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Utilizing natural compounds as ligands to disrupt the binding of SARS-CoV-2 receptor-binding domain to angiotensin-converting enzyme 2, impeding viral infection

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Phytochemistry Letters 2025年 68卷

作者： Wu, Jingyi Chen, Ting-Hsu Shen, Zi-han Tsai, May-Jywan Leong, Max K. Huang, Yan-qiang Weng, Ching-Feng Guangxi Technology Innovation Cooperation Base of Prevention and Control Pathogenic Microbes With Drug Resistance Youjiang Medical University for Nationalities Baise 533000 China Graduate Institute of Brain and Mind Sciences College of Medicine National Taiwan University Taipei 10051 Taiwan Functional Physiology Section Department of Basic Medical Science Xiamen Medical College Fujian Xiamen 361023 China Neural Regeneration Laboratory Department of Neurosurgery Neurological Institute Taipei Veterans General Hospital Taipei 11217 Taiwan Department of Chemistry National Dong Hwa University Hualien 97401 Taiwan Guangxi Zhuang Autonomous Region Engineering Research Center of Clinical Prevention and Control Technology and Leading Drug for Microorganisms with Drug Resistance in Border Ethnic Areasn Baise 533000 China

Currently, no specific antiviral drug has been definitively proven effective in treating patients with severe coronavirus disease 2019 (COVID-19). Various specific strategies have been employed against COVID-19;however, several potent antiviral candidates, including prodrugs and repurposed drugs, are still under urgent investigation, particularly in the search for molecular targets. This study aimed to evaluate the potential of natural compounds and chemicals against RNA viruses using a three-tiered approach to molecular docking. Binding scores obtained from ChemPLP revealed that natural compounds and repurposed drugs exhibited strong affinities for the binding sites on angiotensin-converting enzyme 2 (ACE2) receptors in host cells, the receptor-binding domain (RBD) site of the RBD-ACE2 complex, PL^pro, and 3CL^pro. Conclusively, these findings suggest that alternative medicines and antiviral drug repurposing strategies may provide promising therapeutic remedies for patients with COVID-19, along with further validation via preclinical and clinical trials. © 2025 The Authors

关键词： ACE2 Arachidonic acid Chloroquine COVID-19 Curcumin Darunavir Hydroxychloroquine RBD Remdesivir

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REMOVED: Machine learning in health condition check-up: An approach using Breiman's random forest algorithm

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Measurement: Sensors 2022年 23卷

作者： Yousef Methkal Abd Algani Mahyudin Ritonga B. Kiran Bala Mohammed Saleh Al Ansari Malek Badr Ahmed I. Taloba Department of Mathematics Sakhnin College Israel Department of Mathematics The Arab Academic College for Education in Israel-Haifa Israel Muhammadiyah University of West Sumatra Indonesia Department of Artificial Intelligence and Data Science K.Ramakrishnan College of Engineering (Autonomous) Samayapuram 621112 Trichy India College of Engineering Department of Chemical Engineering University of Bahrain Bahrain The University of Mashreq Research Center Baghdad Iraq Department of Medical Instruments Engineering Techniques Al-Farahidi University Baghdad 10021 Iraq Department of Computer Science College of Science and Arts in Qurayyat Jouf University Saudi Arabia Information System Department Faculty of Computers and Information Assiut University Assiut Egypt

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Comparing relaxation mechanisms in quantum and classical transverse-field annealing

arXiv

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arXiv 2020年

作者： Albash, Tameem Marshall, Jeffrey Department of Electrical and Computer Engineering University of New Mexico AlbuquerqueNM87131 United States Department of Physics and Astronomy Center for Quantum Information and Control CQuIC University of New Mexico AlbuquerqueNM87131 United States QuAIL NASA Ames Research Center Moffett FieldCA94035 United States USRA Research Institute for Advanced Computer Science Mountain ViewCA94043 United States

Annealing schedule control provides new opportunities to better understand the manner and mechanisms by which putative quantum annealers operate. By appropriately modifying the annealing schedule to include a pause (keeping the Hamiltonian fixed) for a period of time, we show it is possible to more directly probe the dissipative dynamics of the system at intermediate points along the anneal and examine thermal relaxation rates, for example, by observing the re-population of the ground state after the minimum spectral gap. We provide a detailed comparison of experiments from a D-Wave device, simulations of the quantum adiabatic master equation and a classical analogue of quantum annealing, spin-vector Monte Carlo, and we observe qualitative agreement, showing that the characteristic increase in success probability when pausing is not a uniquely quantum phenomena. We find that the relaxation in our system is dominated by a single time-scale, which allows us to give a simple condition for when we can expect pausing to improve the time-to-solution, the relevant metric for classical optimization. In the system studied here, only for short pauses is there expected to be an improvement. Finally, we also explore in simulation the role of temperature whilst pausing as a means to better distinguish quantum and classical models of quantum annealers. Copyright © 2020, The Authors. All rights reserved.

关键词： Annealing

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A Markov Traffic Model for Signalized Traffic Networks Based on Bayesian Estimation

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IFAC-PapersOnLine 2020年第2期53卷 15029-15034页

作者： S.Y. Liu S. Lin Y.B. Wang B. De Schutter W.H.K. Lam School of Computer Science and Technology University of Chinese Academy of Sciences Beijing 100089 China Key Lab of Big Data Mining and Knowledge Management Chinese Academy of Sciences College of Civil Engineering and Architecture Zhejiang University PR China Delft Center for Systems and Control Delft University of Technology The Netherlands Department of Civil and Structural Engineering The Hong Kong Polytechnic University Hong Kong SAR China

In order to better understand the stochastic dynamic features of signalized traffic networks, we propose a Markov traffic model to simulate the dynamics of traffic link flow density for signalized urban traffic networks with demand uncertainty. In this model, we have four different state modes for the link according to different congestion levels of the link. Each link can only be in one of the four link state modes at any time, and the transition probability from one state to the other state is estimated by Bayesian estimation based on the distributions of the dynamic traffic flow densities, and the posterior probabilities. Therefore, we use a first-order Markov Chain Model to describe the dynamics of the traffic flow evolution process. We illustrate our approach for a small traffic network. Compared with the data from the microscopic traffic simulator SUMO, the proposed model can estimate the link traffic densities accurately and can give a reliable estimation of the uncertainties in the dynamic process of signalized traffic networks.

关键词： Markov traffic model Traffic signals Bayesian Urban traffic network

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NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

arXiv

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arXiv 2022年

作者： Li, Yawei Zhang, Kai Timofte, Radu Van Gool, Luc Kong, Fangyuan Li, Mingxi Liu, Songwei Du, Zongcai Liu, Ding Zhou, Chenhui Chen, Jingyi Han, Qingrui Li, Zheyuan Liu, Yingqi Chen, Xiangyu Cai, Haoming Qiao, Yu Dong, Chao Sun, Long Pan, Jinshan Zhu, Yi Zong, Zhikai Liu, Xiaoxiao Hui, Zheng Yang, Tao Ren, Peiran Xie, Xuansong Hua, Xian-Sheng Wang, Yanbo Ji, Xiaozhong Lin, Chuming Luo, Donghao Tai, Ying Wang, Chengjie Zhang, Zhizhong Xie, Yuan Cheng, Shen Luo, Ziwei Yu, Lei Wen, Zhihong Wu, Qi Li, Youwei Fan, Haoqiang Sun, Jian Liu, Shuaicheng Huang, Yuanfei Jin, Meiguang Huang, Hua Liu, Jing Zhang, Xinjian Wang, Yan Long, Lingshun Li, Gen Zhang, Yuanfan Cao, Zuowei Sun, Lei Alexander, Panaetov Wang, Yucong Cai, Minjie Wang, Li Tian, Lu Wang, Zheyuan Ma, Hongbing Liu, Jie Chen, Chao Cai, Yidong Tang, Jie Wu, Gangshan Wang, Weiran Huang, Shirui Lu, Honglei Liu, Huan Wang, Keyan Chen, Jun Chen, Shi Miao, Yuchun Huang, Zimo Zhang, Lefei Ayazoglu, Mustafa Xiong, Wei Xiong, Chengyi Wang, Fei Li, Hao Wen, Ruimian Yang, Zhijing Zou, Wenbin Zheng, Weixin Ye, Tian Zhang, Yuncheng Kong, Xiangzhen Arora, Aditya Zamir, Syed Waqas Khan, Salman Hayat, Munawar Khan, Fahad Shahbaz Gao, Dandan Zhou, Dengwen Ning, Qian Tang, Jingzhu Huang, Han Wang, Yufei Peng, Zhangheng Li, Haobo Guan, Wenxue Gong, Shenghua Li, Xin Liu, Jun Wang, Wanjun Zeng, Kun Lin, Hanjiang Chen, Xinyu Fang, Jinsheng Zhang, Shuhao Zhang, Yuhao Sinha, Abhishek Kumar Moorthi, S. Manthira Dhar, Debajyoti Yang, Hao-Hsiang Huang, Zhi-Kai Chen, Wei-Ting Chang, Hua-En Kuo, Sy-Yen Tan, Wei Chen, Hao Xu, Qian Narang, Pratik Singh, Usneek Sameen, Syed Khaitan, Harsh Yinghua, Liu Tianlin, Zhang Xiaoming, Zhang Meng, Dingxuan Tian, Chunwei Morshed, Mashrur M. Ahsan, Ahmad Omar Computer Vision Lab ETH Zurich Switzerland University of Würzburg Germany ByteDance Shenzhen China State Key Laboratory for Novel Software Technology Nanjing University China ByteDance Inc China NetEase Inc. China Shenzhen Institutes of Advanced Technology CAS China University of Macau China Shanghai AI Lab Shanghai China Nanjing University of Science and Technology China Amazon Web Services United States China Alibaba DAMO Academy EFC Yuhang District Zhejiang Hangzhou China East China Normal University China Youtu Lab Tencent China Megvii Technology China University of Electronic Science and Technology of China China School of Artificial Intelligence Beijing Normal University China Alibaba Group China Bilibili AI China Nankai-Baidu Joint Lab Nankai University Tianjin China Platform Technologies Tencent Online Video China Higher School of Economics Russia Huawei Moscow Research Center Russia Hunan University China Xidian University China Xilinx Technology Beijing Limited China College of Information Science and Engineering Xinjiang University Urumqi China Department of Electronic Engineering Tsinghua University Beijing China Nanjing University China McMaster University Canada School of Telecommunication Engineering Xidian University Xi’an China School of Computer Science Wuhan University Wuhan China School of Mathematical Science University of Electronic Science and Technology of China Chengdu China School of Computer Science The University of Sydney Sydney Australia Aselsan Research Ankara Turkey School of Electronic and Information Engineering South-Central University for Nationalities Wuhan China Guangdong University of Technology China Fujian Normal University Fuzhou University Jimei University China Design Group China Abu Dhabi United Arab Emirates Monash University Melbourne Australia Mohamed bin Zayed University of AI United Arab Emirates North China Electric Power University Changping District Beijing China The School of Art

This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-resolve an input image with a magnification factor of ×4 based on pairs of low and corresponding high resolution images. The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29.00dB on DIV2K validation set. IMDN is set as the baseline for efficiency measurement. The challenge had 3 tracks including the main track (runtime), sub-track one (model complexity), and sub-track two (overall performance). In the main track, the practical runtime performance of the submissions was evaluated. The rank of the teams were determined directly by the absolute value of the average runtime on the validation set and test set. In sub-track one, the number of parameters and FLOPs were considered. And the individual rankings of the two metrics were summed up to determine a final ranking in this track. In sub-track two, all of the five metrics mentioned in the description of the challenge including runtime, parameter count, FLOPs, activations, and memory consumption were considered. Similar to sub-track one, the rankings of five metrics were summed up to determine a final ranking. The challenge had 303 registered participants, and 43 teams made valid submissions. They gauge the state-of-the-art in efficient single image super-resolution. © 2022, CC BY.

关键词： Chemical activation

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Doping-driven electronic and lattice dynamics in the phase-change material vanadium dioxide

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Physical Review B 2020年第11期102卷 115148-115148页

作者： Kannatassen Appavoo Joyeeta Nag Bin Wang Weidong Luo Gerd Duscher E. Andrew Payzant Matthew Y. Sfeir Sokrates T. Pantelides Richard F. Haglund, Jr. Department of Physics University of Alabama at Birmingham Birmingham Alabama 35294 USA Department of Physics and Astronomy Vanderbilt University Nashville Tennessee 37235 USA School of Chemical Biological and Materials Engineering University of Oklahoma Norman Oklahoma 73019 USA Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak Ridge Tennessee 37831 USA Key Laboratory of Artificial Structures and Quantum Control School of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 China Department of Materials Science and Engineering University of Tennessee Knoxville Tennessee 37996 USA Center for Functional Nanomaterials Brookhaven National Laboratory Upton New York 11973 USA Department of Electrical Engineering and Computer Science Vanderbilt University Nashville Tennessee 37235 USA

Doping is generally understood as a strategy for including additional positive or negative charge carriers in a semiconductor, thereby tuning the Fermi level and changing its electronic properties in the equilibrium limit. However, because dopants also couple to all of the microscopic degrees of freedom in the host, they may also alter the nonequilibrium dynamical properties of the parent material, especially at large dopant concentrations. Here, we show how substitutional doping by tungsten at the 1 at. % level modifies the complex electronic and lattice dynamics of the phase-change material vanadium dioxide. Using femtosecond broadband spectroscopy, we compare dynamics in epitaxial thin films of pristine and tungsten-doped VO2 over the broadest wavelength and temporal ranges yet reported. We demonstrate that coupling of tungsten atoms to the host lattice modifies the early electron-phonon dynamics on a femtosecond timescale, altering in a counterintuitive way the ps-to-ns optical signatures of the phase transition. Density functional theory correctly captures the enthalpy difference between pristine and W-doped VO2 and shows how the dopant softens critical V-V phonon modes while introducing new phononic modes due to W-V bonds. While substitutional doping provides a powerful method to control the switching threshold and contrast of phase-change materials, determining how the dopant dynamically changes the broadband optical response is equally important for optoelectronics.

关键词： Electronic structure Lattice dynamics Phase transitions Phonons Photonics Functional materials Thin films Band structure methods Electron microscopy Epitaxy Femtosecond laser spectroscopy Film deposition First-principles calculations Laser techniques Monte Carlo methods Scanning electron microscopy

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Data mining-based model and risk prediction of colorectal cancer by using secondary health data:A systematic review

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Chinese Journal of Cancer Research 2020年第2期32卷 242-251页

作者： Hailun Liang Lei Yang Lei Tao Leiyu Shi Wuyang Yang Jiawei Bai Da Zheng Ning Wang Jiafu Ji School of Public Administration and Policy Renmin University of ChinaBeijing 100872China Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing) Beijing Office for Cancer Prevention and ControlPeking University Cancer Hospital&InstituteBeijing 100142China Departm ent of Public Policy City University of Hong KongHong Kong SAR999077China Johns Hopkins Primary Care Policy Center BaltimoreMD 21205USA Ddepartment of Neurosurgery Johns Hopkins MedicineBaltimoreMD 21205USA Department of Biostatistics Johns Hopkins Bloomberg School of Public HealthBaltimoreMD 21205USA Department of Computer Science Johns Hopkins Whiting School of EngineeringBaltimoreMD 21205USA Key Laboratory of Carcinogenesis and Translational Research(Ministiy of Education/Beijing) Center of Gastrointestinal SurgeryPeking University Cancer Hospital&InstituteBeijing 100142China

Objective:Prevention and early detection of colorectal cancer(CRC)can increase the chances of successful treatment and reduce *** data mining technologies have been utilized to strengthen the early detection of CRC in primary *** synthesis on the model’s effectiveness is *** systematic review synthesizes studies that examine the effect of data mining on improving risk prediction of ***:The PRISMA framework guided the conduct of this *** obtained papers via Pub Med,Cochrane Library,EMBASE and Google *** appraisal was performed using Downs and Black’s quality *** evaluate the performance of included models,the values of specificity and sensitivity were comparted,the values of area under the curve(AUC)were plotted,and the median of overall AUC of included studies was ***:A total of 316 studies were reviewed for full *** articles were *** studies implement techniques including artificial neural networks,Bayesian networks and decision *** articles reported the overall model ***,the median AUC is 0.8243[interquartile range(IQR):0.8050-0.8886].In the two articles that reported comparison results with traditional models,the data mining method performed better than the traditional models,with the best AUC improvement of 10.7%.Conclusions:The adoption of data mining technologies for CRC detection is at an early *** numbers of included articles and heterogeneity of those studies implied that more rigorous research is expected to further investigate the techniques’effects.

关键词： Systematic review colorectal cancer disease detection data mining

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Max-min energy balance in wireless-powered hierarchical fog-cloud computing networks

Max-min energy balance in wireless-powered hierarchical fog-...

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作者： Liu, Jingxian Xiong, Ke Ng, Derrick Wing Kwan Fan, Pingyi Zhong, Zhangdui Letaief, Khaled Ben School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing100044 China School of Electrical Engineering and Telecommunications UNSW Sydney SydneyNSW2052 Australia Department of Electronic Engineering Tsinghua University Beijing100084 China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China Hong Kong Peng Cheng Laboratory Shenzhen518055 China

This paper investigates the wireless-powered hierarchical fog-cloud computing networks, where multiple energy-constrained users harvest energy from a hybrid access point (HAP) firstly and then use their harvested energy to offload their computation tasks to fog/cloud servers via the HAP or compute their tasks locally. To pursue multi-user fairness, an optimization problem is formulated to maximize the minimal energy balance among all users by jointly optimizing time assignments, computation central processing unit (CPU) frequencies, and the computing mode selection. Since the problem is mixed-integer combinatorial non-convex, which is intractable, a generalized Benders decomposition (GBD)-based method is proposed, which guarantees the globally optimal solution. To release the high computational complexity of the proposed GBD-based method, a penalized successive convex approximation (P-SCA)-based algorithm is designed as an alternative to obtain a suboptimal solution with low computational complexity. Numerical results show that among different optimizable factors in the system, computing mode selection is the dominant one on affecting the system performance. Moreover, for each user, local computing is a better choice, if it is with relatively poor channel gain and small local computing delay. Otherwise, fog/cloud computing may be a better choice. Additionally, for the users with relatively high channel gains, if their local computing delays are less than those selecting fog computing, cloud computing should be a better choice. © 2002-2012 IEEE.

关键词： Energy transfer

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Transfer Learning for EEG-Based Brain-computer Interfaces: A Review of Progress Made Since 2016

arXiv

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arXiv 2020年

作者： Wu, Dongrui Xu, Yifan Lu, Bao-Liang The Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Brain Science and Technology Research Center Qing Yuan Research Institute Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai200240 China

A brain-computer interface (BCI) enables a user to communicate with a computer directly using brain signals. The most common non-invasive BCI modality, electroencephalogram (EEG), is sensitive to noise/artifact and suffers between-subject/within-subject non-stationarity. Therefore, it is difficult to build a generic pattern recognition model in an EEG-based BCI system that is optimal for different subjects, during different sessions, for different devices and tasks. Usually, a calibration session is needed to collect some training data for a new subject, which is time-consuming and user unfriendly. Transfer learning (TL), which utilizes data or knowledge from similar or relevant subjects/sessions/devices/tasks to facilitate learning for a new subject/session/device/task, is frequently used to reduce the amount of calibration effort. This paper reviews journal publications on TL approaches in EEG-based BCIs in the last few years, i.e., since 2016. Six paradigms and applications - motor imagery, event-related potentials, steady-state visual evoked potentials, affective BCIs, regression problems, and adversarial attacks - are considered. For each paradigm/application, we group the TL approaches into cross-subject/session, cross-device, and cross-task settings and review them separately. Observations and conclusions are made at the end of the paper, which may point to future research directions. Copyright © 2020, The Authors. All rights reserved.

关键词： Brain computer interface

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A Green Paradigm for Internet of Things: Ambient Backscatter Communications

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China Communications 2019年第7期16卷 109-119页

作者： Wei Zhang Yao Qin Wenjing Zhao Minzheng Jia Qiang Liu Ruisi He Bo Ai Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology and also with Institute of Telecommunication Satellites China Academy of Space Technology (CAST) Beijing Key Lab of Transportation Data Analysis and Mining Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 China Department of Information Engineering Beijing Polytechnic College Beijing 100042 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China

Internet of Things (IoT) has attracted extensive interest from both academia and industries, and is recognized as an ultimate infrastructure to connect everything at anytime and anywhere. The implementation of IoT generally faces the challenges from energy constraint and implementation cost. In this paper, we will introduce a new green communication paradigm, the ambient backscatter (AmBC), that could utilize the environmental wireless signals for both powering a tiny-cost device and backscattering the information symbols. Specifically, we will present the basic principles of AmBC, analyze its features and advantages, suggest its open problems, and predict its potential applications for our future IoT.

关键词： ambient backscatter (AmBC) RF-powered device Internet of Things (IoT) battery-free tag wire-less sensor

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