Applying the Block-Based Programming Language ALICE for Developing Programming Competencies in University Students by Mariuxi Vinueza-Morales, Jesennia Cardenas-Cobo, Jessica Cabezas-Quinto, Cristian Vidal-Silva

“…The information society is part of modern life, and algorithmic thinking and programming are relevant to everybody, regardless of educational background. …”
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Detection Technology for Catenary Stagger Value Based on Acceleration Signals by CHEN Hongming, ZHOU Ning, LU Wenwei, YANG Zixian, CHENG Yao, WANG Dong, ZHANG Weihua

“…［Result & Conclusion］ The proposed method accurately detects catenary stagger values across various operating speeds, achieving a root mean square error as low as 5.84, outperforming other existing algorithms. In brief, the study effectively enhances the measurement efficiency of catenary stagger values, avoiding the limitations imposed by previous methods on operational environmental conditions, and provides a novel approach for catenary stagger value detection.…”
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Virtual Reality-Assisted Goalkeeper Training for Upper Limb Rehabilitation in a Safe and Adapted Patient Environment by Vanesa Herrera, Javier Albusac, Eusebio Angulo, Carlos Gonzalez-Morcillo, Ana de Los Reyes-Guzman, David Vallejo

“…It simulates the activity of a handball goalkeeper, compelling the patient to exercise their arms and hands to regain upper limb mobility and trunk inclination to enhance stability, particularly relevant for wheelchair users. The proposed system aims to simplify technology use, featuring a single VR headset integrating body tracking, and functional and spatial-temporal data analysis algorithms, without the need for additional tracking devices. …”
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What patients and caregivers want to know when consenting to the use of digital behavioral markers by Anika Sonig, Christine Deeney, Meghan E. Hurley, Eric A. Storch, John Herrington, Gabriel Lázaro-Muñoz, Casey J. Zampella, Birkan Tunc, Julia Parish-Morris, Jenny Blumenthal-Barby, Kristin Kostick-Quenet

“…Abstract Artificial intelligence (AI)-based computational tools for deriving digital behavioral markers are increasingly able to automatically detect clinically relevant patterns in mood and behavior through algorithmic analysis of continuously and passively collected data. …”
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The future of AI in government services and global risks: insights from design fictions by Pedro Vitor Marques Nascimento, Paloma Beatriz Belchior de Siqueira, Nathalia Chrispim, Ramon Miranda Chaves, Carlos Eduardo Barbosa, Jano Moreira de Souza

“…Abstract The evolution of government services in the context of Artificial Intelligence (AI) and its long-term implications are relevant topics impacting society. Developments in this area are surrounded by controversies about what is technically possible, what is feasible in terms of implementation, and what is desirable. …”
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Ensemble Learning-Driven and UAV Multispectral Analysis for Estimating the Leaf Nitrogen Content in Winter Wheat by Yu Han, Jiaxue Zhang, Yan Bai, Zihao Liang, Xinhui Guo, Yu Zhao, Meichen Feng, Lujie Xiao, Xiaoyan Song, Meijun Zhang, Wude Yang, Guangxin Li, Sha Yang, Xingxing Qiao, Chao Wang

“…Correlation analysis identified highly relevant indices with LNC. Support Vector Regression (SVR), Random Forest (RF), Ridge Regression (RR), K-Nearest Neighbors (K-NN), and ensemble learning algorithms (Voting and Stacking) were employed to model the relationship between selected vegetation indices and LNC. …”
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Review of Urban Rail Transit Ticket Clearing Methods by WANG Yao, LI Jiming, GAO Shen, LIU Guangjie, XU Zhongquan

“…It is necessary to provide a more reasonable clearing method for the construction and design of ticket clearing systems for relevant cities in China. ［Method］Through an introduction to urban rail transit ticket clearing schemes in both domestic and foreign cities, the ticket clearing methods for multi-line travel in major Chinese cities are analyzed and compared, and the applicable ticket clearing method is selected through analyzing the advantages and disadvantages of the clearing models and algorithms. …”
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Applications of machine learning in potentially toxic elemental contamination in soils: A review by Yan Li, Bao Xiang, Tianyang Wang, Yinhai He, Xiaoyang Liu, Yancheng Li, Shichang Ren, Erdan Wang, Guanlin Guo

“…Hyperspectral data combined with ML methods can predict the content of PTEs in large-scale areas at a low cost. In addition, ML algorithms that integrate environmental covariates offer superior performance in spatial predictions compared with traditional geostatistical methods. …”
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Harnessing artificial intelligence of things for cardiac sensing: current advances and network-based perspectives by Hao Ren, Hao Ren, Hao Ren, Fengshi Jing, Yongcong Ma, Ruining Wang, Chaocheng He, Yufan Wang, Jiandong Zhou, Yu Sun

“…A total of 2,128 papers were included in the analysis.ConclusionFrom our perspective, current advancements in AI-powered IoT cardiac sensors primarily focus on optimizing AI algorithms, such as deep learning techniques, and enhancing the functionality of smart wearable devices for precision medicine. …”
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Development of Smart Models to Accurately Predict Dynamic Viscosity of CO2-Saturated Polyethylene Glycol by Ayat Hussein Adhab, Morug Salih Mahdi, Bhavesh Kanabar, Anupam Yadav, Ranganathaswamy M K, Rishabh Thakur, Parveen Kumar, Braj Krishna, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…Additionally, the leverage method is utilized to assess the authenticity of the data for model development, while a relevancy index is used to elucidate the relative contributions of each input factor to the viscosity. …”
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Quantum Technologies for Beyond 5G and 6G Networks: Applications, Opportunities, and Challenges by Engin Zeydan, Chamitha De Alwis, Rabia Khan, Yekta Turk, Abdullah Aydeger, Thippa Reddy Gadekallu, Madhusanka Liyanage

“…A comprehensive overview of quantum technologies relevant to 6G, including quantum communication devices, quantum computing paradigms, and hybrid quantum-classical approaches is provided. …”
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Automatic Analysis of Ultrasound Images to Estimate Subcutaneous and Visceral Fat and Muscle Tissue in Patients with Suspected Malnutrition by Antonio Cuesta-Vargas, José María Arjona-Caballero, Gabriel Olveira, Daniel de Luis Román, Diego Bellido-Guerrero, Jose Manuel García-Almeida

“…The proposed system utilizes computer vision techniques to segment regions of interest (ROIs), calculate relevant variables, and store data for clinical evaluation. …”
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Enhancing Last-Mile Logistics: AI-Driven Fleet Optimization, Mixed Reality, and Large Language Model Assistants for Warehouse Operations by Saverio Ieva, Ivano Bilenchi, Filippo Gramegna, Agnese Pinto, Floriano Scioscia, Michele Ruta, Giuseppe Loseto

“…The framework prioritizes the customizability of AI algorithms and real-time information sharing between stakeholders. …”
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Evaluating the Effect of Thermal Treatment on Phenolic Compounds in Functional Flours Using Vis–NIR–SWIR Spectroscopy: A Machine Learning Approach by Achilleas Panagiotis Zalidis, Nikolaos Tsakiridis, George Zalidis, Ioannis Mourtzinos, Konstantinos Gkatzionis

“…This study explores the thermal stability of phenolic compounds in various functional flours using visible, near and shortwave-infrared (Vis–NIR–SWIR) spectroscopy (350–2500 nm), integrated with machine learning (ML) algorithms. Random Forest models were employed to classify samples based on flour type, baking temperature, and phenolic concentration. …”
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A brain-inspired memory transformation based differentiable neural computer for reasoning-based question answering by Yao Liang, Yao Liang, Yuwei Wang, Yuwei Wang, Hongjian Fang, Hongjian Fang, Feifei Zhao, Yi Zeng, Yi Zeng, Yi Zeng, Yi Zeng, Yi Zeng

“…The Differentiable Neural Computer (DNC) model, despite addressing these issues to some extent, still faces challenges such as algorithmic complexity, slow convergence, and limited robustness. …”
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Real-world implementation and adaptation to local settings of first trimester preeclampsia screening in Italy: a systematic review by Silvia Amodeo, Giulia Bonavina, Anna Seidenari, Paolo Ivo Cavoretto, Antonio Farina

“…All studies on first trimester PE screening in the Italian population were eligible for inclusion. Key-concepts relevant for implementation of PE screening in Italy were extracted and analysed qualitatively. …”
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Bi-modal contrastive learning for crop classification using Sentinel-2 and Planetscope by Ankit Patnala, Scarlet Stadtler, Scarlet Stadtler, Martin G. Schultz, Martin G. Schultz, Juergen Gall, Juergen Gall

“…In recent years, machine learning has become increasingly relevant for automated crop classification. However, the existing algorithms require a huge amount of annotated data. …”
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Cybersecurity and Major Cyber Threats of Smart Meters: A Systematic Mapping Review by Jones Márcio Nambundo, Otávio de Souza Martins Gomes, Adler Diniz de Souza, Raphael Carlos Santos Machado

“…A cutting-edge study was conducted, including a comprehensive review of relevant literature on smart meters, cybersecurity vulnerabilities, and mitigation strategies. …”
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First Results of Assessing the Quality of Medical Care at Pre-Hospital and Hospital Stages for Children with Acute Allergic Pathology by Leyla S. Namazova-Baranova, Elena A. Vishneva, Zharadat I. Dokhshukaeva, Anna A. Alekseeva, Kamilla E. Efendieva, Julia G. Levina, Elena А. Dobrynina, Elena Yu. Dyakonova, Ekaterina A. Romanova, Kazbek S. Mezhidov, Aleksey Yu. Romanov

“…According to our study, the quality of medical care at pre-hospital and hospital stages does not always correspond to current standards, algorithms, and available clinical guidelines.…”
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RNA m7G methylation regulators and targets significantly contribute to chronic obstructive pulmonary disease by Chenyu Zhu, Luyi Tan, Xinyu Zhang, Wenli Cheng, Min Li, Yibo Chen, Wenjuan Zhang

“…In this study, the combined roles of m7G methylation regulators were explored in COPD for the first time by integrated bioinformatic methods. The machine algorithms screened 7 disease signature genes relevant to clinical indicators, including CYFIP2, EIF3D, EIF4G3, GEMIN5, METTL1, SNUPN and NCBP2, and METTL1 was related to the progression in COPD. …”
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