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arXiv 2024年

作者： Surace, Federica Maria Lerose, Alessio Katz, Or Bennewitz, Elizabeth R. Schuckert, Alexander Luo, De De, Arinjoy Ware, Brayden Morong, William Collins, Kate Monroe, Christopher Davoudi, Zohreh Gorshkov, Alexey V. Department of Physics Institute for Quantum Information and Matter California Institute of Technology PasadenaCA91125 United States Rudolf Peierls Centre for Theoretical Physics Clarendon Laboratory OxfordOX1 3PU United Kingdom Institute for Theoretical Physics KU Leuven Celestijnenlaan 200D Leuven3001 Belgium Duke Quantum Center Departments of Physics and Electrical and Computer Engineering Duke University DurhamNC27708 United States School of Applied and Engineering Physics Cornell University IthacaNY14853 United States Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD20742 United States Joint Quantum Institute NIST University of Maryland College ParkMD20742 United States Department of Physics Maryland Center for Fundamental Physics University of Maryland College ParkMD20742 United States

Confinement prohibits isolation of color charges, e.g., quarks, in nature via a process called string breaking: the separation of two charges results in an increase in the energy of a color flux, visualized as a string, connecting those charges. Eventually, creating additional charges is energetically favored, hence breaking the string. Such a phenomenon can be probed in simpler models, including quantum spin chains, enabling enhanced understanding of string-breaking dynamics. A challenging task is to understand how string breaking occurs as time elapses, in an out-of-equilibrium setting. This work establishes the phenomenology of dynamical string breaking induced by a gradual increase of string tension over time. It, thus, goes beyond instantaneous quench processes and enables tracking the real-time evolution of strings in a more controlled setting. We focus on domain-wall confinement in a family of quantum Ising chains. Our results indicate that, for sufficiently short strings and slow evolution, string breaking can be described by the transition dynamics of a two-state quantum system akin to a Landau-Zener process. For longer strings, a more intricate spatiotemporal pattern emerges: the string breaks by forming a superposition of bubbles (domains of flipped spins of varying sizes), which involve highly excited states. We finally demonstrate that string breaking driven only by quantum fluctuations can be realized in the presence of sufficiently long-ranged interactions. This work holds immediate relevance for studying string breaking in quantum-simulation experiments. Copyright © 2024, The Authors. All rights reserved.

关键词： Excited states

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An Effective and Efficient Algorithm for Detecting Exact Deletion Breakpoints from Viral Next-Generation Sequencing Data

An Effective and Efficient Algorithm for Detecting Exact Del...

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2020 International computer Symposium, ICS 2020

作者： Cheng, Ji-Hong Liu, Wen-Chun Chang, Ting-Tsung Hsieh, Sun-Yuan Tseng, Vincent S. National Cheng Kung University Department of Computer Science Taiwan Department of Computer Science and Information Engineering National Cheng Kung University Taiwan Department of Internal Medicine College of Medicine National Cheng Kung University Tainan701 Taiwan Infectious Disease and Signaling Research Center National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9781728192550

The COVID-19 pandemic has caused serious damage to the health, life and, economic stability of human beings all over the world. In order to combat this disease, researchers from all over the world, including computer scientists, are beginning to engage in cross-regional cooperation to conduct research on SARS-CoV-2. One of the latest reports pointed out that the sequence deletion of the specific region of the SARS-CoV-2 genomic is related to its viral infectivity. In addition, the sequence deletion of this specific region is also found in Hepatitis B Virus (HBV), and Hepatocellular carcinoma (HCC). Through next-generation sequencing (NGS) technology, the sequence data of biological genomes can be quickly obtained, but the number of short reads generated by NGS is often as high as one million big data. It is a challenge to detect the information necessary to provide the exact sequence deletion breakpoint from these NGS data, especially in the sequence data of highly variable viral genomes. In our previous research, we proposed VirDelect, a bioinformatics tool that can detect exact breakpoints in Viral NGS data. In this paper, a new method, One-base Alignment Plus (OAP), is proposed to enhance further the core VirDelect algorithm, in order to improve the sequence deletion detection correctness. We use the simulated data of SARS-CoV-2 and HBV with different deletion lengths and the real data of HBV to conduct experiments and evaluate the correctness. The experimental results showed that VirDelect+OAP was able to find deletions that VirDelect could not find in the simulation data, and in the real data, the correctness of VirDelect+OPA was raised effectively. © 2020 IEEE.

关键词： Coronavirus

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Online variant of parcel allocation in last-mile delivery 12

Online variant of parcel allocation in last-mile delivery

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12th International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2020

作者： Liang, Yuan Mao, Changmei Bao, Xiuguo State Key Laboratory of Software Development Environment School of Computer Science Beihang University Beijing100191 China School of Information Management and Engineering Shanghai University of Finance and Economics Shanghai200433 China National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing100029 China

ISBN: (纸本)9781728170817

We investigate the problem of last-mile delivery, where a large amount of crowd-workers have performed a great quantity of location-specific urban logistics parcels. Current existing approaches mainly focus on offline scenarios, where all the spatial-temporal information of parcels and workers are given. However, the offline scenarios can be impractical since parcels and workers appear dynamically in reality, and the information of workers is unknown in advance. In this paper, we study the problem of last-mile delivery on online scenarios to resolve the shortcomings of the offline setting. We first formalize the online parcel allocation in last-mile delivery problem, where all parcels were put in pop-stations in advance, and workers arrive dynamically. Then we propose a baseline algorithm with no competitive ratio, and an algorithm providing theoretical guarantee for the parcel allocation in last-mile delivery. Finally, we verify the effectiveness and efficiency of proposed algorithms through extensive experiments on real and synthetic datasets. © 2020 IEEE.

关键词： Greedy Last-mile delivery Online matching Primal-dual algorithm

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NTRK3 exhibits a pro-oncogenic function in upper tract urothelial carcinomas

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Kaohsiung Journal of Medical sciences 2024年第5期40卷 445-455页

作者： Lim, Lee-Moay Lee, Yi-Chen Lin, Ting-Wei Hong, Zi-Xuan Hsu, Wei-Chi Ke, Hung-Lung Hwang, Daw-Yang Chung, Wen-Yu Li, Wei-Ming Lin, Hui-Hui Kuo, Hung-Tien Huang, A-Mei Graduate Institute of Clinical Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Division of Nephrology Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Graduate Institute of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Anatomy School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Urology School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Department of Urology Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan Department of Urology Kaohsiung Municipal Ta-Tung Hospital Kaohsiung Medical University Kaohsiung Taiwan National Institute of Cancer Research National Health Research Institute Tainan Taiwan Department of Computer Science and Information Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Urology Ministry of Health and Welfare Pingtung Hospital Pingtung Taiwan Department of Medical Research Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan Doctoral Degree Program in Toxicology College of Pharmacy Kaohsiung Medical University Kaohsiung Taiwan Department of Biochemistry School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Research Center for Environmental Medicine Kaohsiung Medical University Kaohsiung Taiwan

Neurotrophic receptor tyrosine kinase 3 (NTRK3) has pleiotropic functions: it acts not only as an oncogene in breast and gastric cancers but also as a dependence receptor in tumor suppressor genes in colon cancer and neuroblastomas. However, the role of NTRK3 in upper tract urothelial carcinoma (UTUC) is not well documented. This study investigated the association between NTRK3 expression and outcomes in UTUC patients and validated the results in tests on UTUC cell lines. A total of 118 UTUC cancer tissue samples were examined to evaluate the expression of NTRK3. Survival curves were generated using Kaplan–Meier estimates, and Cox regression models were used for investigating survival outcomes. Higher NTRK3 expression was correlated with worse progression-free survival, cancer-specific survival, and overall survival. Moreover, the results of an Ingenuity Pathway Analysis suggested that NTRK3 may interact with the PI3K-AKT-mTOR signaling pathway to promote cancer. NTRK3 downregulation in BFTC909 cells through shRNA reduced cellular migration, invasion, and activity in the AKT-mTOR pathway. Furthermore, the overexpression of NTRK3 in UM-UC-14 cells promoted AKT-mTOR pathway activity, cellular migration, and cell invasion. From these observations, we concluded that NTRK3 may contribute to aggressive behaviors in UTUC by facilitating cell migration and invasion through its interaction with the AKT-mTOR pathway and the expression of NTRK3 is a potential predictor of clinical outcomes in cases of UTUC. © 2024 The Authors. The Kaohsiung Journal of Medical sciences published by John Wiley & Sons Australia, Ltd on behalf of Kaohsiung Medical University.

关键词： AKT-mTOR pathway neurotrophic receptor tyrosine kinase 3 (NTRK3) prognosis tropomyosin-related kinase (TrK) upper tract urothelial carcinoma (UTUC)

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A Tutorial on Near-Field XL-MIMO Communications Towards 6G

arXiv

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arXiv 2023年

作者： Lu, Haiquan Zeng, Yong You, Changsheng Han, Yu Zhang, Jiayi Wang, Zhe Dong, Zhenjun Jin, Shi Wang, Cheng-Xiang Jiang, Tao You, Xiaohu Zhang, Rui The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The Purple Mountain Laboratories Nanjing211111 China Shenzhen518055 China The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Research Center of 6G Mobile Communications School of Cyber Science and Engineering The School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Guangdong Shenzhen518172 China The Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

Extremely large-scale multiple-input multiple-output (XL-MIMO) is a promising technology for the sixth-generation (6G) mobile communication networks. By significantly boosting the antenna number or size to at least an order of magnitude beyond current massive MIMO systems, XL-MIMO is expected to unprecedentedly enhance the spectral efficiency and spatial resolution for wireless communication. The evolution from massive MIMO to XL-MIMO is not simply an increase in the array size, but faces new design challenges, in terms of near-field channel modelling, performance analysis, channel estimation, and practical implementation. In this article, we give a comprehensive tutorial overview on near-field XL-MIMO communications, aiming to provide useful guidance for tackling the above challenges. First, the basic near-field modelling for XL-MIMO is established, by considering the new characteristics of non-uniform spherical wave (NUSW) and spatial non-stationarity. Next, based on the near-field modelling, the performance analysis of XL-MIMO is presented, including the near-field signal-to-noise ratio (SNR) scaling laws, beam focusing pattern, achievable rate, and degrees-of-freedom (DoF). Furthermore, various XL-MIMO design issues such as near-field beam codebook, beam training, channel estimation, and delay alignment modulation (DAM) transmission are elaborated. Finally, we point out promising directions to inspire future research on near-field XL-MIMO communications. Copyright © 2023, The Authors. All rights reserved.

关键词： Signal to noise ratio

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An Electrocardiogram Augmentation Method for Automatic Detection of ST-Segment Elevation Myocardial Infarction and Culprit Vessel

An Electrocardiogram Augmentation Method for Automatic Detec...

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Medical Artificial Intelligence (MedAI), IEEE International Conference on

作者： Rihui Song Hengfei Zhang Baoze Zhao Zhidong Tan Liwen Liu Xiaomei Zhou Yuling Zhang Kai Huang School of Computer Science and Engineering Sun Yat-sen University Guangzhou China School of Eletronics and Information Technology Sun Yat-sen University Guangzhou China School of Electronics and Communication Engineering Sun Yat-sen University Guangzhou China M.S. Information Center Third Affiliated Hospital of Sun Yat-sen University Guangzhou China Department of Cardiovascular medicine Sun Yat-sen Memorial Hospital of Sun Yat-sen University Guangzhou China

With the development of deep learning, neural networks have been applied to detect myocardial infarction or culprit vessels using electrocardiograms. Although data augmentation is a widely used technique to improve the performance of neural networks, few augmentation methods are designed for the detection of ST-segment elevation myocardial infarction and culprit vessels. The main purpose of this paper is to improve the accuracy in detecting ST-segment elevation myocardial infarction and culprit vessels with a novel ECG data augmentation algorithm. We propose an augmentation scheme, which synthesizes new samples by splicing and transforming heartbeats. To splice heartbeats without manually labeled segmentation points, we design an automatic detection algorithm for a splicing point. We applied our augmentation method to four neural networks to demonstrate its effectiveness. The experimental results show that the largest increases in accuracy and macro-Fl scores of the models are 6.41% and 5.73%, respectively.

关键词：

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Retraction Note: Research on key technologies of data security and privacy protection in internet of things group intelligence

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Optical and Quantum Electronics 2024年第10期56卷 1-1页

作者： Liu, Yadong Hua, Yahui Chen, Qingrong Academic Affairs Department Xi’an Aeronautical Institute Shaanxi China School of Computer Science Xi’an Aeronautical Institute Shaanxi China Network Information Center Xi’an Aeronautical Institute Shaanxi China

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Aerial Computing: A New Computing Paradigm, Applications, and Challenges

arXiv

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arXiv 2022年

作者： Pham, Quoc-Viet Ruby, Rukhsana Fang, Fang Nguyen, Dinh C. Yang, Zhaohui Le, Mai Ding, Zhiguo Hwang, Won-Joo Korean Southeast Center for the 4th Industrial Revolution Leader Education Pusan National University Busan46241 Korea Republic of College of Computer Science and Software Engineering Shenzhen University China Department of Electrical and Computer Engineering The Department of Computer Science Western University LondonONN6A 3K7 Canada School of Electrical and Computer Engineering Purdue University United States Centre for Telecommunications Research Department of Engineering King’s College LondonWC2R 2LS United Kingdom Department of Information Convergence Engineering Pusan National University Busan46241 Korea Republic of School of Electrical and Electronics Engineering The University of Manchester ManchesterM13 9PL United Kingdom Department of Biomedical Convergence Engineering Pusan National University Yangsan50612 Korea Republic of

In existing computing systems, such as edge computing and cloud computing, several emerging applications and practical scenarios are mostly unavailable or only partially implemented. To overcome the limitations that restrict such applications, the development of a comprehensive computing paradigm has garnered attention in both academia and industry. However, a gap exists in the literature owing to the scarce research, and a comprehensive computing paradigm is yet to be systematically designed and reviewed. This study introduces a novel concept, called aerial computing, via the amalgamation of aerial radio access networks and edge computing, which attempts to bridge the gap. Specifically, first, we propose a novel comprehensive computing architecture that is composed of low-altitude computing, high-altitude computing, and satellite computing platforms, along with conventional computing systems. We determine that aerial computing offers several desirable attributes: global computing service, better mobility, higher scalability and availability, and simultaneity. Second, we comprehensively discuss key technologies that facilitate aerial computing, including energy refilling, edge computing, network softwarization, frequency spectrum, multi-access techniques, artificial intelligence, and big data. In addition, we discuss vertical domain applications (e.g., smart cities, smart vehicles, smart factories, and smart grids) supported by aerial computing. Finally, we highlight several challenges that need to be addressed and their possible solutions. © 2022, CC BY.

关键词： Antennas

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Middle East and North African Health Informatics Association (MENAHIA): Technological initiatives for 'One Health'

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Yearbook of Medical Informatics 2023年第1期32卷 320-329页

作者： Abd-Alrazaq, Alaa Al-Shorbaji, Najeeb Lakhdari, Kheira Elbokl, Ahmed Farouk, Hani Wahba, Hoda Elgasser, Naema Mohell, Rania Emara, Tamer Ayatollahi, Haleh Kalhori, Sharareh R. Niakan Rabiei, Reza Tara, Mahmood Akhu-Zaheya, Laila Al-Qutob, Raeda Alrazak, Sadam Alabed Al-Jafar, Eiman Alhuwail, Dari Ghazal, Hassan Dehbi, Zineb El Otmani Al Idrissi, Najib Fihri, Ouafaa Fassi Belyamani, Lahcen Shahzad, Tariq Ahmed, Zakiuddin Ahmad, Arfan Shah, Zubair Hamra, Eman Abu Taweel, Adel Nashwan, Abdulqadir J. Househ, Mowafa Hamdi, Mounir Al-Thani, Dena Alam, Tanvir Alshammari, Abdulwahhab Alnafrani, Sana Alali, Haitham AI Center for Precision Health Weill Cornell Medicine-Qatarc Doha Qatar EHealth Development Association Amman Jordan Abou Bekr Belkaid University of Tlemcen Chetouane Algeria Ain Shams University Virtual Hospital Ain Shams University Cairo Egypt Ain Shams University Cairo Egypt World Health Organization Cairo Egypt Alexandria Regional Blood Transfusion Center Alexandria University Alexandria Egypt Health Management and Economics Research Center Health Management Research Institute Iran University of Medical Sciences Tehran Iran Department of Health Information Management School of Health Management and Information Sciences Iran University of Medical Sciences Tehran Iran Department of Health Information Management School of Allied Medical Sciences Tehran University of Medical Sciences Tehran Iran Peter L. Reichertz Institute for Medical Informatics (PLRI) Technical University of Braunschweig Hannover Medical School Braunschweig Germany Department of Health Information Technology and Management School of Allied Medical Sciences Shahid Beheshti University of Medical Sciencesc Tehran Iran Department of Medical Informatics Faculty of Medicine Mashhad University of Medical Sciencesc Mashhad Iran School of Nursing Jordan University of Science and Technology Jordan Jordan Centre for Disease Control and Prevention Amman Jordan Faculty of Applied Science and Engineering University of Toronto Toronto Canada Kuwait Health Informatics Association Kuwait Information Science Department College of Life Sciences Kuwait University Kuwait Health Informatics Unit Dasman Diabetes Institute Kuwait Mohammed VI University of Health Sciences Casablanca Morocco National Center for Scientific and Technical Research (CNRST) Rabat Morocco Hassan II Agronomic and Veterinary Institute Rabat Morocco COMSATS University Islamabad Sahiwal Campus Islamabad Pakistan Digital Care Karachi Pakistan College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Al Quds Unive

MENAHIA (Middle East and North African Health Informatics Association) is the International Medical Informatics Association chapter dedicated to the Middle East and North Africa region. This region is rapidly growing in terms of the use of health informatics or what has been recently coined digital health. Human health is highly affected by the health of the environment, animal health, food, nutrition, climate change, and many other factors that are beyond the biological or genetic structure of human beings. The impact of animal health and the health of the environment on people's health is an old phenomenon but recent reemerging and appearance of diseases have clearly demonstrated the link between these. The Novel Coronavirus disease (COVID-19) that almost all of us have been suffering from is an example of this. A number of countries in the region have already shown the depth and the work that they do to integrate the concept of 'One Health' in the public health surveillance system as they have described the work that has been done to capture data from databases other than those dealing with human beings. The examples that were provided to monitor the health of animals, agriculture, environmental health, climate change, and man-made and natural disasters are just examples of what countries have been registering in their databases and informing the health authorities of these changes and emerging trends. © The Author(s) 2023.

关键词： 'One Health' 'One Health' informatics Algeria Artificial Intelligence Climate Change Digital Health Egypt Health Informatics Health information Technologies International Medical Informatics Association (IMIA) Iran Jordan Kuwait MENAHIA Middle East and North Africa Morocco Pakistan Palestine Qatar Saudi Arabia United Arab Emirates Zoonitic Diseases

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Efficient Bipartite Entanglement Detection Scheme with a Quantum Adversarial Solver

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Physical Review Letters 2022年第11期128卷 110501-110501页

作者： Xu-Fei Yin Yuxuan Du Yue-Yang Fei Rui Zhang Li-Zheng Liu Yingqiu Mao Tongliang Liu Min-Hsiu Hsieh Li Li Nai-Le Liu Dacheng Tao Yu-Ao Chen Jian-Wei Pan Hefei National Laboratory for Physical Sciences at the Microscale and Department of Modern Physics University of Science and Technology of China Hefei 230026 China Shanghai Branch CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai 201315 China Shanghai Research Center for Quantum Sciences Shanghai 201315 China JD Explore Academy Beijing 101111 China School of Computer Science Faculty of Engineering University of Sydney Sydney 2006 Australia Hon Hai Quantum Computing Research Center Taipei 114 Taiwan

The recognition of entanglement states is a notoriously difficult problem when no prior information is available. Here, we propose an efficient quantum adversarial bipartite entanglement detection scheme to address this issue. Our proposal reformulates the bipartite entanglement detection as a two-player zero-sum game completed by parameterized quantum circuits, where a two-outcome measurement can be used to query a classical binary result about whether the input state is bipartite entangled or not. In principle, for an N-qubit quantum state, the runtime complexity of our proposal is O(poly(N)T) with T being the number of iterations. We experimentally implement our protocol on a linear optical network and exhibit its effectiveness to accomplish the bipartite entanglement detection for 5-qubit quantum pure states and 2-qubit quantum mixed states. Our work paves the way for using near-term quantum machines to tackle entanglement detection on multipartite entangled quantum systems.

关键词： Entanglement detection Machine learning Quantum entanglement Quantum optics

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