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Amplitude-frequency-aware deep fusion network for optimal contact selection on STN-DBS electrodes

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Science China(Information Sciences) 2022年第4期65卷 48-63页

作者： Linxia XIAO Caizi LI Yanjiang WANG weixin si Hai LIN Doudou ZHANG Xiaodong CAI Pheng-Ann HENG College of Control Science and Engineering China University of Petroleum (East China) Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Department of Neurosurgery Shenzhen Second People's Hospital School of Medicine Shenzhen University Department of Computer Science and Engineering The Chinese University of Hong Kong

Parkinson’s disease(PD) is treated effectively by deep brain stimulation(DBS) of the subthalamic nucleus(STN), using an electrode inserted into the head of a PD patient. The electrode has multiple electrical contacts along its length, so the best may be chosen for selectively stimulating the STN. Neurosurgeons usually determine the optimal stimulated contact via the clinical experience of the neurosurgeon and the motor improvement of PD patients. This is a time-consuming and labor-intensive trial-and-error process. The selection of optimal stimulated contact highly depends on the locations of sweet spots, which are manually identified by the characteristic features of microelectrode recordings(MERs). This paper presents an amplitude-frequency-aware deep fusion network for optimal contact selection on STN-DBS *** method first obtains the amplitude-frequency fusion features by combining the MERs time sequence features and the amplitude sequence features, and then uses the convolutional neural network(CNN) with convolutional block attention module(CBAM) to identify both the border of the STN and the sweet spots to implant the electrode. The optimal stimulated contact can be selected according to the distribution of the sweet spots. Experimental results indicate that, for successful surgeries, neurosurgeons and the proposed AI solution selected the same optimal contacts. Furthermore, the proposed method outperforms the state-of-the-art methods for STN and sweet spot identification. The proposed method shows great potential for optimal contact selection to improve the efficiency of STN-DBS surgery and reduce the dependence on clinicians’ experience.

关键词： Microelectrode recordings optimal contact selection sweet spots microelectrode recordings Optimal contact selection amplitude-frequency feature Amplitude-frequency feature Deep fusion network deep fusion network

Traveling wave solutions in a nonlocal dispersal siR epidemic model with nonlocal time-delay and general nonlinear incidences

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International Journal of Biomathematics 2024年第5期17卷 101-132页

作者： weixin Wu Wenbui Zhang College of Mathematics and Systerm Science Xinjiang University Urumnqi 830017 P.R.China

This paper investigates a nonlocal dispersal epidemic model under the multiple nonlocal distributed delays and nonlinear incidence ***,the minimal wave speed c*and the basic reproduction number Ro are defined,which determine the existence of traveling wave ***,with the help of the upper and lower solutions,Schauder's fixed point theorem,and limiting techniques,the traveling waves satisfying some asymptotic boundary conditions are ***,when Ro>1,for every speed c>c^(*) there exists a traveling wave solution satisfying the boundary conditions,and there is no such traveling wave solution for any 01 or c>0 when R_(0)<***,we analyze the effects of nonlocal time delay on the minimum wave speed.

关键词： Nonlocal distributed delay general nonlinear incidence upper and lower solutions traveling waves

Sunspot Group Detection and Classification by Dual Stream Convolutional Neural Network Method

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Research in Astronomy and Astrophysics 2024年第9期24卷 248-259页

作者： Nyasha Mariam Mkwanda weixin Tian Junlin Li Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China

The automatic detection and analysis of sunspots play a crucial role in understanding solar dynamics and predicting space weather *** paper proposes a novel method for sunspot group detection and classification called the dual stream Convolutional Neural Network with Attention Mechanism(DSCNN-AM).The network consists of two parallel streams each processing different input data allowing for joint processing of spatial and temporal information while classifying *** takes in the white light images as well as the corresponding magnetic images that reveal both the optical and magnetic features of *** extracted features are then fused and processed by fully connected layers to perform detection and *** attention mechanism is further integrated to address the“edge dimming”problem which improves the model’s ability to handle sunspots near the edge of the solar *** network is trained and tested on the SOLAR-STORM1 data *** results demonstrate that the DSCNN-AM achieves superior performance compared to existing methods,with a total accuracy exceeding 90%.

关键词： Sun:magnetic fields Sun:flares (Sun:)sunspots DSCNN Attention mechanism Edge dimming

The emerging role of tranexamic acid and its principal target,plasminogen,in skeletal health

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Acta Pharmaceutica sinica B 2024年第7期14卷 2869-2884页

作者： weixin Xie Antonia Donat Shan Jiang Anke Baranowsky Johannes Keller Department of Trauma and Orthopedic Surgery University Medical Center Hamburg-EppendorfHamburg 20246Germany

The worldwide burden of skeletal diseases such as osteoporosis,degenerative joint disease and impaired fracture healing is steadily *** acid(TXA),a plasminogen inhibitor and anti-fibrinolytic agent,is used to reduce bleeding with high effectiveness and safety in major surgical *** its widespread clinical application,the effects of TXA beyond anti-fibrinolysis have been noticed and prompted renewed interest in its *** clinical trials have characterized the effects of TXA on reducing postoperative infection rates and regulating immune responses in patients undergoing ***,several animal studies suggest potential therapeutic effects of TXA on skeletal diseases such as osteoporosis and fracture *** a direct effect of TXA on the differentiation and function of bone cells in vitro was shown,few mechanisms of action have been ***,we summarize recent findings of the effects of TXA on skeletal diseases and discuss the underlying plasminogen-dependent and-independent mechanisms related to bone metabolism and the immune *** furthermore discuss potential novel indications for TXA application as a treatment strategy for skeletal diseases.

关键词： Tranexamic acid Osteoporosis Osteoarthritis Fracture healing Bone metabolism Inflammation Plasminogen Fibrinolysis

TBAB hydrate formation and growth in a microdevice under static and dynamic conditions

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Petroleum Science 2024年第2期21卷 1396-1404页

作者： Xingxun Li Ming Liu Qingping Li weixin Pang Guangjin Chen Changyu Sun State Key Laboratory of Heavy Oil Processing China University of Petroleum BeijingBeijing102249China State Key Laboratory of Natural Gas Hydrate CNOOC Research Institute Co.Ltd.Beijing100027China

The natural gas hydrate has become one of the most promising future green energy sources on the *** natural gas hydrates mostly exist in the sediments with porous structure, so a solid understanding of the hydrate formation and growth processes in the porous medium is of significance for the exploitation of natural gas hydrate. The micro-packed bed device is one of the efficient microfluidic devices in the engineering field, but it has been rarely used for the hydrate-based research. In this study, a transparent micro-packed bed device filled with glass beads was developed to mimic the porous condition of sediments, and used to in-situ visualize the hydrate formation and growth habits in the pore spaces under both static and dynamic conditions. For the static experiment, two types of hydrate growth patterns in porous medium were observed and identified in the micro-packed bed device, which were the graincoating growth and pore-filling growth. For the dynamic condition, the hydrate formation, growth,distribution habits and hydrate blockage phenomena in the pore spaces were in-situ visually *** impacts of flowrate and subcooling on the pressure variation of the micro-packed bed and the duration of the hydrate growth under dynamic flow condition in pores were in-situ monitored and analyzed. The higher flowrate could result in the faster hydrate growth and more severe blockage in pores, but the effect of subcooling condition might be less significant at the high flowrate.

关键词： Hydrate formation Hydrate growth Microdevice In-situ measurement

Fabrication of YAG:Ce^(3+) and YAG:Ce^(3+),Sc^(3+) Phosphors by Spark Plasma sintering Technique

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Journal of Wuhan University of Technology(Materials Science) 2024年第2期39卷 255-260页

作者：周卫新娄朝刚 School of Electronic Science and Engineering Southeast UniversityNanjing 210096China

In this study,a single-doped phosphors yttrium aluminum garnet(Y_(3)Al_(5)O_(12),YAG):Ce^(3+),single-doped YAG:Sc^(3+),and double-doped phosphors YAG:Ce^(3+),Sc^(3+) were prepared by spark plasma sintering(SPS)(lower than 1 200℃).The characteristics of synthesized phosphors were determined using scanning electron microscopy(SEM),X-ray diffraction(XRD),and fluorescence *** SPS,the lattice structure of YAG was maintained by the added Ce^(3+) and Sc^(3+).The emission wavelength of YAG:Ce^(3+) prepared from SPS(425-700 nm) was wider compared to that of YAG:Ce^(3+) prepared from high-temperature solid-state reaction(HSSR)(500-700 nm).The incorporation of low-dose Sc^(3+) in YAG:Ce^(3+) moved the emission peak towards the short wavelength.

关键词： high-temperature solid-state reaction spark plasma sintering yttrium aluminum garnet phosphors

A calibration and compensation method for an industrial robot with high accuracy harmonic reducers

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Science China(Technological Sciences) 2024年第3期67卷 725-739页

作者： ZHAO YiYang LIU Xun CAO JiaBin LIU JinYu XU Yan YAN weixin School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China College of Computer and Control Engineering Northeast Forestry UniversityHarbin 150040China

Industrial serial robots need high stiffness to keep absolute pose accuracy and meet the requirements in practical applications. However, the weak stiffness feature of robot joints and the payloads affected on robot end-effector, which will also increase the pose error of robot. Especially, the existing calibration methods often consider under no-payload condition without discussing the payload state. In this paper, we report a new industrial serial robot composed by a new harmonic reducer: Model-Y, based on high accuracy and high stiffness, and a kinematic parameter calibration algorithm which is based on a harmonic reducer forcedeformation model. To decrease the accuracy effects of payload, an iterative calibration method for kinematic parameters with payload situation was proposed. simulation and experiments are conducted to verify the effectiveness of the proposed calibration method using the self-developed industrial serial robot. The results show a remarkably improved accuracy in absolute position and orientation with the robot's payload range. The position mean error has 70% decreased to 0.1 mm and the orientation mean error diminished to less than 0.01° after calibration with compensation. Additionally, online linear and circular tests are carried out to evaluate the position error of the robot during large-scale spatial and low-speed continuous movement. The accuracy is consistent with the previous calibration results, indicating the effectiveness and advantages of the proposed strategy in this article.

关键词： industrial serial robot Model-Y harmonic calibration stiffness model online compensation

BMLP:behavior-aware MLP for heterogeneous sequential recommendation

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Frontiers of Computer Science 2024年第3期18卷 235-237页

作者： weixin LI Yuhao WU Yang LIU Weike PAN Zhong MING College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ) Shenzhen 518123China

1 Introduction Recommender systems can effectively alleviate the problem of information ***,traditional recommendation methods cannot capture users’dynamic *** recommendation methods model user sequences to obtain more accurate and dynamic user ***,deep learning-based sequential recommendation methods have achieved great *** is proposed to capture the sequential information[1,2].Attention-based methods[3]use attention mechanisms to learn relationships between ***-based methods[4−6]transform sequences into graph structures to capture relationships of ***,they have the following two limitations.

关键词： sequences behavior sequential

Physics-informed optimization for a data-driven approach in landslide susceptibility evaluation

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第8期16卷 3192-3205页

作者： Songlin Liu Luqi Wang Wengang Zhang weixin Sun Yunhao Wang Jianping Liu School of Civil Engineering Chongqing UniversityChongqing400045China Key Laboratory of New Technology for Construction of Cities in Mountain Area Chongqing UniversityMinistry of EducationChongqing400045China National Joint Engineering Research Center of Geohazards Prevention in the Reservoir Areas Chongqing UniversityChongqing400045China Chongqing Field Scientific Observation Station for Landslide Hazards in Three Gorges Reservoir Area Chongqing UniversityChongqing400045China Chongqing Mingfeng Construction Engineering Co. LtdChongqing405800China

Landslide susceptibility mapping is an integral part of geological hazard ***,the emphasis of many studies has been on data-driven models,notably those derived from machine learning,owing to their aptitude for tackling complex non-linear ***,the prevailing models often disregard qualitative research,leading to limited interpretability and mistakes in extracting negative samples,*** non-landslide *** this study,Scoops 3D(a three-dimensional slope stability analysis tool)was utilized to conduct a qualitative assessment of slope stability in the Yunyang section of the Three Gorges Reservoir *** depth of the bedrock was predicted utilizing a Convolutional Neural Network(CNN),incorporating local boreholes and building on the insights from prior *** Random Forest(RF)algorithm was subsequently used to execute a data-driven landslide susceptibility *** proposed methodology demonstrated a notable increase of 29.25%in the evaluation metric,the area under the receiver operating characteristic curve(ROC-AUC),outperforming the prevailing benchmark ***,the landslide susceptibility map generated by the proposed model demonstrated superior *** result not only validates the effectiveness of amalgamating mathematical and mechanistic insights for such analyses,but it also carries substantial academic and practical implications.

关键词： Physics-informed Machine learning Bedrock depth Scoops 3D Landslide susceptibility