Neuromuscular characteristics of transcranial direct current stimulation over dorsolateral prefrontal cortex in patients with chronic low back pain: a randomized, double-blind, con... by Xin Li, Wenzhao Liang, Zhicheng Li, Shijue Li, Yao Zu, Le Ge, Chuhuai Wang

“…Previous studies suggest that the number, structure, and network patterns of trunk muscle synergy may contribute to this condition. …”
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Links between sea surface temperature anomalies and seismic activity in the Red Sea across multiple temporal scales by Ahmed M. El Kenawy, Emad K. Mohamed, Mohamed M. Abdelaal, Mohamed El Alfy, Azza Ragab, Hassan Aboelkhair

“…Abstract This study evaluates the links between seismic activity and sea surface temperature (SST) variability in the Red Sea from 2003 to 2020. …”
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Developing a framework for medical student feedback literacy using a triangulated thematic analysis by Mohamad Nabil Mohd Noor, Jessica Grace Cockburn, Chan Choong Foong, Chiann Ni Thiam, Yang Faridah Abdul Aziz, Tiiu Sildva, Galvin Sim Siang Lin, Jamuna Vadivelu

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Using Graph-Based Maximum Independent Sets with Large Language Models for Extractive Text Summarization by Cengiz Hark

“…Experiments on the Document Understanding Conference (DUC) and Cable News Network (CNN)/DailyMail datasets are conducted with different summary lengths to evaluate the performance of the framework. …”
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Census and Analysis of Higher-Order Interactions in Real-World Hypergraphs by Xihang Meng, Xuemeng Zhai, Gaolei Fei, Sheng Wen, Guangmin Hu

“…This framework features the encoding, census, and evaluation of higher-order patterns, effectively overcoming their inherent complexity and diversity. …”
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Channel Characterization and Comparison in Industrial Scenario from Sub-6 GHz to Visible Light Bands for 6G by Yue Yin, Pan Tang, Jianhua Zhang, Zheng Hu, Tao Jiang, Liang Xia, Guangyi Liu

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ANALISIS KESIAPAN PROGRAM STUDI DALAM PRODUCTION BASED EDUCATION: STUDI PADA PROGRAM STUDI D3 AKUNTANSI POLINES by Muhammad Noor Ardiansah

“…Resources have been managed, monitored and evaluated well (managed) are: curriculum resources, networking courses, lab facilities, ISO-based management. …”
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Double-diffusive magnetoconvection in a tilted porous parallelogrammic domain with discrete heated-cooled segments: Leveraging machine learning and CFD approach by P. Ravindra, M. Sankar, Suresh Rasappan, Wardah Abdullah Al Majrafi, Pugalarasu Rajan, S. Sanal Kumar

“…In addition, an artificial neural network (ANN) model is developed that uses a softmax activation function to predict Nu‾ and Sh‾, and its performance is evaluated against a regression model, yielding robust results.…”
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A selective CutMix approach improves generalizability of deep learning-based grading and risk assessment of prostate cancer by Sushant Patkar, Stephanie Harmon, Isabell Sesterhenn, Rosina Lis, Maria Merino, Denise Young, G. Thomas Brown, Kimberly M. Greenfield, John D. McGeeney, Sally Elsamanoudi, Shyh-Han Tan, Cara Schafer, Jiji Jiang, Gyorgy Petrovics, Albert Dobi, Francisco J. Rentas, Peter A. Pinto, Gregory T. Chesnut, Peter Choyke, Baris Turkbey, Joel T. Moncur

“…For cancer grading, a Gleason pattern detector was trained on tiles using a ResNet50 convolutional neural network and a selective CutMix training strategy involving a mixture of real and artificial examples. …”
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Primary sclerosing cholangitis–inflammatory bowel disease: Epidemiology, mortality, and impact of diagnostic sequence by Kristel K. Leung, Wenbin Li, Bettina Hansen, Aliya Gulamhusein, Lauren Lapointe-Shaw, Abdel Aziz Shaheen, Amanda Ricciuto, Eric I. Benchimol, Jennifer A. Flemming, Gideon M. Hirschfield

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Attention-based multi-scale convolution and conformer for EEG-based depression detection by Ze Yan, Ze Yan, Ze Yan, Yumei Wan, Xin Pu, Xiaolin Han, Mingming Zhao, Haiyan Wu, Wentao Li, Xueying He, Yunshao Zheng

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Interictal suppression in patients with mesial temporal lobe epilepsy: A simultaneous PET/fMRI study by Jie Hu, Liwei Sun, Kun Guo, Bixiao Cui, Chenyang Yao, Jingjuan Wang, Hui Ouyang, Xu Zhang, Chunlin Li, Jie Lu

“…We also found that the regions within DMN play a critical role in the suppression of SOZs. The pattern of such suppressive network might also serve as potential features for the localization of SOZs. …”
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IMPLEMENTATION OF BACKPROPAGATION AND HYBRID ARIMA-NN METHODS IN PREDICTING ACCURACY LEVELS OF RAINFALL IN MAKASSAR CITY by Hisyam Ihsan, Irwan Irwan, Andi Illa Erviani Nensi

“…Hybrid ARIMA-NN is a combined approach of the ARIMA model used to capture linear patterns in time series data and Artificial Neural Networks (ANN) to handle non-linear and stochastic patterns. …”
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Regional landslide hazard assessment using the IV-RF coupling model and critical monthly average rainfall threshold：A case study from Fuling District, Chongqing by Shuangqing PENG, Pengfei LIU, Gang CHEN, Liping WANG, Wei ZHANG, Wenwen LUO, Xiliang JING

“…Taking Fuling District of Chongqing as a case study, the information value model, BP neural network model, random forest model, information value-BP neural network coupled model, and information value-random forest coupled model were used to evaluate regional landslide susceptibility. …”
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Analysing the most Important Variables Affecting Agricultural Water Security in Mazandaran Province by F. Razzaghi Borkhani, T. Azizi Khalkheili, A.A. Barati

“…Then, the experts were asked to evaluate the cross-effects of the identified variables through pairwise comparisons and in the form of the MICMAC questionnaire. …”
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An enhanced CNN with ResNet50 and LSTM deep learning forecasting model for climate change decision making by Ahmed M. Elshewey, Mona M. Jamjoom, Eman H. Alkhammash

“…It involves long-term, noticeable changes in key climatic factors such as wind power, temperature, wind speed, and wind patterns. Addressing climate change is essential to safeguarding our environment, societies, and economies. …”
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MPFM-VC: A Voice Conversion Algorithm Based on Multi-Dimensional Perception Flow Matching by Yanze Wang, Xuming Han, Shuai Lv, Ting Zhou, Yali Chu

“…Voice conversion (VC) is an advanced technology that enables the transformation of raw speech into high-quality audio resembling the target speaker’s voice while preserving the original linguistic content and prosodic patterns. In this study, we propose a voice conversion algorithm, Multi-Dimensional Perception Flow Matching (MPFM-VC). …”
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Tension and compression behaviors of Moso bamboo (Phyllostachys pubescens) for structural use by Qunying Mou, Siyang Ji, Peng Li, Xianjun Li, Zhangjing Chen, Lin He, Xiazhen Li

“…The variations in bearing capacity and failure modes of bamboo were mainly attributed to its structural characteristics, particularly the three-dimensional network structure of nodes.…”
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Metaphors in the dictionary of German football language by R. V. Beliutin

“…The status of metaphors in the German football language and their firm position in this communicative space are distinguished through an outstanding network of synonymous constructions and variations, multifarious word-building patterns (mainly compounding) in developing new metaphoric units. …”
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Multi-dimensional water quality indicators forecasting from IoT sensors: A tensor decomposition and multi-head self-attention mechanism. by Li Bo, Lv Junrui, Luo Xuegang

“…To overcome these limitations, we propose TGMHA (Tensor Decomposition and Gated Neural Network with Multi-Head Self-Attention), a novel hybrid model that integrates three key innovations: 1) Tensor-based Feature Extraction: We combine Standard Delay Embedding Transformation (SDET) with Tucker tensor decomposition to reconstruct raw time series into low-rank tensor representations, capturing latent spatio-temporal patterns while suppressing sensor noise. 2) Multi-Head Self-Attention for Inter-Indicator Dependencies: A multi-head self-attention mechanism explicitly models complex inter-dependencies among diverse water quality indicators (e.g., pH, dissolved oxygen, conductivity) via parallel feature subspace learning. 3) Efficient Long-Term Dependency Modeling: An encoder-decoder architecture with gated recurrent units (GRUs), optimized by adaptive rank selection, ensures efficient modeling of long-term dependencies without compromising computational performance. …”
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