East Asian aerosol cleanup has likely contributed to the recent acceleration in global warming by Bjørn H. Samset, Laura J. Wilcox, Robert J. Allen, Camilla W. Stjern, Marianne T. Lund, Sharar Ahmadi, Annica Ekman, Maxwell T. Elling, Luke Fraser-Leach, Paul Griffiths, James Keeble, Tsuyoshi Koshiro, Paul Kushner, Anna Lewinschal, Risto Makkonen, Joonas Merikanto, Pierre Nabat, Larissa Narazenko, Declan O’Donnell, Naga Oshima, Steven T. Rumbold, Toshihiko Takemura, Kostas Tsigaridis, Daniel M. Westervelt

“…Here we show, using a large set of simulations from eight Earth System Models, how a time-evolving 75% reduction in East Asian sulfate emissions partially unmasks greenhouse gas-driven warming and influences the spatial pattern of surface temperature change. We find a rapidly evolving global, annual mean warming of 0.07 ± 0.05 °C, sufficient to be a main driver of the uptick in global warming rate since 2010. …”
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Sleep Restriction and Weekend Sleep Compensation Relate to Eating Behavior in School-Aged Children by Chamorro R, Garrido-González M, Gutierrez M, Santos JL, Weisstaub G

“…Actigraphic recordings measured sleep patterns for 4 consecutive days, including a weekend day. …”
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The relationship between social isolation and cognitive function in older patients with chronic obstructive pulmonary disease: a latent profile analysis by Minghua Han, Hongxia Wu, Huize Xu, Jian Zhao, Zhongwen Chang, Qian Zhao

“…The general information questionnaire, Social Network Scale Brief, Hamilton Depression Scale, Social Support Rating Scale, and Montreal Cognitive Assessment Scale were employed. …”
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Pedagogical university students’ ethical attitudes and competences regarding artificial intelligence: An empirical study by Alicja Baum, Maria Trzcińska-Król

“…Students expressed more positive attitudes towards the benefits of AI (M = 3.22) than levels of understanding of its disadvantages (M = 2.72). Respondents rated their competences (M = 2.65) and knowledge (M = 2.85) regarding AI as below average. …”
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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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Beta-adrenergic reactivity of erythrocyte membranes in adolescents with supraventricular and ventricular arrhythmias before and after radiofrequency ablation by Т. Yu. Rebrova, Yu. E. Perevoznikova, E. F. Muslimova, L. I. Svintsova, S. A. Afanasiev, O. Yu. Dzhaffarova

“…The study showed the possibility of using β-ARM to assess the state of the sympathetic nervous system in patients with methodological limitations in analyzing heart rate variability.…”
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A comprehensive machine learning for high throughput Tuberculosis sequence analysis, functional annotation, and visualization by Md. Saddam Hossain, Md. Parvez Khandocar, Farzana Akter Riti, Md. Yeakub Ali, Prithbey Raj Dey, S M Jahurul Haque, Amira Metouekel, Atrsaw Asrat Mengistie, Mohammed Bourhia, Farid Khallouki, Khalid S. Almaary

“…The World Health Organisation reported that in 2022, 1.3 million people died from tuberculosis, with the death rate potentially reaching 66% if proper treatment isn’t provided. …”
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Composite microbeads of cellulose acetate upcycled from waste for water remediation by Lorenzo Antonelli, Susanna Grasso, Massimo Giuseppe De Cesaris, Nina Felli, Chiara Dal Bosco, Stefano Cinti, Alessandra Gentili

“…An experimental 2³ factorial design was performed to define the best operational conditions of the instrumental setup, defining the flow rate, amount and chemical nature of the packed microbeads. …”
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Investigation of farmers’ awareness of water conservation and its determinants in arid regions: A case study of the Turpan-Hami Basin by Dongping Guo, Abdugheni Abliz, Yue Kong, Jialin Li, Xianhe Liu, Buasi Nurahmat

“…The results revealed that: (1) From 2005 to 2024, the water conservation rate in the Turpan–Hami Basin showed a fluctuating upward trend, surpassing 80 %, yet significant regional disparities in farmers’ water conservation awareness remained; (2) Areas with low levels of awareness were spatially associated with regions of low satisfaction with conservation outcomes and high levels of farmland investment. …”
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Direct scribing of metal microgratings using sawtoothed cemented carbide tools with Johnson-Cook model-based plastic deformation simulation by Minwook Kim, Dae Bo Sim, Yong Tae Kim, Bo Hyun Kim, Jong G. Ok

“…The process achieves a material removal rate of ∼36.4 mm3/min while maintaining groove-to-groove repeatability within ±8 % and limiting tool wear to less than 6 µm after ∼1.2 m of scribing. …”
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An interpretable XAI deep EEG model for schizophrenia diagnosis using feature selection and attention mechanisms by Ahmad Almadhor, Stephen Ojo, Thomas I. Nathaniel, Shtwai Alsubai, Abdullah Alharthi, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…The study proposes a novel automated technique for diagnosing Schizophrenia based on electroencephalogram (EEG) sensor data, aiming to enhance interpretability and prediction performance.MethodsThis research utilizes Deep Learning (DL) models, including the Deep Neural Network (DNN), Bi-Directional Long Short-Term Memory-Gated Recurrent Unit (BiLSTM- GRU), and BiLSTM with Attention, for the detection of Schizophrenia based on EEG data. …”
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Multi-Step Natural Gas Load Forecasting Incorporating Data Complexity Analysis with Finite Features by Ning Tian, Bilin Shao, Huibin Zeng, Meng Ren, Wei Zhao, Xue Zhao, Shuqiang Wu

“…Concurrently, variational mode decomposition (VMD) provides frequency-domain decomposition capability, while the gated recurrent unit (GRU) captures long-term dependencies. …”
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Multiscale Water Cycle Mechanisms and Return Flow Utilization in Paddy Fields of Plain Irrigation Districts by Jie Zhang, Yujiang Xiong, Peihua Jiang, Niannian Yuan, Fengli Liu

“…We propose an integrated optimization strategy combining tillering-stage irrigation/drainage control, multiscale hydraulic interception (control gates and pond weirs), and dynamic watershed storage scheduling. …”
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Trade-offs between machine learning and deep learning for mental illness detection on social media by Zhanyi Ding, Zhongyan Wang, Yeyubei Zhang, Yuchen Cao, Yunchong Liu, Xiaorui Shen, Yexin Tian, Jianglai Dai

“…This study evaluates multiple ML models, including logistic regression, random forest, and LightGBM, alongside DL architectures such as ALBERT and Gated Recurrent Units (GRUs), for both binary and multi-class classification of mental health conditions. …”
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Trypanosoma dionisii in China: ecology and tentative epidemiology by Qin Liu, Mu-xin Chen, Yu-chun Cai, Yuan-yuan Li, Zi-yi Wang, Yun-hai Guo, Yu-wan Hao, Jing-bo Xue, Yi-dan Jing, Fan-na Wei, Yong-bin Wang, Yue-jin Li, Hai-fang Wang, Jun-ling Sun, Ya-li Wang, Gang Wang, Na Wang, Nai-li Guo, Jian-cun Fang, Wei-xiao Chen, Xun-ming Zhou, Yang Yu, Yi Zhang, Jun-hu Chen, Qiang Wang, Shi-zhu Li, Ge Yan, Qun Li

“…Although no evidence of a high risk for human epidemic was found, the widespread presence of this parasites in bat species and a relatively high infection rate observed in the surveyed cats and dogs emphasize the emerging threat it poses to human health. …”
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Neural signatures underlying the effect of social structure on empathy and altruistic behaviors by Xia Tian, Zixin Zheng, Renhui Li, Yue-Jia Luo, Chunliang Feng

“…Afterwards, participants rated the pain experienced by these innocents and shared money with other innocents. …”
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Gesture recognition for hearing impaired people using an ensemble of deep learning models with improving beluga whale optimization-based hyperparameter tuning by Mohammed Assiri, Mahmoud M. Selim

“…For the feature extraction process, the squeeze-and-excitation capsule network (SE-CapsNet) effectively captures spatial hierarchies and complex relationships within gesture patterns. In addition, an ensemble of classification processes, such as bidirectional gated recurrent unit (BiGRU), Variational Autoencoder (VAE), and bidirectional long short-term memory (BiLSTM) technique, is employed. …”
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Wind Speed Forecasting in the Greek Seas Using Hybrid Artificial Neural Networks by Lateef Adesola Afolabi, Takvor Soukissian, Diego Vicinanza, Pasquale Contestabile

“…Of all the ANNs examined, the hybrid model combining Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks demonstrated superior forecasting performance compared to the individual models, as evaluated by standard statistical metrics, while it also exhibited a very good performance at high wind speeds, i.e., greater than 15 m/s. …”
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Forecasting Temperature Time Series Data Using Combined Statistical and Deep Learning Methods: A Case Study of Nairobi County Daily Temperature by John Kamwele Mutinda, Amos Kipkorir Langat, Samuel Musili Mwalili

“…Hybrid forecasting models were then constructed by integrating VMD with both statistical (autoregressive integrated moving average [ARIMA]) and deep learning (gated recurrent unit [GRU], long short-term memory [LSTM], and Transformer) architectures. …”
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An Overview of Deep Learning Applications in Groundwater Level Modeling: Bridging the Gap between Academic Research and Industry Applications by Ahmed Shakir Ali Ali, Farhad Jazaei, Peyman Babakhani, Muhammad Masood Ashiq, Alireza Bakhshaee, Brian Waldron

“…Later, this article delves specifically into the latest advancements in DL for modeling GWL, including recurrent neural network (RNN), long short-term memory (LSTM), and gated recurrent unit (GRU), and discusses their technical promising performance and advantages. …”
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