Fiber Sensing in the 6G Era: Vision Transformers for <i>ϕ</i>-OTDR-Based Road-Traffic Monitoring by Robson A. Colares, Leticia Rittner, Evandro Conforti, Darli A. A. Mello

“…We apply vision transformers (ViTs) in a distributed fiber-optic sensing system to evaluate road traffic parameters in smart cities. Convolutional neural networks (CNNs) are also assessed for benchmarking. …”
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Deep Learning Architectures for Single-Label and Multi-Label Surgical Tool Classification in Minimally Invasive Surgeries by Hisham ElMoaqet, Hamzeh Qaddoura, Mutaz Ryalat, Natheer Almtireen, Tamer Abdulbaki Alshirbaji, Nour Aldeen Jalal, Thomas Neumuth, Knut Moeller

“…Nonetheless, our results demonstrated that the proposed CNN-SE-FFM-BiLSTM multi-label model achieved competitive performance to state-of-the-art methods with excellent performance in detecting tools with complex usage patterns and in minority classes. Future work should focus on optimizing models for real-time applications, and broadening dataset evaluations to improve performance in diverse surgical environments. …”
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Multimodal Explainability Using Class Activation Maps and Canonical Correlation for MI-EEG Deep Learning Classification by Marcos Loaiza-Arias, Andrés Marino Álvarez-Meza, David Cárdenas-Peña, Álvaro Ángel Orozco-Gutierrez, German Castellanos-Dominguez

“…On the GIGAScience MI dataset, experiments show that shallow neural networks are good at classifying MI-EEG data, while the CAM-based method finds spatio-frequency patterns. …”
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Artificial Intelligence in Diagnosis and Management of Nail Disorders: A Narrative Review by Vishal Gaurav, Chander Grover, Mehul Tyagi, Suman Saurabh

“…In the specific domain of onychology, AI presents a promising avenue for diagnosing nail disorders, analyzing intricate patterns, and improving diagnostic accuracy. This review provides a comprehensive overview of the current applications of AI in onychology, focusing on its role in diagnosing onychomycosis, subungual melanoma, nail psoriasis, nail fold capillaroscopy, and nail involvement in systemic diseases. …”
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Causal knowledge graph construction for enterprise innovation events in the digital economy and its application to strategic decision-making by Pengfei Wu, Bingtao Xu, Xuhan Zhang

“…We introduce a new architecture that integrates pre-trained language encoders and graph neural networks to jointly model event contexts and global causal structure. …”
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Machine Learning Approaches to Predict No-Shows in Saudi Arabian Primary and General Healthcare Settings by Abdulrahman Alshehri, Abdullah Saeed, Abdullah AlShafea, Sabah Althubiany, Mohammed Alshehri, Amer Alzahrani, Khalid Hakami, Lamia Ibrahim, Abdulrahim Alshehri, Rana Alamri

“…Machine learning models, such as decision trees, random forests, Naive Bayes, logistic regression, and artificial neural networks (ANN), have been developed and evaluated based on accuracy, precision, recall, F1 score, and area under the curve (AUC). …”
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Patients’ preferences on atopic dermatitis skincare and social media use: a qualitative study by Roxana Mazilu, Stefanie Ziehfreund, Stephan Traidl, Alexander Zink

“…Conclusions Patients exhibit diverse patterns of SM use when selecting daily products and critically evaluate the online content, demonstrating a greater trust in healthcare professionals or familial connections. …”
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THE INVERSE GAUSSIAN PLUME METHOD FOR ESTIMATING THE LEVEL OF AIR POLLUTION by Volodymyr Hura, Liubomyr Monastyrskyi

“…Its demonstrated predictive capability makes it an asset for enhancing environmental monitoring programs, potentially supplementing fixed monitoring networks and identifying areas of concern. Furthermore, the model's utility extends significantly into the domain of regulatory compliance, facilitating environmental impact assessments for proposed industrial activities and evaluating the effectiveness of emission control measures.…”
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Advanced Deep Learning Approaches for Forecasting High-Resolution Fire Weather Index (FWI) over CONUS: Integration of GNN-LSTM, GNN-TCNN, and GNN-DeepAR by Shihab Ahmad Shahriar, Yunsoo Choi, Rashik Islam

“…Wildfires in the United States have increased in frequency and severity over recent decades, driven by climate change, altered weather patterns, and accumulated flammable materials. Accurately forecasting the Fire Weather Index (FWI) is crucial for mitigating wildfire risks and protecting ecosystems, human health, and infrastructure. …”
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Scientometric analysis of computational calculations on hydrogen adsorption by D.A. Torres-Ceron, S. Amaya-Roncancio, F. Fuentes-Gandara, E. Restrepo-Parra, L. Bohorquez-Santiago, J.P. Velasquez-Tamayo

“…The retrieved data were analysed with the Bibliometrix package in RStudio to evaluate publication trends, research evolution across three distinct periods and global collaboration networks. …”
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Explainable Artificial Intelligence for predicting the compressive strength of soil and ground granulated blast furnace slag mixtures by Ahmed Mohammed Awad Mohammed, Omayma Husain, Muyideen Abdulkareem, Nor Zurairahetty Mohd Yunus, Nadiah Jamaludin, Elamin Mutaz, Hashim Elshafie, Mosab Hamdan

“…A database of 200 samples was compiled from the literature, and six ML models—linear regression, decision trees, random forest, artificial neural networks, gradient boosting, and extreme gradient boosting were developed and evaluated. …”
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Epitranscriptomic analysis reveals clinical and molecular signatures in glioblastoma by Glaucia Maria de Mendonça Fernandes, Wesley Wang, Saman Seyed Ahmadian, Daniel Jones, Jing Peng, Pierre Giglio, Monica Venere, José Javier Otero

“…Novel differences in N6-Methyladenosine (m6A) RNA methylation patterns between these groups are identified in the first biopsy. …”
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GeoBM: A Python-based tool for integrated visualization of global bibliometric data by Chun Chong Fu, Jorge Fleta-Asín, Fernando Muñoz, Carlos Sáenz-Royo, Loo Keat Wei

“…By providing a dual-focus representation of publication density and collaborative strength, GeoBM offers a powerful tool for the spatial analysis of global research networks, contributing to more nuanced evaluations in science policy, research management, and innovation studies.…”
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Comprehensive Review of Environmental Surveillance for Azole-Resistant <i>Aspergillus fumigatus</i>: A Practical Roadmap for Hospital Clinicians and Infection Control Teams by Masato Tashiro, Yuichiro Nakano, Tomoyuki Shirahige, Satoshi Kakiuchi, Ayumi Fujita, Takeshi Tanaka, Takahiro Takazono, Koichi Izumikawa

“…Our approach aims to enable accurate, ongoing evaluations of emerging resistance patterns, ensuring that institutions maintain efficient and adaptive programs. …”
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Prompt-based fine-tuning with multilingual transformers for language-independent sentiment analysis by Faizad Ullah, Safiullah Faizullah, Imdad Ullah Khan, Turki Alghamdi, Toqeer Ali Syed, Ahmad B. Alkhodre, Muhammad Sohaib Ayub, Asim Karim

“…A hybrid deep learning model is introduced, combining Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNNs) to capture local and sequential text patterns. …”
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Human-Centric Cognitive State Recognition Using Physiological Signals: A Systematic Review of Machine Learning Strategies Across Application Domains by Kaizhe Jin, Adrian Rubio-Solis, Ravi Naik, Daniel Leff, James Kinross, George Mylonas

“…The review highlights a pivotal shift from shallow ML to DL approaches for analysing physiological signals, driven by DL’s ability to autonomously learn complex patterns in large datasets. By 2023, DL has become the dominant methodology, though traditional ML techniques remain relevant. …”
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Revolutionizing Utility of Big Data Analytics in Personalized Cardiovascular Healthcare by Praneel Sharma, Pratyusha Sharma, Kamal Sharma, Vansh Varma, Vansh Patel, Jeel Sarvaiya, Jonsi Tavethia, Shubh Mehta, Anshul Bhadania, Ishan Patel, Komal Shah

“…The term “big data analytics (BDA)” defines the computational techniques to study complex datasets that are too large for common data processing software, encompassing techniques such as data mining (DM), machine learning (ML), and predictive analytics (PA) to find patterns, correlations, and insights in massive datasets. …”
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Epigenetic regulation of histone modifications in glioblastoma: recent advances and therapeutic insights by Li Zhang, Yang Yang, Yanchu Li, Chenyu Wang, Chenbin Bian, Hongbin Wang, Feng Wang

“…These studies demonstrate that modulating histone modifications can alter gene expression patterns, inhibit tumor growth, induce apoptosis, and sensitize tumor cells to conventional treatments. …”
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Research and Optimization of White Blood Cell Classification Methods Based on Deep Learning and Fourier Ptychographic Microscopy by Mingjing Li, Junshuai Wang, Shu Fang, Le Yang, Xinyang Liu, Haijiao Yun, Xiaoli Wang, Qingyu Du, Ziqing Han

“…The proposed method introduces four key innovations to enhance detection accuracy and model efficiency: (1) A novel Conv2Former (Convolutional Transformer) backbone was designed to combine the local pattern extraction capability of convolutional neural networks (CNNs) with the global contextual reasoning of transformers, thereby improving the expressiveness of feature representation. (2) The CARAFE (Content-Aware ReAssembly of Features) upsampling operator was adopted to replace conventional interpolation methods, thereby enhancing the spatial resolution and semantic richness of feature maps. (3) An Efficient Multi-scale Attention (EMA) module was introduced to refine multi-scale feature fusion, enabling the model to better focus on spatially relevant features critical for WBC classification. (4) Soft-NMS (Soft Non-Maximum Suppression) was used instead of traditional NMS to better preserve true positives in densely packed or overlapping cell scenarios, thereby reducing false positives and false negatives. …”
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Asymmetric representation of symmetric semantic information in the human brain by Jiaxin Wang, Kiichi Kawahata, Antoine Blanc, Naoya Maeda, Shinji Nishimoto, Satoshi Nishida

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