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The M-computations induced by accessibility relations in nonstandard models M of Hoare logic

Frontiers of computer science 2016年第4期10卷 717-725页

作者： Cungen CAO Yuefei SUI Zaiyue ZHANG Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Department of Computer Science Jiangsu University of Sciences and Technology Zhenjiang 212003 China

Hoare logic is a logic used as a way of specifying semantics of programming languages, which has been extended to be a separation logic to reason about mutable heap structure. In a model M of Hoare logic, each program α induces an M-computable function fα M on the universe of M; and the M-recursive functions are defined on M. It will be proved that the class of all the M-computable functions fα M induced by programs is equal to the class of all the M- recursive functions. Moreover, each M-recursive function is ∑ 1 NM -definable in M, where the universal quantifier is a num- ber quantifier ranging over the standard part of a nonstandard model M.

关键词： Hoare logic recursive ：Function computable function nonstandard model of Peano arithmetic

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Recent Advances in Fibrous Materials for Hydroelectricity Generation

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Nano-Micro Letters 2025年第2期17卷 109-133页

作者： Can Ge Duo Xu Xiao Feng Xing Yang Zheheng Song Yuhang Song Jingyu Chen Yingcun Liu Chong Gao Yong Du Zhe Sun Weilin Xu Jian Fang College of Textile and Clothing Engineering Soochow UniversitySuzhou 215123People’s Republic of China National Engineering Laboratory for Modern Silk Soochow UniversitySuzhou 215123People’s Republic of China State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200People’s Republic of China Institute of Functional Nano&Soft Materials(FUNSOM) Soochow UniversitySuzhou 215123People’s Republic of China Department of Electrical and Computer Engineering University of MassachusettsAmherstMA 01003USA Department of Materials Imperial College LondonSouth Kensington CampusLondon SW72AZUK College of Textile Science and Engineering Zhejiang Sci-Tech UniversityHangzhou 310018People’s Republic of China School of Materials Science and Engineering Shanghai Institute of Technology100 Haiquan RoadShanghai 201418People’s Republic of China

Depleting fossil energy sources and conventional polluting power generation pose a threat to sustainable *** generation from ubiquitous and spontaneous phase transitions between liquid and gaseous water has been considered a promising strategy for mitigating the energy *** materials with unique flexibility,processability,multifunctionality,and practicability have been widely applied for fibrous materials-based hydroelectricity generation(FHG).In this review,the power generation mechanisms,design principles,and electricity enhancement factors of FHG are first ***,the fabrication strategies and characteristics of varied constructions including 1D fiber,1D yarn,2D fabric,2D membrane,3D fibrous framework,and 3D fibrous gel are ***,the advanced functions of FHG during water harvesting,proton dissociation,ion separation,and charge accumulation processes are analyzed in ***,the potential applications including power supply,energy storage,electrical sensor,and information expression are also ***,some existing challenges are considered and prospects for future development are sincerely proposed.

关键词： Hydroelectricity Fibrous material Streaming potential Ion diffusion

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Block-Based Projection Matrix Design for Compressed Sensing

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Chinese Journal of Electronics 2016年第3期25卷 551-555页

作者： LI Zhetao XIE Jingxiong ZHU Gengming PENG Xin XIE Yanrong CHOI Youngjune The College of Information Engineering Xiangtan University School of Computer National University of Defense Technology Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University School of Computer Science and Engineering Hunan University of Science and Technology College of Information and Communication Engineering Hunan Institute of Science and Technology Department of Information and Computer Engineering Ajou University

The objective of optimizing a projection matrix is to decrease the mutual coherence between a projection matrix and a basis matrix. In this paper, a novel block-based method is proposed to design a projection matrix in compressed sensing. Here, the projection matrix is divided into two blocks. The relationship between the two blocks was obtained by reasoning and proving. Theoretical analysis demonstrates that the mutual coherence between the whole projection matrix and the whole basis matrix keeps as good as the mutual coherence between the block matrix and blocked basis matrix. Experimental results show that the proposed method obtains better performance compared to existing methods.

关键词： Compressed sensing Projection matrix Block optimization Mutual coherence

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Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction

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IEEE Transactions on Medical Imaging 2025年 PP卷 PP页

作者： Ma, Chenglong Li, Zilong Li, Yuanlin Han, Jing Zhang, Junping Zhang, Yi Liu, Jiannan Shan, Hongming Fudan University Institute of Science and Technology for Brain-inspired Intelligence Moe Frontiers Center for Brain Science Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Shanghai200433 China Fudan University Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Shanghai200433 China Shanghai Ninth People's Hospital Department of Oral Maxillofacial Head and Neck Oncology China Shanghai Jiao Tong University School of Medicine College of Stomatology China Shanghai Key Laboratory of Stomatology Shanghai Research Institute of Stomatology National Center for Stomatology National Clinical Research Center for Oral Diseases Shanghai200011 China Sichuan University School of Cyber Science and Engineering Chengdu Sichuan610065 China

Metal artifacts in computed tomography (CT) images can significantly degrade image quality and impede accurate diagnosis. Supervised metal artifact reduction (MAR) methods, trained using simulated datasets, often struggle to perform well on real clinical CT images due to a substantial domain gap. Although state-of-the-art semi-supervised methods use pseudo ground-truths generated by a prior network to mitigate this issue, their reliance on a fixed prior limits both the quality and quantity of these pseudo ground-truths, introducing confirmation bias and reducing clinical applicability. To address these limitations, we propose a novel radiologist-in-the-loop self-training framework for MAR, termed RISE-MAR, which can integrate radiologists' feedback into the semi-supervised learning process, progressively improving the quality and quantity of pseudo ground-truths for enhanced generalization on real clinical CT images. For quality assurance, we introduce a clinical quality assessor model that emulates radiologist evaluations, effectively selecting high-quality pseudo ground-truths for semi-supervised training. For quantity assurance, our self-training framework iteratively generates additional high-quality pseudo groundtruths, expanding the clinical dataset and further improving model generalization. Extensive experimental results on multiple clinical datasets demonstrate the superior generalization performance of our RISE-MAR over state-of-the-art methods, advancing the development of MAR models for practical application. © 2025 IEEE.

关键词： computerized tomography

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Large-scale virtual machines provisioning in clouds： challenges and approaches

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Frontiers of computer science 2016年第1期10卷 2-18页

作者： Zhaoning ZHANG Dongsheng LI Kui WU National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 China Computer Science Department University of Victoria Victoria V8W 2Y2 Canada

The scale of global data center market has been explosive in recent years. As the market grows, the demand for fast provisioning of the virtual resources to support elas- tic, manageable, and economical computing over the cloud becomes high. Fast provisioning of large-scale virtual ma- chines （VMs）, in particular, is critical to guarantee quality of service （QoS）. In this paper, we systematically review the existing VM provisioning schemes and classify them in three main categories. We discuss the features and research status of each category, and introduce two recent solutions, VMThunder and VMThunder＋, both of which can provision hundreds of VMs in seconds.

关键词： cloud computing IaaS large scale virtual ma-chine provisioning

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Lie Reduction and Conditional Symmetries of Some Variable Coefficient Nonlinear Wave Equations

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Communications in Theoretical Physics 2010年第1期53卷 1-5页

作者：黄定江周水庚梅建琴张鸿庆 School of Computer Science Fudan University Shanghai Key Lab of Intelligent Information Processing Fudan University Department of Mathematics East China University of Science and Technology Department of Applied Mathematics Dalian University of Technology

Lie symmetry reduction of some truly ＂variable coefficient＂ wave equations which are singled out from a class of （1 ＋ 1）-dimensional variable coefficient nonlinear wave equations with respect to one and two-dimensional algebras is carried out. Some classes of exact solutions of the investigated equations are found by means of both the reductions and some modern techniques such as additional equivalent transformations and hidden symmetries and so on. Conditional symmetries are also discussed.

关键词： symmetry reduction conditional symmetry exact solutions variable-coefficient nonlinear wave equations

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Protocol for the fabrication of self-standing (nano)cellulose-based 3D scaffolds for tissue engineering

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STAR Protocols 2025年第1期6卷 103583页

作者： Mohan, Tamilselvan Bračič, Matej Bračič, Doris Lackner, Florian Nagaraj, Chandran Štiglic, Andreja Dobaj Kargl, Rupert Kleinschek, Karin Stana Graz University of Technology Institute for Chemistry and Technology of Biobased System (IBioSys) Stremayrgasse 9 Graz 8010 Austria University of Maribor Faculty of Mechanical Engineering Laboratory for Characterization and Processing of Polymers Smetanova Ulica 17 Maribor 2000 Slovenia Department of Internal Medicine Division of Pulmonology Medical University of Graz Graz Austria Institute of Automation Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia Members of the European Polysaccharide Network of Excellence (EPNOE) Austria

Three-dimensional (3D) and porous scaffolds made from nanocellulosic materials hold significant potential in tissue engineering (TE). Here, we present a protocol for fabricating self-standing (nano)cellulose-based 3D scaffolds designed for in vitro testing of cells from skin and cartilage tissues. We describe steps for preparation of nanocellulose ink, scaffold formation using 3D printing, and freeze-drying. We then detail post-processing procedures to enhance mechanical properties, stability, and biocompatibility. This protocol offers researchers a framework for developing versatile and sustainable biomaterials for regenerative medicine. For complete details on the use and execution of this protocol, please refer to Mohan et al.¹ and Štiglic et al.² © 2025 The Authors

关键词： Biotechnology and bioengineering Chemistry Material sciences Tissue Engineering

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Feature-Consistent Cyclic Domain Adversarial Network for Unsupervised Transfer Diagnosis of the Autoimmune Disease Igg4-Rd by Raman Spectroscopy

SSRN

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SSRN 2025年

作者： Zhang, Ziyang Chen, Cheng Qin, Wentao Wu, Xue Liu, Yang Wu, Lijun Lv, Xiaoyi Chang, Chenjie Chen, Xinya Chen, Zhiyuan Xu, Qianxi Li, Zhuoyu Ma, Mengsi Chen, Chen Xinjiang University College of Software Urumqi830046 China Xinjiang Cloud Computing Application Laboratory Xinjiang University Karamay834099 China School of Computer Science and Technology Xinjiang University Urumqi830046 China Key Laboratory of signal detection and processing Xinjiang University Urumqi830046 China Department of Rheumatology＆Immunology People's Hospital of Xinjiang Uygur Autonomous Region Xinjiang Urumqi China Xinjiang Clinical Research Center for Rheumatoid arthritis Xinjiang Urumqi China

Abstracts IgG4-related disease (IgG4-RD) is a multi-organ immune disorder characterized by systemic involvement, diverse pathogenesis, and rarity, which complicates its diagnosis. Traditional medical diagnostic models, predominantly based on supervised learning in machine learning or deep learning frameworks, struggle to address the scarcity of labeled data due to the diagnostic challenges of IgG4-RD. To overcome this limitation, this study proposes a novel framework based on Feature-Consistent Cyclic Domain Adversarial Networks (FCCDAN). The framework first trains a classification model on the source domain for diagnosing source domain diseases under supervised conditions. Subsequently, leveraging the source domain model, the encoder is guided to extract semantic features, while feature consistency loss is integrated into both the generator and discriminator to align the semantic features of the target domain with those of the source domain. Finally, the aligned features are processed through a pre-trained linear mapping to achieve unsupervised classification and diagnosis in the target domain. The proposed model utilizes common autoimmune diseases as a knowledge source, enabling unsupervised transfer diagnosis for IgG4-RD, and demonstrates generalizability through experiments on other disease datasets, achieving an average diagnostic accuracy of 90.62%. This represents improvements of 4.14%, 9.82%, and 10.51% over baseline models, respectively. FCCDAN expands the applicability of Raman spectroscopy in disease diagnosis, maintaining high performance even in label-scarce environments. The overall research workflow also establishes a robust paradigm for the application and advancement of domain adaptation techniques in this context. © 2025, The Authors. All rights reserved.

关键词： Adversarial machine learning

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Data Mining and Neural Network Techniques in Case Based System

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Wuhan University Journal of Natural sciences 2001年第Z1期6卷 601-605页

作者： Ni Zhi wei 1,2 , Cai Qing sheng 1, Li Long shu 2 1.department of computer science, University of science and technology of China,Hefei 230027,China 2.The Key Laboratory of Intelligent Computing and Signal processing ,Ministry of Education Department of Computer Science University of Science and Technology of China Hefei China The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China

This paper first puts forward a case based system framework based on data mining techniques. Then the paper examines the possibility of using neural networks as a method of retrieval in such a case based system. In ... 详细信息

关键词： data mining neural network case based reasoning retrieval algorithm

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Semantic Representation of Evidence-Based Medical Guidelines and Its Use Cases

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Wuhan University Journal of Natural sciences 2015年第5期20卷 397-404页

作者： HU Qing HUANG Zhisheng GU Jinguang College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Department of Computer Science Vrije University Amsterdam

Semantic representation of evidence-based medical guidelines provides the support for the data inter-operability and has been found many applications in the medical domain. In this paper, we describe a semantic representation approach of evidence-based medical guidelines, which is based on the Semantic Web technology standards. We discuss several use cases of that semantic representation of evidence-based medical guideline, and show that they are potentially useful for medical applications.

关键词： evidence-based medical guidelines semantic repre- sentation semantic technology use cases

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