检索结果-内蒙古大学图书馆

Low-Velocity-Favored Transition Radiation

Physical Review Letters 2023年第11期131卷 113002-113002页

作者： Jialin Chen Ruoxi Chen Fuyang Tay Zheng Gong Hao Hu Yi Yang Xinyan Zhang Chan Wang Ido Kaminer Hongsheng Chen Baile Zhang Xiao Lin Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center College of Information Science & Electronic Engineering Zhejiang University Hangzhou 310027 China International Joint Innovation Center the Electromagnetics Academy at Zhejiang University Zhejiang University Haining 314400 China Department of Electrical and Computer Engineering Technion-Israel Institute of Technology Haifa 32000 Israel Department of Electrical and Computer Engineering Rice University Houston Texas 77005 USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas 77005 USA School of Electrical and Electronic Engineering Nanyang Technological University Singapore 639798 Singapore Department of Physics University of Hong Kong Hong Kong 999077 China Key Lab of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Jinhua Institute of Zhejiang University Zhejiang University Jinhua 321099 China Shaoxing Institute of Zhejiang University Zhejiang University Shaoxing 312000 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore 637371 Singapore Centre for Disruptive Photonic Technologies Nanyang Technological University Singapore 637371 Singapore

When a charged particle penetrates through an optical interface, photon emissions emerge—a phenomenon known as transition radiation. Being paramount to fundamental physics, transition radiation has enabled many applications from high-energy particle identification to novel light sources. A rule of thumb in transition radiation is that the radiation intensity generally decreases with the decrease of particle velocity v; as a result, low-energy particles are not favored in practice. Here, we find that there exist situations where transition radiation from particles with extremely low velocities (e.g., v/c<10−3) exhibits comparable intensity as that from high-energy particles (e.g., v/c=0.999), where c is the light speed in free space. The comparable radiation intensity implies an extremely high photon extraction efficiency from low-energy particles, up to 8 orders of magnitude larger than that from high-energy particles. This exotic phenomenon of low-velocity-favored transition radiation originates from the interference of the excited Ferrell-Berreman modes in an ultrathin epsilon-near-zero slab. Our findings may provide a promising route toward the design of integrated light sources based on low-energy electrons and specialized detectors for beyond-standard-model particles.

关键词： Atom or molecule scattering from surfaces Atomic & molecular collisions Cherenkov radiation Crystal optics Electron beams & optics Light-matter interaction Optical sources & detectors Optical transient phenomena Plasmonics

来源：评论

学校读者我要写书评

暂无评论

Electrochemical biosensor based on an atomic layered composite of graphene oxide/graphene as an electrode material towards selective and sensitive detection of miRNA-21

引用

Microchemical Journal 2024年 199卷

作者： Huang, Min-Shin Govindasamy, Mani Chinnapaiyan, Sathishkumar Lin, Yi-Ting Lu, Shao-Yang Samukawa, Seiji Huang, Chi-Hsien Department of Materials Engineering Ming Chi University of Technology New Taipei City 243303 Taiwan International Ph.D. Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Technology New Taipei City 24303 Taiwan Centre for Applied Research Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai-602105 Tamil Nadu India Institute of Fluid Science Tohoku University Sendai 980-8577 Japan College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu 300093 Taiwan Division of Rheumatology Allergy and Immunology Chang Gung Memorial Hospital Taoyuan City 33305 Taiwan College of Engineering Chang Gung University Taoyuan City 33302 Taiwan

Development of an efficient technique towards the detection of miRNAs is highly significant for the timely diagnosis and prognosis of cancers. In this study, we utilized the chemical vapor deposition (CVD) technique to grow bilayer graphene (BLG) on copper foil and subsequently transferred the BLG to fluorine doped tin oxide (FTO) substrate via a facile wet transfer technique. The upper layer of the BLG was modified to graphene oxide (GO) with a low damage plasma treatment (LDPT) process to serve as a biomolecule receiving layer and the lower graphene layer (G) serves as an electron transport layer. The developed GO/G/FTO platform offers superior sensing ability towards the miRNA-21. The results demonstrated that the proposed GO/G/FTO substrate detect the miRNA-21 with a wide linear range (10 fM ∼ 1 nM), low limit of detection (3.18 fM), high sensitivity (0.6 mApM⁻¹cm⁻²), selectivity and stability via the differential pulse voltammetry method. Additionally, the sensors can efficiently discriminate the target miRNA-21 from its complementary base mismatched counterparts. The proposed approach serves as an excellent tool for the early diagnosis of diseases. © 2024 Elsevier B.V.

关键词： Atomic layer oxidation Biosensor Cancer biomarkers Electrochemical Graphene oxide Plasma treatment

来源：评论

学校读者我要写书评

暂无评论

Mutual Consistency Learning for Semi-supervised Medical Image Segmentation

arXiv

引用

arXiv 2021年

作者： Wu, Yicheng Ge, Zongyuan Zhang, Donghao Xu, Minfeng Zhang, Lei Xia, Yong Cai, Jianfei Department of Data Science & AI Faculty of Information Technology Monash University MelbourneVIC3800 Australia Monash-Airdoc Research Monash University MelbourneVIC3800 Australia Monash Medical AI Monash eResearch Centre MelbourneVIC3800 Australia DAMO Academy Alibaba Group Hangzhou311121 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi'an710072 China

In this paper, we propose a novel mutual consistency network (MC-Net+) to effectively exploit the unlabeled data for semi-supervised medical image segmentation. The MC-Net+ model is motivated by the observation that deep models trained with limited annotations are prone to output highly uncertain and easily mis-classified predictions in the ambiguous regions (e.g., adhesive edges or thin branches) for medical image segmentation. Leveraging these challenging samples can make the semi-supervised segmentation model training more effective. Therefore, our proposed MC-Net+ model consists of two new designs. First, the model contains one shared encoder and multiple slightly different decoders (i.e., using different up-sampling strategies). The statistical discrepancy of multiple decoders' outputs is computed to denote the model's uncertainty, which indicates the unlabeled hard regions. Second, we apply a novel mutual consistency constraint between one decoder's probability output and other decoders' soft pseudo labels. In this way, we minimize the discrepancy of multiple outputs (i.e., the model uncertainty) during training and force the model to generate invariant results in such challenging regions, aiming at regularizing the model training. We compared the segmentation results of our MC-Net+ model with five state-of-the-art semi-supervised approaches on three public medical datasets. Extension experiments with two standard semi-supervised settings demonstrate the superior performance of our model over other methods, which sets a new state of the art for semi-supervised medical image segmentation. Our code is released publicly at https://***/ycwu1997/MC-Net. © 2021, CC BY-NC-SA.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Question-Answering System Extracts Information on Injection Drug Use from Clinical Notes

arXiv

引用

arXiv 2023年

作者： Mahbub, Maria Goethert, Ian Danciu, Ioana Knight, Kathryn Srinivasan, Sudarshan Tamang, Suzanne Rozenberg-Ben-Dror, Karine Solares, Hugo Martins, Susana Trafton, Jodie Begoli, Edmon Peterson, Gregory D. Cyber Resilience and Intelligence Division Oak Ridge National Laboratory Oak RidgeTN United States Information Technology Services Division Oak Ridge National Laboratory Oak RidgeTN United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN United States Department of Biomedical Informatics Vanderbilt University NashvilleTN United States Program Evaluation and Resource Center Office of Mental Health and Suicide Prevention Department of Veterans Affairs United States Department of Medicine Stanford University School of Medicine StanfordCA United States Veterans Affairs Great Lakes Health Care System WestchesterIL United States Department of Electrical Engineering and Computer Science University of Tennessee Knoxville KnoxvilleTN United States

Background: Injection drug use (IDU) is a dangerous health behavior that increases mortality and morbidity. Identifying IDU early and initiating harm reduction interventions can benefit individuals at risk. However, extracting IDU behaviors from patients’ electronic health records (EHR) is difficult because there is no International Classification of Disease (ICD) code and the only place IDU information can be indicated is unstructured free-text clinical notes. Although natural language processing can efficiently extract this information from unstructured data, there are no validated tools. Methods: To address this gap in clinical information, we design and demonstrate a question-answering (QA) framework to extract information on IDU from clinical notes. Our framework involves two main steps: (1) generating a gold-standard QA dataset and (2) developing and testing the QA model. We utilize 2323 clinical notes of 1145 patients sourced from the VA Corporate Data Warehouse to construct the gold-standard dataset for developing and evaluating the QA model. We also demonstrate the QA model’s ability to extract IDU-related information on temporally out-of-distribution data. Results: Here we show that for a strict match between gold-standard and predicted answers, the QA model achieves 51.65% F1 score. For a relaxed match between the gold-standard and predicted answers, the QA model obtains 78.03% F1 score, along with 85.38% Precision and 79.02% Recall scores. Moreover, the QA model demonstrates consistent performance when subjected to temporally out-of-distribution data. Conclusions: Our study introduces a QA framework designed to extract IDU information from clinical notes, aiming to enhance the accurate and efficient detection of people who inject drugs, extract relevant information, and ultimately facilitate informed patient care. © 2023, CC BY-NC-ND.

关键词： Data warehouses

来源：评论

学校读者我要写书评

暂无评论

Correction to: Topological localization approach for efficient energy management of WSN

引用

Evolutionary Intelligence 2021年第2期17卷 729-729页

作者： Mohapatra, Hitesh Rath, Amiya Kumar Lenka, Rakesh K Nayak, Rudra Kalyan Tripathy, Ramamani Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Guntur India Department of Computer Science & Engineering Veer Surendra Surendra Sai University of Technology Burla India NAAC Banglore India Department of Computer Science & Engineering IIIT Bhubaneswar India Dept.of Master of Computer Application United School of Business Management Bhubaneswar India

A correction to this paper has been published: https://***/10.1007/s12065-021-00631-9

关键词：

来源：评论

学校读者我要写书评

暂无评论

Lipschitz property of harmonic mappings with respect to the pseudo-hyperbolic metric

arXiv

引用

arXiv 2021年

作者： Huang, Jie Rasila, Antti Zhu, Jian-Feng School of Mathematical Sciences Huaqiao University Quanzhou362021 China Mathematics with Computer Science Program Guangdong Technion 241 Daxue Road Jinping District ShantouGuangdong515063 China Department of Mathematics Technion - Israel Institute of Technology Haifa32000 Israel School of Mathematical Sciences Huaqiao University Quanzhou362021 China Department of Mathematics Shantou University ShantouGuangdong515063 China

In this paper, we show that harmonic Bloch mappings are Lipschitz continuous with respect to the pseudo-hyperbolic metric. This result improves the corresponding result of ([10, Theorem 1]). Furthermore, we prove the similar property for harmonic quasiregular Bloch-type *** Codes Primary: 30C62, 30H30, Secondary: 30C20, 31A05 Copyright © 2021, The Authors. All rights reserved.

关键词： Harmonic analysis

来源：评论

学校读者我要写书评

暂无评论

Muscle Vectors as Temporally Dense "Labels"

Muscle Vectors as Temporally Dense "Labels"

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Xiang Wu Juyang Weng School of Automation Nanjing University of Science and Technology Nanjing China Department of Computer Science and Engineering Michigan State University East Lansing MI USA Cognitive Science Program Michigan State University East Lansing MI USA Neuroscience Program Michigan State University East Lansing MI USA

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

Consider a human who interacts with the physical world to autonomously learn in a task non-specific way through lifetime. It seems obvious that the fully autonomous learner does not have the luxury to have the mother to provide temporally dense state labels, but the context/state at every frame is beneficial (e.g., to generate attention for the next frame). How can we enable the learner to generate frame-wise contexts/states on the fly? Our past work on Developmental Network (DN-1) has shown that frame-wise state labels (e.g., stages within a phoneme) are useful to generate temporally sparse label (the type of the phoneme). However, such dense and sparse labels were handcrafted from a static data set, using human identified frame-wise equivalence. In this paper, we study a conceptually challenging problem - how to enable an autonomous learner to generate frame-wise states autonomously without human handcrafting dense labels at all. We propose that frame-wise muscle actions (e.g., producing a sound) are not only temporally dense and high-dimensional, but also natural as dense labels. However, it is unknown how a neural network can use such high-dimensional vectors as dense labels. In this work, we provide a model for this new issue and experiment with Developmental Network-2 (DN-2) for imitation of audio sequences. Our experimental results showed DN-2 can successfully emerge high-dimensional real-valued vector actions. These actions provide DN-2 with frame-wise temporal context information. This work corresponds to a key step toward our goal to enable the agent to fully autonomously generate frame-wise actions without human-provided dense labels and with only a few human-provided sparse labels.

关键词： Task analysis Turing machines Hidden Markov models Neurons Robot sensing systems Bayes methods Natural languages

来源：评论

学校读者我要写书评

暂无评论

Evaluation of E-government services based on social media using structural equation modeling 4

Evaluation of E-government services based on social media us...

引用

4th International Conference on Information Management and technology, ICIMTech 2019

作者： Nindito, Hendro Madyatmadja, Evaristus Didik Dian Sano, Albert Verasius Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Study Program Bina Nusantara Institute of Creative Technology Malang65126 Indonesia

ISBN: (纸本)9781728133331

Today many local governments have provided aspiration services or social media based complaints about the community to participate in giving aspirations and report problems that occur around the area. To improve the usefulness of this service, we conduct research with the aim of evaluating and identifying the factors that affect the service's application. The impact of this study is that the government can provide services according to the wishes of the community, because the model found can be a reference for the government to increase public trust and satisfaction for users of government services. The influence on the adoption of Aspiration Services is explained by using perceptions of trust, attitudes, and intentions of use that refer to technology acceptance models (TAM). Data processing and analysis in our research using the SEM-PLS method (Structural Equation Model-Partial Least Square). The results in this research will present that services applying technology that gain a positive effect on the awareness of usability and benefit for service users. © 2019 IEEE.

关键词： Least squares approximations

来源：评论

学校读者我要写书评

暂无评论

Multi-stage Speaker Extraction with Utterance and Frame-Level Reference Signals

arXiv

引用

arXiv 2020年

作者： Ge, Meng Xu, Chenglin Wang, Longbiao Chng, Eng Siong Dang, Jianwu Li, Haizhou Tianjin Key Laboratory of Cognitive Computing and Application College of Intelligence and Computing Tianjin University Tianjin China School of Computer Science and Engineering Nanyang Technological University Singapore Japan Advanced Institute of Science and Technology Ishikawa Japan Department of Electrical and Computer Engineering National University of Singapore Singapore Machine Listening Lab University of Bremen Germany

Speaker extraction requires a sample speech from the target speaker as the reference. However, enrolling a speaker with a long speech is not practical. We propose a speaker extraction technique, that performs in multiple stages to take full advantage of short reference speech sample. The extracted speech in early stages is used as the reference speech for late stages. For the first time, we use frame-level sequential speech embedding as the reference for target speaker. This is a departure from the traditional utterance-based speaker embedding reference. In addition, a signal fusion scheme is proposed to combine the decoded signals in multiple scales with automatically learned weights. Experiments on WSJ0-2mix and its noisy versions (WHAM! and WHAMR!) show that SpEx++ consistently outperforms other state-of-the-art baselines. Copyright © 2020, The Authors. All rights reserved.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

BPS2025 - Structural basis of potassium selectivity in kalium channelrhodopsins

引用

Biophysical Journal 2025年第3期124卷 64a-65a页

作者： Seiya Tajima Yoon Seok Kim YoungJu Jo Peter Y. Wang Joseph M. Paggi Charu Ramakrishnan Shunki Takaramoto Takashi Nagata Masae Konno Kota Katayama Hideki Kandori Ron O. Dror Keiichi Inoue Karl Deisseroth Hideaki Kato Research Center for Advanced Science and Technology The University of Tokyo Tokyo Japan Department of Bioengineering Stanford University Stanford CA USA Department of Computer Science Stanford University Stanford CA USA Cracking the Neural Code Program Stanford University Stanford CA USA The Institute for Solid State Physics The University of Tokyo Kashiwa Japan PRESTO Japan Science and Technology Agency Kawaguchi Japan Department of Life Science and Applied Chemistry Nagoya Institute of Technology Nagoya Japan OptoBioTechnology Research Center Nagoya Institute of Technology Nagoya Japan Institute for Computational and Mathematical Engineering Stanford University Stanford CA USA Howard Hughes Medical Institute Stanford University Stanford CA USA Graduate School of Arts and Sciences The University of Tokyo Tokyo Japan

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：