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arXiv 2024年

作者： Denner, Stefan Bujotzek, Markus Bounias, Dimitrios Zimmerer, David Stock, Raphael Maier-Hein, Klaus Division of Medical Image Computing German Cancer Research Center Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Medical Faculty Heidelberg University of Heidelberg Heidelberg Germany

Medical image classification plays a crucial role in clinical decision-making, yet most models are constrained to a fixed set of predefined classes, limiting their adaptability to new conditions. Contrastive Language-Image Pretraining (CLIP) offers a promising solution by enabling zero-shot classification through multimodal large-scale pretraining. However, while CLIP effectively captures global image content, radiology requires a more localized focus on specific pathology regions to enhance both interpretability and diagnostic accuracy. To address this, we explore the potential of incorporating visual cues into zero-shot classification, embedding visual markers—such as arrows, bounding boxes, and circles—directly into radiological images to guide model attention. Evaluating across four public chest X-ray datasets, we demonstrate that visual markers improve AUROC by up to 0.185, highlighting their effectiveness in enhancing classification performance. Furthermore, attention map analysis confirms that visual cues help models focus on clinically relevant areas, leading to more interpretable predictions. To support further research, we use public datasets and will release our code and preprocessing pipeline, providing a reference point for future work on localized classification in medical imaging. Copyright © 2024, The Authors. All rights reserved.

关键词： Radiology

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Manipulating grain boundary migration to fabricate integral core–shell structure with enhanced strain hardening in Ni-based high-entropy alloy

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Journal of Materials science & Technology 2026年 242卷 213-225页

作者： Hyojin Park Qingfeng Wu Yoon–Uk Heo Sun Ig Hong Rae Eon Kim Do Won Lee Soung Yeoul Ahn Zhe Gao Jae Heung Lee Hyo Moon Joo Jongun Moon Young-Sang Na Jae-il Jang Hyoung Seop Kim Department of Materials Science and Engineering Pohang University of Science and Technology (POSTECH) Pohang 37673 South Korea Center for Heterogenic Metal Additive Manufacturing Pohang University of Science and Technology (POSTECH) Pohang 37673 South Korea Graduate Institute of Ferrous & Eco Materials Technology Pohang University of Science and Technology (POSTECH) Pohang 37673 South Korea Department of Materials Science and Engineering Chungnam National University Daejeon 34134 South Korea Division of Materials Science and Engineering Hanyang University Seoul 04763 South Korea Lightweight Materials Research Team Advanced Vehicle Platform Hyundai Motor Group Uiwang 16082 South Korea Division of Advanced Materials Engineering Kongju National University Cheonan 31080 South Korea Korea Institute of Materials Science (KIMS) Changwon 51508 South Korea Advanced Institute for Materials Research (WPI–AIMR) Tohoku University Sendai 980–8577 Japan Institute for Convergence Research and Education in Advanced Technology Yonsei University Seoul 03722 South Korea

A core–shell microstructure represents an approach to achieve superior mechanical properties in alloys through its distinctive architecture, typically developed in powder metallurgy processing. In the present study, an integral core–shell structure has achieved in a cast Ni–based high entropy alloy through a straightforward thermo–mechanical processing (TMP) approach, including hot rolling and heat treatment. Inspired by the formation of a necklace structure during the hot deformation, we employed hot rolling to induce bulged grain boundaries in coarse grains. Subsequent heat treatment constrained the growth of these bulged regions through B2 precipitate formation, leading to the stabilization of the integral core–shell structure, where the deformed grains form the core, and the bulged grains form the shell. The significant synergistic hardening from the microstructural heterogeneity of the integral core–shell structure improves strain hardening in the TMP-processed sample. The integrated TMP approach, combined with alloy design, enables the evolution of integral core–shell structures in cast high entropy alloys, significantly improving material properties without the complexities of powder metallurgy.

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Electrically Programmable Non-Volatile Silicon Photonic Content Addressable Memory (CAM) cell

Electrically Programmable Non-Volatile Silicon Photonic Cont...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Lian, Chuanyu Sun, Hongyi Huang, Yi-Siou Vitale, Steven A. Hu, Juejun Takeuchi, Ichiro Youngblood, Nathan Vagionas, Christos Ríos Ocampo, Carlos A. Department of Materials Science & Engineering University of Maryland College ParkMD20742 United States Institute for Research in Electronics and Applied Physics University of Maryland College ParkMD20742 United States Advanced Materials and Microsystems Group MIT Lincoln Laboratory LexingtonMA02139 United States Department of Materials Science & Engineering MIT CambridgeMA02139 United States Quantum Materials Center Department of Physics University of Maryland College ParkMD20742 United States Electrical & Computer Engineering Department The University of Pittsburgh PittsburghPA15213 United States Department of Informatics Center for Interdisciplinary Research and Innovation Aristotle University of Thessaloniki Thessaloniki Greece

We experimentally demonstrate the first electrically programmable, non-volatile silicon photonic content addressable memory cell using Sb2Se3 phase change material on microring resonators, opening the path for light-based search operations in zero-power look-up tables. © Optica Publishing Group 2024

关键词： Silicon photonics

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Touchstone benchmark: are we on the right way for evaluating AI algorithms for medical segmentation? 24

Touchstone benchmark: are we on the right way for evaluating...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Pedro R. A. S. Bassi Wenxuan Li Yucheng Tang Fabian Isensee Zifu Wang Jieneng Chen Yu-Cheng Chou Saikat Roy Yannick Kirchhoff Maximilian Rokuss Ziyan Huang Jin Ye Junjun He Tassilo Wald Constantin Ulrich Michael Baumgartner Klaus H. Maier-Hein Paul Jaeger Yiwen Ye Yutong Xie Jianpeng Zhang Ziyang Chen Yong Xia Zhaohu Xing Lei Zhu Yousef Sadegheih Afshin Bozorgpour Pratibha Kumari Reza Azad Dorit Merhof Pengcheng Shi Ting Ma Yuxin Du Fan Bai Tiejun Huang Bo Zhao Haonan Wang Xiaomeng Li Hanxue Gu Haoyu Dong Jichen Yang Maciej A. Mazurowski Saumya Gupta Linshan Wu Jiaxin Zhuang Hao Chen Holger Roth Daguang Xu Matthew B. Blaschko Sergio Decherchi Andrea Cavalli Alan L. Yuille Zongwei Zhou Department of Computer Science Johns Hopkins University and Department of Pharmacy and Biotechnology University of Bologna and Center for Biomolecular Nanotechnologies Istituto Italiano di Tecnologia Department of Computer Science Johns Hopkins University NVIDIA Division of Medical Image Computing German Cancer Research Center (DKFZ) and Helmholtz Imaging German Cancer Research Center (DKFZ) ESAT-PSI KU Leuven Division of Medical Image Computing German Cancer Research Center (DKFZ) and Faculty of Mathematics and Computer Science Heidelberg University Division of Medical Image Computing German Cancer Research Center (DKFZ) and Faculty of Mathematics and Computer Science Heidelberg University and HIDSS4Health - Helmholtz Information and Data Science School for Health Shanghai Jiao Tong University Shanghai Artificial Intelligence Laboratory Division of Medical Image Computing German Cancer Research Center (DKFZ) Division of Medical Image Computing German Cancer Research Center (DKFZ) and Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Helmholtz Imaging German Cancer Research Center (DKFZ) and Interactive Machine Learning Group (IML) DKFZ School of Computer Science and Engineering Northwestern Polytechnical University Australian Institute for Machine Learning The University of Adelaide College of Computer Science and Technology Zhejiang University Hong Kong University of Science and Technology (Guangzhou) Hong Kong University of Science and Technology (Guangzhou) and Hong Kong University of Science and Technology Faculty of Informatics and Data Science University of Regensburg Faculty of Electrical Engineering and Information Technology RWTH Aachen University Faculty of Informatics and Data Science University of Regensburg and Fraunhofer Institute for Digital Medicine MEVIS Electronic & Information Engineering School Harbin Institute of Technology (Shenzhen) Shanghai Jiao Tong University and Beijing Academy of Artificial Intelligence (BAAI) S

ISBN: (纸本)9798331314385

How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified metrics, unfair comparisons, and short-term outcome pressure. As a consequence, good performance on standard benchmarks does not guarantee success in real-world scenarios. To address these problems, we present Touchstone, a large-scale collaborative segmentation benchmark of 9 types of abdominal organs. This benchmark is based on 5,195 training CT scans from 76 hospitals around the world and 5,903 testing CT scans from 11 additional hospitals. This diverse test set enhances the statistical significance of benchmark results and rigorously evaluates AI algorithms across out-of-distribution scenarios. We invited 14 inventors of 19 AI algorithms to train their algorithms, while our team, as a third party, independently evaluated these algorithms. In addition, we also evaluated pre-existing AI frameworks—which, differing from algorithms, are more flexible and can support different algorithms—including MONAI from NVIDIA, nnU-Net from DKFZ, and numerous other open-source frameworks. We are committed to expanding this benchmark to encourage more innovation of AI algorithms for the medical domain.

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Artificial intelligence is transforming the study of proteins:Structures and beyond

微生物与宿主健康（英文）

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微生物与宿主健康（英文） 2025年第4期3卷 162-163页

作者： Haiyan Liu Quan Chen Yufeng Liu MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics School of Life SciencesDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaAnhuiChina Biomedical Sciences and Health Laboratory of Anhui Province Anhui Basic Discipline Research Center of Artificial Intelligence Biotechnology and Synthetic BiologyUniversity of Science and Technology of ChinaAnhuiChina School of Biomedical Engineering Suzhou Institute for Advanced ResearchUniversity of Science and Technology of ChinaJiangsuChina MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics School of Life SciencesDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaAnhuiChina Biomedical Sciences and Health Laboratory of Anhui Province Anhui Basic Discipline Research Center of Artificial Intelligence Biotechnology and Synthetic BiologyUniversity of Science and Technology of ChinaAnhuiChina Department of Rheumatology and Immunology The First Affiliated Hospital of USTCDivision of Life Sciences and MedicineHefei National Research Center for Physical Sciences at the MicroscaleCenter for Advanced Interdisciplinary Science and Biomedicine of IHMUniversity of Science and Technology of ChinaAnhuiChina MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics School of Life SciencesDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaAnhuiChina Department of Rheumatology and Immunology The First Affiliated Hospital of USTCDivision of Life Sciences and MedicineHefei National Research Center for Physical Sciences at the MicroscaleCenter for Advanced Interdisciplinary Science and Biomedicine of IHMUniversity of Science and Technology of ChinaAnhuiChina

Recently,the Royal Swedish Academy of sciences announced that one-half of the 2024 Nobel Prize in Chemistry was awarded to David Baker for computational protein design,and the other half was awarded jointly to Demis Hassabis and John Jumper for protein structure prediction. Proteins are the molecule tools of *** carry out their func-tions,many proteins need to fold into particular three-dimen-sional(3D)structures,which are programmed by the amino acid sequences of the proteins[1].The goal of protein structure prediction is to predict the 3D structures from given amino acid ***,protein design aims to identify amino acid sequences that achieve desired structural or func-tional goals.

关键词： intelligence beyond study artificial proteins structures transforming

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Electrically Programmable Non-Volatile Silicon Photonic Content Addressable Memory (CAM) cell

Electrically Programmable Non-Volatile Silicon Photonic Cont...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

ISBN: (纸本)9781957171395

关键词： Silicon photonics

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Expedited Block Transmission in Blockchain Network by using Clusters

Expedited Block Transmission in Blockchain Network by using ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Xiaoqi Hua Jian Chen Peiyun Zhang Zhangjie Fu Haibin Zhu Kezhong Lu Jigang Ren School of Software Nanjing University of Information Science and Technology Nanjing China Engineering Research Center of Digital Forensics of Ministry of Education and the School of Computer Science Nanjing University of Information Science and Technology Nanjing China School of Computer Science Nanjing University of Information Science and Technology Nanjing China Department of Computer Science and Mathematics Nipissing University North Bay ON Canada School of Big Data and Artificial Intelligence Chizhou University Chizhou China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Blockchain technology has garnered increasing attention from researchers. Because blockchain systems may contain malicious or spatially limited nodes that may delay block verification and reduce block transmission rate, this work proposes a block transmission model by designing and using special clusters. This work proposes the cluster formation and selection mechanisms. Nodes are grouped into clusters in a blockchain, and clusters with high fitness values are chosen to transmit blocks by calculating their trust values and block transmission rates. The proposed method is compared with the peers: Layer-Chain, BlockP2P-EP and RNS. According to experimental findings, the proposed method is superior to its peers regarding the time needed for block synchronization and transmission, block occupation storage ratio, transaction throughput, and block transmission success ratio.

关键词： Throughput Blockchains Peer-to-peer computing Delays Synchronization Cybernetics

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High-Bandwidth,Low-Power CMOS Transistor Based CAB for Field Programmable Analog Array

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computers, Materials & Continua 2023年第3期74卷 5885-5900页

作者： Ameen Bin Obadi Alaa El-Din Hussein Samir Salem Al-Bawri Kabir Hossain Abdullah Abdulhameed Muzammil Jusoh Thennarasan Sabapathy Ahmed Jamal Abdullah Al-Gburi Mahmoud A.Albreem Advanced Communication Engineering(ACE) Centre of ExcellenceUniversiti Malaysia Perlis(UniMAP)Faculty of Electronic Engineering TechnologyKangar01000Malaysia Electrical Engineering King Fahd University of Petroleum and MineralsDhahranEastern31261Saudi Arabia Space Science Centre Climate Change InstituteUniversiti Kebangsaan MalaysiaBangi43600Malaysia Department of Electronics&Communication Engineering Faculty of Engineering&PetroleumHadhramout UniversityAl-MukallaHadhramout50512Yemen Faculty of Engineering Norwegian University of Science and Technology(NTNU)GjovikN-2815Norway Faculty of Electronic Engineering Technology Universiti Malaysia Perlis(UniMAP)Kampus Alam UniMAP Pauh PutraArau02600Malaysia Department of General Educational Development Faculty of Science and Information Technology(FSIT)Daffodil International UniversityDhaka1207Bangladesh Department of Electronics and Computer Engineering(FKEKK) Center for Telecommunication Research and Innovation(CeTRI)Universiti Teknikal Malaysia Melaka(UTeM)Durian Tungal76100Malaysia Department of Electrical Engineering University of SharjahSharjah27272United Arab Emirates

This article presents an integrated current mode configurable analog block(CAB)system for field-programmable analog array(FPAA).The proposed architecture is based on the complementary metal-oxide semiconductor(CMOS)transistor level design where MOSFET transistors operating in the saturation region are *** proposed CAB architecture is designed to implement six of thewidely used current mode operations in analog processing systems:addition,subtraction,integration,multiplication,division,and pass *** functionality of the proposed CAB is demonstrated through these six operations,where each operation is chosen based on the user’s selection in the CAB interface *** architecture of the CAB system proposes an optimized way of designing and integrating only three functional cells with the interface circuitry to achieve the six ***,optimized programming and digital tuning circuitry are implemented in the architecture to control and interface with the functional ***,these designed programming and tuning circuitries play an essential role in optimizing the performance of the proposed *** of the proposed CMOS Transistor Based CAB system is carried out using Tanner EDA Tools in 0.35μm standard CMOS *** design uses a±1.5 V power supply and results in maximum 3 dB bandwidth of 34.9 MHz and an approximate size of 0.0537 *** demonstrates the advantages of the design over the current state-of-the-art designs presented for comparison in this ***,the proposed design has a clear aspect of simplicity,low power consumption,and high bandwidth operation,which makes it a suitable candidate for mobile telecommunications applications.

关键词： CMOS field programmable analog array configurable analog block current mode circuit

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Privacy-preserving data aggregation achieving completeness of data queries in smart grid

Privacy-preserving data aggregation achieving completeness o...

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作者： Li, Xinyang Zhao, Meng Ding, Yong Yang, Changsong Wang, Huiyong Liang, Hai Wang, Yujue Guangxi Key Laboratory of Cryptography and Information Security School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic Technology Guilin China Hangzhou Innovation Institute of Beihang University Hangzhou China Institute of Cyberspace Technology HKCT Institute for Higher Education Hong Kong School of Mathematics and Computing Science Guilin University of Electronic Technology Guilin China

In smart grid systems, the control center formulates strategies and provides services by analyzing electricity consumption data. However, ensuring the privacy and security of user data is a critical concern. While traditional data aggregation schemes can provide a certain level of privacy protection for users, they also impose limitations on the control center's access to fine-grained data. To address these challenges, we propose a privacy-preserving data aggregation scheme supporting data query (PAQ). We designed a multi-level data aggregation mechanism based on Paillier semi-homomorphic encryption to achieve efficient aggregation of user data in the control center. Additionally, a data query mechanism based on electricity consumption intervals is introduced, allowing the control center to query aggregated ciphertexts for different user categories from outsourced data on the cloud server. Security analysis demonstrates that PAQ design effectively solves security issues in data aggregation and query processes. Performance analysis indicates that the proposed scheme outperforms existing solutions in terms of efficiency. © 2024 John Wiley & Sons, Ltd.

关键词： Smart power grids

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Leveraging Artificial Intelligence for Advancements in Mental Disorders: A Short Review 16

Leveraging Artificial Intelligence for Advancements in Menta...

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16th International Conference on Ambient Systems, Networks and Technologies Networks, ANT 2025 / 8th International Conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Kasereka, Selain K. Tshibangu, Kenny N. Nyembo, Myriam M. Tshitenge, Lionel K. Muzindusi, Marina K. Ilunga, Godwill W.K. Amor, Soufian Ben Bope, Christian D. Tashev, Tasho Kyamakya, Kyandoghere Mathematics Statistics and Computer Science Department University of Kinshasa Kinshasa Democratic Republic Congo Faculty of English Engineering Studies Technical University of Sofia Sofia Bulgaria ABIL Research Center Kinshasa Democratic Republic Congo Faculty of Computer Science Université Nouveaux Horizons Lubumbashi Democratic Republic Congo LI-PaRAD Université de Versailles-Saint-Quentin-en-Yvelines France Institute of Smart Systems Technologies University of Klagenfurt Klagenfurt Austria Polytechnic Faculty University of Kinshasa Kinshasa Democratic Republic Congo

This study explores the expanding influence of artificial intelligence (AI) on the comprehension and management of mental disorders conditions. By analyzing recent advancements, this article highlights how AI technologies are being applied to diagnose, model, predict, and treat conditions, such as depression, anxiety, and bipolar disorder. It examines innovative approaches, including AI-powered mental wellness apps, that enable users to monitor their symptoms and access personalized support. Additionally, it discusses research on advanced algorithms designed to analyze online social interactions to identify early signs of psychological distress and to facilitate timely interventions. The paper also addresses the challenges involved in integrating AI into mental healthcare and highlights ethical and legal concerns that should be addressed when developing AI mental health models. © 2025 Elsevier B.V.. All rights reserved.

关键词： Backpropagation

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