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Core muscle functional strength training for reducing the risk of low back pain in military recruits:An open-label randomized controlled trial

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Journal of Integrative Medicine 2022年第2期20卷 145-152页

作者： Xin Wang Wen-juan Song Yi Ruan bing-chu li Can Lü Nian Huang Fan-fu Fang Wei Gu School of Traditional Chinese Medicine Naval Medical UniversityShanghai 200433China Department of Rehabilitation Changhai HospitalNaval Medical UniversityShanghai 200433China School of Mechanical Engineering University of Shanghai for Science and TechnologyShanghai 200093China

Background:Core muscle functional strength training(CMFST)has been reported to reduce injuries to the lower extremity.However,no study has confirmed whether CMFST can reduce the risk of low back pain(LBP).Objective:This study identified the effects of CMFST on the incidence of LBP in military recruits.Design,setting,participants and intervention:We performed a prospective,open-label,randomized,controlled study in a population of young healthy male naval recruits from a Chinese basic combat training program.Participants were randomly assigned to either the core group or the control group.In additional to normal basic combat training,recruits in the core group underwent a CMFST program for 12 weeks,while recruits in the control group received no extra training.Main outcome measures:At the beginning of the study and at the 12 th week,the number of participants with LBP was counted,and lumbar muscle endurance was measured.In addition,when participants complained of LBP,they were assessed using the visual analog scale(VAS)and Roland Morris Disability Questionnaire(RMDQ).Results:A total of 588 participants were included in the final analysis(295 in the core group and 293 in the control group).The incidence of LBP in the control group was about twice that of the core group over the 12-week study(20.8%vs 10.8%,odds ratio:2.161–2.159,Plieved the dysfunction of LBP during basic military training.

关键词： Low back pain Core exercise Recruits Randomized controlled trial

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Vinyltrimethylsilane as a novel electrolyte additive for improving interfacial stability of li-rich cathode working in high voltage

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Chinese Chemical Letters 2024年第2期35卷 534-538页

作者： bing Jiang Hao li Bi Luo Lehao liu lihua chu Qiaobao Zhang Meicheng li State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of New EnergyNorth China Electric Power UniversityBeijing 102206China State Key Laboratory of Physical Chemistry of Solid Surfaces College of MaterialsXiamen UniversityXiamen 361005China

Boosting the interfacial stability between electrolyte and li-rich cathode material at high operating voltage is vital important to enhance the cycling stability of li-rich cathode materials for high-performance li-ion batteries.In this work,vinyltrimethylsilane as a new type of organic silicon electrolyte additive is studied to address the interfacial instability of li-rich cathode material at high operating voltage.The cells using vinyltrimethylsilane additive shows the high capacity retention of 73.9%after 300 cycles at 1 C,whereas the cells without this kind of additive only have the capacity retention of 58.9%.The improvement of stability is mainly attributed to the additive helping to form a more stable surface film for li-rich cathode material,thus avoiding direct contact between the electrolyte and the cathode material,slowing down the dissolution of metal ions and the decomposition of the electrolyte under high operating voltage.Our findings in this work shed some light on the design of stable cycling performance of li-rich cathode toward advanced li-ion batteries.

关键词： Vinyltrimethylsilane Electrolyte additive li-rich cathode Interfacial stability Capacity retention

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A Fully-Integrated Memristor Chip for Edge Learning

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Nano-Micro Letters 2024年第9期16卷 123-127页

作者： Yanhong Zhang liang chu Wenjun li School of Elecronics and Information Hangzhou Dianzi UniversityHangzhou 310018People’s Republic of China

It is still challenging to fully integrate computing in memory chip as edge learning devices.In recent work published on Science,a fully-integrated chip based on neuromorphic memristors was developed for edge learning as artificial neural networks with functionality of synapses,dendrites,and somas.A crossbar-array memristor chip facilitated edge learning including hardware realization,learning algorithm,and cycle-parallel sign-and threshold-based learning(STELLAR)scheme.The motion control and demonstration platforms were executed to improve the edge learning ability for adapting to new scenarios.

关键词： Computing in memory Edge learning Fully-integrated chip

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Microbiome changes in esophageal cancer:implications for pathogenesis and prognosis

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Cancer Biology & Medicine 2024年第2期21卷 163-174页

作者： Yi li bing Wei Xia Xue Hongle li Jun li Department of Molecular Pathology Clinical Pathology CenterAffiliated Cancer Hospital of Zhengzhou University and Henan Cancer HospitalZhengzhou 450003China Henan Key Laboratory of Molecular Pathology Zhengzhou 450003China Henan Key Laboratory of Helicobacter pylori&Microbiota and Gastrointestinal Cancer Marshall Medical Research CenterThe Fifth Affiliated Hospital of Zhengzhou UniversityZhengzhou 450052China

Esophageal cancer(EC)is an aggressive malignancy with a poor prognosis.Various factors,including dietary habits,and antacid and antibiotic use,have been shown to influence the esophageal microbiome.Conversely,enrichment and diversity of the esophageal microbiome can also impact its function.Recent studies have revealed prevalent changes in the esophageal microbiome among patients with EC,thus suggesting the potential contribution of the esophageal microbiome to EC development.Additionally,distinct microbiome compositions have been observed in patients with different responses to radiotherapy and chemotherapy,indicating the role of the esophageal microbiome in modulating treatment outcomes.In this review,we have examined previous studies on the esophageal microbiome in healthy individuals and patients with EC or other esophageal diseases,with a focus on identifying microbial communities associated with EC pathogenesis and prognosis.Understanding the role of the microbiome in EC may aid in early detection and optimized treatment strategies,ultimately leading to better outcomes for patients.

关键词： Esophageal cancer microbiome dysbiosis microenvironment carcinogenesis

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The crosstalk between enteric nervous system and immune system in intestinal development,homeostasis and diseases

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Science China(life Sciences) 2024年第1期67卷 41-50页

作者： Xindi Wang Chenbo Ding Hua-bing li Shanghai Institute of Immunology State Key Laboratory of Oncogenes and Related GenesShanghai Jiao Tong University School of MedicineShanghai 200025China Shanghai Jiao Tong University School of Medicine-Yale Institute for Immune Metabolism Shanghai Jiao Tong University School of MedicineShanghai 200025China

The gut is the largest digestive and absorptive organ,which is essential for induction of mucosal and systemic immune responses,and maintenance of metabolic-immune homeostasis.The intestinal components contain the epithelium,stromal cells,immune cells,and enteric nervous system(ENS),as well as the outers,such as gut microbiota,metabolites,and nutrients.The dyshomeostasis of intestinal microenvironment induces abnormal intestinal development and functions,even colon diseases including dysplasia,inflammation and tumor.Several recent studies have identified that ENS plays a crucial role in maintaining the immune homeostasis of gastrointestinal(GI)microenvironment.The crosstalk between ENS and immune cells,mainly macrophages,T cells,and innate lymphoid cells(ILCs),has been found to exert important regulatory roles in intestinal tissue programming,homeostasis,function,and inflammation.In this review,we mainly summarize the critical roles of the interactions between ENS and immune cells in intestinal homeostasis during intestinal development and diseases progression,to provide theoretical bases and ideas for the exploration of immunotherapy for gastrointestinal diseases with the ENS as potential novel targets.

关键词： enteric nervous system macrophages T cells innate lymphoid cells neuro-immune interactions

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Preparation of MXene-based hybrids and their application in neuromorphic devices

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International Journal of Extreme Manufacturing 2024年第2期6卷 164-188页

作者： Zhuohao Xiao Xiaodong Xiao ling bing Kong Hongbo Dong Xiuying li Bin He Shuangchen Ruan Jianpang Zhai Kun Zhou Qin Huang liang chu School of Materials Science and Engineering Jingdezhen Ceramic UniversityJingdezhen 333403JiangxiPeople’s Republic of China School of Mechanical and Vehicle Engineering Linyi UniversityLinyi 276000ShandongPeople’s Republic of China College of New Materials and New Energies Shenzhen Technology UniversityShenzhen 518118GuangdongPeople’s Republic of China School of Mechanical&Aerospace Engineering Nanyang Technological University50 Nanyang AvenueSingapore 639798Singapore Ningbo Institute of Materials Engineering and Technology Chinese Academy of ScienceNingbo 315201ZhejiangPeople’s Republic of China Institute of Carbon Neutrality and New Energy&School of Electronics and Information Hangzhou Dianzi UniversityHangzhou 310018ZhejiangPeople’s Republic of China

The traditional von Neumann computing architecture has relatively-low information processing speed and high power consumption,making it difficult to meet the computing needs of artificial intelligence(AI).Neuromorphic computing systems,with massively parallel computing capability and low power consumption,have been considered as an ideal option for data storage and AI computing in the future.Memristor,as the fourth basic electronic component besides resistance,capacitance and inductance,is one of the most competitive candidates for neuromorphic computing systems benefiting from the simple structure,continuously adjustable conductivity state,ultra-low power consumption,high switching speed and compatibility with existing CMOS technology.The memristors with applying MXene-based hybrids have attracted significant attention in recent years.Here,we introduce the latest progress in the synthesis of MXene-based hybrids and summarize their potential applications in memristor devices and neuromorphological intelligence.We explore the development trend of memristors constructed by combining MXenes with other functional materials and emphatically discuss the potential mechanism of MXenes-based memristor devices.Finally,the future prospects and directions of MXene-based memristors are briefly described.

关键词： MXene etching fabrication memristor neuromorphic

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Channel Estimation for Reconfigurable Intelligent Surface Aided Multiuser Millimeter-Wave/THz Systems

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China Communications 2024年第3期21卷 91-103页

作者： chu Hongyun Pan Xue li Baijiang School of Communications and Information Engineering Xi’an University of Posts and TelecommunicationsXi’an 710121China

It is assumed that reconfigurable intelligent surface(RIS)is a key technology to enable the potential of mmWave communications.The passivity of the RIS makes channel estimation difficult because the channel can only be measured at the transceiver and not at the RIS.In this paper,we propose a novel separate channel estimator via exploiting the cascaded sparsity in the continuously valued angular domain of the cascaded channel for the RIS-enabled millimeter-wave/Tera-Hz systems,i.e.,the two-stage estimation method where the cascaded channel is separated into the base station(BS)-RIS and the RIS-user(UE)ones.Specifically,we first reveal the cascaded sparsity,i.e.,the sparsity exists in the hybrid angular domains of BS-RIS and the RIS-UEs separated channels,to construct the specific sparsity structure for RIS enabled multi-user systems.Then,we formulate the channel estimation problem using atomic norm minimization(ANM)to enhance the proposed sparsity structure in the continuous angular domains,where a low-complexity channel estimator via Alternating Direction Method of Multipliers(ADMM)is proposed.Simulation findings demonstrate that the proposed channel estimator outperforms the current state-of-the-arts in terms of performance.

关键词： atomic norm minimization cascaded channel estimation convex optimization mmWave/THz reconfigurable intelligent surface(RIS) sparsity

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For Mega-Constellations: Edge Computing and Safety Management Based on Blockchain Technology

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China Communications 2024年第2期21卷 59-73页

作者： Zhen Zhang bing Guo Chengjie li College of Computer Science Sichuan UniversityChengdu 610064China The Key Laboratory for Computer Systems of State Ethnic Affairs Commission School of Computer Science and TechnologySouthwest Minzu UniversityChengdu 610225China National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of ChinaChengdu 611731China

In mega-constellation Communication Systems, efficient routing algorithms and data transmission technologies are employed to ensure fast and reliable data transfer. However, the limited computational resources of satellites necessitate the use of edge computing to enhance secure communication.While edge computing reduces the burden on cloud computing, it introduces security and reliability challenges in open satellite communication channels. To address these challenges, we propose a blockchain architecture specifically designed for edge computing in mega-constellation communication systems. This architecture narrows down the consensus scope of the blockchain to meet the requirements of edge computing while ensuring comprehensive log storage across the network. Additionally, we introduce a reputation management mechanism for nodes within the blockchain, evaluating their trustworthiness, workload, and efficiency. Nodes with higher reputation scores are selected to participate in tasks and are appropriately incentivized. Simulation results demonstrate that our approach achieves a task result reliability of 95% while improving computational speed.

关键词： blockchain consensus mechanism edge computing mega-constellation reputation management

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Motion Planning for Autonomous Driving with Real Traffic Data Validation

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Chinese Journal of Mechanical Engineering 2024年第1期37卷 74-86页

作者： Wenbo chu Kai Yang Shen li Xiaolin Tang Western China Science City Innovation Center of Intelligent and Connected Vehicle Chongqing 400044China College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing 400044China School of Civil Engineering Tsinghua UniversityBeijing 100084China

Accurate trajectory prediction of surrounding road users is the fundamental input for motion planning,which enables safe autonomous driving on public roads.In this paper,a safe motion planning approach is proposed based on the deep learning-based trajectory prediction method.To begin with,a trajectory prediction model is established based on the graph neural network(GNN)that is trained utilizing the INTERACTION dataset.Then,the validated trajectory prediction model is used to predict the future trajectories of surrounding road users,including pedestrians and vehicles.In addition,a GNN prediction model-enabled motion planner is developed based on the model predictive control technique.Furthermore,two driving scenarios are extracted from the INTERACTION dataset to validate and evaluate the effectiveness of the proposed motion planning approach,i.e.,merging and roundabout scenarios.The results demonstrate that the proposed method can lower the risk and improve driving safety compared with the baseline method.

关键词： Trajectory prediction Graph neural network Motion planning INTERACTION dataset

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Three-Dimensional Sound Source Location Algorithm for Subsea Leakage Using Hydrophone

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China Ocean Engineering 2024年第2期38卷 326-337页

作者： li Hao-jie CAI Bao-ping YUAN Xiao-bing KONG Xiang-di liU Yong-hong Javed Akbar KHAN chu Zheng-de YANG Chao TANG An-bang College of Mechanical and Electronic Engineering China University of PetroleumQingdao 266580China Shenzhen Urban Public Safety Technology Institute Shenzhen 518000China Institute of Hydrocarbon Recovery Universiti Teknologi PETRONASBandar Seri IskandarPerak Darul Ridzuan 32610Malaysia

Leakages from subsea oil and gas equipment cause substantial economic losses and damage to marine ecosystem,so it is essential to locate the source of the leak.However,due to the complexity and variability of the marine environment,the signals collected by hydrophone contain a variety of noises,which makes it challenging to extract useful signals for localization.To solve this problem,a hydrophone denoising algorithm is proposed based on variational modal decomposition(VMD)with grey wolf optimization.First,the average envelope entropy is used as the fitness function of the grey wolf optimizer to find the optimal solution for the parameters K andα.Afterward,the VMD algorithm decomposes the original signal parameters to obtain the intrinsic mode functions(IMFs).Subsequently,the number of interrelationships between each IMF and the original signal was calculated,the threshold value was set,and the noise signal was removed to calculate the time difference using the valid signal obtained by reconstruction.Finally,the arrival time difference is used to locate the origin of the leak.The localization accuracy of the method in finding leaks is investigated experimentally by constructing a simulated leak test rig,and the effectiveness and feasibility of the method are verified.

关键词： grey wolf optimizer variational modal decomposition mean envelope entropy correlation coefficient time difference of arrival

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