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arXiv 2019年

作者： Zhang, Yue Weng, Jian Weng, Jiasi Li, Ming Luo, Weiqi College of Informatin Science and Technology College of Cyber security National Joint Engineering Research Center of Network Security Detection and Protection Technology Guangdong Key Laboratory of Data Security and Privacy Preserving Jinan University Guangzhou510632 China

With the popularity of Blockchain comes grave security related concerns. Achieving privacy and traceability simultaneously remains an open question. Efforts have been made to address the issues, while they may subject to specific scenarios. This paper studies how to provide a more general solution for this open question. Concretely, we propose Onionchain, featuring a suite of protocols, offering both traceability and privacy. As the term implies, our Onionchain is inspired by Onion routing. We investigate the principles of Onion routing carefully and integrate its mechanism together with Blockchain technology. We advocate the Blockchain community to adopt Onionchain with the regards of privacy and traceability. To this end, a case-study of Onionchain, which runs in the context of Vehicular Ad Hoc networks (VANETs), is proposed, providing the community a guideline to follow. Systematic security analysis and extensive experiments are also conducted to validate our secure and cost-effective Onionchain. Copyright © 2019, The Authors. All rights reserved.

关键词： Blockchain

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Genomic evolution reshapes cell-type diversification in the amniote brain

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Developmental Cell 2025年

作者： Chen, Duoyuan Zhuang, Zhenkun Huang, Maolin Huang, Yunqi Yan, Yuting Zhang, Yanru Lin, Youning Jin, Xiaoying Wang, Yuanmei Huang, Jinfeng Xu, Wenbo Pan, Jingfang Wang, Hong Huang, Fubaoqian Liao, Kuo Cheng, Mengnan Zhu, Zhiyong Bai, Yinqi Niu, Zhiwei Zhang, Ze Xiang, Ya Wei, Xiaofeng Yang, Tao Zeng, Tao Dong, Yuliang Lei, Ying Sun, Yangang Wang, Jian Yang, Huanming Sun, Yidi Cao, Gang Poo, Muming Liu, Longqi Naumann, Robert K. Xu, Chun Wang, Zhenlong Xu, Xun Liu, Shiping BGI Research Hangzhou 310030 China The Institute of Biomedical and Health Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions Shenzhen 1068 Xueyuan Avenue Shenzhen University Town Nanshan District Shenzhen 518055 China School of Life Sciences Zhengzhou University Zhengzhou 450001 China School of Biology and Biological Engineering South China University of Technology Guangzhou 510006 China College of Life Sciences University of Chinese Academy of Sciences Beijing 100049 China BGI Research Shenzhen 518083 China Institute of Neuroscience Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology CAS Center for Excellence in Brain Science and Intelligence Technology University of Chinese Academy of Sciences Chinese Academy of Sciences Shanghai 200031 China HIM-BGI Omics Center Hangzhou Institute of Medicine (HIM) Chinese Academy of Sciences Hangzhou 310018 China China National GeneBank BGI Research Shenzhen 518120 China Guangdong Genomics Data Center BGl research Shenzhen 518120 China Key Laboratory of Spatial Omics of Zhejiang Province BGI Research Hangzhou 310030 China James D. Watson Institute of Genome Sciences Hangzhou 310029 China College of Life Sciences Northwest University Xi'an 710069 China Key Laboratory of Systems Health Science of Zhejiang Province School of Life Science Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Hangzhou 310024 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China State Key Laboratory of Genome and Multi-omics Technologies BGI Research Hangzhou 310030 China Shanxi Medical University BGI Collaborative Center for Future Medicine Shanxi Medical University Taiyuan 030001 China

Over 320 million years of evolution, amniotes have developed complex brains and cognition through largely unexplored genetic and gene expression mechanisms. We created a comprehensive single-cell atlas of over 1.3 million cells from the telencephalon and cerebellum of turtles, zebra finches, pigeons, mice, and macaques, employing single-cell resolution spatial transcriptomics to validate gene expression patterns across species. Our study identifies significant species-specific variations in cell types, highlighting their conservation and diversification in evolution. We found pronounced differences in telencephalon excitatory neurons (EXs) and cerebellar cell types between birds and mammals. Birds predominantly express SLC17A6 in EX, whereas mammals express SLC17A7 in the neocortex and SLC17A6 elsewhere, possibly due to loss of function of SLC17A7 in birds. Additionally, we identified a bird-specific Purkinje cell subtype (SVIL+), implicating the lysine-specific demethylase 11 (LSD1)/KDM1A pathway in learning and circadian rhythms and containing numerous positively selected genes, which suggests an evolutionary optimization of cerebellar functions for ecological and behavioral adaptation. Our findings elucidate the complex interplay between genetic evolution and environmental adaptation, underscoring the role of genetic diversification in the development of specialized cell types across amniotes. © 2025 Elsevier Inc.

关键词： amniote brain science cerebellum evolution of cell types single-nucleus RNA-seq telencephalon

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Root Cause Localization for Unreproducible Builds via Causality Analysis Over System Call Tracing

Root Cause Localization for Unreproducible Builds via Causal...

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IEEE International Conference on Automated Software Engineering (ASE)

作者： Zhilei Ren Changlin Liu Xusheng Xiao He Jiang Tao Xie Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province School of Software Dalian University of Technology Department of Computer and Data Sciences Case Western Reserve University School of Software Dalian University of Technology Department of Computer Science and Technology Peking University

Localization of the root causes for unreproducible builds during software maintenance is an important yet challenging task, primarily due to limited runtime traces from build processes and high diversity of build environments. To address these challenges, in this paper, we propose RepTrace, a framework that leverages the uniform interfaces of system call tracing for monitoring executed build commands in diverse build environments and identifies the root causes for unreproducible builds by analyzing the system call traces of the executed build commands. Specifically, from the collected system call traces, RepTrace performs causality analysis to build a dependency graph starting from an inconsistent build artifact (across two builds) via two types of dependencies: read/write dependencies among processes and parent/child process dependencies, and searches the graph to find the processes that result in the inconsistencies. To address the challenges of massive noisy dependencies and uncertain parent/child dependencies, RepTrace includes two novel techniques: (1) using differential analysis on multiple builds to reduce the search space of read/write dependencies, and (2) computing similarity of the runtime values to filter out noisy parent/child process dependencies. The evaluation results of RepTrace over a set of real-world software packages show that RepTrace effectively finds not only the root cause commands responsible for the unreproducible builds, but also the files to patch for addressing the unreproducible issues. Among its Top-10 identified commands and files, RepTrace achieves high accuracy rate of 90.00% and 90.56% in identifying the root causes, respectively.

关键词： Runtime Noise measurement Process control Monitoring Task analysis Software packages

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Visual Tracking Algorithm Based on Color Name Histogram

Visual Tracking Algorithm Based on Color Name Histogram

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作者： Chenchen Yue Wangsheng Yu Zhiqiang Hou Sugang Ma College of Computer Science and Technology Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an University of Posts and Telecommunications Information and Navigation Institute of Air Force Engineering University

Aimed at the problem that traditional histogram is sensitive to illumination changes in visual tracking,combined with the CN(Color Name) feature,we proposed a new feature(denotes CNH,Color Name Histogram) based on color ***,the method projected the original RGB image to CN space to obtain robust 11 feature ***,we counted the each pixel numbers of feature ***,normalizing the amount of pixels in each *** addition,we adopted a feature adaptive fusion method to combine CNH and HOG(Histogram of Oriented Gradient).In order to prove validity of the proposed algorithm,we use Staple(Sum of Template And Pixel-wise Learners) algorithm frame to make a controlled *** contrast with the reference algorithms,the success of our algorithm increases by 1.5% and the precision increases by 1.7%.The results show that this method retains the advantages of traditional histogram which is insensitive to target deformation,but also enhances the robustness to illumination change.

关键词： Visual tracking Color histogram Color name Feature fusion

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Bug or not bug? Labeling issue reports via user reviews for mobile apps 30

Bug or not bug? Labeling issue reports via user reviews for ...

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30th International Conference on Software Engineering and Knowledge Engineering, SEKE 2018

作者： Li, Haoming Zhang, Tao Wang, Ziyuan College of Computer Science and Technology Harbin Engineering University Harbin150001 China Key Laboratory of Network Assessment Technology Institute of Information Engineering CAS Bejing100093 China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210023 China

ISBN: (纸本)1891706446

A great number of mobile applications (apps) have been released to the market. Therefore, software maintenance for these apps become an important and challenging task. For each app, developers usually submit issue reports to report the bugs, the features, the questions, and other changes appearing in it. In the process of software maintenance, developers refer to the corresponding labels to decide which one should be fixed first. If the label of an issue report is "bug" which means the report describes a serious error, developers should fix the bug first. Otherwise, if the label is not "bug" (e.g., feature or question), developers can resolve it later. However, according to our investigation, 36.7% of issue reports in top-10 popular mobile apps are not labeled. In other words, there are not any labels in them. It is difficult for developers to decide which issue should be resolved preferentially. To resolve this problem, we propose a method to verify whether an issue report describes a bug or not by using user reviews. Developers usually extract useful information from user reviews to maintain mobile apps. In this work, we utilize tfidf, Word2Vec, and Microsoft Concept Graph (MCG) to compute the textual similarity between issue reports and user reviews related to real bug in order to find the issue reports which describe the real bugs. As a result, our approach with Word2Vec performs the best among three similarity metrics. © 2018 Universitat zu Koln. All rights reserved.

关键词： Computer software maintenance

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Unveiling the secrets of the mid-infrared Moon

arXiv

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arXiv 2020年

作者： Wu, Yunzhao Jin, Qi Li, Cui Xu, Tianyi Qi, Wenwen Tan, Wei Li, Xiaoman Shi, Zhicheng He, Hongyan Dai, Shuwu Li, Guo Liu, Fengjing Wang, Jingqiao Wang, Xiaoyan Lu, Yu Cai, Wei Wang, Qi Meng, Lingjie Key Laboratory of Planetary Sciences Purple Mountain Observatory Chinese Academy of Sciences Nanjing210034 China Space Science Institute Macau University of Science and Technology Macau China Cas Center for Excellence in Comparative Planetology China Beijing Institute of Space Mechanics and Electricity Beijing China Beijing Institute of Spacecraft System Engineering Beijing China China Centre for Resources Satellite Data and Application Beijing China Jiangsu Ctr. for Collab. Innovation in Geographical Information Resource Development and Application Nanjing210023 China Earth Observation System and Data Center China National Space Administration Beijing China

The Moon's optical characteristics in visible and long-wavelength infrared (LWIR) have long been observed with our eyes or with instruments. What the mid-infrared (MIR) Moon looks like is still a mystery. For the first time we present detailed appearance of the MIR Moon observed by a high-resolution geostationary satellite and reveal the essence behind its appearance. The appearance of the MIR Moon is opposite to its normal visible appearance. In addition the MIR Moon shows limb darkening. Both the absolute and the relative brightness distribution of the MIR lunar disk changes with the solar incidence angle. The signatures of the MIR Moon are controlled by both the reflection and emission of the lunar surface. We also show first-ever brightness temperature maps of the lunar disk without needing a mosaic, which better show the temperature variation across the lunar disk. They reveal that the relationship between brightness temperature and solar incidence angle i is cos1/bi, and the power parameter is smaller than the Lambertian temperature model of cos1/4i observed for lunar orbit-based measurements. The slower decrease of the brightness temperature when moving away from the sub-solar point than the Lambertian model is due to topographic effects. The brightness temperature is dominated by albedo and the solar incidence angle and influenced by the topography. Our results indicate that the Moon in the MIR exhibits many interesting phenomena which were previously unknown, and contains abundant information about lunar reflection and thermal emission for future study. Copyright © 2020, The Authors. All rights reserved.

关键词： Infrared devices

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Overlapping Community Detection Based on Influence and Seeds Extension

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2019年第1期47卷 153-160页

作者： Yu, Zhi-Yong Chen, Ji-Jie Guo, Kun Chen, Yu-Zhong Xu, Qian College of Mathematics and Computer Sciences Fuzhou University FuzhouFujian350116 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing FuzhouFujian350116 China Ministry of Education Key Laboratory of Spatial Data Mining & Information Sharing FuzhouFujian350116 China State Grid Info-Telecom Great Power Science and Technology Co. Ltd. FuzhouFujian350003 China

Community detection is a significant research direction in the research of social networks. To improve the quality of seeds selection and expansion, we propose an influence seeds extension overlapping community detection (i-SEOCD) algorithm for overlapping community detection. First, i-SEOCD uses a node influence strategy to find the seed communities with tight structures. Second, on the basis of the seed communities, we calculate the similarity among communities and their neighbor nodes. The nodes whose similarity is greater than a predefined threshold are selected. Third, the strategy of optimizing a self-adaptive function is adopted to expand the communities. Finally, the free nodes in the network are assigned to their corresponding communities in order to find out all the overlapping community structures. Experiments on the real and artificial networks show that i-SEOCD is capable of discovering overlapping communities in complex social networks efficiently. © 2019, Chinese Institute of Electronics. All right reserved.

关键词： Population dynamics

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H2O2-Responsive NIR-II AIE Nanobomb for Carbon Monoxide Boosting Low-Temperature Photothermal Therapy

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Angewandte Chemie 2022年第36期134卷

作者： Gongcheng Ma Zhongke Liu Chunguang Zhu Prof. Huajie Chen Prof. Ryan T. K. Kwok Prof. Pengfei Zhang Ben Zhong Tang Prof. Lintao Cai Prof. Ping Gong Guangdong Key Laboratory of Nanomedicine Shenzhen Engineering Laboratory of Nanomedicine and Nanoformulations CAS-HK Joint Lab for Biomaterials Research Laboratory for Biomedical Optics and Molecular Imaging Shenzhen Key Laboratory for Molecular Imaging CAS Key Lab for Health Informatics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China University of Chinese Academy of Sciences Beijing 100049 China Contribution: Data curation (lead) Validation (lead) Writing - original draft (lead) Nano Science and Technology Institute University of Science & Technology of China Suzhou 215123 China Contribution: Data curation (equal) Investigation (equal) Key Laboratory of Environmentally Friendly Chemistry and Application of the Ministry of Education College of Chemistry Xiangtan University Xiangtan 411105 China Contribution: Data curation (supporting) Methodology (supporting) Contribution: Project administration (supporting) Resources (supporting) Supervision (supporting) Writing - review & editing (equal) Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction and Institute for Advanced Study The Hong Kong University of Science and Technology (HKUST) Clear Water Bay Kowloon Hong Kong China Contribution: Funding acquisition (equal) Supervision (equal) Writing - review & editing (equal) Contribution: Conceptualization (lead) Formal analysis (lead) Methodology (equal) Project administration (lead) Resources (equal) Supervision (equal) Writing - original draft (equal) Writing - review & editing (lead) School of Science and Engineering Shenzhen Institute of Aggregate Science and Technology The Chinese University of Hong Kong Shenzhen Guangdong 518172 China Contribution: Formal analysis (supporting) Funding acquisition (equal) Writing - review & editing (supporting) Contribution: Funding acquisition (lead) Project administration (lead) Supervision (lead) Writing - revi

Low-temperature photothermal therapy (PTT), which circumvents the limitations of conventional PTT (e.g., thermotolerance and adverse effects), is an emerging therapeutic strategy which shows great potential for future clinical applications. The expression of heat shock proteins (HSPs) can dramatically impair the therapeutic efficacy of PTT. Thus, inhibition of HSPs repair and reducing the damage of nearby normal cells is crucial for improving the efficiency of low-temperature PTT. Herein, we developed a nanobomb based on the self-assembly of NIRII AIE polymer PBPTV and carbon monoxide (CO) carrier polymer mPEG(CO). This smart nanobomb can be exploded in a tumor microenvironment in which hydrogen peroxide is overexpressed and release CO into cancer cells to significantly inhibit the expression of HSPs and hence improve the antitumor efficiency of the low-temperature PTT.

关键词： Aggregation Induced Emission Gas Therapy Heat Shock Protein NIR-II Photothermal Therapy

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A tree search algorithm for sequence labeling

arXiv

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arXiv 2018年

作者： Lao, Yadi Xu, Jun Lan, Yanyan Guo, Jiafeng Gao, Sheng Cheng, Xueqi Guo, Jun Beijing University of Posts and Telecommunications CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Science

In this paper we propose a novel reinforcement learning based model for sequence tagging, referred to as MM-Tag. Inspired by the success and methodology of the AlphaGo Zero, MM-Tag formalizes the problem of sequence tagging with a Monte Carlo tree search (MCTS) enhanced Markov decision process (MDP) model, in which the time steps correspond to the positions of words in a sentence from le. to right, and each action corresponds to assign a tag to a word. Two long short-term memory networks (LSTM) are used to summarize the past tag assignments and words in the sentence. Based on the outputs of LSTMs, the policy for guiding the tag assignment and the value for predicting the whole tagging accuracy of thewhole sentence are produced.e policy and value are then strengthened with MCTS, which takes the produced raw policy and value as inputs, simulates and evaluates the possible tag assignments at the subsequent positions, and outputs a *** search policy for assigning tags. A reinforcement learning algorithm is proposed to train the model parameters. Our work is the first to apply the MCTS enhanced MDP model to the sequence tagging task. We show that MM-Tag can accurately predict the tags thanks to the exploratory decision making mechanism introduced by MCTS. Experimental results show based on a chunking benchmark showed that MM-Tag outperformed the state-of-the-art sequence tagging baselines including CRF and CRF with LSTM. Copyright © 2018, The Authors. All rights reserved.

关键词： Long short-term memory

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On self-duality and hulls of cyclic codes over 2m[u]huki with oddly even length

arXiv

引用

arXiv 2019年

作者： Cao, Yonglin Cao, Yuan Fu, Fang-Wei School of Mathematics and Statistics Shandong University of Technology Zibo Shandong255091 China Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering Changsha University of Science and Technology Changsha Hunan410114 Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and Statistics Hubei University Wuhan430062 Chern Institute of Mathematics and Lpmc Tianjin Key Laboratory of Network and Data Security Technology Nankai University Tianjin300071 China

Let F2m be a finite field of 2m elements, and R = F2m[u]/huki = 2m + u2m + . . . + uk-1F2m (uk = 0) where k is an integer satisfying k ≥ 2. For any odd positive integer n, an explicit representation for every self-dual cyclic code over R of length 2n and a mass formula to count the number of these codes are given first. Then a generator matrix is provided for the self-dual and 2-quasi-cyclic code of length 4n over F2m derived by every self-dual cyclic code of length 2n over 2m + u2m and a Gray map from 2m + u2m onto F22 m. Finally, the hull of each cyclic code with length 2n over F2m +uF2m is determined and all distinct self-orthogonal cyclic codes of length 2n over 2m + u2m are listed. Copyright © 2019, The Authors. All rights reserved.

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