Fcγ receptor I alpha chain (CD64) expression in macrophages is critical for the onset of meningitis by Escherichia coli K1. by Rahul Mittal, Sunil K Sukumaran, Suresh K Selvaraj, David G Wooster, M Madan Babu, Alan D Schreiber, J Sjef Verbeek, Nemani V Prasadarao

“…Neonatal meningitis due to Escherichia coli K1 is a serious illness with unchanged morbidity and mortality rates for the last few decades. The lack of a comprehensive understanding of the mechanisms involved in the development of meningitis contributes to this poor outcome. …”
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ON THE SPECIFIC STATE OF CRUSTAL STRESSES IN INTRACONTINENTAL OROGENS by Yu. L. Rebetsky

“…If the regional strain rates currently recorded by the GPS-geodesy are taken into account, such additional stresses need to be applied for about 10 million years to fulfill the transition.…”
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SOH Estimation Method for Lithium-Ion Batteries Using Partial Discharge Curves Based on CGKAN by Shengfeng He, Wenhu Qin, Zhonghua Yun, Chao Wu, Chongbin Sun

“…Next, a SOH estimation framework based on the CGKAN model is developed, where 1-Dimensional-Convolutional Neural Networks (1D-CNN) are used to extract deep features from the original data, Bidirectional Gated Recurrent Unit (BiGRU) captures the bidirectional dependencies of the time series, and Kolmogorov–Arnold Networks (KAN) enhances the modeling of complex nonlinear features through its nonlinear mapping capabilities, thereby improving the accuracy of SOH estimation. …”
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Quantifying Objective and Perceived Image Quality Through EEG and Eye-Tracking by Changhyun Lim, Hyun-Jun Jeon, Woojae Jung, Youngshin Kwak, Myong Young Lee, Jung Hyun Ham, Hyun Bin Joo, Oh-Sang Kwon, Dongil Chung

“…Individuals’ pupil diameter successfully tracked (cluster-based permutation p <0.05) both objective and subjective perspectives of image quality. These patterns highlight both the shared characteristics and measurable distinctions between objective image quality and subjective vividness ratings. …”
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AEMS: Adaptive Ensemble GNNs for Multibehavior Stream Recommendation by Ritchie Natuan Caibigan, Punyaphol Horata, Pusadee Seresangtakul

“…The AEMS synergizes long-term preference patterns (derived from historical interactions) with real-time user intents and item attributes (captured through multibehavior signals), integrating them via an adaptive ensemble neural gating mechanism. …”
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Deep learning driven prediction and comparative study of surrounding rock deformation in high speed railway tunnels by Zeping Yang, Zhikai Cheng, Da Wu

“…The methodology incorporates quadratic exponential smoothing for outlier mitigation, followed by sequential feature extraction using convolutional neural networks (CNNs) and bidirectional gated recurrent units (GRUs). Comparative experiments demonstrate the model’s superiority over conventional architectures including RNN, LSTM, GRU, and CNN-GRU. …”
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Forecasting Sales in Live-Streaming Cross-Border E-Commerce in the UK Using the Temporal Fusion Transformer Model by Qi Zhang, Xue Li, Pengbin Gao

“…Our multimodal approach integrates diverse time series data, including historical sales, key opinion leader (KOL) influence, and seasonal patterns. The Temporal Fusion Transformer (TFT) model demonstrated consistently lower Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Squared Error (MSE) across all forecasting horizons compared to other machine learning approaches, including Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and Gated Recurrent Unit(GPU)-accelerated architectures. …”
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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. …”
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Anomaly Detection in Network Traffic via Cross-Domain Federated Graph Representation Learning by Yanli Zhao, Zongduo Liu, Junjie Pang

“…Traditional detection approaches typically rely on statistical features while overlooking the interaction patterns and structural dependencies among traffic flows. …”
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Mannheim Peritoneal Index in the Prediction of Postoperative Complications in Patients with Peritonitis by N. N. Aksenova, F. R. Akhmerov, M. V. Maleyev

“…In patients with local postoperative complications being developed, the MPI values were higher (p<0.05) than in those without them. The mortality rates that have been predicted by means of MPI (16.3%) and actual (15.2%) are actually in agreement. …”
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Amazon Rainforest Exchange of Carbon and Subcanopy Air Flow: Manaus LBA Site—A Complex Terrain Condition by Julio Tóta, David Roy Fitzjarrald, Maria A. F. da Silva Dias

“…We tested the hypothesis that horizontal drainage flow over this study area is significant and can affect the interpretation of the high carbon uptake rates reported by previous works at this site. A similar experimental design as the one by Tóta et al. (2008) was used with a network of wind, air temperature, and CO2 sensors above and below the forest canopy. …”
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Deep Temporal and Structural Embeddings for Robust Unsupervised Anomaly Detection in Dynamic Graphs by Samir Abdaljalil, Hasan Kurban, Rachad Atat, Erchin Serpedin, Khalid Qaraqe

“…We introduce Temporal Structural Graph Anomaly Detection (<sc>T-StructGAD</sc>), an unsupervised framework that leverages Graph Convolutional Gated Recurrent Units (<monospace>GConvGRU</monospace>s) and Long Short-Term Memory networks (<monospace>LSTM</monospace>s) to jointly model both structural and temporal dynamics in graph node embeddings. …”
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Toward AI-Augmented Formal Verification: A Preliminary Investigation of ENGRU and Its Challenges by Chanon Dechsupa, Teerapong Panboonyuen, Wiwat Vatanawood, Praisan Padungweang, Chakchai So-In

“…In this paper, we present ENGRU (Enhanced Gated Recurrent Units), a novel deep learning-based approach for formal verification. …”
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Influence of Previous Emergency Department Visit Information on Care of Current Patients by Ricardo X. Noriega, Juan Nañez, Emily Hartmann, Scott B. Crawford, Chantel D. Sloan-Aagard

“…The primary outcome was the influence of knowledge from prior records on interactions during the most recent visit, measured with 11 Likert-scale ratings. Reviewer agreement was used as an indicator of confidence. …”
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The influence of exercise self-efficacy and gender on the relationship between exercise motivation and physical activity in college students by Jiazhi Sheng, Indang Ariati Binti Ariffin, Jacquline Tham

“…Abstract This study examined the relationships among exercise motivation, exercise self-efficacy, and physical activity rating, as well as the role of exercise self-efficacy in the above relationship. …”
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Prevalence and risk factors of the most common multimorbidity among Canadian adults. by Obed Mortey, Gerald Mugford, Kris Aubrey-Bassler, Hensley H Mariathas, Ugochukwu Odimba, Zhiwei Gao

“…The results from multivariate analysis showed that seven factors were significantly associated with increased odds of the MCM, which included increasing age, being retired from work (retired vs not retired), poorer rating of perceived health, (very good, good, poor vs excellent), increasing problems with sleep quality (satisfied, dissatisfied vs neutral), and abnormal body-mass index (underweight, overweight, obese vs normal). …”
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New Programming Modes of Spinal Cord Stimulation for Chronic Pain: A Systematic Review of Outcomes with Burst and High-Frequency Technology by Jeffrey J. Bergman, Derrick A. Dupré, Nestor D. Tomycz

“…Burst SCS and HF10 SCS have been subjected to randomized controlled studies and have used similar patient pain score reporting on a visual analog scale (VAS) and numeric rating scale (NRS). Results from these studies have reported significant reductions in axial back pain and limb pain in patients sustained for up 20 months with burst SCS treatment and up to 36 months with HF10 SCS. …”
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Spatiotemporal evolution and multi-scenario simulation of the land-use cover change and habitat quality in arid and semi-arid areas: a case study of the urban agglomeration along t... by Tianle Ma, Wenhao Cheng, Wenxuan Yao

“…These findings demonstrate (Hall, Wiley on behalf of the Wildlife Society, 1997, 25(1), 173–82) a reduction in ecological land coverage during the previous period, which correlates with a decrease in the mean HQ. The value ratings in 2010, 2015, and 2020 were 0.4919, 0.4730, and 0.4654, respectively. …”
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Cholera-Related Hypochondriasis and Sleep Effort Among Lebanese General Population by Atifa Nazih Kamaleddine, Sondos Mohamad Naous, Sana Ahmad Tantawi, Lama Ali Alhajj, Nafez Nazih Kamaleddine, Sung Woo Joo, Seockhoon Chung

“…All 472 participants completed the e-survey, including rating scales adapted to assess psychological response to cholera: Stress and Anxiety to Viral Epidemic-6 items (SAVE-6), Obsession with COVID-19 scale (OCS), Coronavirus Reassurance-Seeking Behaviors Scale (CRBS), Insomnia Severity Index, Glasgow Sleep Effort Scale, and Patient Health Questionnaire-9 items. …”
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Assessment of Tourism Development in Belarus: A Comprehensive Analysis of Infrastructure, Cultural Heritage and Natural Resources by Viktoryia Kauchun, Anna Michalska, Walery Zukow

“…Results: The findings indicate moderate tourism development in Belarus (39% rated it as average, 42% as high). Infrastructure quality shows significant regional variation (χ2(4)=31.50, p<0.001, V=0.56). …”
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