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Transcriptomic analysis of Andrias davidianus meat and experimental validation for exploring its bioactive components as functional foods

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Food Science and Human Wellness 2024年第1期13卷 166-172页

作者： Changge Guan Zhenglin Tan Shucheng Li Yi Wang Naoyuki Yamamoto Chong Zhang Songjun Wang Junjie Chen Xinhui Xing key laboratory for Industrial Biocatalysis Ministry of Education of ChinaDepartment of Chemical EngineeringTsinghua UniversityBeijing 100084China School of Life Science and Technology Tokyo Institute of TechnologyYokohama 226-0026Japan Sensing System Research Center National Institute of Advanced Industrial Science and TechnologyTsukuba 305-8565Japan Center for Synthetic and Systems Biology Tsinghua UniversityBeijing 100084China Henan Giant Salamander Protection and Development Association Luoyang 471000China Intelligent computing Research Center Harbin Institute of TechnologyShenzhen 518071China Institute of Biopharmaceutical and Health Engineering Tsinghua Shenzhen International Graduate SchoolShenzhen 518055China Institute of Biomedical Health Technology and Engineering Shenzhen Bay LaboratoryShenzhen 518067China

Andrias davidianus(Chinese giant salamander,CGS)is the largest and oldest extant amphibian species in the world and is a source of prospective functional food in ***,the progress of functional peptides mining was slow due to lack of reference genome and protein sequence *** this study,we illustrated full-length transcriptome sequencing to interpret the proteome of CGS meat and obtain 10703 coding DNA *** functional annotation and amino acid composition analysis,we have discovered various genes related to signal transduction,and 16 genes related to *** have also found vast variety of functional peptides through protein coding sequence(CDS)analysis by comparing the data obtained with the functional peptide ***-Pro-Ile predicted by the CDS analysis was released from the CGS meat through enzymatic hydrolysis,suggesting that our approach is *** study suggested that transcriptomic analysis can be used as a reference to guide polypeptide mining in CGS meat,thereby providing a powerful mining strategy for the bioresources with unknown genomic and proteomic sequences.

关键词： Chinese giant salamander Transcriptomic analysis Bioactive components Functional peptides mining

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The anisotropy of suprathermal electrons in the Martian ionosphere

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Earth and Planetary Physics 2024年第3期8卷 459-471页

作者： YuTian Cao Jun Cui XiaoShu Wu WenJun Liang RuiQi Fu HaoYu Lu Planetary Environmental and Astrobiological Research laboratory(PEARL) School of Atmospheric SciencesSun Yat-sen UniversityZhuhai 519082China key laboratory of Geospace Environment University of Science&Technology of ChinaChinese Academy of SciencesHefei 230026China Center for Excellence in Comparative Planetology Chinese Academy of SciencesHefei 230026China School of Space and Environment Beihang UniversityBeijing 102206China

Suprathermal electrons are an important population of the Martian ionosphere, either produced by photoionization of atmospheric neutrals or supplied from the Solar Wind (SW). This study is dedicated to an in-depth investigation of the pitch angle distribution of suprathermal electrons at two representative energies, 19−55 eV and 124−356 eV, using the extensive measurements made by the Solar Wind Electron Analyzer on board the Mars Atmosphere and Volatile Evolution. Throughout the study, we focus on the overall degree of anisotropy, defined as the standard deviation of suprathermal electron intensity among different directions which is normalized by the mean omni-directional intensity. The available data reveal the following characteristics: (1) In general, low energy electrons are more isotropic than high energy electrons, and dayside electrons are more isotropic than nightside electrons;(2) On the dayside, the anisotropy increases with increasing altitude at low energies but remains roughly constant at high energies, whereas on the nightside, the anisotropy decreases with increasing altitude at all energies;(3) Electrons tend to be more isotropic in strongly magnetized regions than in weakly magnetized regions, especially on the nightside. These observations indicate that the anisotropy is a useful diagnostic of suprathermal electron transport, for which the conversion between the parallel and perpendicular momenta as required by the conservation of the first adiabatic invariant, along with the atmospheric absorption at low altitudes, are two crucial factors modulating the observed variation of the anisotropy. Our analysis also highlights the different roles on the observed anisotropy exerted by suprathermal electrons of different origins.

关键词： Mars ionosphere suprathermal electron pitch angle distribution

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A Secure and Cost-Effective Training Framework Atop Serverless computing for Object Detection in Blasting

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 2139-2154页

作者： Tianming Zhang Zebin Chen Haonan Guo Bojun Ren Quanmin Xie Mengke Tian Yong Wang Department of Computer and Science Shanghai Jiaotong UniversityShanghai200240China Aerospace System Engineering Shanghai Shanghai200240China State key laboratory of Precision Blasting Jianghan UniversityWuhan430056China Beijing Microelectronics Technology Institute Beijing100076China

The data analysis of blasting sites has always been the research goal of relevant *** rise of mobile blasting robots has aroused many researchers’interest in machine learning methods for target detection in the field of *** computing can provide a variety of computing services for people without hardware foundations and rich software development experience,which has aroused people’s interest in how to use it in the field ofmachine *** this paper,we design a distributedmachine learning training application based on the AWS Lambda *** on data parallelism,the data aggregation and training synchronization in Function as a Service(FaaS)are effectively *** also encrypts the data set,effectively reducing the risk of data *** rent a cloud server and a Lambda,and then we conduct experiments to evaluate our *** results indicate the effectiveness,rapidity,and economy of distributed training on FaaS.

关键词： Serverless computing object detection blasting

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Runtime reconfiguration of data services for dealing with out-of-range stream fluctuation in cloud-edge environments

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Digital Communications and Networks 2022年第6期8卷 1014-1026页

作者： Shouli Zhang Chen Liu Xiaohong Li Yanbo Han Division of Intelligence and computing Tianjin UniversityTianjin300072China Beijing key laboratory on Integration and analysis of Large-Scale Stream data North China University of TechnologyBeijing10009China Cloud computing Research Center North China University of TechnologyBeijing10009China

The integration of cloud and IoT edge devices is of significance in reducing the latency of IoT stream data processing by moving services closer to the *** this connection,a key issue is to determine when and where services should be *** service deployment strategies used to be static based on the rules defined at the design ***,dynamically changing IoT environments bring about unexpected situations such as out-of-range stream fluctuation,where the static service deployment solutions are not *** this paper,we propose a dynamic service deployment mechanism based on the prediction of upcoming stream *** effectively predict upcoming workloads,we combine the online machine learning methods with an online optimization algorithm for service deployment.A simulation-based evaluation demonstrates that,compared with those state-of-the art approaches,the approach proposed in this paper has a lower latency of stream processing.

关键词： IoT stream processing Edge computing Out-of-Range stream fluctuation Dynamic service deployment

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A Transfer Function Design for Medical Volume data Using a Knowledge database Based on Deep Image and Primitive Intensity Profile Features Retrieval

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Journal of Computer Science & Technology 2024年第2期39卷 320-335页

作者： Younhyun Jung Jim Kong 盛斌 Jinman Kim School of computing Gachon UniversitySeongnam 13120Korea School of Computer Science The University of SydneySydney 2006Australia Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Direct volume rendering(DVR)is a technique that emphasizes structures of interest(SOIs)within a volume visually,while simultaneously depicting adjacent regional information,e.g.,the spatial location of a structure concerning its *** DVR,transfer function(TF)plays a key role by enabling accurate identification of SOIs interactively as well as ensuring appropriate visibility of *** generation typically involves non-intuitive trial-and-error optimization of rendering parameters,which is time-consuming and *** at mitigating this manual process have led to approaches that make use of a knowledge database consisting of pre-designed TFs by domain *** these approaches,a user navigates the knowledge database to find the most suitable pre-designed TF for their input volume to visualize the *** these approaches potentially reduce the workload to generate the TFs,they,however,require manual TF navigation of the knowledge database,as well as the likely fine tuning of the selected TF to suit the *** this work,we propose a TF design approach,CBR-TF,where we introduce a new content-based retrieval(CBR)method to automatically navigate the knowledge *** of pre-designed TFs,our knowledge database contains volumes with SOI *** an input volume,our CBR-TF approach retrieves relevant volumes(with SOI labels)from the knowledge database;the retrieved labels are then used to generate and optimize TFs of the *** approach largely reduces manual TF navigation and fine *** our CBR-TF approach,we introduce a novel volumetric image feature which includes both a local primitive intensity profile along the SOIs and regional spatial semantics available from the co-planar images to the *** the regional spatial semantics,we adopt a convolutional neural network to obtain high-level image feature *** the intensity profile,we extend the dynamic time warping technique to address subtle alignment

关键词： data retrieval direct volume rendering ray analysis transfer function

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A Cross-Domain Ontology Semantic Representation Based on NCBI-BlueBERT Embedding

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Chinese Journal of Electronics 2022年第5期31卷 860-869页

作者： ZHAO Lingling WANG Junjie WANG Chunyu GUO Maozu Faculty of computing Harbin Institute of Technology Department of Medical Informatics School of Biomedical Engineering and InformaticsNanjing Medical University Beijing key laboratory of Intelligent Processing for Building big data School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture

A common but critical task in biological ontologies data analysis is to compare the difference between ontologies. There have been numerous ontologybased semantic-similarity measures proposed in specific ontology domain, but it still remains a challenge for crossdomain ontologies comparison. An ontology contains the scientific natural language description for the corresponding biological aspect. Therefore, we develop a new method based on natural language processing(NLP) representation model bidirectional encoder representations from transformers(BERT) for cross-domain semantic representation of biological ontologies. This article uses the BERT model to represent the word-level of the ontologies as a set of vectors, facilitating the semantic analysis or comparing the biomedical entities named in an ontology or associated with ontology terms. We evaluated the ability of our method in two experiments: calculating similarities of pair-wise disease ontology and human phenotype ontology terms and predicting the pair-wise of proteins interaction. The experimental results demonstrated the comparative performance. This gives promise to the development of NLP methods in biological data analysis.

关键词： Ontology Semantic representation Semantic similarity Protein-protein interaction

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Indexing dynamic encrypted database in cloud for efficient secure k-nearest neighbor query

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Frontiers of Computer Science 2024年第1期18卷 187-198页

作者： Xingxin LI Youwen ZHU Rui XU Jian WANG Yushu ZHANG College of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 210016China Department of Mathematical Informatics University of TokyoTokyo 113-8654Japan Guangxi key laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin 541004China School of Computer Science China University of GeosciencesWuhan 430074China

Secure k-Nearest Neighbor(k-NN)query aims to find k nearest data of a given query from an encrypted database in a cloud server without revealing privacy to the untrusted cloud and has wide applications in many areas,such as privacy-preservingmachine elearning gand secure biometric *** solutions have been put forward to solve this challenging ***,the existing schemes still suffer from various limitations in terms of efficiency and *** this paper,we propose a new encrypt-then-index strategy for the secure k-NN query,which can simultaneously achieve sub-linear search complexity(efficiency)and support dynamical update over the encrypted database(flexibility).Specifically,we propose a novel algorithm to transform the encrypted database and encrypted query points in the *** indexing the transformed database using spatial data structures such as the R-tree index,our strategy enables sub-linear complexity for secure k-NN queries and allows users to dynamically update the encrypted *** the best of our knowledge,the proposed strategy is the first to simultaneously provide these two *** theoretical analysis and extensive experiments,we formally prove the security and demonstrate the efficiency of our scheme.

关键词： cloud computing secure k-NN query sub-linear complexity dynamicupdate

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RGCNU: Recurrent Graph Convolutional Network With Uncertainty Estimation for Remaining Useful Life Prediction

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IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1640-1642页

作者： Qiwu Zhu Qingyu Xiong Zhengyi Yang Yang Yu School of big data&Software Engineering Chongqing UniversityChongqing 400044 key laboratory of Dependable Service computing in Cyber Physical Society Ministry of EducationChongqing 400044China School of Biology and Engineering Guizhou Medical UniversityGuiyang 550025China

Dear Editor,This letter focuses on the problem of remaining useful life(RUL)prediction of equipment. Existing graph neural network(GCN)-based approaches merely provide the point estimation of RUL. However,the estimated RUL often varies widely due to the model parameters and the noise in data. It is important to know the uncertainty in predictions for reliable risk analysis and maintenance decision *** map the relationship between noisy condition monitoring data and RUL with uncertainty.

关键词： letter estimation prediction

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A Post-Quantum Cross-Domain Authentication Scheme Based on Multi-Chain Architecture

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Computers, Materials & Continua 2024年第2期78卷 2813-2827页

作者： Yi-Bo Cao Xiu-Bo Chen Yun-Feng He Lu-Xi Liu Yin-Mei Che Xiao Wang Ke Xiao Gang Xu Si-Yi Chen Information Security Center State Key Laboratory ofNetworking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China Information Center of China North Industries Group Corporation Beijing100089China School of Information Science and Technology North China University of TechnologyBeijing100144China

Due to the rapid advancements in network technology,blockchain is being employed for distributed data *** the Internet of Things(IoT)scenario,different participants manage multiple blockchains located in different trust domains,which has resulted in the extensive development of cross-domain authentication ***,the emergence of many attackers equipped with quantum computers has the potential to launch quantum computing attacks against cross-domain authentication schemes based on traditional cryptography,posing a significant security *** response to the aforementioned challenges,our paper demonstrates a post-quantum cross-domain identity authentication scheme to negotiate the session key used in the cross-chain asset exchange ***,our paper designs the hiding and recovery process of user identity index based on lattice cryptography and introduces the identity-based signature from lattice to construct a post-quantum cross-domain authentication ***,our paper utilizes the hashed time-locked contract to achieves the cross-chain asset exchange of blockchain nodes in different trust ***,the security analysis reduces the security of the identity index and signature to Learning With Errors(LWE)and Short Integer Solution(SIS)assumption,respectively,indicating that our scheme has post-quantum *** but not least,through comparison analysis,we display that our scheme is efficient compared with the cross-domain authentication scheme based on traditional cryptography.

关键词： Cross-domain identity authentication lattice-based cryptography blockchain hashed time-locked contract

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Scale‐wise interaction fusion and knowledge distillation network for aerial scene recognition

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1178-1190页

作者： Hailong Ning Tao Lei Mengyuan An Hao Sun Zhanxuan Hu Asoke K.Nandi School of Computer Science and Technology Xi'an University of Posts and TelecommunicationsShaanxi Key Laboratory of Network Data Analysis and Intelligent ProcessingXi'anChina Xi'an key laboratory of big data and Intelligent computing Xi'anChina School of Electronic Information and Artificial Intelligence Shaanxi University of Science and TechnologyXi'anChina School of Computer Central China Normal UniversityWuhanChina Department of Electronic and Electrical Engineering Brunel University LondonLondonUK Xi'an Jiaotong University Xi'anChina

Aerial scene recognition(ASR)has attracted great attention due to its increasingly essential *** of the ASR methods adopt the multi‐scale architecture because both global and local features play great roles in ***,the existing multi‐scale methods neglect the effective interactions among different scales and various spatial locations when fusing global and local features,leading to a limited ability to deal with challenges of large‐scale variation and complex background in aerial scene *** addition,existing methods may suffer from poor generalisations due to millions of to‐belearnt parameters and inconsistent predictions between global and local *** tackle these problems,this study proposes a scale‐wise interaction fusion and knowledge distillation(SIF‐KD)network for learning robust and discriminative features with scaleinvariance and background‐independent *** main highlights of this study include two *** the one hand,a global‐local features collaborative learning scheme is devised for extracting scale‐invariance features so as to tackle the large‐scale variation problem in aerial scene ***,a plug‐and‐play multi‐scale context attention fusion module is proposed for collaboratively fusing the context information between global and local *** the other hand,a scale‐wise knowledge distillation scheme is proposed to produce more consistent predictions by distilling the predictive distribution between different scales during *** experimental results show the proposed SIF‐KD network achieves the best overall accuracy with 99.68%,98.74%and 95.47%on the UCM,AID and NWPU‐RESISC45 datasets,respectively,compared with state of the arts.

关键词： deep learning image analysis image classification information fusion

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