Using Compact 1H NMR, NIR, and Raman Spectroscopy Combined with Multivariate Data Analysis to Monitor a Biocatalyzed Reaction in a Microreaction System by Robin Legner, Alexander Wirtz, Martin Jaeger

“…To facilitate the identification of signals suitable for the extraction of concentration-time (c-t) graphs, 2D heterocorrelation spectra were generated through covariance transformations applied to 1D Raman, NIR, and NMR data. By means of this purely mathematical statistical procedure, the relevant signals of the process media were assigned to educts and products and thus made applicable for univariate data evaluation. …”
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Combined interpretation of geophysical, hydrogeochemical and environmental isotope data in a distal lobe of the Maros fluvial fan, Hungary – A novel approach in aquifer characteris... by Teodóra Szőcs, Ágnes Rotár Szalkai, Levente Magyar, László Palcsu, Márton Bujdosó, János Stickel, Zoltán Püspöki

“…This multidisciplinary investigative approach is applicable to any fluvial fan to support water management. …”
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Estimation of Snow Water Equivalent in Semiarid Zone from Data of Global Numerical Models ICON and GFS/NCEP (Case Study of the Selenga River Basin) by A. N. Shikhov, V. N. Chernykh, A. A. Aurzhanaev, S. V. Pyankov, R. K. Abdullin

“…The possibility to use the global numerical (NWP) models ICON and GFS/NCEP for We consider the applicability of ICON and GFS/NCEP global numerical atmospheric model data for calculating the snow water equivalent (SWE) in the Selenga River basin located the semiarid zone. …”
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The Stellar Abundances and Galactic Evolution Survey (SAGES). II. Machine Learning–based Stellar Parameters for 21 Million Stars from the First Data Release by Hongrui Gu, Zhou Fan, Gang Zhao, Huang Yang, Timothy C. Beers, Wei Wang, Jie Zheng, Jingkun Zhao, Chun Li, Yuqin Chen, Haibo Yuan, Haining Li, Kefeng Tan, Yihan Song, Ali Luo, Nan Song, Yujuan Liu

“…These results are applicable to both giant and dwarf stars. Building upon this mapping, we construct a foundational data set for research on metal-poor stars, the structure of the Milky Way, and beyond. …”
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Adsorption isotherms in roasted specialty coffee (Coffea arabica L.): Dataset and statistical tools for optimizing storage conditions and enhancing shelf lifeMendeley Data by Gentil A. Collazos-Escobar, Andrés F. Bahamón-Monje, Nelson Gutiérrez-Guzmán

“…This work presents a comprehensive dataset of adsorption isotherms and infrared spectral data for roasted specialty coffee (Coffea arabica L.). …”
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Enhanced recurrent attention-deep Q learning with optimal node constrains and effective penalty based model for data transmission scheduling on wireless sensor networks by D.R. Anita Sofia Liz, Yesubai Rubavathi C

“…Based on enhanced reliability, efficiency, and energy conservation in network operations, our results highlight the potential of RA-DQL-ONC&EP as a promising approach for improving data transmission scheduling in WSNs. This optimized scheduling enhances network reliability, ensuring timely and accurate data delivery, which can support various applications such as environmental monitoring, healthcare systems, and smart city infrastructure, ultimately fostering societal well-being and progress. …”
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Data-driven non-intrusive reduced order modelling of selective laser melting additive manufacturing process using proper orthogonal decomposition and convolutional autoencoder by Shubham Chaudhry, Azzedine Abdedou, Azzeddine Soulaïmani

“…Abstract This study proposes and compares two data-driven, non-intrusive reduced-order models (ROMs) for additive manufacturing (AM) processes: a combined proper orthogonal decomposition-artificial neural network (POD-ANN) and a convolutional autoencoder-multilayer perceptron (CAE-MLP). …”
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Enhanced data-driven shear strength predictive modeling framework for RCDBs using explainable boosting-based ensemble learning algorithms coupled with Bayesian optimization by Imad Shakir Abbood, Noorhazlinda Abd Rahman, B.H. Abu Bakar

“…Consequently, the proposed data-driven framework could enhance the understanding of the SS of RCDBs and offer guidance for practical applications.…”
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Association between a body shape index and low back pain: a cross-sectional study highlighting gender-specific differences in NHANES data by Shiwei Xie, Heng Xiao, Gengwu Li, Jigen Zheng, Fan Zhang, Yuping Lan, Mingwei Luo

“…Abstract Background This study aimed to investigate the association between A Body Shape Index (ABSI) and low back pain, with a focus on gender and age differences, using cross-sectional data from the NHANES database. Methods A total of 14,268 participants were included from four NHANES cycles (1999–2004 and 2009–2010). …”
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A Low‐Latitude Three‐Dimensional Ionospheric Electron Density Model Based on Radio Occultation Data Using Artificial Neural Networks With Prior Knowledge by Ding Yang, Hanxian Fang

“…Previous ionospheric models using artificial neural networks (ANN) are only data‐driven, whose effects are entirely affected by observational data. …”
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Comparative analysis of machine learning models for malaria detection using validated synthetic data: a cost-sensitive approach with clinical domain knowledge integration by Gudi V. Chandra Sekhar, Chekol Alemu

“…While synthetic data enables controlled algorithm comparison, real-world clinical validation remains essential before deployment.…”
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Classification of Vietnamese Cashew Nut (Anacardium occidentale L.) Products Using Statistical Algorithms Based on ICP/MS Data: A Study of Food Categorization by Trung Nguyen-Quang, Minh Bui-Quang, Thinh Pham-Van, Nhan Le-Van, Khanh Nguyen-Hoang, Duc Nguyen-Minh, Tinh Phung-Thi, Anh Le-Viet, Duc Tran-Ha Minh, Dat Nguyen-Tien, Tuan-Anh Hoang-Le, Minh Truong-Ngoc

“…Multivariate statistical methods, such as principal components analysis (PCA), were employed to analyze the data obtained and establish the provenance of the cashew nuts. …”
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Exploring the impact of coffee consumption and caffeine intake on cognitive performance in older adults: a comprehensive analysis using NHANES data and gene correlation analysis by Jinrui Li, Kai Yu, Fan Bu, Peng Li, Lei Hao

“…Clinical trial number Not applicable.…”
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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis by Idris Zubairu Sadiq, Babangida Sanusi Katsayal, Bashiru Ibrahim, Maryam Ibrahim, Hassan Aliyu Hassan, Umar Muhammad Ghali, Abdullahi Garba Usman, Abubakar Usman, Sani Isah Abba

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Problem of pain in the USA: evaluating the generalisability of high-impact chronic pain models over time using National Health Interview Survey (NHIS) data by Sean Mackey, Titilola Falasinnu, Md Belal Hossain, Mohammad Ehsanul Karim, Kenneth Arnold Weber

“…Initial models (2016 NHIS data) identified correlates associated with HICP, including hospital stays, diagnosis of specific diseases, psychological symptoms and employment status. …”
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Groundwater–CO₂ emissions relationship in Dutch peatlands derived by machine learning using airborne and ground-based eddy covariance data by L. M. van der Poel, L. V. Bataille, B. Kruijt, W. Franssen, W. Jans, J. Biermann, A. Rietman, A. J. V. Buzacott, Y. van der Velde, R. Boelens, R. W. A. Hutjes

“…This study shows the added value of using ML with different types of instantaneous data and holds potential for future applications.…”
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The chronic heart failure evolutions: Different fates and routes by Piergiuseppe Agostoni, Mattia Chiesa, Elisabetta Salvioni, Michele Emdin, Massimo Piepoli, Gianfranco Sinagra, Michele Senni, Alice Bonomi, Stamatis Adamopoulos, Dimitris Miliopoulos, Massimo Mapelli, Jeness Campodonico, Umberto Attanasio, Anna Apostolo, Emanuele Pestrin, Agostino Rossoni, Damiano Magrì, Stefania Paolillo, Ugo Corrà, Rosa Raimondo, Antonio Cittadini, Annamaria Iorio, Andrea Salzano, Rocco Lagioia, Carlo Vignati, Roberto Badagliacca, Pasquale Perrone Filardi, Michele Correale, Enrico Perna, Marco Metra, Gaia Cattadori, Marco Guazzi, Giuseppe Limongelli, Gianfranco Parati, Fabiana De Martino, Maria Vittoria Matassini, Francesco Bandera, Maurizio Bussotti, Federica Re, Carlo M. Lombardi, Angela B. Scardovi, Susanna Sciomer, Andrea Passantino, Caterina Santolamazza, Davide Girola, Claudio Passino, Marlus Karsten, Savina Nodari, Giulio Pompilio, MECKI score research group

“…We implemented a topological data analysis (TDA), based on 43 variables derived from clinical, biochemical, cardiac ultrasound, and exercise evaluations, to identify several patients' clusters. …”
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Smart resilience through IoT‐enabled natural disaster management: A COVID‐19 response in São Paulo state by Alessandro S. Santos, Icaro Goncales, Angelina Silva, Rodrigo Neves, Igor Teixeira, Eder Barbosa, Vagner Gava, Olga Yoshida

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Design and Verification of a Versatile and Lightweight Radar Platform for High-Resolution Imaging of Glacial Subsurface Structures by Lena Krabbe, Niklas Haberberger, Michael Stelzig, Felix Pfluger, Matthias Braun, Martin Vossiek

“…This technology uncovers critical data on glacier dynamics and climate change impacts, enhancing our understanding of past, present, and future environmental shifts. …”
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Theoretical estimate of relative depth-doses for the asymmetric and spherical 106Ru/106Rh COC-type plaque used in radiotherapy by Eduardo De Paiva

“…Despite the limitations of the method, the results may be used as a guide to future experimental and theoretical studies on this applicator, since there is a lack of available data in literature.…”
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