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Decreased levels of phosphorylated synuclein in plasma are correlated with poststroke cognitive impairment

Neural Regeneration research 2025年第9期20卷 2598-2610页

作者： Yi Wang Yuning Li Yakun Gu Wei Ma Yuying Guan Mengyuan Guo Qianqian Shao Xunming Ji Jia Liu Department of Clinical Laboratory Beijing Bo’ai HospitalChina Rehabilitation Research CenterCapital Medical UniversityBeijingChina Beijing institute of Brain Disorders Laboratory of Brain DisordersMinistry of Science and TechnologyCollaborative Innovation Center for Brain DisordersBeijing Advanced Innovation Center for Big Data-based Precision MedicineCapital Medical UniversityBeijingChina Department of Neurosurgery Xuanwu HospitalCapital Medical UniversityBeijingChina

Poststro ke cognitive impairment is a major secondary effect of ischemic stroke in many patients;however,few options are available for the early diagnosis and treatment of this *** aims of this study were to(1)determine the specific relationship between hypoxic andα-synuclein during the occur of poststroke cognitive impairment and(2)assess whether the serum phosphorylatedα-synuclein level can be used as a biomarker for poststro ke cognitive *** found that the phosphorylatedα-synuclein level was significantly increased and showed pathological aggregation around the cerebral infa rct area in a mouse model of ischemic *** addition,neuronalα-synuclein phosphorylation and aggregation were observed in the brain tissue of mice subjected to chronic hypoxia,suggesting that hypoxia is the underlying cause ofα-synuclein-mediated pathology in the brains of mice with ischemic *** phosphorylatedα-synuclein levels in patients with ischemic stroke were significantly lower than those in healt hy subjects,and were positively correlated with cognition levels in patients with ischemic ***,a decrease in serum high-density lipoprotein levels in stroke patie nts was significantly correlated with a decrease in phosphorylatedα-synuclein *** ischemic stroke mice did not show significant cognitive impairment or disrupted lipid metabolism 14 days after injury,some of them exhibited decreased cognitive function and reduced phosphorylatedα-synuclein *** together,our results suggest that serum phosphorylatedα-synuclein is a potential biomarker for poststroke cognitive impairment.

关键词： biomarker high-density lipoprotein ischemic stroke phosphorylatedα-synuclein poststroke cognitive impairment

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RFC:a feature selection algorithm for software defect prediction

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Journal of Systems Engineering and Electronics 2021年第2期32卷 389-398页

作者： XU Xiaolong CHEN Wen WANG Xinheng Jiangsu Key Laboratory of big data Security&Intelligent Processing Nanjing University of Posts and TelecommunicationsNanjing 210023China institute of big data research at yancheng Nanjing University of Posts and TelecommunicationsYancheng 224000China School of Computing and Engineering University of West LondonLondon W55RFUK

Software defect prediction(SDP)is used to perform the statistical analysis of historical defect data to find out the distribution rule of historical defects,so as to effectively predict defects in the new ***,there are redundant and irrelevant features in the software defect datasets affecting the performance of defect *** order to identify and remove the redundant and irrelevant features in software defect datasets,we propose ReliefF-based clustering(RFC),a clusterbased feature selection ***,the correlation between features is calculated based on the symmetric *** to the correlation degree,RFC partitions features into k clusters based on the k-medoids algorithm,and finally selects the representative features from each cluster to form the final feature *** the experiments,we compare the proposed RFC with classical feature selection algorithms on nine National Aeronautics and Space Administration(NASA)software defect prediction datasets in terms of area under curve(AUC)and *** experimental results show that RFC can effectively improve the performance of SDP.

关键词： software defect prediction(SDP) feature selection cluster

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Over-sampling algorithm for imbalanced data classification

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Journal of Systems Engineering and Electronics 2019年第6期30卷 1182-1191页

作者： XU Xiaolong CHEN Wen SUN Yanfei Jiangsu Key Laboratory of big data Security&Intelligent Processing Nanjing University of Posts and TelecommunicationsNanjing 210023China institute of big data research at yancheng Nanjing University of Posts and TelecommunicationsYancheng 224000China Office of Scientific R&D Nanjing University of Posts and TelecommunicationsNanjing 210023China

For imbalanced datasets, the focus of classification is to identify samples of the minority class. The performance of current data mining algorithms is not good enough for processing imbalanced datasets. The synthetic minority over-sampling technique(SMOTE) is specifically designed for learning from imbalanced datasets, generating synthetic minority class examples by interpolating between minority class examples nearby. However, the SMOTE encounters the overgeneralization problem. The densitybased spatial clustering of applications with noise(DBSCAN) is not rigorous when dealing with the samples near the *** optimize the DBSCAN algorithm for this problem to make clustering more reasonable. This paper integrates the optimized DBSCAN and SMOTE, and proposes a density-based synthetic minority over-sampling technique(DSMOTE). First, the optimized DBSCAN is used to divide the samples of the minority class into three groups, including core samples, borderline samples and noise samples, and then the noise samples of minority class is removed to synthesize more effective samples. In order to make full use of the information of core samples and borderline samples,different strategies are used to over-sample core samples and borderline samples. Experiments show that DSMOTE can achieve better results compared with SMOTE and Borderline-SMOTE in terms of precision, recall and F-value.

关键词： imbalanced data density-based spatial clustering of applications with noise(DBSCAN) synthetic minority over sampling technique(SMOTE) over-sampling.

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Server load prediction algorithm based on CM-MC for cloud systems

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Journal of Systems Engineering and Electronics 2018年第5期29卷 1069-1078页

作者： XU Xiaolong ZHANG Qitong MOU Yiqi LU Xinyuan Jiangsu Key Laboratory of big data Security & Intelligent Processing Nanjing University of Posts and Telecommunications State Key Laboratory of Information Security Chinese Academy of Sciences Shanghai Stock Exchange Technology Co. LtdShanghai Stock Exchange institute of big data research at yancheng Nanjing University of Posts and Telecommunications

Accurate prediction of server load is important to cloud systems for improving the resource utilization, reducing the energy consumption and guaranteeing the quality of service(QoS).This paper analyzes the features of cloud server load and the advantages and disadvantages of typical server load prediction algorithms, integrates the cloud model(CM) and the Markov chain(MC) together to realize a new CM-MC algorithm, and then proposes a new server load prediction algorithm based on CM-MC for cloud systems. The algorithm utilizes the historical data sample training method of the cloud model, and utilizes the Markov prediction theory to obtain the membership degree vector, based on which the weighted sum of the predicted values is used for the cloud model. The experiments show that the proposed prediction algorithm has higher prediction accuracy than other typical server load prediction algorithms, especially if the data has significant volatility. The proposed server load prediction algorithm based on CM-MC is suitable for cloud systems, and can help to reduce the energy consumption of cloud data centers.

关键词： cloud computing load prediction cloud model Markov chain energy saving

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Effects of short-range attraction on Jamming transition

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Chinese Physics B 2021年第6期30卷 409-413页

作者： Zhenhuan Xu Rui Wang Jiamei Cui Yanjun Liu Wen Zheng institute of Public-safety and big data College of Data ScienceTaiyuan University of TechnologyTaiyuan 030060China Center for big data research in Health Changzhi Medical CollegeChangzhi 046000China

Enormous progresses to understand the jamming transition have been driven via simulating purely repulsive particles which were somehow idealized in the past two decades. While the attractive systems are both theoretical and practical compared with repulsive systems. By studying the statistics of rigid clusters, we find that the critical packing fraction φ_(c) varies linearly with attraction μ for different system sizes when the range of attraction is short. While for systems with long-range attractions, however, the slope of φ_(c) appears significantly different, which means that there are two distinct jamming scenarios. In this paper, we focus our main attention on short-range attractions scenario and define a new quantity named "short-range attraction susceptibility" χ_(p), which describes the degree of response of the probability of finding jammed states pjto short-range attraction strength μ. Our central results are that χ_(p) diverges in the thermodynamic limit as χ_(p) ∝|φ-φ_(c)^(∞)|^(-γ_(p)), where φ_(c)^(∞) is the packing fraction at the jamming transition for the infinite system in the absence of attraction. χ_(p) obeys scaling collapse with a scaling function in both two and three dimensions, illuminating that the jamming transition can be considered as a phase transition as proposed in previous work.

关键词： short-range attraction Jamming transition short-range attraction susceptibility

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MTSS: multi-path traffic scheduling mechanism based on SDN

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Journal of Systems Engineering and Electronics 2019年第5期30卷 974-984页

作者： XU Xiaolong CHEN Yun HU Liuyun KUMAR Anup Jiangsu Key Laboratory of big data Security&Intelligent Processing Nanjing University of Posts and TelecommunicationsNanjing 210023China institute of big data research at yancheng Nanjing University of Posts and TelecommunicationsYancheng 224000China School of Computer Science Nanjing University of Posts and TelecommunicationsNanjing 210023China Department of Computer Engineering and Computer Science University of LouisvilleLouisville KY40292USA

Large-scale and diverse businesses based on the cloud computing platform bring the heavy network traffic to cloud data ***,the unbalanced workload of cloud data center network easily leads to the network congestion,the low resource utilization rate,the long delay,the low reliability,and the low *** order to improve the utilization efficiency and the quality of services(QoS)of cloud system,especially to solve the problem of network congestion,we propose MTSS,a multi-path traffic scheduling mechanism based on software defined networking(SDN).MTSS utilizes the data flow scheduling flexibility of SDN and the multi-path feature of the fat-tree structure to improve the traffic balance of the cloud data center network.A heuristic traffic balancing algorithm is presented for MTSS,which periodically monitors the network link and dynamically adjusts the traffic on the heavy link to achieve programmable data forwarding and load *** experimental results show that MTSS outperforms equal-cost multi-path protocol(ECMP),by effectively reducing the packet loss rate and *** addition,MTSS improves the utilization efficiency,the reliability and the throughput rate of the cloud data center network.

关键词： cloud data center software defined networking(SDN) load balancing multi-path transmission OpenFlow

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Field Application of Mulberry Straw Arch in Ecological Bank Revetment

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Journal of Renewable Materials 2022年第10期10卷 2607-2621页

作者： Xiaojuan Yu Chao Liu Quan Hua Xiaohui Wang Yongbin Li Geotechnical research institute Yancheng Institute of TechnologyYancheng224051China yancheng City Channel Management Office Yancheng Transportation BureauYancheng224051China

With the growing level of awareness and increasing demand for environmental protection,timber pile revetments with significant ecological effects have experienced increasingly wide application in *** current timber pile revetment system has two problems:continuous dense piles have high construction costs and require large timber consumptions,while the discrete pile-bamboo fence systems have poor retaining *** these problems,an original revetment structure form is proposed:a discrete pile-mulberry straw arch *** investigate the mechanical properties of the mulberry straw,some mechanical tests are conducted on mulberry straw and its arch *** is found that the average compressive strength of mulberry straw is 2.30 MPa,the bending strength is 20.08 MPa and the shear strength is 2.99 MPa;considering the structural characteristics of arches,mulberry straw arches have a high bending strength,which affords immense potential for their application in revetment ***,by doing field study of the discrete timber pile-mulberry straw arch structure for bank revetment,it is found that the arch height of the mulberry straw arch changes 1.4–1.6 cm after 489 d *** soil settlement before the straw arch is 0.13–0.18 cm and the settlement of the pile is 0.66–0.72 *** with bamboo fence structure,the cost of using mulberry straw arch structure as revetment material can save up to 27.07%.Therefore,the discrete timber pile-mulberry straw arch has a rational and stable structure that provides effective support for protecting the riverbank and the toe of gentle slopes and effectively prevents the collapse of bank slopes in the *** new revetment structure proposed in this paper has signifi-cant ecological and economic effects,is easy to construct and feasible for standard production,and consequently has great application potential.

关键词： Mulberry straw arch ecological bank revetment field test

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Optimal Network Function Virtualization and Service Function Chaining:A Survey

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Chinese Journal of Electronics 2018年第4期27卷 704-717页

作者： MIRJALILY Ghasem LUO Zhiquan Department of Electrical Engineering Yazd University Shenzhen research institute of big data The Chinese University of Hong Kong

Network function virtualization(NFV) and Service function chaining(SFC) can fulfill the traditional network functions by simply running special softwares on general-purpose computer servers and switches. This not only provides significantly more agility and flexibility in network service deployment, but can also greatly reduce the capital and operating cost of networks. In this paper,a comprehensive survey on the motivations and state of the art efforts towards implementing the NFV and SFC is provided. In particular, the paper first presents the main concepts of these new emerging technologies; then discusses in details various stages of SFC, including the description, composition, placement and scheduling of service chains. Afterwards, existing approaches to SFC are reviewed according to their application environments, parameters used, and solution strategies. Finally, the paper points out a number of future research directions.

关键词： Network function virtualization(NFV) Virtual network functions Service function chaining(SFC)

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Asking one mechanism in glial cells during neuroinflammation

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Neural Regeneration research 2025年第4期20卷 1077-1078页

作者： Xiaoli Guo Chikako Harada Takayuki Harada Visual research Project Tokyo Metropolitan Institute of Medical ScienceTokyoJapan

Multiple sclerosis(MS),which is characterized by inflammatory demyelination in the central nervous system(CNS),is the most common neurological disease in the young adult *** autoimmune encephalomyelitis(EAE),an animal model of MS,is often used in preclinical *** data indicate that in addition to immune cells such as T cells and dendritic cells,CNS resident microglia and astrocytes play important roles in demyelinating neuroinflammation(Healy et al.,2022).In particular,microglia are key immune-competent cells that can respond to environmental *** depletion of transforming growth factor-β-activated kinase 1,a mitogen-associated protein kinase kinase kinase,in microglia is reported to reduce CNS inflammation and diminish axonal and myelin damage *** suggests that elucidating the mechanisms of microglia-specific responses during pathologies may help in the development of treatments that reduce EAE/MS disease severity(Goldmann et al.,2013).

关键词： inflammation clinical

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Improved RIP-based bounds for guaranteed performance of two compressed sensing algorithms

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Science China Mathematics 2023年第5期66卷 1123-1140页

作者： Yunbin Zhao Zhiquan Luo Shenzhen research institute of big data The Chinese University of Hong KongShenzhenShenzhen 518172China

Iterative hard thresholding(IHT)and compressive sampling matching pursuit(CoSaMP)are two mainstream compressed sensing algorithms using the hard thresholding *** guaranteed performance of the two algorithms for signal recovery was mainly analyzed in terms of the restricted isometry property(RIP)of sensing *** present,the best known bound using the RIP of order 3k for guaranteed performance of IHT(with the unit stepsize)isδ3k<1/√3≈0.5774,and the bound for CoSaMP using the RIP of order 4k isδ4k<0.4782.A fundamental question in this area is whether such theoretical results can be further *** purpose of this paper is to affirmatively answer this question and to rigorously show that the abovementioned RIP bound for guaranteed performance of IHT can be significantly improved toδ3k<(√5−1)/2≈0.618,and the bound for CoSaMP can be improved toδ4k<0.5102.

关键词： iterative hard thresholding compressive sampling matching pursuit compressed sensing guaranteed performance restricted isometry property

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