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Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

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Computer Modeling in Engineering & sciences 2025年第1期142卷 579-607页

作者： Pongsakon Promsawat Weerapan Sae-dan Marisa Kaewsuwan Weerawat Sudsutad Aphirak Aphithana department of Civil Engineering Faculty of EngineeringRamkhamkaeng UniversityBangkok10240Thailand department of Computer Engineering Faculty of EngineeringRamkhamkaeng UniversityBangkok10240Thailand department of Statistics Faculty of ScienceRamkhamkaeng UniversityBangkok10240Thailand

The ability to accurately predict urban traffic flows is crucial for optimising city ***,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility *** learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal ***,these models often become overly complex due to the large number of hyper-parameters *** this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction *** comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest *** the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 ***,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer *** Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time *** numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

关键词： Graph neural networks convolutional neural network deep learning dynamic multi-graph spatio-temporal

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Privacy-preserving explainable AI: a survey

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science China(Information sciences) 2025年第1期68卷 23-56页

作者： Thanh Tam NGUYEN Thanh Trung HUYNH Zhao REN Thanh Toan NGUYEN Phi Le NGUYEN Hongzhi YIN Quoc Viet Hung NGUYEN School of Information and Communication Technology Griffith University School of Computer and Communication sciences Ecole Polytechnique Federale de Lausanne faculty of Mathematics and Computer science University of Bremen faculty of Information Technology HUTECH University department of Computer science Hanoi University of Science and Technology School of Electrical Engineering and Computer science The University of Queensland

As the adoption of explainable AI(XAI) continues to expand, the urgency to address its privacy implications intensifies. Despite a growing corpus of research in AI privacy and explainability, there is little attention on privacy-preserving model explanations. This article presents the first thorough survey about privacy attacks on model explanations and their countermeasures. Our contribution to this field comprises a thorough analysis of research papers with a connected taxonomy that facilitates the categorization of privacy attacks and countermeasures based on the targeted explanations. This work also includes an initial investigation into the causes of privacy leaks. Finally, we discuss unresolved issues and prospective research directions uncovered in our analysis. This survey aims to be a valuable resource for the research community and offers clear insights for those new to this domain. To support ongoing research, we have established an online resource repository, which will be continuously updated with new and relevant findings.

关键词： privacy-preserving explainable AI privacy attacks privacy defences PrivEx PPXAI

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Hybrid Deep Learning Approach for Automating App Review Classification:Advancing Usability Metrics Classification with an Aspect-Based Sentiment Analysis Framework

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Computers, Materials & Continua 2025年第1期82卷 949-976页

作者： Nahed Alsaleh Reem Alnanih Nahed Alowidi department of Computer science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia department of Computer science College of Computer Science and EngineeringUniversity of HailHail81451Saudi Arabia

App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their *** the analysis of these reviews is vital for efficient review *** traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior *** research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and *** propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification *** analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,*** contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews *** advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.

关键词： Requirements Engineering(RE) app review analysis usabilitymetrics hybrid deep learning BERT-BiLSTM-CNN

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Genes and proteins expressed at different life cycle stages in the model protist Euplotes vannus revealed by both transcriptomic and proteomic approaches

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science China Life sciences 2025年第1期68卷 232-248页

作者： Yaohan Jiang Xiao Chen Chundi Wang Liping Lyu Saleh A.Al-Farraj Naomi A.Stover Feng Gao Key Laboratory of Evolution & Marine Biodiversity (Ministry of Education) and Institute of Evolution & Marine Biodiversity Ocean University of China Marine College Shandong University zoology department College of ScienceKing Saud University department of Biology Bradley University Laboratory for Marine Biology and Biotechnology Qingdao Marine Science and Technology Center

Sexual reproduction first appeared in unicellular protists and has continued to be an essential biological process in almost all *** protists, which contain both germline and somatic genomes within a single cell, have evolved a special form of sexual reproduction called conjugation that involves mitosis, meiosis, fertilization, nuclear differentiation, genome rearrangement, and the development of unique cellular structures. The molecular basis and mechanisms of conjugation vary dramatically among ciliates, and many details of the process and its regulation are still largely unknown. In order to better comprehend these processes and mechanisms from an evolutionary perspective, this study provides the first comprehensive overview of the transcriptome and proteome profiles during the entire life cycle of the newly-established marine model ciliate Euplotes vannus. Transcriptome analyses from 14 life cycle stages(three vegetative stages and 11 sexual stages) revealed over 26,000 genes that are specifically expressed at different stages, many of which are related to DNA replication,transcription, translation, mitosis, meiosis, nuclear differentiation, and/or genome rearrangement. Quantitative proteomic analyses identified 338 proteins with homologs associated with conjugation and/or somatic nuclear development in other ciliates, including dicer-like proteins, Hsp90 proteins, RNA polymerase Ⅱ and transcription elongation factors, ribosomal-associated proteins, and ubiquitin-related proteins. Four of these homologs belong to the PIWI family, each with different expression patterns identified and confirmed by RT-qPCR,which may function in small RNA-mediated genome rearrangement. Proteins involved in the nonhomologous end-joining pathway are induced early during meiosis and accumulate in the developing new somatic nucleus, where more than 80% of the germline sequences are eliminated from the somatic genome. A number of new candidate genes and proteins likely t

关键词： sexual reproduction transcriptomic proteomic genome rearrangement PIWI NHEJ

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Synergistic effect of bonding heterogeneity and phonon localization in introducing excellent thermoelectric properties in layered heteroanionic NdZnSbO material

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Journal of Energy Chemistry 2025年第1期100卷 259-272页

作者： Da Wan Shuwei Tang Shulin Bai Xiaodong Li Peng Ai Wanrong Guo Tuo Zheng College of Materials science and Engineering Liaoning Technical University faculty of Chemistry Northeast Normal University

Layered rare-earth metal oxides, harnessing the dual properties of oxides and two-dimensional layered materials, exhibit remarkable thermal stability and quantum confinement effects. Therefore, this work adopts the first-principles calculation combined with the Boltzmann transport theory to predict the thermoelectric properties of NdZnSbO compound. The coexistence of weak interlayer van der Waals interactions, robust intralayer ionic bonding, and partial covalent bonding leads to remarkable bonding heterogeneity, which engenders pronounced phonon scattering and imposes constraints on thermal transport along the out-of-plane direction. The weakened chemical bonds induced by the antibonding states, together with the rattling-like behavior of the Zn atom, culminate in the profound anharmonicity in the layered NdZnSbO compound. The weakening bond and heavy element contribute to the softness of phonon modes, which significantly diminishes the phonon group velocity. The redistribution-dominated four-phonon scattering process spans a large optical gap, which effectively reduces the lattice thermal conductivity. The NdZnSbO compound exhibits direct semiconductor characteristic with a bandgap of 0.73 e V by adopting the Heyd-Scuseria-Ernzerhof(HSE06) functional in combination with spin–orbit coupling(SOC) effect. The multi-valley feature of NdZnSbO compound augur favorably for band degeneracy, thus amplifying the power factor. Consequently, an optimal figure-of-merit(ZT) of 3.40 at 900 K is achieved for the n-type NdZnSbO compound. The present study delves deeply insights into the origins for the low thermal conductivity of NdZnSbO compound and proposes an optimization scheme to enhance overall thermoelectric performance.

关键词： Bond strength (chemical)

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Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

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Computers, Materials & Continua 2025年第1期82卷 1151-1169页

作者： Khalil Ullah Song Jian Muhammad Naeem Ul Hassan Suliman Khan Mohammad Babar Arshad Ahmad Shafiq Ahmad faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China department of Computer science Abbottabad University of Science and TechnologyHavelianAbbottabad22500Pakistan department of Computing and Electronics Engineering Middle East CollegeMuscat124Oman department of CS&IT Pak-Austria Fachhochschule Institute of Applied Sciences and Technology MangHaripur22621Pakistan Industrial Engineering department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile *** networks are sufficiently scaled to interconnect billions of users and *** in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous *** continuously improves its network functionality to support these *** input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in *** article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial *** technique aims to create long-lasting and secure NextG networks using this extended *** viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this ***,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

关键词： Next generation networks massive mimo communication network artificial intelligence 5G adversarial attacks channel estimation information security

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Navigating the pathways:TAR-DNA-binding-protein-43 aggregation,axonal transport,and local synthesis in amyotrophic lateral sclerosis pathology

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Neural Regeneration Research 2025年第10期20卷 2921-2922页

作者： Ori Bar Avi Eran Perlson department of Physiology and Pharmacology Faculty of Medical&Health ScienceTel-Aviv UniversityTel-AvivIsrael Sagol School of Neuroscience Tel-Aviv UniversityTel-AvivIsrael

Neurons are highly polarized cells with axons reaching over a meter long in adult *** survive and maintain their proper function,neurons depend on specific mechanisms that regulate spatiotemporal signaling and metabolic events,which need to be carried out at the right place,time,and *** mechanisms include axonal transport,local synthesis,and liquid-liquid phase *** and malfunctions in these processes are correlated to neurodegenerative diseases such as amyotrophic lateral sclerosis(ALS).

关键词： synthesis local aggregation

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Role of copper chelating agents: between old applications and new perspectives in neuroscience

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Neural Regeneration Research 2025年第3期20卷 751-762页

作者： Rosalba Leuci Leonardo Brunetti Vincenzo Tufarelli Marco Cerini Marco Paparella Nikola Puvača Luca Piemontese department of Pharmacy-Pharmaceutical science University of Bari Aldo MoroBariItaly department of Precision and Regenerative Medicine and Jonian Area(DiMePRe-J) Section of Veterinary Science and Animal ProductionUniversity of Bari Aldo MoroBariItaly department of Engineering Management in Biotechnology Faculty of Economics and Engineering Management in Novi SadUniversity Business Academy in Novi SadNovi SadSerbia

The role of copper element has been an increasingly relevant topic in recent years in the fields of human and animal health, for both the study of new drugs and innovative food and feed supplements. This metal plays an important role in the central nervous system, where it is associated with glutamatergic signaling, and it is widely involved in inflammatory processes. Thus, diseases involving copper(Ⅱ) dyshomeostasis often have neurological symptoms, as exemplified by Alzheimer's and other diseases(such as Parkinson's and Wilson's diseases). Moreover, imbalanced copper ion concentrations have also been associated with diabetes and certain types of cancer, including glioma. In this paper, we propose a comprehensive overview of recent results that show the importance of these metal ions in several pathologies, mainly Alzheimer's disease, through the lens of the development and use of copper chelators as research compounds and potential therapeutics if included in multi-target hybrid drugs. Seeing how copper homeostasis is important for the well-being of animals as well as humans, we shortly describe the state of the art regarding the effects of copper and its chelators in agriculture, livestock rearing, and aquaculture, as ingredients for the formulation of feed supplements as well as to prevent the effects of pollution on animal productions.

关键词： agriculture Alzheimer's disease chelators copper feed supplements multi-target

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Machine Learning Techniques in Predicting Hot Deformation Behavior of Metallic Materials

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Computer Modeling in Engineering & sciences 2025年第1期142卷 713-732页

作者： Petr Opela Josef Walek Jaromír Kopecek department of Metallurgical Technologies Faculty of Materials Science and TechnologyVSB–Technical University of OstravaOstrava70800Czech Republic FZU—Institute of Physics of the Czech Academy of sciences Prague18200Czech Republic

In engineering practice,it is often necessary to determine functional relationships between dependent and independent *** relationships can be highly nonlinear,and classical regression approaches cannot always provide sufficiently reliable ***,Machine Learning(ML)techniques,which offer advanced regression tools to address complicated engineering issues,have been developed and widely *** study investigates the selected ML techniques to evaluate their suitability for application in the hot deformation behavior of metallic *** ML-based regression methods of Artificial Neural Networks(ANNs),Support Vector Machine(SVM),Decision Tree Regression(DTR),and Gaussian Process Regression(GPR)are applied to mathematically describe hot flow stress curve datasets acquired experimentally for a medium-carbon *** the GPR method has not been used for such a regression task before,the results showed that its performance is the most favorable and practically unrivaled;neither the ANN method nor the other studied ML techniques provide such precise results of the solved regression analysis.

关键词： Machine learning Gaussian process regression artificial neural networks support vector machine hot deformation behavior

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Regeneration mechanisms and therapeutic strategies for neuromuscular junctions in aging and diseases

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Neural Regeneration Research 2025年第1期20卷 193-194页

作者： Masashi Fujitani Abu Md Mamun Tarif Yoshinori Otani department of Anatomy and Neuroscience Faculty of MedicineShimane UniversityShimaneJapan

The neuromuscular junction(NMJ)is an essential synaptic structure composed of motor neurons,skeletal muscles,and glial cells that orchestrate the critical process of muscle contraction(Li et al.,2018).The typical NMJ structure is classically described as having a“pretzel-like”shape in mice(Figure 1),whereas human NMJs have a smaller,fragmented structure throughout *** NMJs exhibit smaller or fragmented endplates,partial denervation,reduced numbers of synaptic vesicles,abnormal presynaptic mitochondria,and dysfunctional perisynaptic Schwann cells(Alhindi et al.,2022).

关键词： aging structure Figure

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