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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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Establishing a new testing protocol of the electrochemical stability window for electric double-layer capacitors

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Science China Chemistry 2025年第01期 217-225页

作者： Ruilin Hou Xiaoxi Zhao Tingting Liang Qingyun Dou Shan Xu Xingbin Yan School of Materials Science and engineering Sun Yat-sen University Laboratory of Clean Energy Chemistry and Materials Lanzhou Institute of Chemical Physics Chinese Academy of Sciences College of engineering and Applied sciences Nanjing University Center of industrial Analysis and Testing Guangdong Academy of Science

The electrochemical stability window(ESW) is crucial for determining the energy density of electric double-layer capacitors(EDLCs). However, current ESW testing protocols of EDLCs are strongly affected by artificial factors, thereby leading to unreliable result. To solve this problem, we first identify the key shortcomings of the traditional protocols by analyzing their test principles. Subsequently, taking an aqueous carbon-based EDLC as an example, we design a side reaction descriptor to represent the response difference in the charging capacitance to side reactions between the cyclic voltammetry and galvanostatic chargedischarge methods. With the aid of this descriptor, we propose a new ESW testing protocol, which is not only able to completely avoid the adverse influence of subjective factors but also fully consider the operating condition limitations. The protocol can be extended from the single electrode to the full device. This work proposes a more rigorous definition of ESW and provides a reliable protocol for evaluating the ESW of EDLCs.

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Magnetron sputtered nickel oxide with suppressed interfacial defect states for efficient inverted perovskite solar cells

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Journal of Energy Chemistry 2025年第1期100卷 348-355页

作者： Guoqiang Ma Qin Tan Zhaoning Li Jingwei Xiu Jiafeng Wang Tianle Cheng Dong He Qiang Sun Xuhang Ma Francesco Lamberti Zhubing He Department of Materials Science and engineering Institute of Innovative Materials (I2M) Shenzhen Key Laboratory of Full Spectral Solar Electricity Generation (FSSEG)Southern University of Science and Technology (SUSTech) Core Research Facilities Southern University of Science and Technology Department of Chemical sciences Department of Industrial Engineering University of Padova

Widely used spin-coated nickle oxide （NiOx） based perovskite solar cells often suffer from severe interfacial reactions between the NiOxand adjacent perovskite layers due to surface defect states,which inherently impair device performance in a long-term view,even with surface molecule *** this study,we developed high-quality magnetron-sputtered NiOxthin films through detailed process optimization,and compared systematically sputtered and spin-coated NiOxthin film surfaces from materials to *** sputtered NiOxfilms exhibit improved crystallinity,smoother surfaces,and significantly reduced Ni3+or Ni vacancies compared to their spin-coated ***,the interface between the perovskite and sputtered NiOxfilm shows a substantially reduced density of defect *** solar cells （PSCs） fabricated with our optimally sputtered NiOxfilms achieved a high power conversion efficiency （PCE） of up to 19.93%and demonstrated enhanced stability,maintaining 86.2% efficiency during 500 h of maximum power point tracking under one standard sun ***,with the surface modification using (4-(2,7-dibromo-9,9-dimethylacridin-10（9H）-yl)butyl)p hosphonic acid （DMAcPA）,the device PCE was further promoted to 23.07%,which is the highest value reported for sputtered NiOxbased PSCs so far.

关键词： Nickle oxide Magnetron sputter Defect Stability Perovskite solar cell

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Brain age estimation:premise,promise,and problems

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Neural Regeneration Research 2025年第8期20卷 2313-2314页

作者： Jarrad Perron Ji Hyun Ko Graduate Program in Biomedical engineering Price Faculty of EngineeringUniversity of ManitobaWinnipegMBCanada PrairieNeuro Research Centre Kleysen Institute for Advanced MedicineHealth Sciences CentreWinnipegMBCanada Department of Human Anatomy and Cell Science Rady Faculty of Health SciencesUniversity of ManitobaWinnipegMBCanada

Premise:The com bined effects of modern healthcare practices which prolong lifespan and declining birthrates have created unprecedented changes in age demographics worldwide that are especially pronounced in Japan,South Korea,Europe,and North *** old age is the most significant predictor of dementia,global healthcare systems must rise to the challenge of providing care for those with neurodegenerative disorders.

关键词： estimation providing birth

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MARIE:One-Stage Object Detection Mechanism for Real-Time Identifying of Firearms

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Computer Modeling in engineering & sciences 2025年第1期142卷 279-298页

作者： Diana Abi-Nader Hassan Harb Ali Jaber Ali Mansour Christophe Osswald Nour Mostafa Chamseddine Zaki Computer Science Department Faculty of SciencesLebanese UniversityBeirut146404Lebanon College of engineering and Technology American University of the Middle EastEgaila54200Kuwait Lab-STICC CNRS UMR 6285ENSTA-BretagneBrest29200France

Security and safety remain paramount concerns for both governments and individuals *** today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable to ***,there is a pressing need for swift identification of potential threats to preemptively alert law enforcement and security forces,thereby preventing potential attacks or violent *** advancements in big data analytics and deep learning have significantly enhanced the capabilities of computer vision in object detection,particularly in identifying *** paper introduces a novel automatic firearm detection surveillance system,utilizing a one-stage detection approach named MARIE(Mechanism for Realtime Identification of Firearms).MARIE incorporates the Single Shot Multibox Detector(SSD)model,which has been specifically optimized to balance the speed-accuracy trade-off critical in firearm detection *** SSD model was further refined by integrating MobileNetV2 and InceptionV2 architectures for superior feature extraction *** experimental results demonstrate that this modified SSD configuration provides highly satisfactory performance,surpassing existing methods trained on the same dataset in terms of the critical speedaccuracy *** these innovations,MARIE sets a new standard in surveillance technology,offering a robust solution to enhance public safety effectively.

关键词： Firearm and gun detection single shot multi-box detector deep learning one-stage detector MobileNet inception convolutional neural network

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Photobiomodulation:a novel approach to promote trans-differentiation of adipose-derived stem cells into neuronal-like cells

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Neural Regeneration Research 2025年第2期20卷 598-608页

作者： Daniella Da Silva Madeleen Jansen van Rensburg Anine Crous Heidi Abrahamse Laser Research Centre Faculty of Health SciencesUniversity of JohannesburgDoornfonteinJohannesburgSouth Africa

Photobiomodulation,originally used red and near-infrared lasers,can alter cellular *** has been demonstrated that the visible spectrum at 451-540 nm does not necessarily increase cell proliferation,near-infrared light promotes adipose stem cell proliferation and affects adipose stem cell migration,which is necessary for the cells homing to the site of *** this in vitro study,we explored the potential of adipose-derived stem cells to differentiate into neurons for future translational regenerative treatments in neurodegenerative disorders and brain *** investigated the effects of various biological and chemical inducers on trans-differentiation and evaluated the impact of photobiomodulation using 825 nm near-infrared and 525 nm green laser light at 5 J/*** adipose-derived stem cells can be used in autologous grafting and photobiomodulation has been shown to have biostimulatory *** findings reveal that adipose-derived stem cells can indeed trans-differentiate into neuronal cells when exposed to inducers,with pre-induced cells exhibiting higher rates of proliferation and trans-differentiation compared with the control ***,green laser light stimulation led to notable morphological changes indicative of enhanced trans-differentiation,while near-infrared photobiomodulation notably increased the expression of neuronal *** biochemical analysis and enzyme-linked immunosorbent assays,we observed marked improvements in viability,proliferation,membrane permeability,and mitochondrial membrane potential,as well as increased protein levels of neuron-specific enolase and ciliary neurotrophic ***,our results demonstrate the efficacy of photobiomodulation in enhancing the trans-differentiation ability of adipose-derived stem cells,offering promising prospects for their use in regenerative medicine for neurodegenerative disorders and brain injuries.

关键词： differentiation inducers green photobiomodulation immortalized adipose-derived stem cell near-infrared photobiomodulation neurodegenerative disease neurogenesis photobiomodulation trans-differentiation

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Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

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Computer Modeling in engineering & sciences 2025年第1期142卷 467-500页

作者： Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models Duc-Dam Nguyen Nguyen Viet Tiep Quynh-Anh Thi Bui Hiep Van Le Indra Prakash Romulus Costache Manish Pandey Binh Thai Pham faculty of Civil engineering University of Transport TechnologyThanh XuanHa Noi100000Vietnam faculty of Hydraulic engineering Hanoi University of Civil EngineeringHa Noi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India Research Institute of the University of Bucharest Bucharest050663Romania National Institute of Hydrology and Water Management Bucharest013686Romania Department of Civil engineering Transilvania University of BrasovBrasov500152Romania Danube Delta National Institute for Research and Development Tulcea820112Romania Marwadi University Research Center(MURC) Marwadi UniversityRajkotGujaratBharat360003India Department of Civil engineering Faculty of Engineering&TechnologyMarwadi UniversityRajkotGujaratBharat360003India

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and ***,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and *** models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to *** factors were instrumental in predicting the output variable,which was the probability of landslide *** analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other *** AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of *** results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

关键词： Landslide susceptibility map spatial analysis ensemble modelling information values(IV)

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基于中空二氧化锰的多功能纳米平台增强肿瘤化学动力学治疗（英文）

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Science China Materials 2025年第1期 292-302页

作者：葛德洁任德宝段亚敏罗璇何帅霖钦文君王飞印文马立新杨勇张成 State Key Laboratory of Biocatalysis and Enzyme engineering College of Life Sciences Hubei University Hubei Key Laboratory of industrial Biotechnology College of Life Sciences Hubei University College of Health Science and engineering Hubei University School of Materials Science and engineering Hubei University

活性氧是肿瘤化学动力学治疗具有突出效果的关键,但是肿瘤组织缺氧和高浓度谷胱甘肽的微环境阻碍了活性氧的产生.在此,我们构建了透明质酸修饰和过氧单硫酸盐负载的中空二氧化锰纳米颗粒（HA@HMn/PMS）,其不仅可以实现肿瘤微环境响应性...

活性氧是肿瘤化学动力学治疗具有突出效果的关键,但是肿瘤组织缺氧和高浓度谷胱甘肽的微环境阻碍了活性氧的产生.在此,我们构建了透明质酸修饰和过氧单硫酸盐负载的中空二氧化锰纳米颗粒（HA@HMn/PMS）,其不仅可以实现肿瘤微环境响应性药物释放,而且还可作为活性氧供体来增强肿瘤化学动力学疗效. HA@HMn/PMS在肿瘤部位富集后,消耗局部谷胱甘肽并将二氧化锰还原为二价锰离子,然后通过类芬顿反应和催化过氧单硫酸盐分别生成·OH和·SO4-自由基.·SO4-是一种罕见的自由基,具有优异的氧化能力和非氧依赖特性,它的产生和作用打破了传统活性氧的局限性,并且可以对肿瘤细胞造成严重的损伤.在异植瘤小鼠模型中,研究表明HA@HMn/PMS能够显著抑制小鼠肿瘤生长.本研究通过结合谷胱甘肽的消耗和多种自由基在肿瘤治疗中的协同作用,激发了化学动力学治疗在多功能纳米系统应用方向的潜力.

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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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A promising approach for quantifying focal stroke modeling and assessing stroke progression:optical resolution photoacoustic microscopy photothrombosis

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Neural Regeneration Research 2025年第7期20卷 2029-2037页

作者： Xiao Liang Xingping Quan Xiaorui Geng Yujing Huang Yonghua Zhao Lei Xi Zhen Yuan Ping Wang Bin Liu faculty of Health sciences University of MacaoMacao Special Administrative RegionChina Center for Cognitive and Brain sciences University of MacaoMacao Special Administrative RegionChina Department of Biomedical engineering Southern University of Science and TechnologyShenzhenGuangdong ProvinceChina State Key Laboratory of Quality Research in Chinese Medicine Institute of Chinese Medical SciencesUniversity of MacaoTaipaMacao Special Administrative RegionChina Department of Emergency Zhujiang HospitalSouthern Medical UniversityGuangzhouGuangdong ProvinceChina

To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral ***,these methods often require complex systems and the effect of age on cerebral embolism has not been adequately studied,although ischemic stroke is strongly *** this study,we propose an optical-resolution photoacoustic microscopy-based visualized photothrombosis methodology to create and monitor ischemic stroke in mice simultaneously using a 532 nm pulsed *** observed the molding process in mice of different ages and presented age-dependent vascular embolism ***,we integrated optical coherence tomography angiography to investigate age-associated trends in cerebrovascular variability following a *** imaging data and quantitative analyses underscore the differential cerebrovascular responses to stroke in mice of different ages,thereby highlighting the technique's potential for evaluating cerebrovascular health and unraveling age-related mechanisms involved in ischemic strokes.

关键词： age-dependent cerebral cortex ischemic stroke mouse model optical coherence tomography angiography photoacoustic microscopy photothrombosis vascular imaging

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