Body image flexibility and embodiment in eating disorders: a mixed-methods approach combining network analysis and pilot exposure protocol by Paolo Meneguzzo, Chiara Cazzola, Francesca Buscaglia, Anna Pillan, Filippo Pettenuzzo, Patrizia Todisco

“…Additionally, a pilot group therapy intervention targeting body image concerns was evaluated with 24 ED participants. Results Findings suggest that significant differences in embodiment-related features emerged (self-regulation and body trust), while both groups reported similar levels of interoceptive awareness. …”
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Advanced Support Vector Machine- (ASVM-) Based Detection for Distributed Denial of Service (DDoS) Attack on Software Defined Networking (SDN) by Myo Myint Oo, Sinchai Kamolphiwong, Thossaporn Kamolphiwong, Sangsuree Vasupongayya

“…Software Defined Networking (SDN) has many advantages over a traditional network. …”
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A KeyBERT-Enhanced Pipeline for Electronic Information Curriculum Knowledge Graphs: Design, Evaluation, and Ontology Alignment by Guanghe Zhuang, Xiang Lu

“…TF-IDF 40%), KeyBERT features achieve Accuracy = 0.78 and F1 = 0.75, outperforming TF-IDF’s 0.66/0.69. …”
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DSGAU: Dual-Scale Graph Attention U-Nets for Hyperspectral Image Classification With Limited Samples by Hongzhuang Ji, Leying Song, Zhaohui Xue, Hongjun Su

“…Finally, we introduce the graph attention network with contrastive normalization layer module to replace traditional GCNs, enabling dynamic graph structure updating during propagation alleviating over-smoothing through differential feature enhancement. …”
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Implications of Ho3+-ions on physical, structural, optical, and spectroscopic features of Na2O-PbO-borotellurite glass system for feasible applications in optical and laser technol... by Shiva Kumar B N, Devaraja C, R. S. Gedam

“…The merits of physical and optical parameters viz., molar volume, density, ion concentration, field strength, optical band gaps, refractive index, Urbach energy, steepness parameter, molar polarizability, metallization criterion, electronic oxide polarizability, optical basicity etc., were evaluated using appropriate relations and they found to be in comply with the structural modifications and optical features. …”
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Are you tuned in to others' mind? A cross-modal evaluation of affective theory of mind in people with Parkinson's disease by Elisa Menozzi, Daniela Ballotta, Francesco Cavallieri, Stefania Tocchini, Sara Contardi, Valentina Fioravanti, Franco Valzania, Paolo F. Nichelli, Francesca Benuzzi

“…A dysfunctional amygdala-centred network might represent the shared bases for impairments in fear and anger recognition and affective ToM abilities in PD.…”
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Surfactant representation using COSMO screened charge density for adsorption isotherm prediction using Physics-Informed Neural Network (PINN) by Achmad Anggawirya Alimin, Kattariya Srasamran, Wanutchaya Yuenyong, Ampira Charoensaeng, Bor-Jier Shiau, Uthaiporn Suriyapraphadilok

“…A Physics-Informed Neural Network (PINN) was structured by integrating adsorption isotherm into artificial neural networks (ANN). …”
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Novel insight into prediction model for sleep quality among college students: a LASSO-derived sleep evaluation by Ling Yao, Ling Yao, Qingquan Chen, Kang Yang, Zhihua Zheng, Zhihan Chen, Danna Wang, Yining Xia, Dingquan Chen, Lufeng Chen

“…Multinomial logistic regression, LASSO regression, and Boruta feature selection methods were utilized to select relevant variables. …”
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Enhancing Vertical Application and Network Co-Design: A Solution for Multipath Channel Switching in ROS2 With 3GPP Integration by Geza Szabo

“…These steps significantly enhance the co-design process, as demonstrated by our novel quantitative evaluation method. We also evaluate the contribution of Key Performance Indicators (KPIs) from the VAL layer, analyzing how network performance impacts safety zones in robotics.…”
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Research on 3D reconstruction and digital protection of woodcarving works based on the combination of U-Net model and 6G network by Yanli Dai, Xinyong Yu

“…The U-Net model achieved outstanding semantic segmentation with an average IoU of 0.97 and a Dice coefficient of 0.98, ensuring the detailed capture of wood carving features. The integration with 6G networks resulted in remarkably low data transmission delays—0.98 ms for transmission, 3.04 ms for processing, and 0.91 ms for queuing—highlighting the potential of 6G in supporting real-time, high-fidelity 3D reconstruction. …”
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A hybrid compound scaling hypergraph neural network for robust cervical cancer subtype classification using whole slide cytology images by Pooja Govindaraj, Sasikaladevi Natarajan, Pradeepa Sampath, Akilesh Thimma Suresh, Rengarajan Amirtharajan

“…CSCNN balances the network’s depth, width, and resolution, supporting effective feature representation with minimal computational overhead. kd-HGNN captures higher-order relationships between the features, and its propagation mechanism ensures better feature diffusion across distant nodes. …”
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A Fault Diagnosis Framework for Pressurized Water Reactor Nuclear Power Plants Based on an Improved Deep Subdomain Adaptation Network by Zhaohui Liu, Enhong Hu, Hua Liu

“…To address these issues, this study proposes a novel framework integrating three key stages: (1) feature selection via a signed directed graph to identify key parameters within datasets; (2) temporal feature encoding using Gramian Angular Difference Field (GADF) imaging; and (3) an improved Deep Subdomain Adaptation Network (DSAN) using weighted Focal Loss and confidence-based pseudo-label calibration. …”
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Distributed denial-of-service (DDoS) on the smart grids based on VGG19 deep neural network and Harris Hawks optimization algorithm by Abdurahim Alhashmi, H. Idwaib, Selçuk Alparslan Avci, Javad Rahebi, Raheleh Ghadami

“…The suggested approach uses the robust feature extraction capability of VGG19-DNN for network traffic pattern analysis to detect abnormal traffic flows indicative of DDoS attacks. …”
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Recognizing Digital Ink Chinese Characters Written by International Students Using a Residual Network with 1-Dimensional Dilated Convolution by Huafen Xu, Xiwen Zhang

“…Additionally, residual connections facilitate the training of deep one-dimensional convolutional neural networks. Moreover, the paper proposes a more expressive ten-dimensional feature representation that includes spatial, temporal, and writing direction information for each sampling point, thereby improving classification accuracy. …”
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ViTAU: Facial paralysis recognition and analysis based on vision transformer and facial action units by Jia GAO, Wenhao CAI, Junli ZHAO, Fuqing DUAN

“…Our proposed method integrates ViT with facial AUs, designing a ViT-based facial paralysis recognition network that enhances the extraction of local area features through its self-attention mechanism, thereby enabling precise recognition of facial paralysis. …”
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Edges are all you need: Potential of medical time series analysis on complete blood count data with graph neural networks. by Daniel Walke, Daniel Steinbach, Sebastian Gibb, Thorsten Kaiser, Gunter Saake, Paul C Ahrens, David Broneske, Robert Heyer

“…<h4>Methods</h4>In this study, we evaluated the performance and time consumption of several GNNs (e.g., Graph Attention Networks) on similarity graphs compared to simpler, state-of-the-art machine learning algorithms (e.g., XGBoost) on the classification of sepsis from blood count data as well as the importance and slope of each feature for the final classification. …”
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Energy-efficient distributed heterogeneous clustered spectrum-aware cognitive radio sensor network for guaranteed quality of service in smart grid by Emmanuel Ogbodo, David Dorrell, Adnan Abu-Mahfouz

“…Hence, it is suitable for efficient grid automation in cognitive radio sensor network–based smart grids. The traditional model lacks these capability features.…”
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Survey of video behavior recognition by Huilan LUO, Chanjuan WANG, Fei LU

“…Behavior recognition is developing rapidly,and a number of behavior recognition algorithms based on deep network automatic learning features have been proposed.The deep learning method requires a large number of data to train,and requires higher computer storage and computing power.After a brief review of the current popular behavior recognition method based on deep network,it focused on the traditional behavior recognition methods.Traditional behavior recognition methods usually followed the processes of video feature extraction,modeling of features and classification.Following the basic process,the recognition process was overviewed according to the following steps,feature sampling,feature descriptors,feature processing,descriptor aggregation and vector coding.At the same time,the benchmark data set commonly used for evaluating the algorithm performance was also summarized.…”
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CRGAN: A Context-Aware Clothing Design and Recommendation System for Young Sri Lankan Females Using Generative Adversarial Networks by Nethmi Pathirana, Azma Imtiaz, Shakir Saheel, Kasun Karunanayaka, Adrian David Cheok

“…The proposed system leverages a Conditional Generative Adversarial Network (GAN) model, trained on three predefined parameters&#x2013;attire type, temperature conditions, and the user&#x2019;s skin tone. …”
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Enhanced Hybrid U-Net Framework for Sophisticated Building Automation Extraction Utilizing Decay Matrix by Ting Wang, Zhuyi Gong, Anqi Tang, Qian Zhang, Yun Ge

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