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Intelligent method to experimentally identify the fracture mechanism of red sandstone

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International Journal of Minerals,Metallurgy and Materials 2023年第11期30卷 2134-2146页

作者： Zida Liu Diyuan Li Quanqi Zhu Chenxi Zhang Jinyin Ma Junjie Zhao School of Resources and Safety Engineering Central South UniversityChangsha 410083China

Tensile and shear fractures are significant mechanisms for rock failure.Understanding the fractures that occur in rock can reveal rock failure mechanisms.Scanning electron microscopy(SEM)has been widely used to analyze tensile and shear fractures of rock on a mesoscopic scale.To quantify tensile and shear fractures,this study proposed an innovative method composed of SEM images and deep learning techniques to identify tensile and shear fractures in red sandstone.First,direct tensile and preset angle shear tests were performed for red sandstone to produce representative tensile and shear fracture surfaces,which were then observed by SEM.Second,these obtained SEM images were applied to develop deep learning models(AlexNet,VGG13,and SqueezeNet).Model evaluation showed that VGG13 was the best model,with a testing accuracy of 0.985.Third,the features of tensile and shear fractures of red sandstone learned by VGG13 were analyzed by the integrated gradient algorithm.VGG13 was then implemented to identify the distribution and proportion of tensile and shear fractures on the failure surfaces of rock fragments caused by uniaxial compression and Brazilian splitting tests.Results demonstrated the model feasibility and suggested that the proposed method can reveal rock failure mechanisms.

关键词： tensile and shear fractures rock failure deep learning scanning electron microscopy red sandstone

Baseline symptoms of depression and anxiety negatively impact the effectiveness of CBTi in treating acute insomnia among young adults

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General Psychiatry 2023年第3期36卷 168-174页

作者： Chenxi Zhang Shufei Zeng Yan Xu Shuai Liu Shixu Du Leqin Fang Zhihong Lv Lili zhang Bin zhang Department of Psychiatry Nanfang HospitalSouthern Medical UniversityGuangzhouChina Center of Sleep Medicine Nanfang HospitalSouthern Medical UniversityGuangzhouChina

Background Cognitive-behavioural therapy for insomnia(CBTi)is the first-line treatment for those with this sleep disorder.However,depressive and anxiety symptoms often co-occur with acute insomnia,which may affect the effectiveness of CBTitreatment.Aims This study aimed to determine the impact of depressive and anxiety symptoms on the efficacy of CBTi in treating acute insomnia.Methods A single-arm clinical trial was conducted among individuals who have acute insomnia.Participants underwent self-guided CBTi for 1-week.Their insomnia,depressive symptoms and anxiety symptoms were evaluated using the Insomnia Severity Index and the Hospital Anxiety and Depression Scale at baseline,post-treatment and 3-month follow-up.Repeated measures analysis of variance was used to assess the effectiveness of CBTi in treating insomnia,depressive symptoms and anxiety symptoms.A multivariate Cox regression model was used to determine the impact of depressive and anxiety symptoms on insomnia.Results The study found significant reductions in insomnia,depressive symptoms and anxiety symptoms at both post-treatment and 3-month follow-up(F=17.45,p<0.001;F=36.37,p=0.001;and F=81.51,p<0.001,respectively).The duration of CBTi treatment had a positive impact on insomnia recovery(hazard ratio(HR)=0.94,p=0.018).However,baseline depressive symptoms(HR=1.83,p=0.004)and baseline anxiety symptoms(HR=1.99,p=0.001)had significant negative effects on insomnia recovery.Conclusions The study showed that a 1-week self-guided CBTi treatment is effective in treating acute insomnia and comorbid depressive and anxiety symptoms.However,baseline depressive and anxiety symptoms negatively impact treatment effectiveness.Therefore,clinicians should assess for depressive and anxiety symptoms before treating acute insomnia with monotherapy CBTi.

关键词： impact CBT treatment

Dynamic Evolutionary Game-based Modeling,Analysis and Performance Enhancement of Blockchain Channels

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 188-202页

作者： PeiYun zhang MengChu Zhou chenxi Li Abdullah Abusorrah IEEE the School of Computer Science Nanjing University of Information Science&TechnologyNanjing 210044China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the School of Computer and Information Anhui Normal UniversityWuhu 241003China the Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia

The recent development of channel technology has promised to reduce the transaction verification time in blockchain operations.When transactions are transmitted through the channels created by nodes,the nodes need to cooperate with each other.If one party refuses to do so,the channel is unstable.A stable channel is thus required.Because nodes may show uncooperative behavior,they may have a negative impact on the stability of such channels.In order to address this issue,this work proposes a dynamic evolutionary game model based on node behavior.This model considers various defense strategies'cost and attack success ratio under them.Nodes can dynamically adjust their strategies according to the behavior of attackers to achieve their effective defense.The equilibrium stability of the proposed model can be achieved.The proposed model can be applied to general channel networks.It is compared with two state-of-the-art blockchain channels:Lightning network and Spirit channels.The experimental results show that the proposed model can be used to improve a channel's stability and keep it in a good cooperative stable state.Thus its use enables a blockchain to enjoy higher transaction success ratio and lower transaction transmission delay than the use of its two peers.

关键词： Blockchain channel network evolutionary game malicious behavior secure computing stability analysis

Ion energy-induced nanoclustering structure in a-C:H film for achieving robust superlubricity in vacuum

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Friction 2022年第12期10卷 1967-1984页

作者： Qingyuan YU Xinchun CHEN Chenhui zhang Chenxi Zhang Wenli DENG Yinhui WANG Jianxun XU Wei QI State Key Laboratory of Tribology Tsinghua UniversityBeijing 100084China

Hydrogenated amorphous carbon(a-C:H)films are capable of providing excellent superlubricating properties,which have great potential serving as self-lubricating protective layer for mechanical systems in extreme working conditions.However,it is still a huge challenge to develop a-C:H films capable of achieving robust superlubricity state in vacuum.The main obstacle derives from the lack of knowledge on the influencing mechanism of deposition parameters on the films bonding structure and its relation to their self-lubrication performance.Aiming at finding the optimized deposition energy and revealing its influencing mechanism on superlubricity,a series of highly-hydrogenated a-C:H films were synthesized with appropriate ion energy,and systematic tribological experiments and structural characterization were conducted.The results highlight the pivotal role of ion energy on film composition,nanoclustering structure,and bonding state,which determine mechanical properties of highly-hydrogenated a-C:H films and surface passivation ability and hence their superlubricity performance in vacuum.The optimized superlubricity performance with the lowest friction coefficient of 0.006 coupled with the lowest wear rate emerges when the carbon ion energy is just beyond the penetration threshold of subplantation.The combined growth process of surface chemisorption and subsurface implantation is the key for a-C:H films to acquire stiff nanoclustering network and high volume of hydrogen incorporation,which enables a robust near-frictionless sliding surface.These findings can provide a guidance towards a more effective manipulation of self-lubricating a-C:H films for space application.

关键词： hydrogenated amorphous carbon(a-C:H) superlubricity ion energy nanoclustering bonding structure mechanical properties

Chemerin promotes proliferation and migration of ovarian cancer cells by upregulating expression of PD-L1

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2022年第2期23卷 164-170页

作者： chenxi GAO Jinming SHI Jingxin zhang Yin LI Yi zhang Department of Gynecology the First Affiliated Hospital of China Medical UniversityShenyang 110001China Department of Integration of Chinese and Western Medicine School of Basic Medical SciencesPeking UniversityBeijing 100191China

Ovarian cancer is the third-most-common malignant reproductive tumor in women.According to the American Cancer Society,it has the highest mortality rate of gynecological tumors.The five-year survival rate was only 29%... 详细信息

关键词： cancer mortality

New wheel-shaped Ln_(6) clusters for conversion of CO_(2) and magnetic properties

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稀土学报:英文版 2023年第10期41卷 1574-1582,I0004页

作者： Wenmin Wang Na Qiao Xiaoyan Xin Chen Yang Ying Chen Shanshan Dong Chenxi Zhang College of Chemistry and Materials Taiyuan Normal UniversityJinzhong030619China College of Chemical Engineering and Materials Science Tianjin University of Science and TechnologyTianjin300457China

A series of novel hexanuclear lanthanide dusters,namely,[Ln_(6)(HL)_(6)(NO_(3))_(6)]·3CH_(3)CN(Ln=Gd(1),Tb(2),Dy(3)and Er(4))was assembled using a multidentate ligand H3L(trolamine).The clusters 1-4 show a wheel-shaped Ln_(6)topology with the approximate diameter and thickness of 1.5 and 0.7 nm,respectively.All of them show high thermal stability.In the aspect of the catalytic capacities for the cycloaddition reactions of CO_(2)and epoxide,the reaction conditions,the substrate scope,and possible catalytic mechanism were investigated.The highest yield for clusters 1-4 is up to 99%at 333 K for 12 h.In particular,cluster 1 can be reused at least three times with no obvious loss of catalytic performance and keep the integrity of the crystal structure.Magnetic investigations reveal that cluster 1 exhibits a relatively large magnetocaloric effect with-ΔS_(m)=41.43 J/(kg·K)(T=3.0 K,7.0 T);while cluster 3 displays slow magnetic relaxation behavior under zero dc field with U_(eff)=0.51 K andτ_(0)=2.54×10^(-5)s.

关键词： Wheel-shaped Ln_(6)clusters Conversion of CO_(2) Magnetocaloric effect Single-molecular magnet behavior Rare earths

Intrusion Detection Algorithm Based on Density,Cluster Centers,and Nearest Neighbors

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China Communications 2016年第7期13卷 24-31页

作者： Xiujuan Wang Chenxi Zhang Kangfeng Zheng Computer Sciences Beijing University of Technology Computer Science And Technology Beijing University of Posts and Telecommunications

Intrusion detection aims to detect intrusion behavior and serves as a complement to firewalls.It can detect attack types of malicious network communications and computer usage that cannot be detected by idiomatic firewalls.Many intrusion detection methods are processed through machine learning.Previous literature has shown that the performance of an intrusion detection method based on hybrid learning or integration approach is superior to that of single learning technology.However,almost no studies focus on how additional representative and concise features can be extracted to process effective intrusion detection among massive and complicated data.In this paper,a new hybrid learning method is proposed on the basis of features such as density,cluster centers,and nearest neighbors(DCNN).In this algorithm,data is represented by the local density of each sample point and the sum of distances from each sample point to cluster centers and to its nearest neighbor.k-NN classifier is adopted to classify the new feature vectors.Our experiment shows that DCNN,which combines K-means,clustering-based density,and k-NN classifier,is effective in intrusion detection.

关键词：聚类中心基于密度入侵行为测算法入侵检测方法最近邻混合学习分类器

Mature typhoon “cloud gyro” model and numerical simulation study

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Science China Earth Sciences 2020年第5期63卷 749-756页

作者： Xiaogang HUANG Xiangcheng LI Xiaoping CHENG Chenxi Zhang Juli DING College of Meteorology and Oceanography National University of Defense TechnologyNanjing 211101China PLA Troop 92664 Haiyang 265100China

Due to the coarse temporal resolution of the best track databases for typhoons,some small-scale characteristics of typhoon motion have been neglected.In order to reveal the fine features of typhoon motion,the dense cloud within the radius of maximum wind(RMW)of mature typhoons,defined as a“cloud gyro”that simultaneously spins around its own rotational axis and precesses around the vertical axis,is approximated to a rigid body.Based on the principles of gyrodynamics,the derived mathematical model of a typhoon track indicates that typhoon movement is composed of translational motion governed by the steering flow and superimposed precessional motion that manifests as the inherent characteristics of typhoon tracks,especially with the external torque.High temporal resolution numerical simulation of a real case verifies the conclusion of this study,which is that the smaller the RMW,the larger the tangential wind speed or the larger the external torque,and the more obviously precessional motion manifests.

关键词： Mature typhoon Cloud gyro Precession angular velocity

CLEAN:Frequent Pattern-Based Trajectory Compression and Computation on Road Networks

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China Communications 2020年第5期17卷 119-136页

作者： Peng Zhao Qinpei Zhao Chenxi Zhang Gong Su Qi zhang Weixiong Rao Tongji University Shanghai 201804China IBM T.J.Watson Research Center New York 10598USA

The volume of trajectory data has become tremendously huge in recent years. How to effectively and efficiently maintain and compute such trajectory data has become a challenging task. In this paper, we propose a trajectory spatial and temporal compression framework, namely CLEAN. The key of spatial compression is to mine meaningful trajectory frequent patterns on road network. By treating the mined patterns as dictionary items, the long trajectories have the chance to be encoded by shorter paths, thus leading to smaller space cost. And an error-bounded temporal compression is carefully designed on top of the identified spatial patterns for much low space cost. Meanwhile, the patterns are also utilized to improve the performance of two trajectory applications, range query and clustering, without decompression overhead. Extensive experiments on real trajectory datasets validate that CLEAN significantly outperforms existing state-of-art approaches in terms of spatial-temporal compression and trajectory applications.

关键词： trajectory compression pattern mining spatial-temporal compressions range query clustering