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15th International Workshop on Computational Diffusion MRI, CDMRI 2024, held in conjunction with 27th International Conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2024

作者： Xiao, Taohui Cheng, Jian Fan, Wenxin Yang, Jing Li, Cheng Dong, Enqing Wang, Shanshan School of Mechanical Electrical and Information Engineering Shandong University Weihai264209 China State Key Laboratory of Software Development Environment Beihang University Beijing China Key Laboratory of Data Science and Intelligent Computing Institute of International Innovation Beihang University Zhejiang Hangzhou China Paul C. Lauterbur Research Center for Biomedical Imaging Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China Peng Cheng Laboratory Guangdong Shenzhen China

ISBN: (纸本)9783031869198

Neurite Orientation Dispersion and Density Imaging (NODDI) is an important imaging technology used to evaluate the microstructure of brain tissue, which is of great significance for the discovery and treatment of various neurological diseases. Current deep learning-based methods perform parameter estimation through diffusion magnetic resonance imaging (dMRI) with a small number of diffusion gradients. These methods speed up parameter estimation and improve accuracy. However, the diffusion directions used by most existing deep learning models during testing needs to be strictly consistent with the diffusion directions during training. This results in poor generalization and robustness of deep learning models in dMRI parameter estimation. In this work, we first verify that the parameter estimation performance of current mainstream methods will significantly decrease when the testing diffusion directions and the training diffusion directions are inconsistent. A robust NODDI parameter estimation method with adaptive sampling under continuous representation (RobNODDI) is proposed. Furthermore, long short-term memory (LSTM) units and fully connected layers are selected to learn continuous representation signals. To this end, we use a total of 100 subjects to conduct experiments based on the Human Connectome Project (HCP) dataset, of which 60 are used for training, 20 are used for validation, and 20 are used for testing. The test results indicate that RobNODDI improves the generalization performance and robustness of the deep learning model, enhancing the stability and flexibility of deep learning NODDI parameter estimatimation applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep learning

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Solid-state stepwise temperature-programmable synthesis of bioinspired Fe-N-C oxygen reduction electrocatalyst featuring Fe-N_(5)configuration

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Nano Research 2025年第3期18卷 654-665页

作者： Wei Sang Somboon Chaemchuen Longyang Zhang Zechen Wang Xingchuan Li Cocoro Andrew Nagasaka Mo Xiong Naoki Ogiwara Cheng Chen Zhao Wang Jian Zhang Francis Verpoort Shichun Mu Zongkui Kou Tingting Wang State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China Department of Basic Science School of Arts and SciencesThe University of TokyoKomabaMeguro-kuTokyo 153-8902Japan MOE Key Laboratory for Non-Equilibrium Synthesis and Modulation of Condensed Matter School of PhysicsXi’an Jiao tong UniversityXi’an 710049China Sanya Science and Education Innovation Park of Wuhan University of Technology Sanya 572000China Department of Chemical Engineering Faculty of EngineeringMahidol UniversityNakhon Pathom 73170Thailand School of Mathematical&Physical Sciences Wuhan Textile UniversityWuhan 430200China Joint Institute of Chemical Research(FFMiEN) Peoples Friendship University of Russia(RUDN University)6 Miklukho-Maklaya Str.117198 MoscowRussia National Research Tomsk Polytechnic University Lenin Avenue 30634050 TomskRussia Hubei Key Laboratory of Ferro &Piezo-electric Materials and DevicesFaculty of Physics and Electronic SciencesHubei UniversityWuhan 430062China School of Chemistry and Chemical Engineering Hainan UniversityHaikou 57022China

The bioinspired Fe-N-C features an asymmetric Fe-N_(5)configuration to produce active metal-oxygen intermediates by introducing axial N ligand into a symmetric Fe-N_(4) structure,enabling highly active oxygen reduction reaction(ORR).However,the artificial creation of active Fe-N_(5)configuration with a direct,facile and green method has been rarely developed yet,as current techniques involve complex processes and costly ***,we advance a novel solid-state stepwise temperature-programmable(SST)route to directly produce bioinspired Fe-N_(5)-*** then demonstrate that such a Fe-N_(5)-C exhibits a quite higher half-wave potential(0.92 V)with 22-fold faster ORR kinetics(15.6 mA·cm^(−2)@0.85 V)over that of the commercial Pt/C ***,we perform density functional theory(DFT)to find that the Fe is discharged with an extra 0.1 e^(−)through the axially coordinate N ligand,which significantly enhances the ability to activate O_(2) and enables an easier desorption of the crucial intermediate ^(*)OH on the Fe-N_(5)configuration over the conventional Fe-N_(4) structure.

关键词： single atom catalysts Fe-N_(5)coordination solvent-free synthesis oxygen reduction reaction(ORR) metal-air battery

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Extracting embedded messages using adaptive steganography based on optimal syndrome-trellis decoding paths

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Digital Communications and Networks 2022年第4期8卷 455-465页

作者： Jialin Li Xiangyang Luo Yi Zhang Pei Zhang Chunfang Yang Fenlin Liu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000China

Privacy protection is the key to maintaining the Internet of Things(IoT)communication *** is an important way to achieve covert communication that protects user data *** technology is the key to checking steganography security,and its ultimate goal is to extract embedded *** methods cannot extract under known cover *** this end,this paper proposes a method of extracting embedded messages under known cover ***,the syndrome-trellis encoding process is ***,a decoding path in the syndrome trellis is obtained by using the stego sequence and a certain parity-check matrix,while the embedding process is simulated using the cover sequence and parity-check *** the decoding path obtained by the stego sequence and the correct parity-check matrix is optimal and has the least distortion,comparing the path consistency can quickly filter the coding parameters to determine the correct matrices,and embedded messages can be extracted *** proposed method does not need to embed all possible messages for the second time,improving coding parameter recognition *** experimental results show that the proposed method can identify syndrome-trellis coding parameters in stego images embedded by adaptive steganography quickly to realize embedded message extraction.

关键词： Information security Image steganography STC coding Parameter recognition

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Cooperative computing Techniques for a Deeply Fused and Heterogeneous Many-Core Processor Architecture

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Journal of Computer Science & Technology 2015年第1期30卷 145-162页

作者：郑方李宏亮吕晖过锋许晓红谢向辉 State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125 China

Due to advances in semiconductor techniques, many-core processors have been widely used in high performance computing. However, many applications still cannot be carried out efficiently due to the memory wall, which has become a bottleneck in many-core processors. In this paper, we present a novel heterogeneous many-core processor architecture named deeply fused many-core （DFMC） for high performance computing systems. DFMC integrates management processing ele- ments （MPEs） and computing processing elements （CPEs）, which are heterogeneous processor cores for different application features with a unified ISA （instruction set architecture）, a unified execution model, and share-memory that supports cache coherence. The DFMC processor can alleviate the memory wall problem by combining a series of cooperative computing techniques of CPEs, such as multi-pattern data stream transfer, efficient register-level communication mechanism, and fast hardware synchronization technique. These techniques are able to improve on-chip data reuse and optimize memory access performance. This paper illustrates an implementation of a full system prototype based on FPGA with four MPEs and 256 CPEs. Our experimental results show that the effect of the cooperative computing techniques of CPEs is significant, with DGEMM （double-precision matrix multiplication） achieving an efficiency of 94%, FFT （fast Fourier transform） obtaining a performance of 207 GFLOPS and FDTD （finite-difference time-domain） obtaining a performance of 27 GFLOPS.

关键词： heterogeneous many-core processor data stream transfer register-level communication mechanism hardwaresynchronization technique processor prototype

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Angle-resolved magneto-chiral anisotropy in a non-centrosymmetric atomic layer superlattice

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Science Bulletin 2025年第9期70卷 1406-1409页

作者： Cheng, Long Bao, Mingrui Zhang, Xue Zhang, Jingxian Yang, Qun Li, Qiang Cao, Hui Qiu, Dawei Li, Hui Cheng, Guanglei Zhou, Hua Zuo, Jian-Min Zhou, Xiaodong Shen, Jian Zhu, Zhifeng Wang, Wenbo Zhai, Xiaofang School of Physical Science and Technology ShanghaiTech University Shanghai201210 China CAS Key Laboratory of Microscale Magnetic Resonance and School of Physical Sciences University of Science and Technology of China Hefei230026 China School of Information Science and Technology ShanghaiTech University Shanghai201210 China State Key Laboratory of Surface Physics and Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China X-ray Science Division Advanced Photon Source Argonne National Laboratory LemontIL60439 United States Institutes of Physical Science and Information Technology Anhui University Hefei230601 China Department of Materials Science and Engineering and Materials Research Laboratory University of Illinois Urbana–Champaign UrbanaIL61801 United States ShanghaiTech Laboratory for Topological Physics ShanghaiTech University Shanghai201210 China

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Unraveling the Morphological and Energetic Properties of 2PACz Self-Assembled Monolayers Fabricated With Upscaling Deposition Methods

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Energy & Environmental Materials 2025年第2期8卷 295-308页

作者： Silvia Mariotti Ilhem Nadia Rabehi Congyang Zhang Xiaomin Huo Jiahao Zhang Penghui Ji Tianhao Wu Tongtong Li Shuai Yuan Xiaomin Liu Ting Guo Chenfeng Ding Hengyuan Wang Annalisa Bruno Luis K.Ono Yabing Qi Energy Materials and Surface Sciences Unit (EMSSU) Okinawa Institute of cience and Technology Graduate University (OIST) State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM) Nanjing University of Posts & Telecommunications School of Physical and Mathematical Science & School of Materials Science Engineering & EEnergy Research Institute NTU Nanyang Technological University

Self-assembled monolayers（SAMs） are widely used as hole transport materials in inverted perovskite solar cells,offering low parasitic absorption and suitability for semitransparent and tandem solar *** SAMs have shown to be promising in small-area devices（≤1 cm2）,their application in larger areas has been limited by a lack of knowledge regarding alternative deposition methods beyond the common spin-coating ***,we compare spin-coating and upscalable methods such as thermal evaporation and spray-coating for [2-（9H-carbazol-9-yl）ethyl]phosphonic acid（2PACz）,one of the most common carbazole-based *** impact of these deposition methods on the device performance is investigated,revealing that the spray-coating technique yields higher device ***,our work provides guidelines for the deposition of SAM materials for the fabrication of perovskite solar *** addition,we provide an extensive characterization of 2PACz films focusing on thermal evaporation and spray-coating methods,which allow for thicker 2PACz *** is found that the optimal 2PACz deposition conditions corresponding to the highest device performances do not always correlate with the monolayer characteristics.

关键词： 2PACz Evaporation Perovskite solar cells Self-assembled monolayer Spray-coating

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Cryptanalysis of full PRIDE block cipher

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Science China(Information Sciences) 2017年第5期60卷 169-180页

作者： Yibin DAI Shaozhen CHEN State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Information Science and Technology Institute

PRIDE is a lightweight block cipher proposed at CRYPTO 2014 by Albrecht et al., who claimed that the construction of linear layers is efficient and secure. In this paper, we investigate the key schedule and find eight 2-round iterative related-key differential characteristics, which can be used to construct 18-round related-key differentials. A study of the first subkey derivation function reveals that there exist three weak-key classes, as a result of which all the differences of subkeys for each round are identical. For the weak-key classes,we also find eight 2-round iterative related-key differential characteristics. Based on one of the related-key differentials, we launch an attack on the full PRIDE block cipher. The data and time complexity are 2;chosen plaintexts and 2;encryptions, respectively. Moreover, by using multiple related-key differentials, we improve the cryptanalysis, which then requires 2;chosen plaintexts and 2;encryptions, respectively. Finally, we use two 17-round related-key differentials to analyze full PRIDE, which requires 2;plaintexts and 2;*** are the first results on full PRIDE, and show that the PRIDE block cipher is not secure against related-key differential attack.

关键词： cryptanalysis block cipher PRIDE iterative characteristics related-key differential

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Stego key searching for LSB steganography on JPEG decompressed image

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Science China(Information Sciences) 2016年第3期59卷 60-74页

作者： Jiufen LIU Yuguo TIAN Tao HAN Junchao WANG Xiangyang LUO Zhengzhou Information Science and Technology Institute State Key Laboratory of Mathematical Engineering and Advanced Computing

At present, steganalysis research focuses on detecting the existence of a hidden message. However,extracting the hidden information, i.e., an extracting attack, is crucial in obtaining effective evidence in computer forensics. Due to the difficulty of an extracting attack, research in this field is limited. In steganography with a stego key, an extracting attack is equivalent to recovering the stego key. In this paper we study a method for recovering the stego key in least significant bit(LSB) steganography with a decompressed JPEG image as the cover image. Firstly, the recovery of the stego key is translated into a cryptanalysis problem for a sequential cipher. The method for recovering the stego key is based on estimating the modification positions. The minimum size of the data used to recover the stego key successfully is discussed. Secondly, when a decompressed JPEG image is used as the cover image, the probability of recovering the cover pixels using recompression is *** is used to compute the error of the estimated sequence. Finally, an algorithm to recover the stego key in LSB steganography with a decompressed JPEG image as the cover image is proposed. The experimental results for the steganographic software, Hide and Seek 4.1 and its variant, which is a typical representative of LSB steganography, show that the proposed method can successfully recover the stego key in LSB replacement and LSB matching, i.e., the extracting attack is successful, and it outperforms three previous methods in terms of computational complexity.

关键词： steganalysis extracting attack LSB steganography decompressed JPEG image recompression stego key

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Software Vulnerability Mining and Analysis Based on Deep Learning

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Computers, Materials & Continua 2024年第8期80卷 3263-3287页

作者： Shibin Zhao Junhu Zhu Jianshan Peng State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China

In recent years,the rapid development of computer software has led to numerous security problems,particularly software *** flaws can cause significant harm to users’privacy and *** security defect detection technology relies on manual or professional reasoning,leading to missed detection and high false detection *** intelligence technology has led to the development of neural network models based on machine learning or deep learning to intelligently mine holes,reducing missed alarms and false ***,this project aims to study Java source code defect detection methods for defects like null pointer reference exception,XSS(Transform),and Structured Query Language(SQL)***,the project uses open-source Javalang to translate the Java source code,conducts a deep search on the AST to obtain the empty syntax feature library,and converts the Java source code into a dependency *** feature vector is then used as the learning target for the neural *** types of Convolutional Neural Networks(CNN),Long Short-Term Memory(LSTM),Bi-directional Long Short-Term Memory(BiLSTM),and Attention Mechanism+Bidirectional LSTM,are used to investigate various code defects,including blank pointer reference exception,XSS,and SQL injection *** results show that the attention mechanism in two-dimensional BLSTM is the most effective for object recognition,verifying the correctness of the method.

关键词： Vulnerability mining software security deep learning static analysis

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An efficient quantum meet-in-the-middle attack against NTRU-2005

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Chinese Science Bulletin 2013年第28期58卷 3514-3518页

作者： WANG Hong MA Zhi MA ChuanGui State Key Laboratory of Mathematical Engineering and Advanced Computing

NTRU is one of the most widely used public-key cryptosystems and its security has been an active research *** paper proposes a new way to find NTRU-2005 private *** algorithm is based on meet-in-the-middle attack and a quantum algorithm for searching the fixed weight *** with the current classical and quantum meet-in-the-middle attacks,our algorithm has lower time and space ***,this attack can also be applied against different versions of *** result can help to understand the security of NTRU better.

关键词：中间人攻击量子算法 NTRU 空间复杂度公钥密码安全性私钥搜索

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