Assessing water quality environmental grades using hyperspectral images and a deep learning model: A case study in Jiangsu, China by Hongran Li, Hui Zhao, Chao Wei, Min Cao, Jian Zhang, Heng Zhang, Dongqing Yuan

“…This study addresses these limitations by leveraging hyperspectral images (HSIs) analysis and introducing a capsule network (CapsNet) model enhanced with a multidimensional integration attention (MDIA) mechanism. …”
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A hybrid integration framework based on LOOCV and SARIMA: relationship exploring and predictive analysis between discipline attention and literature research by Yulin Zhao, Junke Li, Kai Liu, Chaowang Shang

“…Based on this, this paper proposed a relationship analysis and predictive analysis (RAPA) framework based on leave-one-out cross-validation (LOOCV) and Seasonal Auto-Regressive Integrated Moving Average (SARIMA) to explore the relationship between subject attention and literature research from the perspective of junior high school information technology. …”
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A hybrid framework for assessing regional inertia estimation in bulk power systems using COI-driven spectral clustering by Alexander Sanchez-Ocampo, Mario R. Arrieta Paternina, Juan M. Ramirez, Lucas L. Fernandes, Alejandro Zamora-Mendez, Petr Korba, Miguel Ramirez-Gonzalez

“…This paper proposes a novel grid partitioning method that enhances spectral clustering to identify regional centres of inertia (RCOIs) using complex network analysis. These RCOIs enable precise inertia estimation through an auto-regressive moving average (ARMAX) model, which combines data-driven and model-based approaches to achieve this. …”
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Performance degradation assessment method for linear motor feed systems driven by digital twins by Zeqing Yang, Yiding Yao, Wei Cui, Yingshu Chen, Beibei Liu, Yi Jin, Yanrui Zhang, Hongwei Zhao, Guofeng Zhang, Wei Yi, Zonghua Zhang

“…A current simulation dataset for both normal and demagnetization degradation conditions is constructed.In response to the challenges posed by the temporal dependence of operational data and the difficulty of identifying degradation states, and leveraging the superior data transformation capabilities of Gramian Angular Field (GAF), which effectively preserves temporal information, this study proposes a performance degradation assessment model combining GAF encoding with the AlexNet convolutional neural network. …”
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Study on dynamic resilient modulus prediction model of subgrade fine-grained soil based on physical property parameters by Fang Guo, Wei Gu

“…Subsequently, using the data from this study and previous research, a correlation analysis was conducted on the factors affecting the resilient modulus, identifying the factors that contribute significantly to the resilient modulus. …”
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EEG-Driven Arm Movement Decoding: Combining Connectivity and Amplitude Features for Enhanced Brain–Computer Interface Performance by Hamidreza Darvishi, Ahmadreza Mohammadi, Mohammad Hossein Maghami, Meysam Sadeghi, Mohamad Sawan

“…A feedforward neural network achieved average metrics of: Pearson correlation 0.829 ± 0.077, R-squared value 0.675 ± 0.126, and root mean square error (RMSE) 0.579 ± 0.098 in predicting EMG amplitudes indicative of arm movement angles. …”
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Evaluating Time Series Models for Monthly Rainfall Forecasting in Arid Regions: Insights from Tamanghasset (1953–2021), Southern Algeria by Ballah Abderrahmane, Morad Chahid, Mourad Aqnouy, Adam M. Milewski, Benaabidate Lahcen

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Application of state of health estimation and remaining useful life prediction for lithium-ion batteries based on AT-CNN-BiLSTM by Feng-Ming Zhao, De-Xin Gao, Yuan-Ming Cheng, Qing Yang

“…Initially, key parameters such as voltage, current, temperature, and SOH are extracted and averaged for each cycle to ensure the uniformity and reliability of the input data. …”
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Characteristics and framework analysis of Department of Defense hospital Antibiotic Stewardship Programs guided by the Centers for Disease Control and Prevention Core Elements by LeeAnne C. Lynch, Katrin Mende, Rana F. Hamdy, Cara H. Olsen, Paige E. Waterman, David R. Tribble

“… Abstract Objective: Characterization and assessment of Department of Defense’s (DoD’s) Antibiotic Stewardship Programs (ASPs) to determine adherence to Centers for Disease Control and Prevention (CDC) Core Elements and compare to national adherence Design: Retrospective, observational with supplemental survey Methods: Facility characteristics and CDC Core Elements (CE) adherence data for 2017–2021 were retrieved from the National Healthcare Safety Network’s (NHSN) annual hospital survey with DoD data from the Defense Health Agency and national data from the Antibiotic Resistance and Patient Safety Portal. …”
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Prediction of Magnetic Fields in Single-Phase Transformers Under Excitation Inrush Based on Machine Learning by Qingjun Peng, Hantao Du, Zezhong Zheng, Haowei Zhu, Yuhang Fang

“…Experimental results indicate that the mean absolute percentage error (MAPE) for predicting the transformer’s magnetic field using the deep neural network (DNN) model is 4.02%. The average time to obtain a single magnetic field data prediction is 0.41 s, which is 46.68 times faster than traditional finite element analysis (FEA) method, validating the effectiveness of machine learning for magnetic field prediction.…”
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Hybrid SARIMA+BO-LSTM Framework for Forecasting EV Adoption: A Road to Net-Zero in Ireland by Afaq Khattak, Brian Caulfield

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Multimodal GeoAI: An integrated spatio-temporal topic-sentiment model for the analysis of geo-social media posts for disaster management by David Hanny, Bernd Resch

“…The analysis of online communication on social networks has become a central research interest to improve disaster management. …”
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Pharmacovigilance of drug-induced cataract using the FDA Adverse Event Reporting System by Si-Yuan Hong, Wen-Rui Lu, Xiao-Dong Chen, Hui-Ying Rao, Han Chen

“…This study investigates the associations between medications and cataract development using real-world data from the FDA Adverse Event Reporting System (FAERS) from Q1 2004 to Q3 2024. …”
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Understanding the Engagement and Interaction of Superusers and Regular Users in UK Respiratory Online Health Communities: Deep Learning–Based Sentiment Analysis by Xiancheng Li, Emanuela Vaghi, Gabriella Pasi, Neil S Coulson, Anna De Simoni, Marco Viviani

“…MethodsWe conducted sentiment analysis on anonymized data from 2 UK respiratory OHCs hosted by Asthma UK (AUK), and the British Lung Foundation (BLF) charities between 2006-2016 and 2012-2016, respectively, using the Bio-Bidirectional Encoder Representation from Transformers (BioBERT), a pretrained language representation model. …”
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An innovative approach to advanced voice classification of sacred Quranic recitations through multimodal fusion by Esraa Hassan, Abeer Saber, Omar Alqahtani, Nora El-Rashidy, Samar Elbedwehy

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Mechanistic insights into the cardiovascular effects of acute heat exposure: A multi-omics analysis based on a randomized crossover trial by Xinlei Zhu, Xihao Du, Yixiang Zhu, Lu Zhou, Cong Liu, Yue Niu, Qingli Zhang, Yixuan Jiang, Haidong Kan, Renjie Chen

“…The network-based xMWAS analysis was further conducted. …”
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Fractal-Based Robotic Trading Strategies Using Detrended Fluctuation Analysis and Fractional Derivatives: A Case Study in the Energy Market by Ekaterina Popovska, Galya Georgieva-Tsaneva

“…This paper presents an integrated robotic trading strategy developed for the day-ahead energy market that includes different methods for time series analysis and forecasting, such as Detrended Fluctuation Analysis (DFA), Rescaled Range Analysis (R/S analysis), fractional derivatives, Long Short-Term Memory (LSTM) Networks, and Seasonal Autoregressive Integrated Moving Average (SARIMA) models. …”
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Associations between sex work laws and sex workers' health: A systematic review and meta-analysis of quantitative and qualitative studies. by Lucy Platt, Pippa Grenfell, Rebecca Meiksin, Jocelyn Elmes, Susan G Sherman, Teela Sanders, Peninah Mwangi, Anna-Louise Crago

“…Quantitative findings were limited by high heterogeneity in the meta-analysis for some outcomes and insufficient data to conduct meta-analyses for others, as well as variable sample size and study quality. …”
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Enhanced Flood Monitoring in the Pearl River Basin via GAIN-Reconstructed GRACE Terrestrial Water Storage Anomalies by Jing Wang, Haiyang Li, Shuguang Wu, Guigen Nie, Yawei Wang

“…Using the reconstructed data, we develop the Flood Potential Index (FPI) by integrating GRACE-based TWSA with precipitation data and analyze key characteristics of FPI variability against actual flood events. …”
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Enhancing water saturation predictions from conventional well logs in a carbonate gas reservoir with a hybrid CNN-LSTM model by Ali Gohari Nezhad, Mohammad Emami Niri

“…The methodology includes data pre-processing to de-noise and transform data into a proper format, feature engineering followed by feature selection based on domain knowledge, models’ training, testing, and optimizing. …”
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