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Interpretable machine learning for chiral induced symmetry breaking of spin density boosting hydrogen evolution

Journal of Energy Chemistry 2025年第4期103卷 68-78页

作者： Xin Song Zhonghua Li Li Sheng Yang Liu School of Chemistry and Chemical Engineering Key Laboratory of Microsystems and Microstructures ManufacturingMinistry of EducationHarbin Institute of TechnologyHarbin 150001HeilongjiangChina School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001HeilongjiangChina

The integration of machine learning and electrocatalysis presents nota ble advancements in designing and predicting the performance of chiral materials for hydrogen evolution reactions(HER).This study utilizes theoretical calculations and machine learning techniques to assess the HER performance of both chiral and achiral M-N-SWCNTs(M=In,Bi,and Sb)single-atom catalysts(SACs).The stability preferences of metal atoms are dependent on chirality when interacting with chiral *** HER activity of the right-handed In-N-SWCNT is 5.71 times greater than its achiral counterpart,whereas the left-handed In-N-SWCNT exhibits a 5.12-fold *** calculated hydrogen adsorption free energy for the right-handed In-N-SWCNT reaches as low as-0.02 *** enhancement is attributed to the symmetry breaking in spin density distribution,transitioning from C_(2V)in achiral SACs to C_(2)in chiral SACs,which facilitates active site transfer and enhances local spin ***-handed M-N-SWCNTs exhibit superiorα-electron separation and transport efficiency relative to left-handed variants,owing to the chiral induced spin selectivity(CISS)effect,with spin-upα-electron density reaching 3.43×10^(-3)e/Bohr^(3)at active *** learning provides deeper insights,revealing that the interplay of weak spatial electronic effects and appropriate curvature-chirality effects significantly enhances HER performance.A weaker spatial electronic effect correlates with higher HER activity,larger exchange current density,and higher turnover *** curvature-chirality effect undersco res the influence of intrinsic structures on HER *** findings offer critical insights into the role of chirality in electrocatalysis and propose innovative approaches for optimizing HER through chirality.

关键词： Symmetry breaking Machine learning Spin density CISS DFT Hydrogen evolution reaction

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Enhancing isomorphism between word embedding spaces for distant languages bilingual lexicon induction

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Neural Computing and Applications 2024年第24期36卷 15091-15102页

作者： Ding, Qiuyu Cao, Hailong Feng, Zihao Zhao, Tiejun School of Computer Science and Technology Harbin Institute of Technology Heilongjiang Harbin150001 China

Most of the bilingual lexicon induction (BLI) models learn a mapping function that can transfer word embedding (WE) spaces from one language to another. This usually relies on the isomorphism hypothesis, which posits that words in different languages share the same structures and relationships (i.e. similar in geometric structure). However, WE’s isomorphism weakens substantially in distant language pairs, resulting in low accuracy of BLI. To address this problem, we propose a novel BLI method incorporating synonymous knowledge. The main idea is to stabilize the distance between words to optimize the monolingual WE space, yielding higher isomorphism. Specifically, we first induce monolingual synonym pairs from Wordnet and construct monolingual synonym lexicons. We then generate pseudo-sentences by substituting words in the training corpus with synonyms. Finally, the original sentences and pseudo-sentences are jointly used to generate monolingual WEs, enabling the word vectors of synonyms to be closer naturally. Comprehensive experiments on standard BLI datasets in diverse distant languages demonstrate that our method significantly outperforms the strong BLI systems in word translation. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Embeddings

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Offline/online attribute-based searchable encryption scheme from ideal lattices for IoT

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Frontiers of computer science 2024年第3期18卷 239-241页

作者： Yang YANG Guoyin ZHANG Sizhao LI Zechao LIU College of Computer Science and Technology Harbin Engineering UniversityHarbin 150001China

1 Introduction The Internet of Things(IoT)has facilitated the development of numerous fields in our ***,some equipment in IoT environment lacks sufficient storage and data processing capabilities[1].A feasible strateg... 详细信息

关键词： IoT encryption scheme

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A Local Differential Privacy Trajectory Protection Method Based on Temporal and Spatial Restrictions for Staying Detection

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Tsinghua science and technology 2024年第2期29卷 617-633页

作者： Weiqi Zhang Zhenzhen Xie Akshita Maradapu Vera Venkata Sai Qasim Zia Zaobo He Guisheng Yin College of Computer Science and Technology Harbin Engineering UniversityHarbin 150001China School of Computer Science and Technology Shandong UniversityQingdao 266237China Department of Computer Science Georgia State UniversityAtlantaGA 30303USA College of Information Science and Technology Jinan UniversityGuangzhou 510632China

The widespread availability of GPS has opened up a whole new market that provides a plethora of location-based ***-based social networks have become very popular as they provide end users like us with several such services utilizing GPS through our ***,when users utilize these services,they inevitably expose personal information such as their ID and sensitive location to the *** to untrustworthy servers and malicious attackers with colossal background knowledge,users'personal information is at risk on these ***,many privacy-preserving solutions for protecting trajectories have significantly decreased utility after *** have come up with a new trajectory privacy protection solution that contraposes the area of interest for ***,Staying Points Detection Method based on Temporal-Spatial Restrictions(SPDM-TSR)is an interest area mining method based on temporal-spatial restrictions,which can clearly distinguish between staying and moving ***,our privacy protection mechanism focuses on the user's areas of interest rather than the entire ***,our proposed mechanism does not rely on third-party service providers and the attackers'background knowledge *** test our models on real datasets,and the results indicate that our proposed algorithm can provide a high standard privacy guarantee as well as data availability.

关键词： local-differential privacy stay points detection trajectory data areas of interest temporal-spatial clustering

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Multi-Scale Spiking Pyramid Wireless Communication Framework for Food Recognition

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IEEE Transactions on Multimedia 2025年 27卷 2734-2746页

作者： Li, Wenrui Li, Jiahui Ma, Mengyao Hong, Xiaopeng Fan, Xiaopeng Harbin Institute of Technology Department of Computer Science and Technology Harbin150001 China Wireless Technology Lab Shenzhen518129 China

Food recognition applications in human health have recently garnered significant attention in the field of computer vision. With the advancement of mobile devices, robust food recognition in wireless communication has become a practical and challenging application scenario. We propose a novel Multi-scale Spiking Pyramid Transmission Network (MSPTN) to tackle this challenge. The MSPTN learns diverse and complementary local and global feature maps simultaneously, generating a comprehensive description of food images that capture the correlations of feed-specific features. The feature sender uses a three-layer Spiking Neural Network (SNN). The proposed sender compresses features into sparse and discrete spike trains, significantly reducing the required transmission bandwidth and improving channel utilization and energy efficiency. Our model introduces the Compressed Factorized Bilinear block (CFB), which employs a low-rank feature approximation to reduce computational complexity and feature transmission volume while preserving the discriminate features. The enhancement reasoning module is proposed to enhance the received features by projecting them into a higher-dimensional space and utilizing the self-attention mechanism and sum pooling to compress them back to the original dimension. We conduct extensive experiments on the ETH Food-101 and Food2k datasets. Our results reveal that the MSPTN demonstrates state-of-the-art recognition performance, even with binary spike trains. Meanwhile, the MSPTN also exhibits remarkable robustness in wireless communication scenarios. With the combination of CFB, SNN, and EFB, our model achieves significant efficiency gains, including a nearly nine-fold decrease in feature transmission volume and a three-fold improvement in runtime & computational memory speed. © 1999-2012 IEEE.

关键词： Bandwidth

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RNN based EPON dynamic bandwidth allocation algorithm for complex network

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Journal of Optical Communications 2024年第3期45卷 555-562页

作者： Yu, Jinxia Fu, Yanyan Xiao, Fan Jia, Huijuan Qin, Panke Zhao, Zongqu You, Junru Liu, Feiyang Han, Shangya Wang, Jiawei College of Computer Science and Technology Henan Polytechnic University Jiaozuo454000 China College of Computer Science and Technology Harbin Engineering University Harbin150001 China College of Computer Science and Technology Jilin University Changchun130012 China

In the development of ethernet passive optical networks (EPONs), quality of service (QoS) support and fairness per optical network unit (ONU) are crucial issues. However, making an elaborate analysis of the existing prediction-based bandwidth allocation algorithm, light load penalty, low prediction precision are pointed out. We present an improved dynamic bandwidth pre-allocation algorithm (R-DBA), which employs recurrent neural network (RNN) to predict the high-priority service traffic in EPON. And we introduce mixed integer linear programming (MILP) for optimally building DBA algorithm. This algorithm achieves the prediction of the high-priority service traffic by RNN during the waiting time and supports bandwidth pre-allocation, thus ensuring the fairness of the bandwidth allocation. © 2022 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Complex networks

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Modified filter for mean elements estimation with state jumping

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Journal of Systems Engineering and Electronics 2024年第4期35卷 999-1012页

作者： YU Yanjun YUE Chengfei LI Huayi WU Yunhua CHEN Xueqin Research Center of Satellite Technology Harbin Institute of TechnologyHarbin 150001China Institute of Space Science and Applied Technology Harbin Institute of Technology(Shenzhen)Shenzhen 518055China College of Astronautics Nanjing University of Aeronautics and AstronauticsNanjing 211106China

To investigate the real-time mean orbital elements(MOEs)estimation problem under the influence of state jumping caused by non-fatal spacecraft collision or protective orbit trans-fer,a modified augmented square-root unscented Kalman filter(MASUKF)is *** MASUKF is composed of sigma points calculation,time update,modified state jumping detec-tion,and measurement *** with the filters used in the existing literature on MOEs estimation,it has three main ***,the state vector is augmented from six to nine by the added thrust acceleration terms,which makes the fil-ter additionally give the state-jumping-thrust-acceleration ***,the normalized innovation is used for state jumping detection to set detection threshold concisely and make the filter detect various state jumping with low ***,when sate jumping is detected,the covariance matrix inflation will be done,and then an extra time update process will be con-ducted at this time instance before measurement *** this way,the relatively large estimation error at the detection moment can significantly ***,typical simulations are per-formed to illustrated the effectiveness of the method.

关键词： unscented Kalman filter mean orbital elements(MOEs)estimation state jumping detection nonlinear system

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SCancerRNA:Expression at the Single-cell Level and Interaction Resource of Non-coding RNA Biomarkers for Cancers

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Genomics, Proteomics & Bioinformatics 2024年第3期22卷 125-131页

作者： Hongzhe Guo Liyuan Zhang Xinran Cui Liang Cheng Tianyi Zhao Yadong Wang Faculty of Computing Harbin Institute of TechnologyHarbin 150001China College of Bioinformatics Science and Technology Harbin Medical UniversityHarbin 150001China School of Medicine and Health Harbin Institute of TechnologyHarbin 150001China

Non-coding RNAs(ncRNAs)participate in multiple biological processes associated with cancers as tumor suppressors or oncogenic *** to their high stability in plasma,urine,and many other fluids,ncRNAs have the potential to serve as key biomarkers for early diagnosis and screening of *** cancer progression,tumor heterogeneity plays a crucial role,and it is particularly important to understand the gene expression patterns of individual *** the development of single-cell RNA sequencing(scRNA-seq)technologies,uncovering gene expression in different cell types for human cancers has become feasible by profiling transcriptomes at the cellular ***,a well-organized and comprehensive online resource that provides access to the expression of genes corresponding to ncRNA biomarkers in different cell types at the single-cell level is not available ***,we developed the SCancerRNA database to summarize experimentally supported data on long ncRNA,microRNA,PIWI-interacting RNA,small nucleolar RNA,and circular RNA biomarkers,as well as data on their differential expression at the cellular ***,we collected biological functions and clinical applications of biomarkers to facilitate the application of ncRNA biomarkers to cancer diagnosis,as well as the monitoring of progression and targeted *** also allows users to explore interaction networks of different types of ncRNAs,and build computational models in the *** is freely accessible at http://***/BioMarker.

关键词： Non-coding RNA Biomarker Cancer Single cell Interaction network

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Content-Aware Dynamic In-loop Filter with Adjustable Complexity for VVC Intra Coding

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IEEE Transactions on Circuits and Systems for Video technology 2025年第6期35卷 6114-6128页

作者： Man, Hengyu Wang, Hao Lu, Riyu Wan, Zhaolin Fan, Xiaopeng Zhao, Debin Harbin Institute of Technology Department of Computer Science and Technology Harbin150001 China City University of Hong Kong Department of Computer Science 999077 Hong Kong

Recently, neural network-based in-loop filters have been rapidly developed, effectively improving the reconstruction quality and compression efficiency in video coding. Existing deep in-loop filters typically employed networks with fixed structures to process all image blocks. However, under various bitrate conditions, compressed image blocks with different textures exhibit varying degradations, which poses a challenge for high-quality and low-complexity filtering. Additionally, different complexity requirements for coding tools in various scenarios limit the versatility of fixed models. To address these problems, a content-aware dynamic in-loop filter (dubbed DILF) with adjustable complexity is proposed in this paper. Specifically, DILF comprises a policy network and a filtering network. For each reconstructed image block, the policy network dynamically generates a filtering network topology based on pixel information and the quantization parameter (QP), guiding the filtering network to skip redundant layers and conduct content-aware image enhancement, thereby improving the filtering performance. In addition, by introducing a user-defined balancing factor into the policy network, the content-aware filtering network topology can be further adjusted according to user's requirements, facilitating adjustable complexity with a single model. We integrate DILF into Versatile Video Coding (VVC) to replace the built-in deblocking filter. Extensive experiments demonstrate the efficiency of DILF in processing image blocks with varying degrees of degradation and its flexibility in controlling complexity. When the balancing factor is set to 2e-5, DILF achieves bitrate savings of 8.07%, 17.97%, and 20.93% on average for YUV components over VVC reference software VTM-11.0 under all-intra configuration. Compared to static networks with fixed structures, DILF demonstrates superior performance and lower computational complexity. © 1991-2012 IEEE.

关键词： Image coding

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Indoor Uncertain Semantic Trajectory Similarity Join

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Journal of computer science & technology 2024年第6期39卷 1441-1465页

作者： Hong-Bo Yin Dong-Hua Yang Kai-Qi Zhang Hong Gao Jian-Zhong Li Faculty of Computing Harbin Institute of TechnologyHarbin 150001China Center of Analysis Measurement and ComputingHarbin Institute of TechnologyHarbin 150001China Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

With the widespread deployment of indoor positioning systems, an unprecedented scale of indoor trajectories is being produced. By considering the inherent uncertainties and the text information contained in such an indoor trajectory, a new definition named Indoor Uncertain Semantic Trajectory is defined in this paper. In this paper, we focus on a new primitive, yet quite essential query named Indoor Uncertain Semantic Trajectory Similarity Join (IUST-Join for short), which is to match all similar pairs of indoor uncertain semantic trajectories from two sets. IUST-Join targets a number of essential indoor applications. With these applications in mind, we provide a purposeful definition of an indoor uncertain semantic trajectory similarity metric named IUS. To process IUST-Join more efficiently, both an inverted index on indoor uncertain semantic trajectories named 3IST and the first acceleration strategy are proposed to form a filtering-and-verification framework, where most invalid pairs of indoor uncertain semantic trajectories are pruned at quite low computation cost. And based on this filtering-and-verification framework, we present a highly-efficient algorithm named Indoor Uncertain Semantic Trajectory Similarity Join Processing (USP for short). In addition, lots of novel and effective acceleration strategies are proposed and embedded in the USP algorithm. Thanks to these techniques, both the time complexity and the time overhead of the USP algorithm are further reduced. The results of extensive experiments demonstrate the superior performance of the proposed work.

关键词： filtering-and-verification framework indoor uncertain semantic trajectory inverted index trajectory similarity join

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