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ON LOCALIZATION IN SENSOR NETWORK WITH INACCURATE AND INCOMPLETE DISTANCE MEASUREMENTS

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Journal of Electronics(China) 2007年第1期24卷 60-63页

作者： sun guolin Wang yi guo Wei School of Commun. and Info. Eng. Univ. of Electronic Sci. and Tech. of China Chengdu 610054 China

The sensor network localization problem has received a lot of attention in recent years because many important applications resort to node position information. In contrast to the many interesting algorithms proposed in the literature,this paper provides a relatively straightforward procedure that can tackle localization problem for sensor network in a Least Squares Euclidean Dis-tance Matrix Approximation (LS-EDMA) framework. Simulation results reveal that our proposed algorithm is more robust than another popular Multi-Dimensional Scaling (MDS) and Semi-Definite Programming (SDP) based localization techniques,especially with inaccurate and incomplete distance measurements.

关键词： Localization Sensor network Least squares approximation

Exosomes:the next-generation therapeutic platform for ischemic stroke

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Neural Regeneration Research 2025年第5期20卷 1221-1235页

作者： Wenjing yin Hongyin Ma Yang Qu Jiaxin Ren yingying sun Zhen-Ni guo yi Yang Stroke Center Department of NeurologyFirst Hospital of Jilin UniversityChangchunJilin ProvinceChina Neuroscience Research Center Department of NeurologyFirst Hospital of Jilin UniversityChangchunJilin ProvinceChina

Current therapeutic strategies for ischemic stroke fall short of the desired objective of neurological functional ***,there is an urgent need to develop new methods for the treatment of this *** are natural cell-derived vesicles that mediate signal transduction between cells under physiological and pathological *** have low immunogenicity,good stability,high delivery efficiency,and the ability to cross the blood–brain *** physiological properties of exosomes have the potential to lead to new breakthroughs in the treatment of ischemic *** rapid development of nanotechnology has advanced the application of engineered exosomes,which can effectively improve targeting ability,enhance therapeutic efficacy,and minimize the dosages *** in technology have also driven clinical translational research on *** this review,we describe the therapeutic effects of exosomes and their positive roles in current treatment strategies for ischemic stroke,including their antiinflammation,anti-apoptosis,autophagy-regulation,angiogenesis,neurogenesis,and glial scar formation reduction ***,it is worth noting that,despite their significant therapeutic potential,there remains a dearth of standardized characterization methods and efficient isolation techniques capable of producing highly purified *** optimization strategies should prioritize the exploration of suitable isolation techniques and the establishment of unified workflows to effectively harness exosomes for diagnostic or therapeutic applications in ischemic ***,our review aims to summarize our understanding of exosome-based treatment prospects in ischemic stroke and foster innovative ideas for the development of exosome-based therapies.

关键词： blood–brain barrier electroacupuncture engineering exercise exosomes ischemic stroke mesenchymal stem cells microglia neuroprotection stents

松果菊苷对过氧化氢损伤的PC12细胞的保护作用及机制研究

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中国药理学通报 2009年第4期25卷 515-518页

作者：匡荣孙意国邓同乐郑筱祥浙江大学生物医学工程学院教育部生物医学工程重点实验室浙江杭州310027 浙江省食品药品检验所浙江杭州310004

目的研究松果菊苷(echinacoside,ECH)对过氧化氢(H2O2)诱导的PC12细胞损伤的保护作用及机制。方法用终浓度为0.4 mmol.L-1的H2O2损伤PC12细胞,测定细胞存活率和Na+,K+-ATP酶的活性;用激光共聚焦法(LSCM)检测线粒体膜电位(MMP);用RT-PCR... 详细信息

目的研究松果菊苷(echinacoside,ECH)对过氧化氢(H2O2)诱导的PC12细胞损伤的保护作用及机制。方法用终浓度为0.4 mmol.L-1的H2O2损伤PC12细胞,测定细胞存活率和Na+,K+-ATP酶的活性;用激光共聚焦法(LSCM)检测线粒体膜电位(MMP);用RT-PCR法检测Bcl-2和p53 mRNA表达量的变化。结果10 mg.L-1松果菊苷可以提高H2O2损伤的PC12细胞存活率和Na+,K+-ATP酶的活力、升高线粒体膜电位、降低p53 mRNA水平但增高Bcl-2 mRNA水平(P<0.05或P<0.01)。结论松果菊苷可保护H2O2诱导的PC12细胞损伤,升高MMP、下调p53mRNA和上调Bcl-2 mRNA可能是其作用机制。

关键词：松果菊苷过氧化氢 PC12细胞线粒体膜电位 p53 mRNA Bcl-2 mRNA

含V型缺口分数阶黏弹性复合材料反平面界面断裂的辛方法

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计算力学学报 2024年第4期41卷 689-695页

作者：徐成辉孙义国冷森邓子辰西北工业大学力学与土木建筑学院西安710129 西北工业大学复杂系统动力学与控制工信部重点实验室西安710129

本文提出求解含V型缺口的分数阶黏弹性复合材料反平面界面断裂问题的辛方法.分数阶Kelvin-Zener模型用于描述材料的黏弹性特征;借助Laplace变换,将时域内黏弹性反平面断裂问题的基本方程转换到频域空间;通过引入位移的对偶变量广义应力... 详细信息

本文提出求解含V型缺口的分数阶黏弹性复合材料反平面界面断裂问题的辛方法.分数阶Kelvin-Zener模型用于描述材料的黏弹性特征;借助Laplace变换,将时域内黏弹性反平面断裂问题的基本方程转换到频域空间;通过引入位移的对偶变量广义应力,建立问题的哈密顿求解体系.在该体系下,对偶方程的本征值和本征解可以利用分离变量法求解,本征解级数展开的系数通过本征解的辛共轭正交关系和外边界条件确定.这样将得到含缺口黏弹性复合材料反平面应力/应变强度因子的解析表达式.最后通过Laplace逆变换,得到时域空间内的应力/应变强度因子.数值算例验证本文方法的准确性,并揭示了分数阶参数、缺口角度和外载荷对应力/应变强度因子的影响.

关键词：辛方法分数阶黏弹性界面断裂反平面应力强度因子

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阴极电泳斑印缺陷问题的分析解决

材料保护 2022年第8期55卷 195-197页

作者：孙国义山东阿诺达汽车零件制造有限公司山东德州253400

通过对电泳斑印缺陷问题的调查,分析造成该缺陷的主要原因是磷化成膜不完整,磷化膜表面存在花斑缺陷。针对龙门式电泳线体磷化系统进行改进,改进后的磷化系统由磷化槽体及槽底冲洗系统、磷化除渣系统、磷化循环加热系统、侧循环系统、... 详细信息

通过对电泳斑印缺陷问题的调查,分析造成该缺陷的主要原因是磷化成膜不完整,磷化膜表面存在花斑缺陷。针对龙门式电泳线体磷化系统进行改进,改进后的磷化系统由磷化槽体及槽底冲洗系统、磷化除渣系统、磷化循环加热系统、侧循环系统、出槽喷淋系统等组成,形成独立稳定的磷化系统,使槽液整体的循环混合速度、混合的均匀性以及除渣效率得到了明显改善,产品表面的磷化膜成膜均一、完整,使电泳漆膜成膜平整度、均匀性得到保证,有效提升了产品合格率。

关键词：电泳缺陷斑印磷化循环

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太原通达桥改造工程悬索桥施工关键技术

筑路机械与施工机械化 2019年第8期36卷 85-91,96页

作者：孙国一中交一公局集团有限公司

为了使通达桥在合同工期内完工,保证施工质量,达到通车要求,采取合理优化设计结构、调整施工工序以及加快施工进度的一系列技术措施。对索塔承台结构进行优化,承台围堰采用无内支撑圆形钢板桩围堰,明确索塔塔柱吊装时间,侧面安装千斤顶... 详细信息

为了使通达桥在合同工期内完工,保证施工质量,达到通车要求,采取合理优化设计结构、调整施工工序以及加快施工进度的一系列技术措施。对索塔承台结构进行优化,承台围堰采用无内支撑圆形钢板桩围堰,明确索塔塔柱吊装时间,侧面安装千斤顶调整精度。通过采取以上措施,主桥整体施工工期较相似工程有明显提升,实现了按期完工、顺利通车。

关键词：桥梁工程体系转换定位控制施工周期

Application of the improved dung beetle optimizer,muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area,China

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 18-23页

作者： Jiarui Cai Bo sun Huijun Wang yi Zheng Siyu Zhou Huixin Li Yanyan Huang Peishu Zong Collaborative Innovation Center on forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjingChina Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) ZhuhaiChina China Meteorological Administration Key Laboratory of Transportation MeteorologyNanjingChina Jiangsu Meteorological Observatory NanjingChina

Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical *** learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many *** this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,*** two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction *** addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.

关键词： Groundwater depth Multi-head attention Improved dung beetle optimizer CNN-LSTM CNN-GRU Ningxia

Particles Separation using Micromachined Ultrasonic Device

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Particles Separation using Micromachined Ultrasonic Device

The detection, extraction and parameter estimation of extreme-mass-ratio inspirals with deep learning

第二届全国压电和声波理论及器件技术研讨会

作者： Hui Yang,Hongming sun,yi Zhang,Hang guo (Pen-Tung Sah MEMS Research Center,Xiamen University,P.R.China)

In our During the past 10 years,there is a fast growing demand to develop micro-instruments or Lab-on-Chips that can fast identify,test,and analyze bio-molecules,cells,and other *** the first step for identification and test,particles should be *** present,two types of methods, contact and non-contact methods,can be used for particles *** they can operate continuously and preserve the particles of interest in suspension for subsequent use without fouling the separation equipment,non-contact methods are more suitable for particle *** with other non-contact methods,such as electrophoretic or magnetic method,ultrasonic method only requires that density or compressibility of the particles is different from that of the medium surrounding the particles,it is therefore ultrasonic separation technique can also be used to separate those which are not charged particles or nonmagnetic ***,many research groups are studying using ultrasonic technique,combined with MEMS(MicroElectroMechanical Systems) technology,to separate or manipulate the *** this paper,we propose and investigate a new ultrasonic microdevice to separate *** first start from the fundamental of ultrasonics to obtain the radiation force on microparticles for *** force on a compressible particle in a standing wave field can be derived as proportional to the radius of the particle,wave number,ultrasound energy density,and density-compressibility constant F(λ,σ).It is noted that if F(λ,σ) is positive the acoustic radiation force will make particles to be concentrated at the nodes,and if F(λ,σ) is negative the acoustic radiation force will make particles to be concentrated at the ***,the radiation force due to the standing wave field can be utilized to separate microparticles within the *** can derive the relationships between the radiation force and particle *** some biological par

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 86-96页

作者： Qianyun Yun Wen-Biao Han yi-Yang guo He Wang Minghui Du Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Shanghai Astronomical Observatory Chinese Academy of Sciences School of Physics and Astronomy Shanghai Jiao Tong University School of Astronomy and Space Science University of Chinese Academy of Sciences Taiji Laboratory for Gravitational Wave Universe (Beijing/Hangzhou) University of Chinese Academy of Sciences Lanzhou Center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu Province Key Laboratory of Quantum Theory and Applications of MoE Lanzhou University Institute of Theoretical Physics & Research Center of Gravitation Lanzhou University International Centre for Theoretical Physics Asia-Pacific (ICTP-AP) University of Chinese Academy of Sciences (UCAS) Center for Gravitational Wave Experiment National Microgravity Laboratory Institute of Mechanics Chinese Academy of Sciences

One of the primary goals of space-borne gravitational wave detectors is to detect and analyze extreme-mass-ratio inspirals(EMRIs). This task is particularly challenging because EMRI signals are complex, lengthy, and faint. In this work, we introduce a2-layer convolutional neural network(CNN) approach to detect EMRI signals for space-borne detectors, achieving a true positive rate(TPR) of 96.9% at a 1% false positive rate(FPR) for signal-to-noise ratio(SNR) from 50 to 100. Especially, the key intrinsic parameters of EMRIs such as the mass, spin of the supermassive black hole(SMBH) and the initial eccentricity of the orbit can also be inferred directly by employing a neural network. The mass and spin of the SMBH can be determined at 99% and 92% respectively. This will greatly reduce the parameter spaces and computing cost for the following Bayesian parameter *** model also has a low dependency on the accuracy of the waveform model. This study underscores the potential of deep learning methods in EMRI data analysis, enabling the rapid detection of EMRI signals and efficient parameter estimation.

关键词： gravitational wave EMRIs deep-learing