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Neural network based approach for time to crash prediction to cope with software aging

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Journal of Systems Engineering and Electronics 2015年第2期26卷 407-414页

作者： Moona Yakhchi Javier Alonso Mahdi Fazeli Amir Akhavan Bitaraf Ahmad Patooghy School of Computer Science Institute for Research in Fundamental Sciences (IPM) institute of advanced studies on cybersecurity University of Leon Department of Computer Engineering Iran University of Technology

Recent studies have shown that software is one of the main reasons for computer systems unavailability. A growing ac- cumulation of software errors with time causes a phenomenon called software aging. This phenomenon can result in system per- formance degradation and eventually system hang/crash. To cope with software aging, software rejuvenation has been proposed. Software rejuvenation is a proactive technique which leads to re- moving the accumulated software errors by stopping the system, cleaning up its internal state, and resuming its normal operation. One of the main challenges of software rejuvenation is accurately predicting the time to crash due to aging factors such as me- mory leaks. In this paper, different machine learning techniques are compared to accurately predict the software time to crash un- der different aging scenarios. Finally, by comparing the accuracy of different techniques, it can be concluded that the multilayer per- ceptron neural network has the highest prediction accuracy among all techniques studied.

关键词： software reliability software rejuvenation machine learning

Brain region-specific roles of brain-derived neurotrophic factor in social stress-induced depressive-like behavior

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Neural Regeneration Research 2025年第1期20卷 159-173页

作者： Man Han Deyang Zeng Wei Tan Xingxing Chen Shuyuan Bai Qiong Wu Yushan Chen Zhen Wei Yufei Mei Yan Zeng Brain Science and advanced Technology institute Wuhan University of Science and TechnologyWuhanHubei ProvinceChina Geriatric Hospital Affiliated to Wuhan University of Science and Technology WuhanHubei ProvinceChina School of Public Health Wuhan University of Science and TechnologyWuhanHubei ProvinceChina

Brain-derived neurotrophic factor is a key factor in stress adaptation and avoidance of a social stress behavioral *** studies have shown that brain-derived neurotrophic factor expression in stressed mice is brain region–specific,particularly involving the corticolimbic system,including the ventral tegmental area,nucleus accumbens,prefrontal cortex,amygdala,and *** how brain-derived neurotrophic factor participates in stress processing in different brain regions will deepen our understanding of social stress *** this review,we discuss the expression and regulation of brain-derived neurotrophic factor in stress-sensitive brain regions closely related to the pathophysiology of *** focused on associated molecular pathways and neural circuits,with special attention to the brain-derived neurotrophic factor–tropomyosin receptor kinase B signaling pathway and the ventral tegmental area–nucleus accumbens dopamine *** determined that stress-induced alterations in brain-derived neurotrophic factor levels are likely related to the nature,severity,and duration of stress,especially in the above-mentioned brain regions of the corticolimbic ***,BDNF might be a biological indicator regulating stress-related processes in various brain regions.

关键词： amygdala chronic mild stress chronic social defeat stress corticolimbic system depression hippocampus medial prefrontal cortex nucleus accumbens social stress models ventral tegmental area

Single-cell omics: experimental workflow, data analyses and applications

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Science China Life Sciences 2025年第1期68卷 5-102页

作者： Fengying Sun Haoyan Li Dongqing Sun Shaliu Fu Lei Gu Xin Shao Qinqin Wang Xin Dong Bin Duan Feiyang Xing Jun Wu Minmin Xiao Fangqing Zhao Jing-Dong J.Han Qi Liu Xiaohui Fan Chen Li Chenfei Wang Tieliu Shi Department of Clinical Laboratory the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City) Pharmaceutical Informatics institute College of Pharmaceutical SciencesZhejiang University Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University) Ministry of EducationOrthopaedic DepartmentTongji HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji University Frontier Science Center for Stem Cells School of Life Sciences and TechnologyTongji University Translational Medical Center for Stem Cell Therapy and institute for Regenerative Medicine Shanghai East HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji University Research institute of Intelligent Computing Zhejiang Lab Shanghai Research institute for Intelligent Autonomous Systems Center for Single-cell Omics School of Public HealthShanghai Jiao Tong University School of Medicine National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang University Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal University Beijing institutes of Life Science Chinese Academy of Sciences Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary StudiesCenter for Quantitative Biology (CQB)Peking University Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases Women's HospitalZhejiang University School of Medicine Key Laboratory of advanced Theory and Application in Statistics and Data Science-MOE School of StatisticsEast China Normal University

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome,proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial sc RNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field,offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

关键词： single-cell sequencing genome epigenome proteomics metabolomics multimodal spatial transcriptomics CRISPR screening

Design of S-band photoinjector with high bunch charge and low emittance based on multi-objective genetic algorithm

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Nuclear Science and Techniques 2023年第3期34卷 93-105页

作者： Ze-Yi Dai Yuan-Cun Nie Zi Hui Lan-Xin Liu Zi-Shuo Liu Jian-Hua Zhong Jia-Bao Guan Ji-Ke Wang Yuan Chen Ye Zou Hao-Hu Li Jian-Hua He The institute for advanced studies Wuhan UniversityWuhan 430072China

High-brightness electron beams are required to drive LINAC-based free-electron lasers(FELs)and storage-ring-based synchrotron radiation light *** bunch charge and RMS bunch length at the exit of the LINAC play a crucial role in the peak current;the minimum transverse emittance is mainly determined by the injector of the ***,a photoin-jector with a high bunch charge and low emittance that can simultaneously provide high-quality beams for 4th generation synchrotron radiation sources and FELs is *** design of a 1.6-cell S-band 2998-MHz RF gun and beam dynamics optimization of a relevant beamline are presented in this *** dynamics simulations were performed by combining ASTRA and the multi-objective genetic algorithm NSGA *** effects of the laser pulse shape,half-cell length of the RF gun,and RF parameters on the output beam quality were analyzed and *** normalized transverse emittance was optimized to be as low as 0.65 and 0.92 mm·mrad when the bunch charge was as high as 1 and 2 nC,***,the beam stability properties of the photoinjector,considering misalignment and RF jitter,were simulated and analyzed.

关键词： Electron linear accelerator Photoinjector Beam dynamics Multi-objective genetic algorithm

Narrow bandgap molecular dyads incorporating Y-series acceptor backbones for efficient single-molecular organic solar cells

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Science China Chemistry 2023年第11期66卷 3205-3212页

作者： Yuan Gao Bo Xiao Shanshan Wang Mingxia Chen Wei Wang Xinrong Yang Yiming Shao Rui Sun Jie Min The institute for advanced studies Wuhan UniversityWuhan 430072China

The performance of organic solar cells(OSCs)is mainly related to the bulk heterojunction(BHJ)microstructure of specific active layer systems,which is often in a metastable state.A promising strategy to address the abovementioned shortcomings of BHJs is to develop single-component active layer *** to the single-component small molecule materials with defined chemical structures generally exhibit poor absorption spectra,herein we first introduced narrow bandgap Y-series acceptors into the molecular skeleton of single-component materials,and designed two molecular dyads,SM-Et-1Y and *** optical bandgaps(E_g~(opt)s)of the two dyads are 1.364 and 1.361 eV,respectively,which are much smaller than those of previously reported single-component ***,the SM-Et-2Y-based single-component OSCs(SCOSCs)showed a power conversion efficiency(PCE)of 5.07%,superior to SM-Et-1Y(2.53%),which is one of the highest PCEs reported for SCOSCs to ***,both SM-Et-1Y-and SM-Et-2Y-based devices exhibited excellent photo-stability,retaining over 90%of their initial performance after 250 h of continuous *** results provide a deeper understanding of the molecular backbone and a guiding principle for the rational design or selection of non-fullerene single-component materials with suitable donor/acceptor ratios.

关键词： donor-acceptor dyads single-material organic solar cells Y-series acceptors operational stability optical bandgap

Synthesis of photocatalytic La_(1–x)A_xTiO_(3.5–δ)(A=Ba, Sr, Ca) nano perovskites and their application for photocatalytic oxidation of congo red dye in aqueous solution

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Journal of Rare Earths 2015年第2期33卷 160-167页

作者： M.Bradha T.Vijayaraghavan S.P.Suriyaraj R.Selvakumar Anuradha M.Ashok Nanotech Research Facility PSG Institute of Advanced StudiesCoimbatore-641 004 India Nanobiotechnology Laboratory PSG Institute of Advanced StudiesCoimbatore-641 004 India

A-site substituted La0.8A0.2TiO3.5–δ（A=Ba, Sr, Ca） nano perovskites were prepared by sol-gel method and characterized using thermogravimetry/differential thermal analysis（TGA/DTA）, X-ray diffraction（XRD）, ultraviolet-visible（UV-Vis） spectroscopy and transmission electron microscopy（TEM）. XRD analysis showed that the La0.8A0.2TiO3.5–δ（A=Ba, Sr, Ca） nano perovskites derived after calcination at 800 oC were in single phase with orthorhombic structure. The particle size of all nano perovskites was found to be ~20 nm. The synthesized nano perovskites were tested for the photocatalytic decomposition of an azo dye, Congo red. The sequential behavior of La0.8A0.2TiO3.5–δ（A=Ba, Sr, Ca） nanoperovskites for photocatalytic decomposition of congo red in aqueous solution by visible light at room temperature was studied at various time intervals and the efficiency of degradation of the nanoperovskites was compared. Among all the A-site substituted La0.8A0.2TiO3.5–δ（A=Ba, Sr, Ca） nano perovskites, Ba substituted compound showed the highest dye degradation.

关键词： nano perovskite oxidation photocatalyst congo red dye degradation rare earths

DGA-Based Botnet Detection Toward Imbalanced Multiclass Learning

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Tsinghua Science and Technology 2021年第4期26卷 387-402页

作者： Yijing Chen Bo Pang Guolin Shao Guozhu Wen Xingshu Chen College of cybersecurity Sichuan UniversityChengdu 610065China cybersecurity Research institute Sichuan UniversityChengdu 610065China

Botnets based on the Domain Generation Algorithm(DGA) mechanism pose great challenges to the main current detection methods because of their strong concealment and robustness. However, the complexity of the DGA family and the imbalance of samples continue to impede research on DGA detection. In the existing work, the sample size of each DGA family is regarded as the most important determinant of the resampling proportion;thus,differences in the characteristics of various samples are ignored, and the optimal resampling effect is not *** this paper, a Long Short-Term Memory-based Property and Quantity Dependent Optimization(***)method is proposed. This method takes advantage of LSTM to automatically mine the comprehensive features of DGA domain names. It iterates the resampling proportion with the optimal solution based on a comprehensive consideration of the original number and characteristics of the samples to heuristically search for a better solution around the initial solution in the right direction;thus, dynamic optimization of the resampling proportion is *** experimental results show that the *** method can achieve better performance compared with existing models to overcome the difficulties of unbalanced datasets;moreover, it can function as a reference for sample resampling tasks in similar scenarios.

关键词： botnet Domain Generation Algorithm(DGA) multiclass imbalance resampling

An Anomalous Behavior Detection Model in Cloud Computing

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Tsinghua Science and Technology 2016年第3期21卷 322-332页

作者： Xiaoming Ye Xingshu Chen Haizhou Wang Xuemei Zeng Guolin Shao Xueyuan Yin Chun Xu College of Computer Science Cybersecurity Research Institute Sichuan University

This paper proposes an anomalous behavior detection model based on cloud computing. Virtual Machines （VMs） are one of the key components of cloud Infrastructure as a Service （laaS）. The security of such VMs is critical to laaS security. Many studies have been done on cloud computing security issues, but research into VM security issues, especially regarding VM network traffic anomalous behavior detection, remains inadequate. More and more studies show that communication among internal nodes exhibits complex patterns. Communication among VMs in cloud computing is invisible. Researchers find such issues challenging, and few solutions have been proposed--leaving cloud computing vulnerable to network attacks. This paper proposes a model that uses Software-Defined Networks （SDN） to implement traffic redirection. Our model can capture inter-VM traffic, detect known and unknown anomalous network behaviors, adopt hybrid techniques to analyze VM network behaviors, and control network systems. The experimental results indicate that the effectiveness of our approach is greater than 90%, and prove the feasibility of the model.

关键词： virtual machine network behavior anomaly detection cloud computing

Antiproton-nucleus reactions at intermediate energies

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Nuclear Science and Techniques 2015年第2期26卷 104-110页

作者： Alexei Borisovich Larionov Frankfurt institute for advanced studies National Research Centre Kurchatov Institute

Antiproton-induced reactions on nuclei at the beam energies from hundreds Me V up to several Ge V provide an excellent opportunity to study interactions between the antiproton and secondary particles(mesons, baryons and antibaryons) with nucleons. The antiproton projectile is unique in the sense that most of the annihilation particles are relatively slow in the target nucleus frame. Hence, the prehadronic effects do not much influence their interactions with the nucleons of the nuclear residue. Moreover, the particles with momenta less than about 1 Ge V/c are sensitive to nuclear mean field potentials. This paper discusses the microscopic transport calculations of the antiproton-nucleus reactions and is focused on three related problems:(i) antiproton potential determination,(ii) possible formation of strongly bound antiproton-nucleus systems, and(iii) strangeness production.

关键词：原子核反应反质子能量相互作用次级粒子核平均场核系统 iii