design offers a scalable and transferable solution, paving the way for tackling similar challenges in other domains of biomedical and cytogenetic imagi

关键词： Molecular imaging

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Asymmetric Heat Transfer with Linear Conductive Metamaterials

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Physical Review Applied 2023年第3期20卷 034013-034013页

作者： Yishu Su Ying Li Minghong Qi Sebastien Guenneau Huagen Li Jian Xiong Center for Composite Materials and Structures Harbin Institute of Technology Harbin 150001 China Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou 310027 China International Joint Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang The Electromagnetics Academy of Zhejiang University Zhejiang University Haining 314400 China UMI 2004 Abraham de Moivre-CNRS Imperial College London London SW7 2AZ United Kingdom Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore

Asymmetric heat-transfer systems, often referred to as thermal diodes or thermal rectifiers, have garnered increasing interest due to their wide range of application possibilities. Most of those previous macroscopic asymmetric thermal devices either resort to nonlinear thermal conductivities with strong temperature dependence that may be quite limited by or fixed in natural materials or rely on active modulation that necessitates auxiliary energy payloads. Here, we establish a straightforward strategy of passively realizing asymmetric heat transfer with linear conductive materials. The strategy also introduces an interrogative perspective into the previous design of passive asymmetric heat transfer utilizing nonlinear thermal conductivity, correcting the misconception that thermal rectification is impossible with separable nonlinear thermal conductivity. The nonlinear-perturbation mode can be versatilely engineered to produce an effective and wide-ranging perturbation in heat conduction, which imitates and bypasses intrinsic thermal nonlinearity constraints set by naturally occurring counterparts. Independent experimental characterizations of surface thermal radiation and thermal convection verify that heat exchange between a graded linear thermal metamaterial and the ambient surroundings can be tailored to achieve macroscopic asymmetric heat transfer. Our work is envisaged to inspire conceptual models for heat-transfer control, serving as a robust and convenient platform for advanced thermal management and thermal computation.

关键词： Heat radiation Heat transfer Metamaterials Thermal conductivity

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