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Energy Geoscience 2024年第4期5卷 1-7页

作者： Hongmin Yu Youqi Wang Chuanjie Cheng Quanqi Dai Jingjing Sun Qingxin Zhang SINOPEC Petroleum Exploration and Production research Institute Beijing102206China research and Development center for the Sustainable Development of Continental Sandstone Mature Oilfield National Energy AdministrationBeijing102206China

The integrated simulation and optimization technology of reservoir-wellbore-pipe network is developed to reflect the mutual influence and restriction among reservoir engineering,oil production engineering and surface engineering,and to obtain the scheme with minimum conflict and optimal benefit in each *** technology is based on the concept of global optimization to maximize production and profit,reduce costs and increase *** paper elaborates the current situation of integrated simulation technology of reservoir-wellbore-pipe network both at home and abroad,discusses its correlation with the primary business of Sinopec and its development from three aspects of modeling,cloud platform and *** on its future development are put forward from underlying data,software platform,popularization and application,and cross-border integration to provide means and guidance for the construction of intelligent oil and gas *** results show that the integrated simulation of reservoir-wellbore-pipe network can better reflect the optimization requirements of each step,avoid the ineffective operation of field equipment,and effectively improve the efficiency of research and *** solution,global optimization method and pressure fitting,which can make the simulation results reflect the real situation,are the key technologies for the *** theoretical technology and main function research of integrated simulation technology have been mature,but the large-scale application and local function improvement of oil and gas fields are yet to be *** the future,the integrated simulation of reservoir-wellbore-pipe network will develop from digitalization to modeling and intellectualization,from local simulation to cloud computing,and from manual intervention to intelligent *** suggest speeding up the construction of the unified database and model base of the whole underlying platform,strengthening the constr

关键词： Reservoir-wellbore-pipe network Integrated production modelling Prospect Development suggestion Simulation

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An Efficient Long Short-TermMemory and Gated Recurrent Unit Based Smart Vessel Trajectory Prediction Using Automatic Identification System data

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Computers, Materials and Continua 2024年第1期81卷 1789-1808页

作者： Zaman U. Khan J. Lee E. Hussain S. Balobaid A.S. Aburasain R.Y. Kim K. Department of Computer engineering Chungnam National University Daejeon 34134 South Korea Department of Environmental IT engineering Chungnam National University Daejeon 34134 South Korea Autonomous Ship research center Samsung Heavy Industries Daejeon 34051 South Korea ICAROS center (PRISMA Lab) University of Naples Federico II Naples 80131 Italy Department of Computer Science College of Computer Science and Information Technology Jazan University Jazan 45142 Saudi Arabia

Maritime transportation, a cornerstone of global trade, faces increasing safety challenges due to growing sea traffic volumes. This study proposes a novel approach to vessel trajectory prediction utilizing Automatic Identification System (AIS) data and advanced deep learning models, including Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Bidirectional LSTM (DBLSTM), Simple Recurrent Neural Network (SimpleRNN), and Kalman Filtering. The research implemented rigorous AIS data preprocessing, encompassing record deduplication, noise elimination, stationary simplification, and removal of insignificant trajectories. Models were trained using key navigational parameters: latitude, longitude, speed, and heading. Spatiotemporal aware processing through trajectory segmentation and topological data analysis (TDA)was employed to capture dynamic *** using a three-month AIS dataset demonstrated significant improvements in prediction accuracy. The GRU model exhibited superior performance, achieving training losses of 0.0020 (Mean Squared Error, MSE) and 0.0334 (Mean Absolute Error, MAE), with validation losses of 0.0708 (MSE) and 0.1720 (MAE). The LSTM model showed comparable efficacy, with training losses of 0.0011 (MSE) and 0.0258 (MAE), and validation losses of 0.2290 (MSE) and 0.2652 (MAE). Both models demonstrated reductions in training and validation losses, measured by MAE, MSE, Average Displacement Error (ADE), and Final Displacement Error (FDE). This research underscores the potential of advanced deep learning models in enhancing maritime safety through more accurate trajectory predictions, contributing significantly to the development of robust, intelligent navigation systems for the maritime industry. © 2024 The Authors. Published by Tech Science Press.

关键词： AIS data deep learning GRU LSTM smart vessel Trajectory prediction

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Multivariate analysis of oral mucosal ulcers during orthodontic treatment

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World Journal of Clinical Cases 2024年第26期12卷 5868-5876页

作者： Jing Chang Xue Li The Fifth Clinic Peking University School and Hospital of StomatologyNational Center for StomatologyNational Clinical Research Center for Oral DiseasesNational Engineering Research Center of Oral Biomaterials and Digital Medical Devices Beijing 100081China

BACKGROUND Orthodontic treatment can easily cause local soft tissue reactions in the oral cavity of patients under mechanical stress,leading to oral mucosal ulcers and affecting their quality of *** present,only limited literature has explored the factors leading to oral ulcers in orthodontic treatment,and these research results are still *** To investigate the current status and related factors of oral mucosal ulcers during orthodontic treatment,aiming to provide a valuable reference for preventing this disease in clinical *** A total of 587 patients who underwent orthodontic treatment at the Peking University School of Stomatology and Hospital of Stomatology between 2020 and 2022 were selected and allocated to an observation or control group according to the incidence of oral mucosal ulcers during orthodontic therapy.A questionnaire survey was constructed to collect patient data,including basic information,lifestyle and eating habits,treatment details,mental factors,and trace element levels,and a comparative analysis of this data was performed between the two *** A logistic regression model with oral ulcers as the dependent variable was *** regression results showed that age(≥60 years:odds ratio[OR]:6.820;95%confidence interval[CI]:2.226–20.893),smoking history(smoking:OR:4.434;95%CI:2.527–7.782),toothbrush hardness(hard:OR:2.804;95%CI:1.746–4.505),dietary temperature(hot diet:OR:1.399;95%CI:1.220–1.722),treatment course(>1 year:OR:3.830;95%CI:2.203–6.659),and tooth brushing frequency(>1 time per day:OR:0.228;95%CI:0.138–0.377)were independent factors for oral mucosal ulcers(Ptreatment course for>1 year,tooth brushing frequency of≤1 time per day,and m

关键词： Orthodontic treatment Oral ulcers Multivariate Logistic regression Prevent disease

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Energy-efficient computation offloading assisted by RIS-based UAV

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The Journal of China Universities of Posts and Telecommunications 2024年第1期31卷 37-48页

作者： Li Linpei Zhao Chuan Su Yu Huo Jiahao Huang Yao Li Haojin School of Intelligence Science and Technology University of Science and Technology BeijingBeijing 100083China Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China Shunde Innovation School University of Science and Technology BeijingFoshan 528399China School of Computer and Communication engineering University of Science and Technology BeijingBeijing 100083China research Department of 5G and Drone China Mobile(Chengdu)Institute of Research and DevelopmentChengdu 610200China College of Communication engineering Chengdu University of Information TechnologyChengdu 610225China research and Development center Sony(China)LimitedBeijing 100027China

The new applications surge with the rapid evolution of the mobile *** explosive growth of the data traffic aroused by the new applications has posed great computing pressure on the local *** is essential to innovate the computation offloading methods to alleviate the local computing burden and improve the offloading *** edge computing(MEC)assisted by reflecting intelligent surfaces(RIS)-based unmanned aerial vehicle(UAV)is a promising method to assist the users in executing the computation tasks in proximity at low *** this paper,we propose an energy-efficient MEC system assisted by RIS-based UAV,where the UAV with RIS mounted relays the computation tasks to the MEC *** energy efficiency maximization problem is formulated by jointly optimizing the UAV's trajectory,the transmission power of all users,and the phase shifts of the reflecting elements placed on the *** that the optimization problem is non-convex,we propose a deep deterministic policy gradient(DDPG)-based *** combining the DDPG algorithm with the energy efficiency maximization problem,the optimization problem can be ***,the numerical results are illustrated to show the performance of the system and the superiority compared with the benchmark schemes.

关键词： mobile edge computing unmanned aerial vehicle reflecting intelligent surface

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Modelling the preventive treatment under media impact on tuberculosis:A comparison in four regions of China

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Infectious Disease Modelling 2024年第2期9卷 483-500页

作者： Jun Zhang Yasuhiro Takeuchi Yueping Dong Zhihang Peng School of Mathematics and Statistics and Key Laboratory of Nonlinear Analysis&Applications(Ministry of Education)Central China Normal UniversityWuhan430079China College of Science and engineering Aoyama Gakuin UniversityKanagawa252-5258Japan National Key Laboratory of intelligent Tracking and Forecasting for Infectious Diseases Chinese Center for Disease Control and PreventionBeijing102206China

Preventive treatment for people with latent Tuberculosis infection(LTBI)has aroused our great *** this paper,we propose and analyze a novel mathematical model of TB considering preventive treatment with media *** basic reproduction number R_(0)is defined by the next generation matrix *** the case without media impact,we prove that the disease-free equilibrium is globally asymptotically stable(unstable)if R_(0)1).Furthermore,we obtain that a unique endemic equilibrium exists when R_(0)>1,which is globally asymptotically stable in the case of permanent immunity and no media *** fit the model to the newly reported TB cases data from 2009 to 2019 of four regions in China and estimate the *** we estimatedR_(0)=0.50131 in Henan,R_(0)=1.282>1 in Jiangxi andR_(0)=1.930>1 in Xinjiang imply that TB will continue to persist in these three regions without further prevention and control ***,sensitivity analysis is carried out to illustrate the role of model parameters for TB *** finding reveals that appropriately improving the rate of timely treatment for actively infected people and increasing the rate of individuals with LTBI seeking preventive treatment could achieve the goal of TB *** addition,another interesting finding shows that media impact can only reduce the number of active infections to a limited extent,but cannot change the prevalence of TB.

关键词： Latent tuberculosis infection Preventive treatment Media impact Mathematical model Tuberculosis elimination

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A secure visualization platform for pathogenic genome analysis with an accurate reference database

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Biosafety and Health 2024年第4期6卷 235-243页

作者： Guomei Fan Chongye Guo Qian Zhang Dongmei Liu Qinglan Sun Zhigang Cui Haijian Zhou Yuanchun Zhou Zhibin Guo Juncai Ma Linhuan Wu Microbial Resource and Big data center Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China Chinese National Microbiology data center(NMDC) Beijing 100101China National Key Laboratory of intelligent Tracking and Forecasting for Infectious Diseases National Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionBeijing 102206China Computer Network Information center Chinese Academy of SciencesBeijing 100190China State Key Laboratory of Microbial Resources Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China

Investigating the genetic and developmental characteristics,infection transmission attributes,and epidemiological trends of pathogens using genomic data represents the foundation for pathogen surveillance and is a crucial prerequisite for guaranteeing global health *** meet the analytical demands of research relating to pathogen prevention and control,we designed a secure visualization system capable of pathogen genome assembly,annotation,species identification,sequence typing,antibiotic resistance and virulence analysis,genomic mobile element and transferable resistance gene annotation,and phylogenetic tree *** highly pathogenic organisms requiring complete data protection,we have developed a secure computing tool that utilizes a trusted execution environment,is combined with blockchain and privacy computing technologies,and is specifically designed for nucleotide basic local alignment search tool(BLASTn)comparison *** technological advancement offers scientific support for in‐depth investigations into pathogen transmission and epidemiological mechanisms,environmental adaptability,evolutionary trends,and immune evasion mechanisms,as well as the identification of new or emerging pathogen ***,in turn,aids efforts in infectious disease prevention,treatment,and research.

关键词： Pathogen surveillance One-stop analysis tools Sequence typing Horizontal transfer Secure computing

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Cell softness reveals tumorigenic potential via ITGB8/AKT/glycolysis signaling in a mice model of orthotopic bladder cancer

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Chinese Medical Journal 2024年第2期137卷 209-221页

作者： Shi Qiu Yaqi Qiu Linghui Deng Ling Nie Liming Ge Xiaonan Zheng Di Jin Kun Jin Xianghong Zhou Xingyang Su Boyu Cai Jiakun Li Xiang Tu Lina Gong Liangren Liu Zhenhua Liu Yige Bao Jianzhong Ai Tianhai Lin Lu Yang Qiang Wei Department of Urology Institute of UrologyNational Clinical Research Center for Geriatrics and Center of Biomedical Big DataWest China Hospital of Sichuan UniversityChengduSichuan 610041China Department of Molecular Oncology Institute of Oncology Research(IOR)Oncology Institute of Southern Switzerland(IOSI)Bellinzona 6500Switzerland Department of Science and Drug Technology University of TurinTurinItaly National Clinical research center of Geriatrics The Center of Gerontology and GeriatricsWest China HospitalSichuan UniversityChengduSichuan 610000China Department of Pathology West China HospitalSichuan UniversityChengduSichuan 610041China Department of Pharmaceutics and Bioengineering School of Chemical EngineeringSichuan UniversityChengduSichuan 610000China

Background:Bladder cancer,characterized by a high potential of tumor recurrence,has high lifelong monitoring and treatment *** date,tumor cells with intrinsic softness have been identified to function as cancer stem cells in several cancer ***,the existence of soft tumor cells in bladder tumors remains ***,our study aimed to develop a microbarrier microfluidic chip to efficiently isolate deformable tumor cells from distinct types of bladder cancer ***:The stiffness of bladder cancer cells was determined by atomic force microscopy(AFM).The modified microfluidic chip was utilized to separate soft cells,and the 3D Matrigel culture system was to maintain the softness of tumor *** patterns of integrinβ8(ITGB8),protein kinase B(AKT),and mammalian target of rapamycin(mTOR)were determined by Western *** immunostaining was conducted to examine the interaction between F-actin and tripartite motif containing 59(TRIM59).The stem-cell-like characteristics of soft cells were explored by colony formation assay and in vivo studies upon xenografted tumor ***:Using our newly designed microfluidic approach,we identified a small fraction of soft tumor cells in bladder cancer *** importantly,the existence of soft tumor cells was confirmed in clinical human bladder cancer specimens,in which the number of soft tumor cells was associated with tumor ***,we demonstrated that the biomechanical stimuli arising from 3D Matrigel activated the F-actin/ITGB8/TRIM59/AKT/mTOR/glycolysis pathways to enhance the softness and tumorigenic capacity of tumor ***,we detected a remarkable up-regulation in ITGB8,TRIM59,and phospho-AKT in clinical bladder recurrent tumors compared with their non-recurrent ***:The ITGB8/TRIM59/AKT/mTOR/glycolysis axis plays a crucial role in modulating tumor softness and ***,the soft tumor cells become more sensitive to chemother

关键词： Soft tumor cells 3D Matrigel Stemness Non-muscle invasive bladder neoplasms Microfluidic analytical techniques

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Wastewater Surveillance Provides Spatiotemporal SARS-CoV-2 Infection Dynamics

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engineering 2024年第9期40卷 70-77页

作者： Xiawan Zheng Kathy Leung Xiaoqing Xu Yu Deng Yulin Zhang Xi Chen Chung In Yau Kenny W.K.Hui Eddie Pak Ho-Kwong Chui Ron Yang Hein Min Tun Gabriel Matthew Leung Joseph Tsz Kei Wu Malik Peiris Leo Lit Man Poon Tong Zhang Environmental Microbiome engineering and Biotechnology Lab Center for Environmental Engineering ResearchDepartment of Civil EngineeringThe University of Hong KongHong Kong 999077China WHO Collaborating Centre for Infectious Disease Epidemiology and Control School of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong 999077China Laboratory of data Discovery for Health Litd.(D24H) Hong Kong 999077China The University of Hong Kong-Shenzhen Hospital Hong Kong 999077China School of Public Health Li Ka Shing Faculty of MedicineThe University of Hong KongHong Kong 999077China HKU-Pasteur research Pole The University of Hong KongHong Kong 999077China Drainage Services Department The Government of the Hong Kong Special Administrative RegionHong Kong 999077China Environmental Protection Department The Government of the Hong Kong Special Administrative RegionHong Kong 999077China The Jockey Club School of Public Health and Primary Care Faculty of MedicineThe University of Hong KongHong Kong 999077China

Wastewater surveillance(WWS)can leverage its wide coverage,population-based sampling,and high monitoring frequency to capture citywide pandemic trends independent of clinical *** we conducted a nine months daily WWS for severe acute respiratory syndrome coronavirus 2(SARSCoV-2)from 12 wastewater treatment plants(WWTPs),covering approximately 80%of the population,to monitor infection dynamics in Hong Kong,*** found that the SARS-CoV-2 virus concentration in wastewater was correlated with the daily number of reported cases and reached two pandemic peaks three days earlier during the study *** addition,two different methods were established to estimate the prevalence/incidence rates from wastewater *** estimated results from wastewater were consistent with findings from two independent citywide clinical surveillance programmes(rapid antigen test(RAT)surveillance and serology surveillance),but higher than the cases number reported by the Centre for Health Protection(CHP)of Hong Kong,***,the effective reproductive number(R_(t))was estimated from wastewater measurements to reflect both citywide and regional transmission *** findings demonstrate that large-scale intensive WWS from WWTPs provides cost-effective and timely public health information,especially when the clinical surveillance is inadequate and *** approach also provides insights into pandemic dynamics at higher spatiotemporal resolutions,facilitating the formulation of effective control policies and targeted resource allocation.

关键词： SARS-CoV-2 Wastewater surveillance Prevalence Effective reproductive number

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Optimal Control Method for On-Ramp Merging on Highways Considering Fairness and Safety

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Journal of Traffic and Transportation engineering(English Edition) 2024年

作者： Sen Xia Haigen Min Yukun Fang Jianqiu Wang Jie Li Xiaobo Qu Xiangmo Zhao School of Information and engineering， Chang'an University Innovation center for Western China Traffic Safety and intelligent Cooperative Control China Mobile (Shanghai) Information and Communication Technology Co.Ltd. Shandong Hi-Speed Information Group Co.Ltd. School of Vehicle and Mobility， Tsinghua University

On-ramp merging can generate a traffic bottleneck due to predictability and coordination issues between vehicles on the main road and those from the ramp， which may result in traffic congestion and accidents. Connected and automated vehicles (CAVs) with vehicle-to-everything(V2X) communication have the potential to improve vehicles coordination and facilitate merging. Current research mainly focuses on enhancing traffic efficiency and reducing fuel consumption， neglecting the importance of fairness in right-of-way allocation and vehicle safety during merging. Thus， in this study， a double-layer optimized ramp-merge control model is proposed， where the upper layer aims to determine the merging sequence considering both fairness and efficiency， and the lower layer focuses on trajectory optimization considering safety constraints. Simulation results show that the proposed method reduces driving delays by 28.88% on average compared with the first-in-first-out method， and decreases unfair delay percentage in the merging sequence by 76.38% on average compared with the short delay method， validating the advantage of the proposed method in both traffic efficiency and fairness. Furthermore， compared with the Hamiltonian analysis method and the boundary adjustment method， the proposed model significantly reduces security risks by 63.47% and 65.14% respectively. Comparison of the results of the proposed method with NGSIM data further demonstrates the effectiveness of the proposed method.

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Classification and structural characteristics of amorphous materials based on interpretable deep learning

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中国物理B:英文版 2023年第9期32卷 356-363页

作者：崔佳梅李韵洁赵偲郑文 Institute of Public Safety and Big data College of Data ScienceTaiyuan University of TechnologyJinzhong 030600China shanxi engineering research center for intelligent data assisted treatment Changzhi Medical CollegeChangzhi 046000China

Defining the structure characteristics of amorphous materials is one of the fundamental problems that need to be solved urgently in complex materials because of their complex structure and long-range *** this study,we develop an interpretable deep learning model capable of accurately classifying amorphous configurations and characterizing their structural *** results demonstrate that the multi-dimensional hybrid convolutional neural network can classify the two-dimensional(2D)liquids and amorphous solids of molecular dynamics *** classification process does not make a priori assumptions on the amorphous particle environment,and the accuracy is 92.75%,which is better than other convolutional neural ***,our model utilizes the gradient-weighted activation-like mapping method,which generates activation-like heat maps that can precisely identify important structures in the amorphous configuration *** obtain an order parameter from the heatmap and conduct finite scale analysis of this *** findings demonstrate that the order parameter effectively captures the amorphous phase transition process across various *** results hold significant scientific implications for the study of amorphous structural characteristics via deep learning.

关键词： amorphous interpretable deep learning image classification finite scale analysis

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