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International Journal of Intelligent systems Technologies and Applications 2019年第4期18卷 405-425页

作者： Fouaz, Berrhail Hacene, Belhadef Hamza, Hentabli Saeed, Faisal MISC Laboratory NTIC Faculty Constantine 2 University Algeria LAS Laboratory Setif 1 University Algeria Faculty of Computer Science and Information System Universiti Teknologi Malaysia Malaysia College of Computer Science and Engineering Taibah University Medina Saudi Arabia

Similarity searching plays an increasingly important role in virtual screening. It is a screening technique that works by comparing the features of the target compound with the features of each compound in the database of compounds. This comparison can be described in three steps. The first step involves the representation of the target compound and the database compounds with an equivalent representation, which is set of binary elements describing the presence or the absence of attributes of compounds (fingerprint). The second step uses similarity coefficient to calculate the score of similarity between two compounds representation. The third step is to rank the database compounds in appropriate order of the similarity score, in order to determine the actives compounds. Many approaches and techniques have been introduced in literature to enhancing and improving similarity-based virtual screening. In this work, our primary interests are to investigate the effect of using different combinations of fingerprint and similarity coefficient in ligand-based virtual screening (LBVS). We use in this investigation the MDDR (drug data report database) to evaluate the different combinations descriptor-coefficient. Some obtained results of combinations with some coefficients demonstrate superiority in performances to these obtained in combination with Tanimoto coefficient. © 2019 Inderscience Enterprises Ltd.

关键词： Ligands

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Generation of a Compendium of Transcription Factor Cascades and Identification of Potential Therapeutic Targets using Graph Machine Learning

arXiv

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arXiv 2023年

作者： Sivarajkumar, Sonish Tandale, Pratyush Bhardwaj, Ankit Johnson, Kipp W. Titus, Anoop Glicksberg, Benjamin S. Khader, Shameer Yadav, Kamlesh K. Subramanian, Lakshminarayanan Molecular Robotics Kerala India School of Computing and Information University of Pittsburgh Pennsylvania PA United States Health Informatics & Data Science Georgetown University WashingtonDC United States Department of Computer Science Courant Institute of Mathematical Sciences New York University New YorkNY United States Institute for Next Generation Healthcare Mount Sinai Health System New YorkNY United States Department of Preventive Cardiology DeBakey Heart & Vascular Center Houston Methodist HoustonTX United States Hasso Plattner Institute for Digital Health Icahn School of Medicine at Mount Sinai New YorkNY United States Faculty of Medicine Imperial College London London United Kingdom School of Engineering Medicine Texas A&M University HoustonTX United States Department of Translational Medical Sciences Center for Genomic and Precision Medicine Texas A&M University HoustonTX United States

Transcription factors (TFs) play a vital role in the regulation of gene expression thereby making them critical to many cellular processes. In this study, we used graph machine learning methods to create a compendium of TF cascades using data extracted from the STRING database. A TF cascade is a sequence of TFs that regulate each other, forming a directed path in the TF network. We constructed a knowledge graph of 81,488 unique TF cascades, with the longest cascade consisting of 62 TFs. Our results highlight the complex and intricate nature of TF interactions, where multiple TFs work together to regulate gene expression. We also identified 10 TFs with the highest regulatory influence based on centrality measurements, providing valuable information for researchers interested in studying specific TFs. Furthermore, our pathway enrichment analysis revealed significant enrichment of various pathways and functional categories, including those involved in cancer and other diseases, as well as those involved in development, differentiation, and cell signaling. The enriched pathways identified in this study may have potential as targets for therapeutic intervention in diseases associated with dysregulation of transcription factors. We have released the dataset, knowledge graph, and graphML methods for the TF cascades, and created a website to display the results, which can be accessed by researchers interested in using this dataset. Our study provides a valuable resource for understanding the complex network of interactions between TFs and their regulatory roles in cellular processes. Copyright © 2023, The Authors. All rights reserved.

关键词： Transcription factors

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Control design considering magnetic flux characteristic uncertainty for magnetic levitation system with magnetic flux and current feedback

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and systems 2019年第10期139卷 1159-1166页

作者： Urasaki, Shinpachiro Kobayashi, Yoshimitsu Kami, Yasushi Mitani, Yuichiroh Nobuyama, Eitaku Department of Electronic Control Engineering National Institute of Technology Gifu College 2236-2. Kamimakuwa. Motosu. Gifu 501-0495 Japan Department of Electrical and Computer Engineering National Institute of Technology Akashi College 679-3. Nishioka. Uozumi Akashi. Hyogo674-8501 Japan Department of Mechanical Engineering National Institute of Technology Numazu College 3600. Ooka. Numazu Shizuoka410-8501 Japan Department of Systems Innovation and Informatics Faculty of Computer Science and System Engineering Kyushu Institute of Technology 680-4.Kawazu. Iizuka Fukuoka820-8502 Japan

This paper describes control design considering magnetic flux characteristic uncertainty for magnetic levitation system with magnetic flux and current feedback. The position of the levitated object is calculated from the hall voltage and current of the electromagnet. We show the uncertainty for magnetic flux characteristic and design the stabilizing controller by proportional feedback with the hall voltage and current. Moreover, we tried to design servo controller by two-degree-of-freedom control by using a finite number of frequency response (FNFR) model including the uncertainty and confirmed the validity of the proposed method by experiment results. © 2019 The Institute of Eleclrical Engineers of Japan.

关键词： Frequency response

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Bacteria Flagella-Mimicking Polymer Multilayer Magnetic Microrobots

SSRN

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SSRN 2024年

作者： Wu, Zhiguang Lu, Liang Bai, Shuang Shi, Jiaqi Zhang, Zhuotao Pan, Yunlu Wang, Wei Wu, Wenfeng Sun, Shoubin Li, Xu Hou, Gang Huang, Tianyun Jia, Yuxin Zuo, Kaiwen Granovsky, Alexander Wu, He Nikolai, Perov School of Medicine and Health Harbin Institute of Technology Harbin China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China The First Affiliated Hospital of Harbin Medical University Harbin China National Center for Respiratory Medicine State Key Laboratory of Respiratory Health and Multimorbidity National Clinical Research Center for Respiratory Diseases Institute of Respiratory Medicine Chinese Academy of Medical Sciences Department of Pulmonary and Critical Care Medicine Center of Respiratory Medicine China-Japan Friendship Hospital Beijing China College of Science Sichuan Agricultural University Chengdu China The Fourth Affiliated Hospital of Harbin Medical University Harbin China Department of Ophthalmology The Second Hospital Jilin University Changchun China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China Department of Mathematics Imperial College London United Kingdom Department of Computer Science University of Warwick Coventry United Kingdom Magnetism Department Faculty of Physics Lomonosov Moscow State University Moscow Russia Harbin Medical University China

Learning from natural bacteria flagellum, we demonstrate a magnetic polymer multilayer conical microrobot that bestow the controllable propulsion upon external rotating magnetic field with uniform intensity. The magnetic microrobots were constructed by template-assisted Layer-by-Layer technique technique and subsequent functionalization of magnetic particle onto the big opening of the microrobots. Geometric variables of the polymer microrobots, such as the diameter and wall thickness, can be controlled by selection of porous template and layers of assembly. The microrobots perform controllable propulsion through the manipulation of magnetic field. The comparative analysis of the movement behavior reveals that the deformation of microrobots may attributed to the propulsion upon rotating magnetic field, which is similar as that of natural bacteria. The influence of actuation frequencies and frequencies on the velocity of the microrobots is studied. Such use of polymer polymer multilayer tubular micro/nanoarchitectures results in significant savings in the processing costs and provides a simple and cost-effective fabrication route for the mass production of magnetic polymer microrobots. © 2024, The Authors. All rights reserved.

关键词： Bacteria

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Multispectral sensors calibration for lightweight UAV 9

Multispectral sensors calibration for lightweight UAV

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9th IGRSM International Conference and Exhibition on Geospatial and Remote Sensing: Geospatial Enablement, IGRSM 2018

作者： Mansor, Yaakob Mansor, Shattri Zulhaidi, Helmi Ramli, Abdul Rahman Isola, Ajibola I Centre of Foundation Studies for Agricultural Science Malaysia Department of Civil Faculty of Engineering Malaysia Department of Computer and Communication System Faculty of Engineering Malaysia Malaysia

Using a suitable gimbal sensor, a lightweight multispectral sensor weight less than 500 g, such as visible imagery in the 400-700 nm (4000x3000 pixels), NIR imagery in the 520-920 nm region (2048 x 1536 pixels) and thermal 8-14μm (160x120 pixels) were placed on low-cost Hexacopter UAVs to perform aerial acquisitions of oil palm plant at very low altitude. Reliability data analysis is generated from the correction of undesirable and defect of sensor characteristics. Here, the sensor correction and calibration such as geometric, radiometric, vignetting, resolution and directional effects. Radiometric calibration using an upwelling water methodology where with thermosensor, the coefficient of determination, R2 = 1 and without thermosensor, R2 = 0.9455. For multi-temporal or multi-sensor image analysis, relative DN-to-radiance radiometric calibration was performed by using the white material as calibration, then convert the other colored area without the material based on the ratio of the white panel area and the color reflected in that area and compatible with in-situ spectroscopy device. © Published under licence by IOP Publishing Ltd.

关键词： Pixels

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Dynamic A-MPDU adaptation method for airtime fairness in channel bonding-ready WLANs

Dynamic A-MPDU adaptation method for airtime fairness in cha...

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IEEE Pacific Rim Conference on Communications, computers and Signal Processing

作者： Yusuke Shimizu Daiki Nobayashi Hitomi Tamura Kazuya Tsukamoto Graduate School of Computer Science and System Engineering Kyushu Institute of Technology Fukuoka Japan Faculty of Engineering Kyushu Institute of Technology Fukuoka Japan Graduate School of Engineering Fukuoka Institute of Technology Fukuoka Japan Faculty of Computer Science and Engineering Kyushu Institute of Technology Fukuoka Japan

Channel bonding is a technology to increase the transmission rate by bundling and using multiple continuous channels. However, the communication performance is likely to degrade frequently due to the channel competition caused by the rapid increase of the wireless LAN devices. Dynamic channel bonding is expected to become the mainstream in the future from the viewpoint of efficient channel utilization even under the severe competitive condition. However, since the implementation of the dynamic channel bonding to real PC and simulator is in the preliminary stage, the detailed performance investigation has not been carried out. None of existing studies examines the performance of the dynamic channel bonding at the frame level with CSMA/CA functions under the diverse channel competition condition. In this study, we first examine the performance of the dynamic channel bonding with CSMA/CA functions through theoretical approach (2 M/M/1/K) from the view point of frame level. In addition, we then implement the channel bonding mechanism into the Scenargie simulator and then verify its effectiveness through the comparison between simulation results and theoretical ones. Simulation results show that the dynamic channel bonding is suffering from the performance degradation due to the performance anomaly problem caused by the airtime unfairness, we thus propose a dynamic A-MPDU adaptation method. We showed that our proposed method can maximize throughput while achieving airtime fairness, irrespective of different patterns of channel competition.

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Analysis of smart city environment by artificial intelligent techniques

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AIP Conference Proceedings 2023年第1期2831卷

作者： Sujay Mugaloremutt Jayadeva A. K. Gnanasekar Prashant Sunagar N. Harshith Sahil Sanjeev Salvi Ashok Kumar Department of Health System Management Studies JSS Academy of Higher Education & Research (Faculty of Management Studies) Mysuru-570015 India Department of Electronics & Communication Engineering Rajalakshmi Institute of Technology Chembarambakkam Chennai Tamil Nadu-600124 India Department of Civil Engineering M.S. Ramaiah Institute of Technology MSR Nagar Bengaluru Karnataka-560054 India Department of Civil Engineering Pimpri Chinchwad College of Engineering and Research Ravet Pune Maharashtra-412101 India Department of Computer Science Banasthali Vidyapith Banasthali Rajasthan-304022 India

The expectation of artificial intelligence is happened to realize in such a way that it essentially and most peculiarly supports the sustainable enhancement of fore coming smart environment surrounding the cities. The contribution towards the different developing fields of artificial intelligence have been made in determining the transformation towards traditional cities with conventional facilities into fully built smart environmental cities. The knowledge of producing better standards of living by rebuilding technology into daily activities of human is the primary requirements of the smart city emergence with esteemed technologies. In this proposed study, the concepts are enlightened towards few enhanced and developed technologies and identification of solutions to different problems that has been faced by people due to absence of digital environment. It illustrates certain problems that has been related to the smart city infrastructure, security, public safety, which lends suitable solutions for the denoted problems. It not only creates the emphasis on the technique of artificial intelligence but also on the Internet of Things (IoT) applications, pattern recognitions, deep and machine learning, analytics of big data and infrastructures associated with cloud computing in establishing the development as a completely equipped smart city.

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Removal notice to “Machine learning in health condition check-up: An approach using Breiman's random forest algorithm”

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Measurement: Sensors 2023年 27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

This article has been removed: please see Elsevier Policy on Article Withdrawal ( https://***/about/policies/article-withdrawal ). This article has been removed at the request of the Authors, due to incomplete authorisation for the publication of the article from one of the author's institutions. The authors sincerely apologize for the inconvenience.

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Exploring the metabolic landscape of lung adenocarcinoma and squamous cell carcinoma: a total-body [18F]FDG PET/CT approach

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European journal of nuclear medicine and molecular imaging 2025年 2025 Jun 3页

作者： Xuetong Tao Haiyan Wang Jiaxiang Qu Zixiang Chen Yaping Wu Ruohua Chen Jianjun Liu Na Zhang Hairong Zheng Dong Liang Meiyun Wang Zhanli Hu Lauterbur Research Center for Biomedical Imaging Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China. Key Laboratory of Biomedical Imaging Science and System State Key Laboratory of Biomedical Imaging Science and System Chinese Academy of Sciences Shenzhen 518055 China. Research Center for Medical AI Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China. Biomedical Imaging Laboratory (BIG) Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau 999078 Macau SAR China. Department of Medical Imaging Henan Provincial People's Hospital & People's Hospital of Zhengzhou University Zhengzhou 450003 China. Department of Nuclear Medicine Ren Ji Hospital School of Medicine Shanghai Jiao Tong University Shanghai 201807 China. Key Laboratory of Biomedical Imaging Science and System State Key Laboratory of Biomedical Imaging Science and System Chinese Academy of Sciences Shenzhen 518055 China. zl.hu@***. Research Center for Medical AI Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China. zl.hu@***.

PURPOSE:Cancer is increasingly recognized not just as a localized disease but as a systemic condition with profound impacts on metabolism at both cellular and whole-body levels. This study seeks to unveil the systemic metabolic disruptions in early-stage, untreated lung cancer patients, specifically adenocarcinoma (ADC) and squamous cell carcinoma (SqCC), using a novel network-based approach with total-body static and dynamic PET/CT imaging. By analyzing inter-organ metabolic dependencies, we aim to uncover how lung cancer induces whole-body metabolic reprogramming, providing insights into potential biomarkers for monitoring disease progression and treatment response. METHODS:This retrospective study included 32 early-stage untreated lung cancer patients and 20 healthy volunteers. Static and dynamic total-body PET/CT scans were performed to assess glucose consumption across the body. Twenty-five regions of interest (ROIs) representing major organs were selected, and metabolic status was quantified using the average SUV and Ki values for each ROI. Inter-organ metabolic dependencies were quantified using mutual information (MI), which measures the amount of shared information between two variables, capturing both linear and nonlinear relationships, followed by Bonferroni correction to control for multiple comparisons. Population-level metabolic networks were constructed to visualize alterations in interregional connectivity for ADC, SqCC, and healthy cohorts. Furthermore, to capture personalized metabolic deviations, individual networks were constructed for each cancer patient. RESULTS:The analysis revealed distinct metabolic network patterns in ADC and SqCC patients compared to healthy controls. ADC patients exhibited selective enhancements in metabolic connectivity, particularly between the central nervous system and peripheral organs such as the adrenal glands and pancreas, suggesting activation of compensatory neuroendocrine mechanisms. In contrast, SqCC patients

关键词： Adenocarcinoma Lung cancer Lung cancer metabolism Metabolic network Squamous cell carcinoma Total-body imaging [18F]FDG PET/CT

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Learning by active forgetting for neural networks

arXiv

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arXiv 2021年

作者： Peng, Jian Sun, Xian Deng, Min Tao, Chao Tang, Bo Li, Wenbo Wu, Guohua Zhu, Qing Liu, Yu Lin, Tao Li, Haifeng School of Geosciences and Info-Physics Central South University Changsha410086 China Chinese Academy of Sciences Aerospace Information Research Institute Department Beijing100094 China Department of Electrical and Computer Engineering Mississippi State University StarkvilleMS39762 United States Institute of Intelligent Machines Chinese Academy of Sciences Hefei230031 China Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University Chengdu611756 China Institute of Remote Sensing and Geographic Information System Peking University Beijing100094 China College of Biosystems Engineering and Food Science Zhejiang University Hangzhou310058 China

Remembering and forgetting mechanisms are two sides of the same coin in a human learning-memory system. Inspired by human brain memory mechanisms, modern machine learning systems have been working to endow machine with lifelong learning capability through better remembering while pushing the forgetting as the antagonist to overcome. Nevertheless, this idea might only see the half picture. Up until very recently, increasing researchers argue that a brain is born to forget, i.e., forgetting is a natural and active process for abstract, rich, and flexible representations. This paper presents a learning model by active forgetting mechanism with artificial neural networks. The active forgetting mechanism (AFM) is introduced to a neural network via a "plug-and-play" forgetting layer (P&PF), consisting of groups of inhibitory neurons with Internal Regulation Strategy (IRS) to adjust the extinction rate of themselves via lateral inhibition mechanism and External Regulation Strategy (ERS) to adjust the extinction rate of excitatory neurons via inhibition mechanism. Experimental studies have shown that the P&PF offers surprising benefits: self-adaptive structure, strong generalization, long-term learning and memory, and robustness to data and parameter perturbation. This work sheds light on the importance of forgetting in the learning process and offers new perspectives to understand underlying mechanisms of neural networks. © 2021, CC BY.

关键词： Learning systems

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