Prognostic and therapeutic potential of disulfidptosis-related genes in colon adenocarcinoma: a comprehensive multi-omics study by Ye Song, Haoran Zhu, Junyang Wei, Shanxue Yin

“…Single-cell analysis revealed distinct spatial distribution patterns between T cells and epithelial cells. The ProjecTILs algorithm identified a higher proportion of Th1 cells, while Graph Convolutional Network (GCN) analysis showed no significant differences in T cell subtype proportions across different phenotypes. …”
Get full text

Update of safety profile of bile acid sequestrants: A real-world pharmacovigilance study of the FDA adverse event reporting system. by Wangqi Chen, Yuxia Xie, Qinghua Li, Zhenghui Zhu, Xinyan Li, Hong Zhu

“…<h4>Conclusion</h4>This large-scale FAERS study updates the safety profiles of BASs, highlighting distinct risk patterns and delayed complications. The findings support personalized monitoring strategies that consider both drug-specific characteristics and temporal AE patterns.…”
Get full text

Detection Method for Three-Phase Electricity Theft Based on Multi-Dimensional Feature Extraction by Wei Bai, Lan Xiong, Yubei Liao, Zhengyang Tan, Jingang Wang, Zhanlong Zhang

“…In light of this, we propose the Catch22-Conv-Transformer method, a multi-dimensional feature extraction-based approach tailored for the detection of anomalous electricity usage patterns. This methodology leverages both the Catch22 feature set and complementary features to extract sequential features, subsequently employing convolutional networks and the Transformer architecture to discern various types of theft behaviors. …”
Get full text

Enhancing Genomic Data Representation Through BERT-LSTM Hybrid Architecture by Kyeong Ho Kim, Minji Kim, Sohui Kim, Jong-Min Lee

“…We introduce a hybrid architecture that combines Bidirectional Encoder Representations from Transformers (BERT) with Long Short-Term Memory (LSTM) networks to generate comprehensive and compact gene embeddings. …”
Get full text

Inspiring Social Capital Through Community Green Space: Pathways and Implications by Lin YE, Shi HE, Yinghao LI, Zhaohui YAN, Lei HUANG

“…These institutional transformations have fundamentally reshaped social relationship patterns, eroding traditional kinship-based connections and resulting in fragmented community networks and a continuous decline in residents’ sense of belonging. …”
Get full text

High-throughput behavioral screening in Caenorhabditis elegans using machine learning for drug repurposing by Antonio García-Garví, Antonio-José Sánchez-Salmerón

“…We evaluate two main approaches: traditional machine learning models based on behavioral features extracted from the worm’s skeleton using Tierpsy Tracker, and deep neural networks that directly analyse video sequences. …”
Get full text

Global ground-based tropospheric ozone measurements: reference data and individual site trends (2000–2022) from the TOAR-II/HEGIFTOM project by R. Van Malderen, A. M. Thompson, A. M. Thompson, D. E. Kollonige, D. E. Kollonige, R. M. Stauffer, H. G. J. Smit, E. Maillard Barras, C. Vigouroux, I. Petropavlovskikh, I. Petropavlovskikh, T. Leblanc, V. Thouret, P. Wolff, P. Effertz, P. Effertz, D. W. Tarasick, D. Poyraz, G. Ancellet, M.-R. De Backer, S. Evan, V. Flood, M. M. Frey, J. W. Hannigan, J. L. Hernandez, M. Iarlori, B. J. Johnson, N. Jones, R. Kivi, E. Mahieu, G. McConville, K. Müller, T. Nagahama, J. Notholt, A. Piters, N. Prats, R. Querel, D. Smale, W. Steinbrecht, K. Strong, R. Sussmann

“…Reprocessing with uniform procedures, the TOAR-II working group Harmonization and Evaluation of Ground-based Instruments for Free-Tropospheric Ozone Measurements (HEGIFTOM) homogenized public data from five networks: ozonesondes, In-service Aircraft for a Global Observing System (IAGOS) profiles, solar absorption Fourier transform infrared (FTIR) spectrometer measurements, lidar observations, and Dobson Umkehr data. …”
Get full text

Enhancing DDoS Attacks Mitigation Using Machine Learning and Blockchain-Based Mobile Edge Computing in IoT by Mahmoud Chaira, Abdelkader Belhenniche, Roman Chertovskih

“…Our solution leverages the decentralized and tamper-resistant nature of Blockchain technology to enable secure and efficient data collection and processing at the network edge. We evaluate multiple machine learning models, including K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), Transformer architectures, and LightGBM, using the CICDDoS2019 dataset. …”
Get full text

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. …”
Get full text

A Variational-Mode-Decomposition-Cascaded Long Short-Term Memory with Attention Model for VIX Prediction by Do-Hyeon Kim, Dong-Jun Kim, Sun-Yong Choi

“…Financial time-series forecasting presents a significant challenge due to the inherent volatility and complex patterns in market data. This study introduces a novel forecasting framework that integrates Variational Mode Decomposition (VMD) with a Cascaded Long Short-Term Memory (LSTM) network enhanced by an Attention mechanism. …”
Get full text

A clustering-based federated deep learning approach for enhancing diabetes management with privacy-preserving edge artificial intelligence by Xinyi Yang, Juan Li

“…We develop tailored models that enhance prediction accuracy by clustering patients based on carbohydrate (CHO) intake patterns. Utilizing Simple Recurrent Neural Network (SimpleRNN) and Gated Recurrent Unit (GRU) methods, the study evaluates the performance of local patients who contribute to training the cluster and global (non-cluster) models. …”
Get full text

Enhancing hand-drawn diagram recognition through the integration of machine learning and deep learning techniques by Vanita Agrawal, MVV Prasad Kantipudi, Jayant Jagtap

“…This research proposes improvised methods such as Fossum Soergel k-means clustering, morphological Canny Bessel radial basis contour shape factor, Fisher kernel k-nearest neighbor, sing-scurve fuzzy rule generation, and wide context faster regional convolutional neural network to enhance the system’s performance. The system’s performance is evaluated by experimentation with benchmark datasets of hand-drawn flowcharts, finite automata, and business process models. …”
Get full text

Evolution of public broadcasting: TeleJurnal’s viewership trends and strategic implications for business sustainability by Săseanu Ramona, Stanomir Ruxandra, Bădulescu Andreea-Alexandra

“…This research examines the viewership trends of TeleJurnal, the network’s main flagship news program, utilizing data from 2018 to 2022, and projects forecasts for 2023–2025. …”
Get full text

Alzheimer’s Disease Prediction Using Fisher Mantis Optimization and Hybrid Deep Learning Models by Sameer Abbas, Mustafa Yeniad, Javad Rahebi

“…The selected features were classified using a CNN-LSTM model, capturing both spatial and temporal patterns. The MLP-LSTM model was included only for benchmarking purposes. …”
Get full text

Gait Recognition via Enhanced Visual–Audio Ensemble Learning with Decision Support Methods by Ruixiang Kan, Mei Wang, Tian Luo, Hongbing Qiu

“…Gait is considered a valuable biometric feature, and it is essential for uncovering the latent information embedded within gait patterns. Gait recognition methods are expected to serve as significant components in numerous applications. …”
Get full text

Apoptosis-associated genetic mechanisms in the transition from rheumatoid arthritis to osteoporosis: A bioinformatics and functional analysis approach by Hao-Ju Lo, Chun-Hao Tsai, Tsan-Wen Huang

“…Weighted Gene Co-expression Network Analysis (WGCNA) further examined gene relationships with the disease status, identifying co-expression patterns. …”
Get full text

CAPSE-ViT: A Lightweight Framework for Underwater Acoustic Vessel Classification Using Coherent Spectral Estimation and Modified Vision Transformer by Najamuddin NAJAMUDDIN, Usman Ullah SHEIKH, Ahmad Zuri SHA’AMERI

“…Further, the features are processed via a vision transformer (ViT) network. This method enables the model to learn more complex relationships and patterns within the data, thereby improving the classification performance. …”
Get full text

Uncovering genetic mechanisms associated with harmful use of alcohol in admixed Latin Americans by Edson H. B. Amaral, Gabriela de S. G. Britto, Raquel B. de São Pedro, Alberto O. Moreira, Marília O. Scliar, Ricardo Lyra, Natália P. Lima, Caroline A. Feitosa, Camila A. V. Figueiredo, Helena M. Pitangueira, Thiago Magalhães da Silva, Luydson R. S. Vasconcelos, Rodrigo F. Carmo, Maurício L. Barreto, Eduardo Tarazona-Santos, Bernardo L. Horta, Ana L. Brunialti-Godard, Pablo R. S. Oliveira

“…Abstract Background Harmful use of alcohol (HUA) refers to drinking patterns that are associated with increased risk of medical complications and adverse social impacts. …”
Get full text

Quantitative Real-Time RT-PCR Verifying Gene Expression Profile of Cavitations Within Human Jaw Bone by Shahram Ghanaati, Eva Dohle, Fabian Schick, Johann Lechner

“…<b>Methods:</b> This study is designed to determine whether BMDJ/FDOJ samples are indicative of medullary bone pathology by evaluating FDOJ gene expression patterns using quantitative real-time PCR. …”
Get full text

‘Stupid Girls’ vs. ‘Real Men’: Identity Construction and Social Media Polarization over Revenge Porn by Marta Sánchez Cócera

“…Additionally, a more detailed analysis of evaluative resources and linguistic patterns is carried out. …”
Get full text