Warming leads to both earlier and later snowmelt floods over the past 70 years by Yuhan Guo, Yuting Yang, Dawen Yang, Lu Zhang, Hongxing Zheng, Jinghua Xiong, Fangzheng Ruan, Juntai Han, Ziwei Liu

“…Using streamflow observations from 1950–2020 and an event-based analysis that distinguishes flood-generating mechanisms across 2339 Northern Hemisphere, snow-affected catchments, we show that the earlier snowmelt effect can be substantially offset or even reversed by a decelerated snowmelt rate under warming. This results in delayed snowmelt floods in approximately 30% of the catchments, contributing to an overall minor shift on a hemispheric scale (−0.87 ± 2.4 days per decade). …”
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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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Attachment Theory and Physical Well-Being by Mikhail Yu. Kozlov

“…Unsafe internal attachment patterns have a negative impact on the development of a wide range of somatic pathologies, primarily cardiovascular and immune systems, and impaired functioning of the HPA axis, mediated by associative anxiety. …”
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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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Fungal Sepsis in a Tertiary Neonatal Intensive Care Unit: A Cross-sectional Study by Kheya Ghosh Uttam, Purbasha Gupta, Sumon Poddar

“…The general mortality rate was 32.9% (<italic>n</italic> = 26). The babies in group I had a higher mortality rate (37.7%) compared with the babies in group II (23%). …”
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Evaluation of the Effects of Anesthetics and Surgery on Sleep Quality in Patients Undergoing Posterior Spinal Instrumentation Surgery: A Prospective Randomised Clinical Trial by Selcan Akesen, Gökay Eken, Yücel Bilgin, Saltuk Buğra Güler, Elifgül Ulutaş

“…Introduction: The aim of the study is to evaluate the impact of the anesthesia methods and surgical procedure on the sleep patterns and sleep quality of patients undergoing posterior spinal instrumentation, using the Pittsburgh Insomnia Rating Scale-20 (PIRS-20). …”
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AI-DBS study: protocol for a longitudinal prospective observational cohort study of patients with Parkinson’s disease for the development of neuronal fingerprints using artificial... by Martijn Beudel, Rick Schuurman, Rob M A de Bie, Deborah Hubers, Mariëlle J Stam, Martijn G J de Neeling, Bart J Keulen, Arthur W G Buijink, Bernadette C M van Wijk

“…Correlations will be tested between spectral features of LFP data and symptom severity, which will be assessed using (1) inertial sensor data from a wearable smartwatch, (2) clinical rating scales and (3) patient diaries and analysed using conventional descriptive statistics and artificial intelligence algorithms. …”
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Investigation on Potential-Induced Degradation in a 50 MWp Crystalline Silicon Photovoltaic Power Plant by Jingsheng Huang, Hongtao Li, Yaojie Sun, He Wang, Hong Yang

“…The results obtained in this paper show that the maximum power degradation rate of solar modules was as high as 53.26% after only one year of operation because of PID in the field. …”
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Understanding the changes in multi-structure, physicochemical properties, and in vitro digestibility of quinoa starch by annealing with hydrogen-infused and plasma-activated water... by Hang Liu, Ge Tian, Shanshan Gao, Shuang Liu

“…The total hydrolysis rate and rapidly digestive starch content decreased in QS after ANN treatment, and resistant starch level markedly increased. …”
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Response surface optimization reveals monthly total flavonoid peaks in Ginkgo biloba leaves with corresponding DPPH scavenging activity by Xiaoyu Shen, Yangjie Lu, Qi Zhu, Yangbo Zhang, Li Zeng

“…Following RS optimization, the optimal extraction conditions for GB flavonoids were identified as follows: extraction rate of 1.175% at 61 °C for 30 min using 77% ethanol. …”
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Investigating thermal effects on void formation in electromigration using thermoreflectance imaging by Kengo ARAKI, Kanji TAMAI, Reiko KURIYAMA, Kazuya TATSUMI

“…Furthermore, the void growth rate and the line temperature near the voids followed an exponential relation in the void growth period. …”
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Predictive Growth Modeling of Listeria monocytogenes in Rice Balls and Its Risk Assessment by Seoungsoon Yeo, Misook Kim

“…The effects of temperature on bacterial growth rate and lag time were evaluated using the square root model. …”
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Mouthwash Use in General Population: Results from Adult Dental Health Survey in Grampian, Scotland by Kirstin Rhodes, Rochelle Morgan, Iain Bovaird, Claudia Cunningham, Michal M. Kawecki, Tatiana V. Macfarlane, Ray Watkins

“…Objectives: The purpose of this study was to determine the pattern of mouthwash use and to investigate the associated factors in general population.Material and Methods: An Adult Dental Health Survey was conducted on 3,022 residents of Grampian region of Scotland (adjusted participation rate 58.2%). …”
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Experience with Early Enteral Feeding in a Patient with Venoarterial Extracorporeal Membrane Oxygenation by V. V. Lomivorotov, S. M Yefremov, A. V. Bogachev, I. A. Kornilov

“…In addition, an inverse correlation was found between the serum concentration of lactate and the daily volume of diuresis. The rate of hourly diuresis had a direct correlation with respiratory index and an inverse correlation with oxygenation index. …”
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The 2015 guidelines for the laboratory diagnosis of rheumatic diseases by the All-Russian Public Organization «Association of Rheumatology of Russia» by E. N. Aleksandrova, A. A. Novikov, E. L. Nasonov

“…The important laboratory markers of RDs are acutephase indicators (erythrocyte sedimentation rate, C-reactive protein, etc.) that can assess the inflammatory activity of the disease, its progression pattern, and prognosis during the chronic inflammatory process, as well as therapeutic efficiency. …”
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An analysis of spatial distribution characteristics and driving factors of traditional villages in the Loess Plateau. by Xiaobin Bao, Yingna Yang, Jianqing Qi, Yanbing He

“…Among them, the density of cultural heritage sites (q = 0.546) is the primary driving factor, followed by annual precipitation (q = 0.458), population size (q = 0.457), and urbanization rate (q = 0.354). The interaction between factors is significant and mostly shows non-linear enhancement, for instance, the interactive explanatory power of population size and the density of cultural heritage sites is as high as 0.852.…”
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Automatic Detection of Concrete Spalling Using Piecewise Linear Stochastic Gradient Descent Logistic Regression and Image Texture Analysis by Nhat-Duc Hoang, Quoc-Lam Nguyen, Xuan-Linh Tran

“…This improvement can enhance the capability of logistic regression in dealing with spall detection as a complex pattern classification problem. Experiments with 1240 collected image samples show that PL-SGDLR can help to deliver a good detection accuracy (classification accuracy rate = 90.24%). …”
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