A Correlation Analysis-Based Structural Load Estimation Method for RC Beams Using Machine Vision and Numerical Simulation by Chun Zhang, Yinjie Zhao, Guangyu Wu, Han Wu, Hongli Ding, Jian Yu, Ruoqing Wan

“…The classical regression assessment method based on experimental data not only relies on costly structure experiments; it also lacks interpretability. Therefore, a novel load estimation method for RC beams, based on correlation analysis between detected crack images and strain contour plots calculated by FEM, is proposed. …”
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Anomaly detection solutions: The dynamic loss approach in VAE for manufacturing and IoT environment by Praveen Vijai, Bagavathi Sivakumar P

“…The proposed model addresses key challenges, including data imbalance, interpretability issues, and computational complexity. …”
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Flexible analysis of spatial transcriptomics data (FAST): a deconvolution approach by Meng Zhang, Joel Parker, Lingling An, Yiwen Liu, Xiaoxiao Sun

“…Consequently, there is a critical need for the development of highly flexible, robust, and user-friendly reference-free deconvolution methods capable of unifying or leveraging case-specific information in the analysis of spatial transcriptomics data. Results We propose a novel reference-free method based on regularized non-negative matrix factorization (NMF), named Flexible Analysis of Spatial Transcriptomics (FAST), that can effectively incorporate gene expression data, spatial, and histology information into a unified deconvolution framework. …”
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Hyperhomocysteinemia-induced VCID results in visual deficits, reduced neuroinflammation and vascular alterations in the retina by Erica M. Weekman, Colin B. Rogers, Tiffany L. Sudduth, Donna M. Wilcock

“…These changes provide novel insights and reproduce some prior observations. …”
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Predicting the shield effectiveness of carbon fiber reinforced mortars utilizing metaheuristic algorithms by Mana Alyami, Irfan Ullah, Furqan Ahmad, Hisham Alabduljabbar

“…Machine learning (ML) models present a faster, cost-effective alternative for simulating outcomes and exploring various scenarios. This study adopts a novel approach by utilizing hybrid models, which offer greater accuracy than individual or ensemble ML models. …”
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Multimodal approach to public health interventions using EGG and mobile health technologies by Xiao Zhang, Han Liu, Mingyang Sun, Shuangyi Feng

“…While recent advancements like Contrastive Language-lmage Pre-training(CLIP) models excel in cross-modal understanding, their application to EEG-based tasks remains limited due to the unique characteristics of EEG data.MethodsIn response, we introduce PH-CLIP (Public Health Contrastive Language-lmage Pretraining), a novel framework that combines CLIP's representational power with a multi-scale fusion mechanism designed specifically for EEG data within mobile health technologies. …”
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Feature selection based on Mahalanobis distance for early Parkinson disease classification by Mustafa Noaman Kadhim, Dhiah Al-Shammary, Ahmed M. Mahdi, Ayman Ibaida

“…This paper proposes a novel feature selection method based on the Mahalanobis distance for Parkinson's disease (PD) classification. …”
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Computer-aided cholelithiasis diagnosis using explainable convolutional neural network by Dheeraj Kumar, Mayuri A. Mehta, Ketan Kotecha, Ambarish Kulkarni

“…Although several computer-aided cholelithiasis diagnosis approaches have been introduced in the literature, their use is limited because Convolutional Neural Network (CNN) models are black box in nature. Therefore, a novel approach for cholelithiasis classification using custom CNN with post-hoc model explanation is proposed. …”
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Assessing chemical exposure risk in breastfeeding infants: An explainable machine learning model for human milk transfer prediction by Xiaojie Huang, Jiajia Chen, Peineng Liu

“…This study introduces an explainable machine learning model to predict the risk of chemical transfer through human milk. Our novel framework integrates ensemble resampling methods with advanced feature selection techniques, addressing data imbalance and enhancing predictive accuracy. …”
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The Economics of Immortality: The Demi-Immortal Oriental, Enlightenment Vitalism, and Political Economy in Dracula by J. Jeffrey Franklin

“…Intending to add a new interpretation to this long list, the current essay argues, first, that Dracula belongs to a character-type that I will define as the “demi-immortal Oriental.” …”
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On supergravity and noncritical strings by Andrea Dei, Pietro Ferrero, Leonardo Rastelli

“…In particular, we find a novel class of solutions with RR flux, parametrized by a function of three variables that solves an elegant PDE. …”
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DynamicVLN: Incorporating Dynamics into Vision-and-Language Navigation Scenarios by Yanjun Sun, Yue Qiu, Yoshimitsu Aoki

“…To bridge this gap, we propose a novel task called Dynamic Vision-and-Language Navigation (DynamicVLN), incorporating various dynamic scenarios to enhance the agent’s decision-making abilities and adaptability. …”
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Integrating Model‐Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation by Karthik Raman, Rukmini Kumar, Cynthia J. Musante, Subha Madhavan

“…However, several challenges, including the availability of relevant, labeled, high‐quality datasets, data privacy concerns, model interpretability, and algorithmic bias, must be carefully managed. …”
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An Automated Approach for Epilepsy Detection Based on Tunable Q-Wavelet and Firefly Feature Selection Algorithm by Ahmed I. Sharaf, Mohamed Abu El-Soud, Ibrahim M. El-Henawy

“…Therefore, computer-aided detection provides an asset to the neurophysiologist in interpreting the EEG. This paper introduces a novel approach to recognize and classify the epileptic seizure and seizure-free EEG signals automatically by an intelligent computer-aided method. …”
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DVGEDR: a drug repositioning method based on dual-view fusion and graph enhancement mechanism in heterogeneous networks by Dongjiang Niu, Lianwei Zhang, Beiyi Zhang, Qiang Zhang, Shanyang Ding, Hai Wei, Zhen Li

“…In this paper, first, a novel drug repositioning method, namely DVGEDR, is proposed, which generates two subgraphs of the target drug–disease pair to fuse biological information and integrate drug–disease associations from two distinct perspectives: drug–disease heterogeneous network and similarity networks. …”
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Automated karyogram analysis for early detection of genetic and neurodegenerative disorders: a hybrid machine learning approach by Sumaira Tabassum, M. Jawad Khan, Javaid Iqbal, Asim Waris, M. Adeel Ijaz

“…Identifying anomalies is often costly, time-consuming, heavily reliant on expert interpretation, and requires considerable manual effort. …”
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Is Nuclear Anarchy Sustainable? A Temporal Approach by Ye. I. Uchaev, A. A. Kvartalnov

“…The article develops a novel temporal approach to the sustainability of nuclear anarchy. …”
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Exploring the application of AI in the education of children with autism: a public health perspective by Liu Lan, Ke Li, Diao Li

“…Recent advancements in artificial intelligence (Al), particularly Transformer-based models, offer a novel opportunity to enhance and personalize social skills training.MethodsThis study introduces a Public Health-Driven Transformer (PHDT) model specifically designed to improve social skills in children with ASD. …”
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Pressure Transient Analysis for a Well Drilling into a Large-Size Cave in Fracture-Caved Carbonate Gas Reservoirs by Jie Jin, Qingyu Li, Detang Lu

“…This paper develops a novel pressure transient analysis model for FCCGR by coupling the fluctuating pressure and minor energy loss. …”
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OCT-based diagnosis of glaucoma and glaucoma stages using explainable machine learning by Md Mahmudul Hasan, Jack Phu, Henrietta Wang, Arcot Sowmya, Michael Kalloniatis, Erik Meijering

“…A total of 334 normal and 268 glaucomatous eyes (86 early, 72 moderate, 110 advanced) were included, signal processing theory was employed, and model interpretability was rigorously evaluated. Leveraging SHapley Additive exPlanations (SHAP)-based global feature ranking and partial dependency analysis (PDA) estimated decision boundary cut-offs on machine learning (ML) models, a novel algorithm was developed to implement an XAI tool. …”
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