GRLGRN: graph representation-based learning to infer gene regulatory networks from single-cell RNA-seq data by Kai Wang, Yulong Li, Fei Liu, Xiaoli Luan, Xinglong Wang, Jingwen Zhou

“…The reconstruction of GRNs can help investigate cellular dynamics, drug design, and metabolic systems, and the rapid development of single-cell RNA sequencing (scRNA-seq) technology provides important opportunities while posing significant challenges for reconstructing GRNs. …”
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Single-Image Superresolution for RGB Remote Sensing Imagery via Multiscale CNN-Transformer Feature Fusion by Xudong Yao, Haopeng Zhang, Sizhe Wen, Zhenwei Shi, Zhiguo Jiang

“…Single-image superresolution (SISR) of remote sensing images aims to improve image resolution through algorithmic means while restoring rich high-frequency detailed information. …”
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Revolutionizing Electric Vehicle Charging Stations with Efficient Deep Q Networks Powered by Multimodal Bioinspired Analysis for Improved Performance by Sugunakar Mamidala, Yellapragada Venkata Pavan Kumar, Rammohan Mallipeddi

“…The DQN enables continuous learning from changing demand and grid conditions, while ALO and MFO identify optimal station locations, reducing energy consumption and emissions. …”
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Analysis of the Current State of Digitalization İmplementation in the Banking System of Azerbaijan by K. N. Atayev

“…According to statistical data for 2024, the majority of banking operations were conducted through electronic channels, while the volume of non-cash payments and electronic commerce transactions reached record levels. …”
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Identification of key genes and immune infiltration mechanisms in limb ischemia-reperfusion injury: a bioinformatics and experimental study by Qiyun Shi, Taotao Tian, Yanfeng Li

“…Random forest, LASSO regression, algorithms identified feature genes, validated in a rat limb IRI model using RT-qPCR, and histology. …”
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Exploring Transfer Learning for Anthropogenic Geomorphic Feature Extraction from Land Surface Parameters Using UNet by Aaron E. Maxwell, Sarah Farhadpour, Muhammad Ali

“…Semantic segmentation algorithms, such as UNet, that rely on convolutional neural network (CNN)-based architectures, due to their ability to capture local textures and spatial context, have shown promise for anthropogenic geomorphic feature extraction when using land surface parameters (LSPs) derived from digital terrain models (DTMs) as input predictor variables. …”
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Comprehensive multi-omics and machine learning framework for glioma subtyping and precision therapeutics by Yi Ding, Zhaiyue Xu, Wenjing Hu, Peng Deng, Mian Ma, Jiandong Wu

“…Dual checkpoint blockade or T-cell-rejuvenation strategies may benefit CS2 tumours, while metabolic inhibitors could prove effective in CS3. …”
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A Distributed Collaborative Navigation Strategy Based on Adaptive Extended Kalman Filter Integrated Positioning and Model Predictive Control for Global Navigation Satellite System/... by Wanqiang Chen, Yunpeng Jing, Shuo Zhao, Lei Yan, Quancheng Liu, Zichang He

“…In the field of multi-robot cooperative localization and task planning, traditional filtering algorithms encounter synchronization and consistency issues during multi-source data fusion. …”
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Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China by Ningjing Yang, Yuning Wang, Ying Li, Dongying Xiao, Ruirui Cui, Nana Li, Rong Liu, Jing Chai, Xingrong Shen, Debin Wang

“…., lipid lowering medication prescription) using self-designed algorithms. While the encounter-based measures included number or rate of visits for HL, currently-noticed hyperlipidemia (CNHL, or HL noticed during the current consultation), and ever-diagnosed hyperlipidemia (EDHL). …”
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Optimizing AI Transformer Models for <italic>CO</italic>&#x2082; Emission Prediction in Self-Driving Vehicles With Mobile/Multi-Access Edge Computing Support by Javier Saez-Perez, Pablo Benlloch-Caballero, David Tena-Gago, Jose Garcia-Rodriguez, Jose Maria Alcaraz Calero, Qi Wang

“…Furthermore, we have deployed a 5G emulation testbed with MEC capabilities to demonstrate the proposed Deep Learning (DL) resilience of the model to changes and concurrent connections. While delays for 2 to 16 connected vehicles have grown linearly with a maximum delay value of 41.01 ms, resource limitations have arisen with 32 or more cars due to varied delays, necessitating additional physical resources for the emulated 5G network to achieve better performance under high stress. …”
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Comprehensive Multi-indicator Prediction Model for Storage Quality of Multi-cultivar Kiwifruit Based on Visible-Near Infrared Spectroscopy by Zizhao LIANG, Xin LI, Pu LIU, Wenqiang GUAN, Ming LI

“…The relative prediction deviations (RPDs) of SSC in the single-cultivar model all exceeded 2.3. For hardness, while the RPD of 'Xu Xiang' was 1.8, those of other cultivars exceeded 2.3. …”
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LSTM-Enhanced Deep Reinforcement Learning for Robust Trajectory Tracking Control of Skid-Steer Mobile Robots Under Terra-Mechanical Constraints by Jose Manuel Alcayaga, Oswaldo Anibal Menéndez, Miguel Attilio Torres-Torriti, Juan Pablo Vásconez, Tito Arévalo-Ramirez, Alvaro Javier Prado Romo

“…This contribution strengthens the robustness and adaptability of DRL agents by enabling better generalization of learned policies compared with their baseline counterparts, while also significantly improving trajectory tracking performance. …”
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Analysis of spatio-temporal fungal growth dynamics under different environmental conditions by Liselotte De Ligne, Guillermo Vidal-Diez de Ulzurrun, Jan M. Baetens, Jan Van den Bulcke, Joris Van Acker, Bernard De Baets

“…Fortunately, more automated ways of measurement are gaining momentum due to the availability of cheap imaging and processing equipment and the development of dedicated image analysis algorithms. In this paper, we use image analysis to assess the impact of environmental conditions on the growth dynamics of two economically important fungal species, Coniophora puteana and Rhizoctonia solani. …”
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HoRNS-CNN model: an energy-efficient fully homomorphic residue number system convolutional neural network model for privacy-preserving classification of dyslexia neural-biomarkers by Opeyemi Lateef Usman, Ravie Chandren Muniyandi, Khairuddin Omar, Mazlyfarina Mohamad, Ayoade Akeem Owoade, Morufat Adebola Kareem

“…The model can predict 400,000 neural-biomarker features in one hour, providing an effective tool for analyzing neuroimages while ensuring privacy and security.…”
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Improving aboveground biomass estimation by integrating ICESat-2 LiDAR sampling and tree species stratification strategies using multi-source datasets by Pan Liu, Chunying Ren, Zongming Wang, Mingming Jia

“…The AGB estimates exhibited a south-north gradient in all models, while UTSS performed best in both the low and high values. …”
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Appropriateness of NHS 111 Wales outcomes—using the Call Prioritisation Streaming System: a RAND/UCLA modified Delphi method by Craig Brown, Conrad Fivaz, Rebecca Malin, Mike Brady, Rhiannon Elizabeth Roynon, Peter Noblett

“…It achieves this by integrating individual patient data with a comprehensive computerised knowledge base, employing advanced software algorithms to produce recommendations and dispositions.Objectives While CPSS offers many advantages, its introduction marked a major shift in clinical digital processes. …”
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Practical applications of methods to incorporate patient preferences into medical decision models: a scoping review by Jakub Fusiak, Kousha Sarpari, Inger Ma, Ulrich Mansmann, Verena S. Hoffmann

“…Abstract Background Algorithms and models increasingly support clinical and shared decision-making. …”
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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence–Enabled ECGs by Scott Anjewierden, Donnchadh O'Sullivan, Kathryn E. Mangold, Grace Greason, Itzhak Zachi Attia, Francisco Lopez‐Jimenez, Paul A. Friedman, Samuel J. Asirvatham, Jason Anderson, Benjamin W. Eidem, Jonathan N. Johnson, Shisheer Havangi Prakash, Talha Niaz, Malini Madhavan

“…We aimed to develop novel artificial intelligence–enabled ECG algorithms for LVSD and RVSD detection in pediatric patients. …”
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Hidden diversity in anthropophilic sand flies of the Monticola Series (Diptera, Psychodidae) by Bruno Leite Rodrigues, Alessandra Gutierrez de Oliveira, Leonardo Estevam Honorato da Silva, Thiago Vasconcelos dos Santos, Lidiane de Nazaré Carvalho de Oliveira, Felipe Dutra Rêgo, Andrey José de Andrade, Glédson Bandeira Maia, Israel de Souza Pinto, José Dilermando Andrade Filho, Eunice Aparecida Bianchi Galati

“…Species-delimitation algorithms split our dataset into at least three putative species for each taxon. …”
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Automated Recognition of Abnormalities in Gastrointestinal Endoscopic Images – Evaluation of an AI Tool for Identifying Polyps and Other Irregularities by Weronika Jarych, Elżbieta Tokarczyk, Patryk Iglewski, Daria Ziemińska, Karina Motolko, Rafał Burczyk, Konrad Duszyński, Michał Kociński, Jan Reinald Wendt

“…In conclusion, the study highlights the promising role of AI in gastrointestinal endoscopy while underscoring the importance of continued research, algorithmic refinement, and the establishment of regulatory frameworks to fully harness its clinical potential. …”
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