First experimental validation of silicon-based sensors for monitoring ultra-high dose rate electron beams by Elisabetta Medina, Elisabetta Medina, Arianna Ferro, Arianna Ferro, Mohammad Abujami, Mohammad Abujami, Aurora Camperi, Matteo Centis Vignali, Emanuele Data, Emanuele Data, Damiano Del Sarto, Damiano Del Sarto, Umberto Deut, Umberto Deut, Fabio Di Martino, Fabio Di Martino, Fabio Di Martino, Mohammad Fadavi Mazinani, Marco Ferrero, Veronica Ferrero, Simona Giordanengo, Oscar A. Martì Villarreal, Mohammad Amin Hosseini, Mohammad Amin Hosseini, Felix Mas Milian, Felix Mas Milian, Luigi Masturzo, Luigi Masturzo, Luigi Masturzo, Luigi Masturzo, Diango M. Montalvan Olivares, Diango M. Montalvan Olivares, Marco Montefiori, Marco Montefiori, Giovanni Paternoster, Jake Harold Pensavalle, Jake Harold Pensavalle, Jake Harold Pensavalle, Jake Harold Pensavalle, Valentina Sola, Valentina Sola, Roberto Cirio, Roberto Cirio, Roberto Sacchi, Roberto Sacchi, Anna Vignati, Anna Vignati

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STOCHASTIC PRICING MODEL FOR THE REAL ESTATE MARKET: FORMATION OF LOG-NORMAL GENERAL POPULATION by Oleg V. Rusakov, Michael B. Laskin, Olga I. Jaksumbaeva

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Rules of the automated synthesis final markovs-koy a chain describing finishing of the multipack-age message in connection "point-point" by Vladimir Anatolievich Tsimbal, Oleg Igorevich Sorokin, Maxim Arturovich Lyagin, Andrey Aleksandrovich Berezhnoy, Nikita Viktorovich Kruchkov, Vitaliy Vladimirovich Hoptar

“…Rules are developed for the automated synthesis of a matrix of transitive probabilities and a matrix of steps of the transitions necessary for research of efficiency (under is likelihood-time characteristics) deliveries of multi-package messages in systems of data transmission with various parametres. Developed scientific and methodological apparatus is the basis for further study of the dependence of the probability of prompt delivery of multipackage messages in data transmission systems with different parameters: the number of sources, receipts, recipient, and also at different length of the package, the receipt, the transfer rate of information.…”
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Current research on profile monitoring Atuais pesquisas em monitoramento de perfis by William H. Woodall

“…At each sampling stage one observes a collection of data points that can be represented by a curve (or profile). …”
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THE AUTOMATED CONTROL SYSTEM OF PARAMETERS OF STATIONARYAND MOBILE OBJECTS by Valery Petrovich Mochalov, Natalia Yurievna Bratchenko, Sergey Vladimirovich Yakovlev

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MACHINE LEARNING TECHNIQUES FOR RETINOPATHY DETECTION IN DIABETIC PATIENTS by Ajay Kushwaha, Ahankari Sachin Suresh, Chennoju Phanindra, Anil Kumar Sahu, Devanand Bhonsle, Yamini Chouhan

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Attitude of Students of Computer Science Specialites to Including Computer Simulators and Business Games in the Academic Process by Polina Mikisheva, Nazgul Mustafina

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IFRS Statements and Managerial Accounting Principles: Harmonization Potential by Yuliya Andreevna Shcheglovskaya

“…The article is devoted to the problem of compelling sufficient data base system as a required element for effective and timely managerial decision process based on IFRS framework, statements and management accounting principles. …”
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Transcriptome datasets of salt-stressed tomato plants treated with zinc oxide nanoparticlesMendeley DataSRR30014447 - SRR30014450SRR30014447 - SRR30014450PRJNA1141123SRR30014447 -... by Mostafa Ahmed, Zoltán Tóth, Diaa Attia Marrez, Roquia Rizk, Donia Abdul-Hamid, Kincső Decsi

“…All the aforementioned data is encompassed under the Mendeley database. …”
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Spectral-Spatial Collaborative Pretraining Framework With Multiconstraint Cooperation for Hyperspectral–Multispectral Image Fusion by Jia Jia, Haoyang Yu, Chengjun Wang, Ke Zheng, Jiaxin Li, Jiaochan Hu

“…Specifically, in the first stage, both spatial and spectral inverse modules are adaptively pretrained from the original HSI and MSI, providing initialize parameters for further optimization; in the second stage, the model learns spatial and spectral degradation modules to support the construction of inverse modules for the subsequent stage; in the third stage, guided by pretrained parameters, we further optimize the inverse mapping and effectively extract spectral-spatial information at a different resolution, thereby enhancing the fusion performance and applicability. Experimental results on simulated and real satellite data verify the superiority of our proposed method in recovering spatial details and preserving spectral fidelity.…”
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ICA-Based Resting-State Networks Obtained on Large Autism fMRI Dataset ABIDE by Sjir J. C. Schielen, Jesper Pilmeyer, Albert P. Aldenkamp, Danny Ruijters, Svitlana Zinger

“…The Autism Brain Imaging Data Exchange (ABIDE) facilitates this research through its extensive data-sharing initiative. …”
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Tracking U.S. Land Cover Changes: A Dataset of Sentinel-2 Imagery and Dynamic World Labels (2016–2024) by Antonio Rangel, Juan Terven, Diana-Margarita Córdova-Esparza, Julio-Alejandro Romero-González, Alfonso Ramírez-Pedraza, Edgar A. Chávez-Urbiola, Francisco. J. Willars-Rodríguez, Gendry Alfonso-Francia

“…To ease the complexities of remote sensing data handling, we supply comprehensive code for data loading, basic analysis, and visualization. …”
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Dataset on Programming Competencies Development Using Scratch and a Recommender System in a Non-WEIRD Primary School Context by Jesennia Cárdenas-Cobo, Cristian Vidal-Silva, Nicolás Máquez

“…This resource is particularly valuable for researchers and practitioners interested in computational thinking development, educational data mining, personalized learning systems, and digital equity initiatives. …”
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A Complementary Dataset of Scalp EEG Recordings Featuring Participants with Alzheimer’s Disease, Frontotemporal Dementia, and Healthy Controls, Obtained from Photostimulation EEG by Aimilia Ntetska, Andreas Miltiadous, Markos G. Tsipouras, Katerina D. Tzimourta, Theodora Afrantou, Panagiotis Ioannidis, Dimitrios G. Tsalikakis, Konstantinos Sakkas, Emmanouil D. Oikonomou, Nikolaos Grigoriadis, Pantelis Angelidis, Nikolaos Giannakeas, Alexandros T. Tzallas

“…Additionally, a fully preprocessed version is included, using EEGLAB-based pipelines that involve filtering, artifact removal, and Independent Component Analysis, preparing the data for machine learning applications. This new dataset enables the study of brain responses to visual stimulation across different cognitive states and supports the development and validation of automated classification algorithms for dementia detection. …”
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Visual Footprint of Separation Through Membrane Distillation on YouTube by Ersin Aytaç, Mohamed Khayet

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A Machine Learning Dataset of Artificial Inner Ring Damage on Cylindrical Roller Bearings Measured Under Varying Cross-Influences by Christopher Schnur, Payman Goodarzi, Yannick Robin, Julian Schauer, Andreas Schütze

“…In practical machine learning (ML) applications, covariate shifts and dependencies can significantly impact model robustness and prediction quality, leading to performance degradation under distribution shifts. …”
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Synthetic Dataset for Analyzing Geometry-Dependent Optical Properties of All-Pass Micro-Ring Resonators by Sebastian Valencia-Garzon, Esteban Gonzalez-Valencia, Nelson Gómez-Cardona, Andres Calvo-Salcedo, J. A. Jaramillo-Villegas, Jorge Montoya-Cardona, Erick Reyes-Vera

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Nearest-Better Network-Assisted Fitness Landscape Analysis of Contaminant Source Identification in Water Distribution Network by Yiya Diao, Changhe Li, Sanyou Zeng, Shengxiang Yang

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Historical Bolide Infrasound Dataset (1960–1972) by Elizabeth A. Silber, Rodney W. Whitaker

“…Air Force Technical Applications Center’s global microbarometer network between 1960 and 1972. …”
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Computing Non-Dominated Flexible Skylines in Vertically Distributed Datasets with No Random Access by Davide Martinenghi

“…Top-<i>k</i> queries are a key tool in vertically distributed scenarios and are widely applied in critical applications involving sensitive data. Classical top-<i>k</i> algorithms typically resort to <i>sorted access</i> to sequentially scan the dataset and to <i>random access</i> to retrieve a tuple by its id. …”
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