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作者： Ayoub Charef Zahi Jarir Mohamed Quafafou LAMIGEP Research Laboratory EMSI Moroccan School of Engineering Sciences Marrakech Laboratory of Computer Systems Engineering (LISI) Cadi Ayyad University Marrakech Marrakech Morocco Department of Computer Science University of Aix-Marseille Marseille France

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

This study examines the safety behaviors of delivery and private motorcycle riders in Marrakech, Morocco, with a particular focus on mobile phone distractions. Data were collected over a two-week period at five key intersections, recording 5731 riders during peak traffic hours. Trained observers captured rider characteristics, traffic context, and unsafe behaviors at different times of day morning, noon, and evening to account for variations in traffic conditions. Decision tree analysis was used to explore the relationships between rider type, road conditions, time of day, gender, and mobile phone usage while riding. The findings revealed that private riders were more likely to use mobile phones while riding compared to delivery riders. Unsafe behaviors were influenced by environmental factors, rider demographics, and the timing of the behaviors. Significant differences in behavior were observed between private and delivery riders, with gender also playing a role in safety practices. These results highlight the need for targeted interventions, including educational campaigns to address mobile phone and policies designed for specific rider groups.

关键词： Visualization Head Motorcycles Mobile handsets Weaving Road safety Safety Timing Decision trees Vehicle dynamics

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Orchestrated desaturation reprogramming from stearoyl-CoA desaturase to fatty acid desaturase 2 in cancer epithelial-mesenchymal transition and metastasis

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Cancer Communications 2025年第3期45卷 245-280页

作者： Zhicong Chen Yanqing Gong Fukai Chen Hyeon Jeong Lee Jinqin Qian Jing Zhao Wenpeng Zhang Yamin Li Yihui Zhou Qiaobing Xu Yu Xia Liqun Zhou Ji-Xin Cheng Department of Obstetrics and Gynecology Center for Reproductive MedicineGuangdong Provincial Key Laboratory of Major Obstetric DiseasesGuangdong Provincial Clinical Research Center for Obstetrics and GynecologyGuangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal MedicineThe Third Affiliated HospitalGuangzhou Medical UniversityGuangzhouGuangdongP.R.China Department of Biomedical Engineering Department of Electrical and Computer EngineeringPhotonics CenterBoston UniversityBostonMassachusettsUSA Department of Urology Peking University First HospitalBeijingP.R.China College of Biomedical Engineering&Instrument Science Key Laboratory for Biomedical Engineering of Ministry of EducationZhejiang UniversityHangzhouZhejiangP.R.China MOE Key Laboratory of Bioorganic Phosphorus Chemistry&Chemical Biology Department of ChemistryTsinghua UniversityBeijingP.R.China State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision InstrumentTsinghua UniversityBeijingP.R.China Department of Biomedical Engineering Tufts UniversityMedfordMassachusettsUSA

Background:Adaptative desaturation in fatty acid(FA)is an emerging hallmark of cancer metabolic *** such as stearoyl-CoA desaturase(SCD)and fatty acid desaturase 2(FADS2)have been implicated in multiple cancers,and their dominant and compensatory effects have recently been ***,how tumors initiate and sustain their self-sufficient FA desaturation to maintain phenotypic transition remains *** study aimed to explore the molecular orchestration of SCD and FADS2 and their specific reprogramming mechanisms in response to cancer ***:The potential interactions between SCD and FADS2 were explored by bioinformatics analyses across multiple cancer cohorts,which guided subsequent functional and mechanistic *** expression levels of desaturases were investigated with online datasets and validated in both cancer tissues and cell *** desaturation activities were characterized through various isomer-resolved lipidomics methods and sensitivity assays using desaturase ***-situ lipid profilingwas conducted using multiplex stimulated Raman scattering *** assays were performed both in vitro and in vivo,with RNA-sequencing employed for the mechanism ***:After integration of the RNA-protein-metabolite levels,the data revealed that a reprogramming fromSCD-dependent to FADS2-dependent desaturation was linked to cancer epithelial-mesenchymal transition(EMT)and progression in both patients and cell ***2 overexpression and SCD suppression concurrently maintained EMT plasticity.A FADS2/β-catenin selfreinforcing feedback loop facilitated the degree of lipid unsaturation,membrane fluidity,metastatic potential and EMT ***,SCD inhibition triggered a lethal apoptosis but boosted survival plasticity by inducing EMT and enhancing FA uptake via adenosine monophosphate-activated protein kinase ***,this desaturation reprogramming increased tra

关键词： metabolic reprogramming stearoyl-CoA desaturase fatty acid desaturase 2 epithelialmesenchymal transition cancer metastasis

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Modular Multilevel DC-DC Converter with Inherent Bipolar Operation Capability for Resilient Bipolar MVDC Grids

Modular Multilevel DC-DC Converter with Inherent Bipolar Ope...

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作者： Zhao, Shanshan Chen, Yu Cui, Shenghui Hu, Jingxin State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology China Seoul National University Department of Electrical and Computer Engineering Korea Republic of Institute for Power Generation and Storage Systems E. on Energy Research Center RWTH Aachen University Germany

Bipolar medium-voltage dc (MVDC) distribution systems are of great interests nowadays due to its high availability and reliability. A bipolar MVDC grid can be established by the installation of power-balancers or directly by converters with inherent bipolar operation capability to avoid the extra cost and volume. Therefore, this paper proposes a modular multilevel dc-dc converter (MMDC) with inherent bipolar operation capability for the interconnection of bipolar MVDC grids and LVDC girds. Considering that the MMDC is normally only capable of operating with monopole MVDC distribution systems due to the symmetric structure and operation scheme, a center-Tapped high-frequency interface transformer is employed on the MV side of the MMDC. Based on the concept of the flux dc-bias cancellation, a dedicated operation method is proposed, whereby the power flows of the two MVDC poles can be regulated independently with a simple control scheme, and no penalty of increased current rating is imposed on the semiconductor devices or the interface transformer compared to the conventional MMDC with monopole operation. Additionally, the MMDC can realize single-pole operation in case one pole is faulty and deliver at least 50% of the rated power capacity, which significantly enhance the reliability and availability of the power delivery. The validity of the proposed bipolar operation scheme of the MMDC has been verified by both simulations and experiments with a down-scale prototype. © 2017 CPSS.

关键词： Poles

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Multiuser Communication Aided by Movable Antenna 24

Multiuser Communication Aided by Movable Antenna

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24th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2023

作者： Zhu, Lipeng Ma, Wenyan Ning, Boyu Zhang, Rui University of Electronic Science and Technology of China National Key Laboratory of Science and Technology on Communications 611731 China The Chinese University of HongKong Shenzhen Research Institute of Big Data Shenzhen518172 China National University of Singapore Department of Electrical and Computer Engineering Singapore117583 Singapore

ISBN: (纸本)9781665496261

This paper investigates the multiuser communication aided by movable antenna (MA) via antenna position optimization, where the uplink transmission from multiple user terminals (UTs) each equipped with a single MA to a base station (BS) with a fixed-position antenna (FPA) array is considered. Specifically, we formulate an optimization problem for minimizing the total transmit power of UTs, subject to a minimum-achievable-rate requirement for each UT, where the positions of MAs and the transmit powers of UTs, as well as the receive combining matrix at the BS are jointly optimized. To solve this non-convex optimization problem, we first express the combining matrix of the BS and the total transmit power of UTs as a function of the MAs' position vectors, which are then optimized by using the gradient descent method in an iterative manner. Simulation results demonstrate that compared to conventional FPA systems, the proposed MA-enhanced multiple access systems can significantly decrease the total transmit power of UTs by moving antennas within small regions of several-wavelength size. © 2023 IEEE.

关键词： Convex optimization

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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case

Optimal Linear Deception Attacks on Remote State Estimation ...

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IEEE Conference on Decision and Control

作者： Jun Shang Hanwen Zhang Jing Zhou Tongwen Chen Department of Control Science and Engineering Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems and Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack’s stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback–Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples.

关键词： Wireless communication Measurement Technological innovation System performance Kalman filters State estimation Intelligent sensors

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Automatic Scene Generation: State-of-the-Art Techniques, Models, Datasets, Challenges, and Future Prospects

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IEEE Access 2025年 13卷 95753-95796页

作者： Ahmed Fime, Awal Mahmud, Saifuddin Das, Arpita Islam, Md. Sunzidul Kim, Jong-Hoon Southern Illinois University School of Computing CarbondaleIL62901 United States Bradley University Department of Computer Science and Information Systems PeoriaIL61625 United States The University of Texas at Arlington Department of Computer Science and Engineering ArlingtonTX76019 United States Khulna University of Engineering and Technology Department of Computer Science and Engineering Khulna9203 Bangladesh Kent State University Advanced Telerobotics Research Laboratory Department of Computer Science KentOH44240 United States

Automatic scene generation is an essential area of research with applications in robotics, recreation, visual representation, training and simulation, education, and more. This survey provides a comprehensive review of the current state-of-the-arts in automatic scene generation, focusing on techniques that leverage machine learning, deep learning, embedded systems, and natural language processing (NLP). We categorize the models into four main types: Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), Transformers, and Diffusion Models. Each category is explored in detail, discussing various sub-models and their contributions to the field. We also review the most commonly used datasets, such as COCO-Stuff, Visual Genome, and MS-COCO, which are critical for training and evaluating these models. Methodologies for scene generation are examined, including image-to-3D conversion, text-to-3D generation, graph-based methods, and interactive scene generation. Evaluation metrics such as Fréchet Inception Distance (FID), Kullback-Leibler (KL) Divergence, Inception Score (IS), Intersection over Union (IoU), and Mean Average Precision (mAP) are discussed in the context of their use in assessing model performance. The survey identifies key challenges and limitations in the field, such as maintaining realism, handling complex scenes with multiple objects, and ensuring consistency in object relationships and spatial arrangements. By summarizing recent advances and pinpointing areas for improvement, this survey aims to provide a valuable resource for researchers and practitioners working on automatic scene generation. © 2013 IEEE.

关键词： Deep learning

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Energy Consumption Prediction of a CNC Machining Process With Incomplete Data

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IEEE/CAA Journal of Automatica Sinica 2021年第5期8卷 987-1000页

作者： Jian Pan Congbo Li Ying Tang Wei Li Xiaoou Li the State Key Laboratory of Mechanical Transmission Chongqing UniversityChongqing 400044China the Department of Electrical and Computer Engineering Rowan UniversityGlassboroNJ 08028 USA the Computer Science Department The Research and Advanced Studies Centre of the National Polytechnic InstituteMexico City 07360Mexico

Energy consumption prediction of a CNC machining process is important for energy efficiency optimization *** improve the generalization abilities,more and more parameters are acquired for energy prediction *** the data collected from workshops may be incomplete because of misoperation,unstable network connections,and frequent transfers,*** work proposes a framework for energy modeling based on incomplete data to address this ***,some necessary preliminary operations are used for incomplete data ***,missing values are estimated to generate a new complete data set based on generative adversarial imputation nets(GAIN).Next,the gene expression programming(GEP)algorithm is utilized to train the energy model based on the generated data ***,we test the predictive accuracy of the obtained *** experiments are designed to investigate the performance of the proposed framework with different rates of missing *** results demonstrate that even when the missing data rate increases to 30%,the proposed framework can still make efficient predictions,with the corresponding RMSE and MAE 0.903 k J and 0.739 k J,respectively.

关键词： Energy consumption prediction incomplete data generative adversarial imputation nets(GAIN) gene expression programming(GEP)

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Large-Scale Radiomics Analysis for Prostate Cancer Detection Harnessing Machine and Deep Learning Models 22

Large-Scale Radiomics Analysis for Prostate Cancer Detection...

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22nd IEEE International Symposium on Biomedical Imaging, ISBI 2025

作者： Mylona, Eugenia Zaridis, Dimitrios I. Kalantzopoulos, Charalampos N. Pezoulas, Vasileios C. Tachos, Nikolaos S. Matsopoulos, George K. Regge, Daniele Papanikolaou, Nikolaos Tsiknakis, Manolis Marias, Kostas Fotiadis, Dimitrios I. Biomedical Research Institute Forth IoanninaGR 45110 Greece University of Ioannina Unit of Medical Technology Intelligent Information Systems Greece School of Electrical & Computer Engineering National Technical University of Athens Biomedical Engineering Laboratory Athens15780 Greece Candiolo Cancer Institute FPO-IRCCS Department of Radiology Strada Provinciale Candiolo Turin10060 Italy Champalimaud Foundation Computational Clinical Imaging Group Portugal Institute of Computer Science Forth Computational Biomedicine Laboratory HeraklionGR 70013 Greece Hellenic Mediterranean University Department of Electrical and Computer Engineering HeraklionGR 71004 Greece

ISBN: (纸本)9798331520526

Prostate cancer (PCa) is the second most common cancer in men, making early detection crucial for effective treatment. This study explores the efficacy of machine learning (ML) and deep learning (DL) models in detecting PCa lesions using radiomics features derived from multiparametric MRI data. Leveraging a dataset of 7621 retrospective and 2132 prospective cases from 12 clinical centers across Europe, we compared the performance of various ML (LASSO, Random Forest, SVM, XGBoost) and DL models (CNN, MLP, Transformer, CNN&MLP). Radiomic features were extracted and refined through a robust feature selection process. Models' performance was evaluated through nested cross-validation (CV) and externally. The CNN&MLP model achieved the highest ROC AUC (0.86) and PR AUC (0.90) in CV, while LASSO showed consistent generalization in external validation. Our findings indicate that DL models excel in high-dimensional data analysis but face challenges in generalizing to external datasets, highlighting the importance of external validation for clinical applicability. © 2025 IEEE.

关键词： Deep learning

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Enhancing memristor performance with 2D SnO_(x)/SnS_(2) heterostructure forneuromorphic computing

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science China Materials 2025年第2期68卷 581-589页

作者： Yangwu Wu Sifan Li Yun Ji Zhengjin Weng Houying Xing Lester Arauz Travis Hu Jinhua Hong Kah-Wee Ang Song Liu State Key Laboratory of Chemo/Biosensing and Chemometrics College of Chemistry and Chemical EngineeringHunan UniversityChangsha 410082China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Joint International Research Laboratory of Information Display and Visualization School of Electronic Science and EngineeringSoutheast UniversityNanjing 210096China Department of Mechanical Engineering California State UniversityLos Angeles5151 State University DrLos AngelesCA 90032USA College of Materials Science and Engineering Hunan UniversityChangsha 410082China Shenzhen Research Institute Hunan UniversityShenzhen 518000China

Layered metal dichalcogenides (LMDs) neuromorphic memristor devices offer a promising alternative toconventional von Neumann architectures, addressing speedand energy efficiency constraints. However, challenges remainin controlling resistive switching and operating voltage incrystalline LMD memristors due to environmental stabilization issues, which hinder neural network hardware development. Herein, we introduce an optimization method formemristor operation by controlling oxidation through ozonetreatment, creating a SnO_(x)/SnS_(2) resistive layer. These optimized memristors demonstrate low switching voltages (~1 V),rapid switching speeds (~20 ns), high switching ratios (10^(2)),and the ability to emulate synaptic weight plasticity. Crosssectional transmission electron microscopy and energy-dispersive X-ray spectroscopy identified defects and Ti conductive filaments in the resistive switching layer, contributingto uniform switching and minimized operating variation. Thedevice achieved 90% accuracy in MNIST handwritten recognition, and hardware-based image convolution was successfully implemented, showcasing the potential of SnO_(x)/SnS_(2)memristors for neuromorphic applications.

关键词： SnO_(x)/SnS_(2) oxidation layered metal dichalcogenides convolutional image processing neuromorphic computing

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Van der Waals device integration beyond the limits of van der Waals forces using adhesive matrix transfer

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Nature Electronics 2024年第1期7卷 17-28页

作者： Satterthwaite, Peter F. Zhu, Weikun Jastrzebska-Perfect, Patricia Tang, Melbourne Spector, Sarah O. Gao, Hongze Kitadai, Hikari Lu, Ang-Yu Tan, Qishuo Tang, Shin-Yi Chueh, Yu-Lun Kuo, Chia-Nung Lue, Chin Shan Kong, Jing Ling, Xi Niroui, Farnaz Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA United States Department of Chemical Engineering Massachusetts Institute of Technology CambridgeMA United States Department of Physics Massachusetts Institute of Technology CambridgeMA United States Department of Chemistry Boston University BostonMA United States Department of Materials Science and Engineering National Tsing Hua University Hsinchu Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei Taiwan College of Semiconductor Research National Tsing Hua University Hsinchu Taiwan Department of Physics National Cheng Kung University Tainan Taiwan Taiwan Consortium of Emergent Crystalline Materials National Science and Technology Council Taipei Taiwan Program on Key Materials Academy of Innovative Semiconductor and Sustainable Manufacturing National Cheng Kung University Tainan Taiwan Division of Materials Science and Engineering Boston University BostonMA United States The Photonics Center Boston University BostonMA United States

Pristine van der Waals (vdW) heterostructures formed between two-dimensional (2D) and other materials can be used to create optical and electronic devices. However, the weak vdW forces alone do not allow direct physical stacking of arbitrary layers. As a result, vdW heterostructure fabrication typically requires solvents, sacrificial layers or high temperatures, which can introduce damage and contaminants. Here, we show that adhesive matrix transfer can eliminate these limitations and can provide vdW integration beyond the limits of vdW forces. In the approach, a hybrid high- and low-adhesion surface is used to decouple the forces driving the transfer from the vdW forces defining the heterostructure of interest. We show that the technique can be used to achieve direct vdW integration of diverse 2D materials (MoS2, WSe2, PtS2 and GaS) with dielectrics (SiO2 and Al2O3), which is conventionally forbidden but critical for active devices and scalable, aligned heterostructure formation. The approach also allows single-step 2D material-to-device integration, which we illustrate by fabricating arrays of monolayer MoS2 transistors. As any exposure to solvents or polymers is avoided, the interfaces and surfaces remain pristine. Thus, intrinsic 2D material properties can be probed without the influence of processing steps. The materials can be further engineered through surface treatments and used to fabricate unconventional device form factors. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.

关键词： Van der Waals forces

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