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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Educational Reforms and Healthcare Competitiveness through Data-Driven Analysis by Artem Artyukhov, Olha Yeremenko, Nadiia Artiukhova, Artur Lapidus, Olena Churikanova, Kseniia Bliumska-Danko

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Attention-fused residual transformer CNN for robust lower limb movement recognition by A. Anitha, D. Jeraldin Auxillia

“…The AF-RT-CNN architecture combines residual blocks, attention mechanism and Transformer Encoder aiding robust feature extraction, good generalization capability and pattern recognition. The proposed framework was evaluated across 11 healthy individuals and 11 patients with lower limb impairments, across three distinct categories of lower limb movements sit, stand and gait. …”
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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

“…Based on this, our study developed a hybrid modeling framework to forecast FWI over a 14-day horizon, integrating Graph Neural Networks (GNNs) with Temporal Convolutional Neural Networks (TCNNs), Long Short-Term Memory (LSTM), and Deep Autoregressive Networks (DeepAR). …”
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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

“…AI algorithms, particularly deep convolutional neural networks (CNNs), have demonstrated high sensitivity and specificity in interpreting nail images, aiding differential diagnosis as well as enhancing the efficiency of diagnostic processes in a busy clinical setting. …”
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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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Skin Lesion Diagnosis Through Deep Learning and Hybrid Texture Feature Augmentation by Irpan Adiputra Pardosi, Roni Yunis, Arwin Halim

“…The framework integrates handcrafted features with Convolutional Neural Networks (CNNs) to enhance classification accuracy. …”
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SPEED (SPlEnic Embolisation Decisions) study-Decision to treat acute traumatic splenic artery injury in the context of trauma protocol. by Paul Jenkins, Jim Zhong, James Harding, Lexy Sorrell, Jason Smith, Victoria Allgar, Carl Roobottom

“…Data will be collected on an anonymised (REDCap) database. This project will evaluate the impact of service design on embolisation rates and outcomes, as well as evaluating the impact of the variation upon treatment selection and outcomes. …”
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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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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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Prognostic Value of Radiological and Laboratory Biomarkers for Assessing Risk of Adverse Outcome in Patients with COVID-19 by А. D. Strutynskaya, M. А. Karnaushkina, L. I. Dvoretskiy, I. Е. Tyurin

“…The predictive model was built using gradient boosting and artificial neural network with sigmoid activation function.Results. …”
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Studying the Role of Vegetarianism as a Potential Strategy for Cancer Prevention and Treatment, a Bibliometric Analysis by Maria Chrysafi, Maria Gialeli, Constantinos Giaginis, Andreas Y. Troumbis, Georgios K. Vasios

“…Author keywords, their co-occurrence network, and thematic trends were studied. Conclusions: Through synthesizing and critically evaluating insights from the scientific literature, we aim to contribute to the understanding of the potential benefits of vegetarianism in cancer prevention and management. …”
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O2O Recycling Closed-Loop Supply Chain Modeling Based on Classification Process considering Environmental Index by Shidi Miao, Di Liu, Junfeng Ma

“…It is premised on the double lines of online service platform and offline recycling service system, thus forming a pattern of online disposal and offline trading. This mode is capable of integrating upstream and downstream resources on the network platform, creating a recycling and processing mode for the entire industry chain of waste sorting, and developing a circular development mode featuring “resources-products-waste-renewable resources” to realize the recycling of resources. …”
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Synthesis and Characterization of Chemically Cross-Linked Acrylic Acid/Gelatin Hydrogels: Effect of pH and Composition on Swelling and Drug Release by Syed Majid Hanif Bukhari, Samiullah Khan, Muhammad Rehanullah, Nazar Mohammad Ranjha

“…The prepared samples were evaluated for porosity and sol-gel fraction analysis. …”
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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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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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