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Transforming Education with Photogrammetry:Creating Realistic 3D Objects for Augmented Reality Applications

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 185-208页

作者： Kaviyaraj Ravichandran Uma Mohan department of Computational Intelligence School of ComputingSRM Institute of Science and TechnologyKattankulathur603203India

Augmented reality(AR)is an emerging dynamic technology that effectively supports education across different *** increased use of mobile devices has an even greater *** the demand for AR applications in education continues to increase,educators actively seek innovative and immersive methods to engage students in ***,exploring these possibilities also entails identifying and overcoming existing barriers to optimal educational ***,this surge in demand has prompted the identification of specific barriers,one of which is three-dimensional(3D)*** 3D objects for augmented reality education applications can be challenging and time-consuming for the *** address this,we have developed a pipeline that creates realistic 3D objects from the two-dimensional(2D)*** for augmented and virtual reality can then utilize these created 3D *** evaluated the proposed pipeline based on the usability of the 3D object and performance ***,with 117 respondents,the co-creation team was surveyed with openended questions to evaluate the precision of the 3D object created by the proposed photogrammetry *** analyzed the survey data using descriptive-analytical methods and found that the proposed pipeline produces 3D models that are positively accurate when compared to real-world objects,with an average mean score above *** study adds new knowledge in creating 3D objects for augmented reality applications by using the photogrammetry technique;finally,it discusses potential problems and future research directions for 3D objects in the education sector.

关键词： Augmented reality education immersive learning 3D object creation photogrammetry and StructureFromMotion

A Support Vector Machine(SVM)Model for Privacy Recommending Data Processing Model(PRDPM)in Internet of Vehicles

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Computers, Materials & Continua 2025年第1期82卷 389-406页

作者： Ali Alqarni department of Computer Science and Artificial Intelligence College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia

Open networks and heterogeneous services in the Internet of Vehicles(IoV)can lead to security and privacy *** key requirement for such systems is the preservation of user privacy,ensuring a seamless experience in driving,navigation,and *** privacy needs are influenced by various factors,such as data collected at different intervals,trip durations,and user *** address this,the paper proposes a Support Vector Machine(SVM)model designed to process large amounts of aggregated data and recommend privacy preserving *** model analyzes data based on user demands and interactions with service providers or neighboring *** aims to minimize privacy risks while ensuring service continuity and *** SVMmodel helps validate the system’s reliability by creating a hyperplane that distinguishes between maximum and minimum privacy *** results demonstrate the effectiveness of the proposed SVM model in enhancing both privacy and service performance.

关键词： Support vector machine big data IoV privacy-preserving

RE-SEGNN:recurrent semantic evidence-aware graph neural network for temporal knowledge graph forecasting

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Science China(Information Sciences) 2025年

作者： Wenyu CAI Mengfan LI Xuanhua SHI Yuanxin FAN Quntao ZHU Hai JIN National Engineering Research center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and Technology

Temporal knowledge graph(TKG) reasoning, has seen widespread use for modeling real-world events, particularly in extrapolation settings. Nevertheless, most previous studies are embedded models, which require both entity and relation embedding to make predictions, ignoring the semantic correlations among different entities and relations within the same timestamp. This can lead to random and nonsensical predictions when unseen entities or relations occur. Furthermore, many existing models exhibit limitations in handling highly correlated historical facts with extensive temporal depth. They often either overlook such facts or overly accentuate the relationships between recurring past occurrences and their current counterparts. Due to the dynamic nature of TKG, effectively capturing the evolving semantics between different timestamps can be *** address these shortcomings, we propose the recurrent semantic evidenceaware graph neural network(RE-SEGNN), a novel graph neural network that can learn the semantics of entities and relations simultaneously. For the former challenge, our model can predict a possible answer to missing quadruples based on semantics when facing unseen entities or relations. For the latter problem, based on an obvious established force, both the recency and frequency of semantic history tend to confer a higher reference value for the current. We use the Hawkes process to compute the semantic trend, which allows the semantics of recent facts to gain more attention than those of distant facts. Experimental results show that RE-SEGNN outperforms all SOTA models in entity prediction on 6 widely used datasets, and 5 datasets in relation prediction. Furthermore, the case study shows how our model can deal with unseen entities and relations.

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Endoscopy-assisted lightweight diagnosis system based on transformers for colon polyp detection

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Optoelectronics Letters 2025年第1期21卷 57-64页

作者： FAN Weiming YU Jiahui JU Zhaojie School of Automation and Electrical Engineering Shenyang Ligong University department of Biomedical Engineering Zhejiang University School of computing University of Portsmouth

The integration of endoscopy has significantly propelled the diagnosis and treatment of gastrointestinal diseases, with colonoscopy establishing itself as the primary method for early diagnosis and preventive care in colorectal cancer(CRC). Although deep learning holds promise in mitigating missed polyp rates, modern endoscopy examinations pose additional challenges, such as image blurring and atomizing. This study explores lightweight yet powerful attention mechanisms, introducing the spatial-channel transformer(SCT), an innovative approach that leverages spatial channel relationships for attention weight calculation. The method utilizes rotation operations for inter-dimensional dependencies, followed by residual transformation, encoding inter-channel and spatial information with minimal computational overhead. Extensive experiments on the CVC-Clinic DB polyp detection dataset, addressing endoscopy pitfalls, underscore the superiority of our SCT over other state-of-the-art methods. The proposed model maintains high performance, even in challenging scenarios.

关键词： Endoscopy

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

Small molecule inhibitor DDQ-treated hippocampal neuronal cells show improved neurite outgrowth and synaptic branching

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Neural Regeneration Research 2025年第9期20卷 2624-2632页

作者： Jangampalli Adi Pradeepkiran Priyanka Rawat Arubala P.Reddy Erika Orlov PHemachandra Reddy department of Internal Medicine Texas Tech University Health Sciences CenterLubbockTXUSA department of Nutritional Sciences College of Human SciencesTexas Tech UniversityLubbockTXUSA department of Pharmacology&Neuroscience Texas Tech University Health Sciences CenterLubbockTXUSA department of Neurology Texas Tech University Health Sciences CenterLubbockTXUSA department of Speech Language and Hearing SciencesTexas Tech University Health Sciences CenterLubbockTXUSA department of Public Health Texas Tech University Health Sciences CenterLubbockTXUSA

The process of neurite outgrowth and branching is a crucial aspect of neuronal development and *** and dendrites,sometimes referred to as neurites,are extensions of a neuron's cellular body that are used to start *** we explored the effects of diethyl(3,4-dihydroxyphenethylamino)(quinolin-4-yl)methylphosphonate(DDQ)on neurite developmental features in HT22 neuronal *** this work,we examined the protective effects of DDQ on neuronal processes and synaptic outgrowth in differentiated HT22cells expressing mutant Tau(mTau)*** investigate DDQ chara cteristics,cell viability,biochemical,molecular,western blotting,and immunocytochemistry were *** outgrowth is evaluated through the segmentation and measurement of neural *** neural processes can be seen and measured with a fluorescence microscope by manually tracing and measuring the length of the neurite *** neuronal processes can be observed and quantified with a fluorescent microscope by manually tracing and measuring the length of the neuronal ***-treated mTau-HT22 cells(HT22 cells transfected with cDNA mutant Tau)were seen to display increased levels of synaptophysin,MAP-2,andβ-***,we confirmed and noted reduced levels of both total and p-Tau,as well as elevated levels of microtubule-associated protein 2,β-tubulin,synaptophysin,vesicular acetylcholine transporter,and the mitochondrial biogenesis protein-pe roxisome prolife rator-activated receptor-gamma coactivator-1α.In mTa u-expressed HT22 neurons,we observed DDQ enhanced the neurite characteristics and improved neurite development through increased synaptic *** findings conclude that mTa u-HT22(Alzheimer's disease)cells treated with DDQ have functional neurite developmental chara *** key finding is that,in mTa u-HT22 cells,DDQ preserves neuronal structure and may even enhance nerve development function with mTa u inhibition.

关键词： diethyl(3 4-dihydroxyphenethylamino)(quinolin-4-yl)methylphosphonate(DDQ) hippocampal neuronal cells HT22 neurite outgrowth neuronal development small molecule

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LiDAR-Visual SLAM with Integrated Semantic and Texture Information for Enhanced Ecological Monitoring Vehicle Localization

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Computers, Materials & Continua 2025年第1期82卷 1401-1416页

作者： Yiqing Lu Liutao Zhao Qiankun Zhao Foreign Environmental Cooperation center Ministry of Ecology and Environment of PRCBeijing100035China Beijing computing center Co. Ltd.Beijing Academy of Science and TechnologyBeijing100083China Beijing Guyu Interactive Artificial Intelligence Application Co. Ltd.Beijing100024China

Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental *** vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant *** address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data ***,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less ***,visual texture information complements LiDAR-Visual localization by providing additional contextual *** incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of *** approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.

关键词： LiDAR-Visual simultaneous localization and mapping integrated semantic texture information

Exosomes:the next-generation therapeutic platform for ischemic stroke

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Neural Regeneration Research 2025年第5期20卷 1221-1235页

作者： Wenjing Yin Hongyin Ma Yang Qu Jiaxin Ren Yingying Sun Zhen-Ni Guo Yi Yang Stroke center Department of NeurologyFirst Hospital of Jilin UniversityChangchunJilin ProvinceChina Neuroscience Research center Department of NeurologyFirst Hospital of Jilin UniversityChangchunJilin ProvinceChina

Current therapeutic strategies for ischemic stroke fall short of the desired objective of neurological functional ***,there is an urgent need to develop new methods for the treatment of this *** are natural cell-derived vesicles that mediate signal transduction between cells under physiological and pathological *** have low immunogenicity,good stability,high delivery efficiency,and the ability to cross the blood–brain *** physiological properties of exosomes have the potential to lead to new breakthroughs in the treatment of ischemic *** rapid development of nanotechnology has advanced the application of engineered exosomes,which can effectively improve targeting ability,enhance therapeutic efficacy,and minimize the dosages *** in technology have also driven clinical translational research on *** this review,we describe the therapeutic effects of exosomes and their positive roles in current treatment strategies for ischemic stroke,including their antiinflammation,anti-apoptosis,autophagy-regulation,angiogenesis,neurogenesis,and glial scar formation reduction ***,it is worth noting that,despite their significant therapeutic potential,there remains a dearth of standardized characterization methods and efficient isolation techniques capable of producing highly purified *** optimization strategies should prioritize the exploration of suitable isolation techniques and the establishment of unified workflows to effectively harness exosomes for diagnostic or therapeutic applications in ischemic ***,our review aims to summarize our understanding of exosome-based treatment prospects in ischemic stroke and foster innovative ideas for the development of exosome-based therapies.

关键词： blood–brain barrier electroacupuncture engineering exercise exosomes ischemic stroke mesenchymal stem cells microglia neuroprotection stents

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Cortical hem signaling center: functions, development, and potential implications for evolution and brain disorders

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Neural Regeneration Research 2025年第4期20卷 1079-1080页

作者： Victor V.Chizhikov Igor Y.Iskusnykh department of Anatomy and Neurobiology University of Tennessee Health Science CenterMemphisTNUSA

Development of the telencephalon relies upon several signaling centers-localized cellular populations that supply secreted factors to pattern the cortical *** such signaling center is the cortical hem,which arises during embryonic development at the telencephalic dorsal midline,adjacent to the choroid plexus and hippocampal primordium(Figure 1A).While the cortical hem has also been described in reptiles and birds,most of our knowledge about the developmental roles of the cortical hem is derived from the analysis in *** cortical hem produces several types of secreted molecules,including wingless-related integration site(Wnt)and bone morphogenetic(Bmp)*** cortical hem is particularly important for the development of the hippocampus,which is involved in learning and memory,and the neocortex,which is the most complex brain region that mediates multiple types of behavior and higher cognitive functions(Mangale et al.,2008;Dal-Valle-Anton and Borrell,2022).

关键词： epithelium Figure center

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