La Palma 2021 Eruption (Canary Islands): Measurements and Modelling of Lava Flow Cooling Rates and Applications for Infrastructure Reconstruction and Risk Mitigation by Luis González-de-Vallejo, Aaron Álvarez-Hernández, Mercedes Ferrer, John P. Lockwood, Nemesio M. Pérez, Pedro A. Hernández, Ana Miranda-Hardisson, José A. Rodríguez-Losada, David Afonso-Falcón, Héctor de-los-Ríos, Javier Páez-Padilla, Luis E. Hernández-Gutiérrez

“…To estimate the cooling rates of the lava flows, two physical cooling models were developed based on thermal behavior and geological–geotechnical data. …”
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The radial spreading of volcanic umbrella clouds deduced from satellite measurements by Fred Prata, Andrew T. Prata, Rebecca Tanner, Roy G. Grainger, Michael Borgas, Thomas J. Aubry

“…This model also predicts the observed radial velocities. The data and the model estimates of the volumetric flow rate for the 15 January 2022 Hunga eruption are found to be 3.6–5 × 1011 m3s−1, the largest ever measured.…”
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Artificial Intelligence in Medicine: Transforming The Future of Healthcare by Tashfeen Alam Jan, Shumaila Naz

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Microbiological hazards associated with the use of water in the post‐harvest handling and processing operations of fresh and frozen fruits, vegetables and herbs (ffFVH). Part 2 – A... by EFSA Panel on Biological Hazards (BIOHAZ), Ana Allende, Avelino Alvarez‐Ordóñez, Valeria Bortolaia, Sara Bover‐Cid, Alessandra De Cesare, Wietske Dohmen, Laurent Guillier, Lieve Herman, Liesbeth Jacxsens, Lapo Mughini‐Gras, Maarten Nauta, Jakob Ottoson, Luisa Peixe, Fernando Perez‐Rodriguez, Panagiotis Skandamis, Elisabetta Suffredini, Jen Banach, Bin Zhou, Maria Teresa daSilva Felício, Laura Martino, Winy Messens, Angela Botteon

“…Model parameters include: (i) the dilution rate of the process water, representing the speed of system saturation, equal to the water flux divided by the tank volume; (ii) the transfer rates of total bacterial counts (TBC) and COD from product to water; and (iii) the specific inactivation rate of microorganisms due to HOCl. …”
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Exploring the relationship between data sample size and traffic flow prediction accuracy by Jianhu Zheng, Minghua Wang, Mingfang Huang

“…This paper investigates the relationship between traffic flow prediction performance and data sample size, considering data sample missing rates, duration, and road segment coverage. …”
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A weight clustering algorithm based on sliding window model for stream data by Jiashun Chen, Jianjing Chen, Zhaoman Zhong

“…Building on this, we introduce a sliding window model clustering algorithm, which incorporates detailed threshold calculation processes to enhance clustering accuracy. The algorithm operates in two key stages: (1) constructing a sliding window tailored to the characteristics of streaming data to perform intra-window clustering, and (2) merging clusters within the landmark window to achieve global clustering. …”
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SauDial: The Saudi Arabic dialects game localization datasetMendeley Data by Naif Alanazi, Mohammed Al-Batineh, Hussein Abu-Rayyash

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Using SDPC for Visual Exploratory Analysis of Semiconductor Production Line Sensor Data by Xinxiao Li, Xian-Hua Han, Yongqing Sun

“…Vast amounts of data are continuously collected through sensors fitted into various pieces of equipment and processes in semiconductor production lines. …”
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MEDIUM-RANGE HAIL FORECAST BASED ON GLOBAL ATMOSPHERIC MODEL OUTPUT DATA by A. K. Kagermazov, L. M. Fedchenko, L. T. Sozaeva, M. M. Zhaboeva

“…The results of the forecast were compared with the data of observations on the fall of hail provided by the paramilitary services for active influence on meteorological and other geophysical processes, located within the radius of representativeness of the actual data of the aerological sounding at the Mineralnye Vody station. …”
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Evidence for a constant occipital spotlight of attention using MVPA on EEG data. by María Melcón, Sander van Bree, Yolanda Sánchez-Carro, Laura Barreiro-Fernández, Luca D Kolibius, Elisabet Alzueta, Maria Wimber, Almudena Capilla, Simon Hanslmayr

“…Furthermore, we simulated data with the attentional electrophysiological correlates to control for the ground truth that would give rise to certain classification patterns. …”
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Nonidentifiability of the source of intrinsic noise in gene expression from single-burst data. by Piers J Ingram, Michael P H Stumpf, Jaroslav Stark

“…Over the last few years, experimental data on the fluctuations in gene activity between individual cells and within the same cell over time have confirmed that gene expression is a "noisy" process. …”
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Predicting wheat yield using deep learning and multi-source environmental data by Muhammad Ashfaq, Imran Khan, Dilawar Shah, Shujaat Ali, Muhammad Tahir

“…The results showed that all models achieved less than 10% yield error rates, highlighting their ability to effectively integrate spatial, temporal, and static data. …”
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Eigenvector biomarker for prediction of epileptogenic zones and surgical success from interictal data by Sayantika Roy, Armelle Varillas, Armelle Varillas, Emily A. Pereira, Patrick Myers, Patrick Myers, Golnoosh Kamali, Kristin M. Gunnarsdottir, Kristin M. Gunnarsdottir, Nathan E. Crone, Adam G. Rouse, Jennifer J. Cheng, Michael J. Kinsman, Patrick Landazuri, Patrick Landazuri, Utku Uysal, Carol M. Ulloa, Nathaniel Cameron, Sara Inati, Kareem A. Zaghloul, Varina L. Boerwinkle, Sarah Wyckoff, Niravkumar Barot, Jorge González-Martínez, Joon Y. Kang, Sridevi V. Sarma, Sridevi V. Sarma

“…However, because there is no clinically validated biomarker of the EZ, surgical success rates vary between 30%–70%. The current standard for EZ localization often requires invasive monitoring of patients for several weeks in the hospital during which intracranial EEG (iEEG) data is captured. …”
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Data-driven framework for prediction of mechanical properties of waste glass aggregates concrete by Kennedy C. Onyelowe, Shadi Hanandeh, Viroon Kamchoom, Ahmed M. Ebid, Hamza Imran, Miguel Angel Duque Vaca, Greys Carolina Herrera Morales, Nestor Ulloa, Krishna Prakash Arunachalam

“…Sensitivity analysis was conducted using Hoffman and Gardener’s method as well as the SHAP technique to determine the most influential parameter in the prediction process. Results indicate that the Firefly and Wolf algorithms exhibited the highest prediction accuracy across all four properties, with Wolf emerging as the overall best-performing model due to its superior generalization ability, lower error rates, and high correlation with experimental results. …”
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Bayesian Tapered Narrowband Least Squares for Fractional Cointegration Testing in Panel Data by Oyebayo Ridwan Olaniran, Saidat Fehintola Olaniran, Ali Rashash R. Alzahrani, Nada MohammedSaeed Alharbi, Asma Ahmad Alzahrani

“…Fractional cointegration has been extensively examined in time series analysis, but its extension to heterogeneous panel data with unobserved heterogeneity and cross-sectional dependence remains underdeveloped. …”
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Optimization of Machining Parameters for Reducing Drum Shape Error Phenomenon in Wire Electrical Discharge Machining Processes by Shih-Ming Wang, Li-Jen Hsu, Hariyanto Gunawan, Ren-Qi Tu

“…This study employed experimental analysis to investigate the effect of individual parameters on the shape error and machining removal rate (MRR). Key influential parameters, including open voltage (OV), pulse ON time (ON), pulse OFF time (OFF), and servo voltage (SV), were chosen for data collection using full factorial and Taguchi orthogonal arrays. …”
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LSTM‐based real‐time stress detection using PPG signals on raspberry Pi by Amin Rostami, Koorosh Motaman, Bahram Tarvirdizadeh, Khalil Alipour, Mohammad Ghamari

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Enhancing sleep stage classification with ballistocardiogram signals: feature selection using attention mechanism and XGBoost by Chao Luo, Banteng Liu, Jiayu Chai, Zhijian Teng

“…BCG signals were processed using continuous wavelet transform and low-pass filtering to extract heart rate variability (HRV) and respiratory rate variability (RRV). …”
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Predicting student retention: A comparative study of machine learning approach utilizing sociodemographic and academic factors by Reymark D. Deleña, Norniña J. Dia, Redeemtor R. Sacayan, Joseph C. Sieras, Suhaina A. Khalid, Amer Hussien T. Macatotong, Sacaria B. Gulam

“…Limitations and future directions are discussed, particularly regarding behavioral data integration and model interpretability.…”
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Application research of sample data generation based on improved Cycle-GAN in intrusion detection by ZENG Qingpeng, GUO Hangkai

“…Experiments on the CIC-IDS2017 and NSL-KDD data sets showed that, compared to similar models trained with the original data, the F1 score increased from 0.853 2 to 0.978 6 and the recall rate from 0.914 8 to 0.984 2 on the CIC-IDS2017 data set, and the F1 score increased from 0.646 2 to 0.844 3 and the recall rate from 0.726 to 0.876 8 on the NSL-KDD data set. …”
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