Lower Limb Torque Prediction for Sit-To-Walk Strategies Using Long Short-Term Memory Neural Networks by Chamalka Kenneth Perera, Alpha. A. Gopalai, Darwin Gouwanda, Siti. A. Ahmad, Pei-Lee Teh

“…STW itself can be generalized into strategies based on individual needs and movement patterns. In this study, three long short-term memory (LSTM) neural networks were empirically trained for hip and knee torque prediction considering these STW strategies and subject anthropometry. …”
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Event-Type Identification in Power Grids Using a Spectral Correlation Function-Aided Convolutional Neural Network by Ozgur Alaca, Ali Riza Ekti, Jhi-Young Joo, Nils Stenvig

“…This study introduces a novel event-type identification method, utilizing a Spectral Correlation Function (SCF)-aided Convolutional Neural Network (CNN). The proposed method employs a six-stage cascaded structure consisting of: (1) data collection, (2) clipping, (3) augmentation, (4) feature extraction (FE), (5) training, and (6) testing. …”
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Landsat Time Series Reconstruction Using a Closed-Form Continuous Neural Network in the Canadian Prairies Region by Masoud Babadi Ataabadi, Darren Pouliot, Dongmei Chen, Temitope Seun Oluwadare

“…To address these challenges, this research explores the application of a closed-form continuous-depth neural network (CFC) integrated within a recurrent neural network (RNN) called CFC-mmRNN for reconstructing historical Landsat time series in the Canadian Prairies region from 1985 to present. …”
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Network analysis of socioeconomic disparities and public transport in COVID-19 spread: a case study in northeast Brazil by Taise F Cavalcante, Waneska de S Barboza, Cliomar A dos Santos, Adriano Antunes de S Araújo, Lucindo José Quintans-Júnior, Paulo Ricardo Martins-Filho

“…Our findings revealed a higher positivity rate during periods of increased viral spread (OR = 4.3, 95% CI: 3.1–5.9) and in neighborhoods with poorer conditions (OR = 1.5, 95% CI: 1.1–2.1). Network analysis revealed affluent neighborhoods as significant transmission hubs of the disease. …”
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FISNET: A Learnable Fusion-Based Iris Segmentation Network Improving Robustness Across NIR and VIS Modalities by Geetanjali Sharma, Gaurav Jaswal, Aditya Nigam, Raghavendra Ramachandra

“…Segmenting irises captured under different imaging conditions is challenging for a single model due to variations in spectral features, texture, lighting conditions, and noise patterns between NIR and VIS images. To tackle this problem, we present Fused Iris Segmentation Network (FISNET) that combines segmentation maps from two models to achieve enhanced precision and accuracy. …”
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Petrographic image classification of complex carbonate rocks from the Brazilian pre-salt using convolutional neural networks by Mateus Basso, João Paulo da Ponte Souza, Guilherme Furlan Chinelatto, Luis Augusto Antoniossi Mansini, Alexandre Campane Vidal

“…The use of ML enables the analysis of large datasets, the identification of complex patterns, and can save time and reduce costs compared to conventional approaches. …”
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WideConvNet: A Novel Wide Convolutional Neural Network Applied to ERP-Based Classification of Alcoholics by Abdul Baseer Buriro, Attaullah Buriro, Aziz Altaf Khuwaja, Abdul Aziz Memon, Nabeel Siddiqui, Stephen J. Weddell, Richard D. Jones

“…This paper presents WideConvNet, a novel convolutional neural network (ConvNet or CNN) that outperforms three established end-to-end models – EEGNet, Shallow Convolutional Neural Network (ShallowConvNet), and Deep Convolutional Neural Network (DeepConvNet) – in classifying event-related potentials (ERPs) from electroencephalogram (EEG) signals. …”
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Graph theory-based analysis of functional connectivity changes in brain networks underlying cognitive fatigue: An EEG study. by Yabing Lou, Rui Pi, Ruifeng Sun, Jilin Wu, Wei Wang, Ziman Zhu, Tengteng Dai, Weijun Gong

“…The selected frequency band subsequently served as the basis for weighted Phase Lag Index (wPLI) computation, yielding a functional connectivity matrix derived from wPLI measurements. Network topology was evaluated through application of five global graph theory metrics (global efficiency [Eg], local efficiency [Eloc], clustering coefficient [Cp], shortest path length [Lp], and small-world property [Sigma]) complemented by two local graph theory metrics (nodal efficiency [NE] and degree centrality [DC]). …”
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ToxDL 2.0: Protein toxicity prediction using a pretrained language model and graph neural networks by Lin Zhu, Yi Fang, Shuting Liu, Hong-Bin Shen, Wesley De Neve, Xiaoyong Pan

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Fracturing effects evaluation and gas water production characteristics analysis at different layers of surface horizontal wells by Mingqiang LI, Chunhui YE, Tengfei CAO, Ke YANG, Zhainan ZHANG, Wenjie LIU

“…Based on micro-seismic monitoring, the differences in the fracturing effects of the U1 and U2 wells were analyzed from the perspectives of the plane and height parameters of the fracture network and the types of fractures. A technical method for evaluating the effect of hydraulic fracturing in surface horizontal wells was initially formed by combining fracturing construction parameters with micro-seismic monitoring results. …”
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A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images by Mishmala Sushith, A. Sathiya, V. Kalaipoonguzhali, V. Sathya

“…This paper presents a novel hybrid deep learning framework that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for diabetic retinopathy (DR) early detection and progression monitoring using retinal fundus images. …”
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Supply-Demand Matching Evaluation and Coupling Coordination of Cultural Ecosystem Services in Urban Park Green Spaces by Yang YU, Xian YANG, Xiang LI, Liyuan QIAN, Sixiang ZHOU

“…Finally, based on the combined results of the supply-demand matching evaluation and the coupling coordination analysis, optimization strategies for CES in Chengdu’s park green spaces are proposed at the subarea level.ResultsThe comprehensive supply level of CES in Chengdu’s park green spaces exhibits a cluster distribution pattern that is “higher in the south, and lower in the north”, with high-value areas concentrated in the central and southwestern parts of the main urban area, and low-value areas mainly distributed in the northeastern part. …”
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Spatial transformation mechanism of city networks in the middle and lower Ganga Plain in modern times: a perspective on cultural routes by Xihui Wang, Wei Dong, Yicun Pang, Hang Yin

“…The urban system in the middle and lower Ganga Plain experienced a critical spatial transition period from a traditional to modern pattern between the 18th and 19th centuries, developing a network structure influenced by cultural routes. …”
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Quantitative Assessment of Bolt Looseness in Beam–Column Joints Using SH-Typed Guided Waves and Deep Neural Network by Ru Zhang, Xiaodong Sui, Yuanfeng Duan, Yaozhi Luo, Yi Fang, Rui Miao

“…The received signals were converted into time–frequency spectra, and the effective components were extracted to form the input pattern for the neural network. Numerical simulations were performed on a beam–column joint with eight bolts, and the number of training samples was increased using data augmentation techniques. …”
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Evaluating the effects of climate-induced heatwaves on the thermal dynamics and water quality of a deep reservoir in Portugal by Manuel Almeida, Senlin Zhu, Rita M. Cardoso, Pedro M.M. Soares, Pedro Coelho

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Empirical classification of fatigue-induced physiological tremor in robot-assisted manipulation tasks using BiLSTM-GRU network by Poongavanam Palani, Siddhant Panigrahi, Gunarajulu Renganathan, Yuichi Kurita, Asokan Thondiyath

“…On the master end, the participants were seated comfortably and asked to trace the patterns embedded over an image of an organ that was displayed on the screen. …”
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Real-world treatment patterns and outcomes among patients initiating sequential regorafenib and trifluridine/tipiracil ± bevacizumab in patients with metastatic colorectal cancer i... by Tanios Bekaii-Saab, Ila Sruti, Junxin Shi, Wei Dai, Gregory Patton, Sreevalsa Appukkuttan, Brian Hocum, Arvind Katta, Svetlana Babajanyan, David Cosgrove

“…However, in the absence of recommendations regarding preferred treatment order, our study aimed to improve the understanding of real-world optimal treatment sequences.MethodsThis retrospective study assessed real-world outcomes and treatment patterns among mCRC patients who initiated sequential regorafenib and FTD/TPI ± bevacizumab between the first line and sixth line from September 2015 to November 2022 in The US Oncology Network. …”
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StyleGraph: A Heterogeneous Graph Neural Framework for Stylistic and Semantic Rumor Detection on Social Media by Haider Jaffar, Ali Mohades, Mohammad Ebrahim Shiri

“…StyleGraph was evaluated using Graph Convolutional Networks (GCNs), Graph Attention Networks (GATs), and Cluster GCNs on the PHEME dataset under both 5-event and 9-event settings. …”
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Spatiotemporal evaluation of irrigation groundwater quality in Hungarian agricultural sites using hydrochemical and machine learning approaches by Musaab A. A. Mohammed, Norbert P. Szabó, Viktória Mikita, Péter Szűcs

“…The research integrates hydrochemical assessment with machine learning to enhance the spatiotemporal evaluation of irrigation water quality. Groundwater samples from the Debrecen area (2019–2024) were analyzed using Hierarchical Cluster Analysis (HCA), irrigation indices (SAR, Na%, IWQI), and Self-Organizing Maps (SOMs) to understand spatial and temporal patterns. …”
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Coupling Coordination Evaluation and Optimization of Water–Energy–Food System in the Yellow River Basin for Sustainable Development by Pengcheng Zhang, Yaoyao Fu, Boliang Lu, Hongbo Li, Yijie Qu, Haslindar Ibrahim, Jiaxuan Wang, Hao Ding, Shenglin Ma

“…The interdependence among the three major systems is strong (0.881–0.939), and while the coupling coordination degree has increased over time despite fluctuations, a qualitative leap has not yet been achieved. The evaluation index follows a spatial distribution pattern of midstream > downstream > upstream, characterized by a predominantly high coupling degree. …”
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