DEVELOPING AND VALIDATING COMPREHENSIVE INDICATORS TO EVALUATE THE ECONOMIC EFFICIENCY OF HYDROGEN ENERGY INVESTMENTS by Galevskiy S. G., Haidong Qian

“…Finally, hydrogen energy projects need supportive policies and technology. Regulation and regional disparities persist. Technology can solve these problems and boost hydrogen energy sector growth and low-carbon futures. …”
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Design and Methodology of a Real Estate Fund Index for the Czech Market by Černohorský, Adam

“…Indices were computed using Python-based time-series processing, with quarterly rebalancing and weight capping to reduce concentration risk. …”
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Insights into sustainability and circular economy trends in luxury fashion: A LinkedIn topic modelling study by Aya Abdelmeguid, Georgios Tsironis, Mohamed Afy-Shararah, Konstantinos P. Tsagarakis, Konstantinos Salonitis

“…Additionally, utilising the Google Collab Platform and Python language, this study identifies circular economy and sustainability trends within luxury fashion. …”
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Sistema informático para la gestión del plan de trabajo mensual de los docentes universitarios by Mailyn Torres Vivanco, Ailen Castellanos Gutiérrez

“…En la presente investigación se realiza una revisión de los antecedentes históricos, conceptuales y referenciales acerca del proceso de gestión de información del plan de trabajo de los docentes universitarios. …”
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On the issue of ensuring secure access to information systems using biometric authentication based on a fuzzy image of the user’s identity and neural network transformations by O. I. Bokova, S. V. Kanavin, N. S. Khokhlov, I. V. Gilev, L. A. Lekar

“…Based on two-step authentication of the user’s identity, secure access to the information systems of registered users is implemented. A listing of the program code in Python for creating and training a neural network of a bioidentifier classifier is provided. …”
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ELNdataBridge: facilitating data exchange and collaboration by linking Electronic Lab Notebooks via API by Martin Starman, Fabian Kirchner, Martin Held, Catriona Eschke, Sayed-Ahmad Sahim, Regine Willumeit-Römer, Nicole Jung, Stefan Bräse

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Leveraging Datathons to Teach AI in Undergraduate Medical Education: Case Study by Michael Steven Yao, Lawrence Huang, Emily Leventhal, Clara Sun, Steve J Stephen, Lathan Liou

“…Participant skills in leveraging Python for analyzing medical datasets improved after the datathon, and survey respondents enjoyed participating in the datathon. …”
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Sistema de análisis de supervivencia en el despliegue de servicios telemáticos en centros de datos by Luis Manuel Valera Pérez, Hector Lázaro Martinez Miranda

“…Para su implementación se realizó una revisión de los métodos existentes para el modelado de fallos, análisis de supervivencia en condiciones de censura y truncamiento, así como de métodos como el de Kaplan-Meier, las tablas de vida y el modelo de regresión de Cox. …”
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A workflow for modeling radiolysis in chemically, physically, and geometrically complex scenarios by Giuseppe De Salvo, Stefan Merkens, Andreas Körner, Birk Fritsch, Paolo Malgaretti, Andreas Hutzler, Andrey Chuvilin

“…Model complexity is scrutinized, and potential simplifications are explored using characteristic numbers in experimentally relevant parameter regimes. The reported approach improves computational modeling and correlative experimental methods by promoting cross-community approaches.…”
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Poloxamer-Driven Drug Delivery System for Anti-Inflammatory Drugs Using Small-Angle Neutron Scattering Approach by Rodrigo Rhinow, Margareth K. K. D. Franco, Mont Kumpugdee Vollrath, Guinther Kellermann, Fabiano Yokaichiya

“…The data analysis involved modeling the data using a Python-based routine. The model used consisted of an isotropic solution of polydisperse spherical micelles. …”
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Enhancing prediction of crop yield and soil health assessment for sustainable agriculture using machine learning approach by Kapil Netaji Vhatkar, Shweta Ashish Koparde, Sonali Kothari, Jayesh Sarwade, Kishor Sakur

“…The goal of this research is • to make sophisticated models for precise crop production forecasting and thorough evaluation of soil health, • to improve sustainability by optimize farming methods, and • to assist farmers in making well-informed decisions.Iterative Partitioning-Ensemble Filter (IP-EF) is a technique used for feature selection, enhancing model performance by iteratively partitioning data and refining feature subsets. …”
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ДИНАМІКА НЕСПІВМІРНОЇ НАДСТРУКТУРИ В КРИСТАЛАХ ІЗ СИМЕТРІЄЮ ТЕРМОДИНАМІЧНОГО ПОТЕНЦІАЛУ n=4 by Serhiy Sveleba, Ivan Katerynchuk, Ivan Kuno, Yaroslav Shmygelsky, Serhiy Velgosh, Yu. Bukhnii

“…As the maps of dynamic regimes show, the stochastic regime of an incommensurable superstructure has the coexistence of commensurate long-period phases with incommensurate phases that alternate with each other. …”
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Machine learning-based prediction of optimal antenatal care utilization among reproductive women in Nigeria by Jamilu Sani, Adeyemi Oluwagbemiga, Mohamed Mustaf Ahmed

“…Permutation and Gini importance analyses identified the place of delivery, region, residence, and educational level as the most influential predictors. …”
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Obtención de un modelo de minería de datos aplicado a la deserción universitaria del programa de Ingeniería de Sistemas de la Universidad de Cundinamarca by Holmes Yesid Ayala-Yaguara, Gina Maribel Valenzuela-Sabogal, Alexander Espinosa-García

“…En el proyecto se seleccionaron cinco técnicas de minería de datos para evaluarlas: vecinos más cercanos (K nearest neighbors, KNN), árboles de decisión (decision tree, DT), árboles aleatorios (random forest, RF), regresión logística (logistic regression, LR) y máquinas de vectores soporte (support vector machines, SVM). …”
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Predicting Credit Card Fraud using Supervised Machine Learning Methods: Comparative Analysis by Güner Altan, Metin Recep Zafer

“…The accuracy scores of the algorithms used in the model setup were determined as follows: Logistic Regression, 92.5%; Decision Tree, 93.1%; K-Nearest Neighbour 86.4%; Random Forest 91.8% and Gradient Boosting 86.9% and performance metrics, such as precision, recall, F1 score, and ROC-AUC, were also examined. …”
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Optimized machine learning mechanism for big data healthcare system to predict disease risk factor by Venkata Nagaraju Thatha, Silpa Chalichalamala, Udayaraju Pamula, D. Pramodh Krishna, Manjunath Chinthakunta, Srihari Varma Mantena, Shariff Vahiduddin, Ramesh Vatambeti

“…Additionally, its application in healthcare systems, including clinical decisions and remote patient monitoring, proves its real-world applicability in enhancing early diagnosis and preventive care measures. …”
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Implementation of an Internet of Things Architecture to Monitor Indoor Air Quality: A Case Study During Sleep Periods by Afonso Mota, Carlos Serôdio, Ana Briga-Sá, Antonio Valente

“…Based on the generated data, predictive models can be designed to support decisions on intelligent natural ventilation systems, achieving an optimized, efficient, and ubiquitous solution to moderate the IAQ.…”
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Prediction of mung bean production using machine learning algorithms by Azanu Mirolgn Mequanenit, Aleka Melese Ayalew, Ayodeji Olalekan Salau, Eyerusalem Alebachew Nibret, Million Meshesha

“…Among these, mung bean production takes the highest level of income for most smallholder farmers in all regions of Ethiopia who cultivate mung bean crops. …”
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Technical Aspects of Deploying UAV and Ground Robots for Intelligent Logistics Using YOLO on Embedded Systems by Wissem Dilmi, Sami El Ferik, Fethi Ouerdane, Mustapha K. Khaldi, Abdul-Wahid A. Saif

“…Image processing—particularly vision-based AI—enables real-time tracking, object recognition, and intelligent decision-making, thereby improving supply chain resilience. …”
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Identifying the spatiotemporal evolution of nucleic acid testing sites and their influencing factors to support public health emergency management: A case study in Hangzhou, China by Song Yao, Mingjun Cheng, Yunchen Zhu, Xiangyang Quan, Fangqi Wang, Zhaoxuan Xia, Shan Huang, Yonghua Li

“…The results show that: (1) The number of NAT sites underwent four phases over time and exhibited substantial spatial concentration in Shangcheng, Gongshu, Xihu, and Binjiang districts. (2) The population density, human footprint, and the digital elevation model were the dominant potential influencing factors for the location of NAT sites, with the explanatory power of interactions among influencing factors being higher than that of individual factors. (3) The location of NAT sites in the Shangcheng, Gongshu, Xihu, and Binjiang districts has a significant positive correlation with population density, while the relationship was not significant in other regions. These findings can provide decision-making insights for managing public health emergencies in Hangzhou, as well as in other cities with similar economic and policy conditions.…”
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