An Innovative Priority-Aware Mission Planning Framework for an Agile Earth Observation Satellite by Guangtong Zhu, Zixuan Zheng, Chenhao Ouyang, Yufei Guo, Pengyu Sun

“…The proposed approach effectively maintains satellite maneuver constraints while achieving significant improvements in priority-based target acquisition and computational efficiency. …”
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Clays Are Not Created Equal: How Clay Mineral Type Affects Soil Parameterization by P. Lehmann, B. Leshchinsky, S. Gupta, B. B. Mirus, S. Bickel, N. Lu, D. Or

“…Presently, the soil clay content is used to parameterize soil hydraulic and mechanical properties (SHMP) for land surface models while disregarding the type of clay mineral. This undifferentiated use of clay leads to inconsistent parameterization, particularly between tropical and temperate soils, as shown herein. …”
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A Data-Driven Loose Contact Diagnosis Method for Smart Meters by Wenpeng Luan, Yajuan Huang, Bochao Zhao, Hanju Cai, Yang Han, Bo Liu

“…To mitigate these risks through early fault detection, this study proposes a data-driven framework integrating the Local Outlier Factor (LOF) and Multiple Linear Regression (MLR) algorithms. Voltage differentials, extracted from operational data collected via a simulated multi-meter metering enclosure, are leveraged to diagnose terminal contact degradation. …”
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Advancing Stability in Robot Manipulators: A Review of Recent Progress and Parameters by Shabnom Mustary, Mohammod Abul Kashem, Jannatul Mawya Sony, Nayem Hossain, Mohammad Asaduzzaman Chowdhury

“…ABSTRACT In this review, we present an overview of the current state‐of‐the‐art in robotics while emphasizing stability and control aspects with pragmatic consideration over robotic manipulators. …”
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Machine Learning and the Conundrum of Stroke Risk Prediction by Yaacoub Chahine, Matthew J Magoon, Bahetihazi Maidu, Juan C del Álamo, Patrick M Boyle, Nazem Akoum

“…The current paradigm of stroke risk assessment and mitigation is focused on clinical risk factors and comorbidities. Standard algorithms predict risk using regression-based statistical associations, which, while useful and easy to use, have moderate predictive accuracy. …”
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Enhancing Autonomous Driving in Urban Scenarios: A Hybrid Approach with Reinforcement Learning and Classical Control by Rodrigo Gutiérrez-Moreno, Rafael Barea, Elena López-Guillén, Felipe Arango, Fabio Sánchez-García, Luis M. Bergasa

“…The use of Deep Learning algorithms in the domain of Decision Making for Autonomous Vehicles has garnered significant attention in the literature in recent years, showcasing considerable potential. …”
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Highly adaptive Lasso for estimation of heterogeneous treatment effects and treatment recommendation by Nizam Sohail, Codi Allison, Rogawski McQuade Elizabeth, Benkeser David

“…However, few of these methods are interpretable, while those that do emphasize interpretability often suffer in terms of performance. …”
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A review on machine learning applications in hydrogen energy systems by Zaid Allal, Hassan N. Noura, Ola Salman, Flavien Vernier, Khaled Chahine

“…This study explores hydrogen energy systems, including production, storage, and applications, while establishing a connection between machine learning solutions and the challenges these systems face. …”
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Design and Implementation of an Ultra-Low-Power Hazardous Gas Monitoring System by Hongyu Liu, Yuchen Wang, Jiankang Yu, Shuqing Wang, Huijuan Chen

“…While ensuring real-time data acquisition and transmission, it achieves extremely low power consumption. …”
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Safeguarding against Cyber Threats: Machine Learning-Based Approaches for Real-Time Fraud Detection and Prevention by Vikas R. Shetty, Pooja R., Rashmi Laxmikant Malghan

“…In addition, deep learning techniques and artificial neural networks (ANN) are used to detect complex fraud patterns, while logistic regression is used to model the probability of fraudulent events. …”
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Scheduling Approach for the Simulation of a Sustainable Resource Supply Chain by Henning Strubelt, Sebastian Trojahn, Sebastian Lang, Abdulrahman Nahhas

“…The process sequence is determined by means of a priority index. Genetic algorithms are then applied to improve the priority index to further increase performance. …”
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Real-Time Performance Evaluation for Flooding and Recursive Time Synchronization Protocols over Arduino and XBee by Tarek R. Sheltami, Danish Sattar, Elhadi M. Shakshuki, Ashraf S. Mahmoud

“…Different time synchronization algorithms are aimed at achieving these objectives using various methods. …”
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Integrating emotional AI, IoT, and robotics for patient-centered healthcare: challenges and future directions by Nassim Bout, Ghizlane Moukhliss, Hicham Belhadaoui, Nadia Afifi, Mounia Abik

“…Drawing from recent literature and supported by two illustrative design prototypes, the paper examines how IoT facilitates real-time physiological monitoring, robotics enhances patient engagement and mobility, and emotional AI introduces empathy-driven responses through multimodal data interpretation. While these technologies offer substantial potential for scalable and responsive care, challenges persist—including data privacy, algorithmic bias, interoperability constraints, and affordability in under-resourced settings. …”
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Application of CT Radiomics in Predicting Differentiation Level of Lung Adenocarcinoma by Shuai ZHANG, Peng HAN, Suya ZHANG, Dingli YE, Zhicheng HUANG

“…ResultsThe poorly differentiation group consisted of 175 cases, while the moderate-to-high differentiation group had 332 cases. …”
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Canadian Public Health Laboratory Network laboratory Guidelines for the Diagnosis of Neurosyphilis in Canada by Tom Wong, Kevin Fonseca, Max A Chernesky, Richard Garceau, Paul N Levett, Bouchra Serhir

“…Antibody assays include a VDRL assay and the FTA-Abs, while polymerase chain reaction for T. pallidum can be used as direct detection assays for some specimens. …”
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A multi-faceted review of wind turbine optimization techniques: Metaheuristics and related issues by Hegazy Rezk, Abdul Ghani Olabi, Tabbi Wilberforce, Enas Taha Sayed

“…Wind energy conversion is increasingly attracting attention as a viable renewable energy source due to its ability to satisfy electricity requirements while considering economic and environmental factors. …”
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A Solution for Predicting the Timespan Needed for Grinding Roller Bearing Rings by Cezarina Chivu, Mitica Afteni, Gabriel Radu Frumusanu, Florin Susac

“…The two algorithms can be used to estimate the values of the different performance indicators of manufacturing processes. …”
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An efficient video slice encryption scheme and its application by Qinyou Huang, Luping Wang, Jie Chen

“…Full encryption algorithms have higher security compared to selective encryption, though they compromise time efficiency. …”
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An efficient approach towards index structures for skyline queries by Huaiguang Song, Zhongbo Wu, Binglei Guo, Zhao Wu, Min Wang

“…Extensive experiments show that U-INDG outperforms the most efficient index-based skyline algorithms currently available. It significantly reduces query time across various types of datasets, with speedups ranging from approximately 2.4 $$\times $$ × to 7.8 $$\times $$ × compared to state-of-the-art algorithms, while ensuring stable performance.…”
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Combining machine learning and single-cell sequencing to identify key immune genes in sepsis by Hao Wang, Linghan Len, Li Hu, Yingchun Hu

“…Next, a Biological association network was constructed, and five key hub genes (CD4, HLA-DOB, HLA-DRB1, HLA-DRA, AHNAK) were identified using a combination of three topological analysis algorithms (MCC, Closeness, and MNC) and four machine learning algorithms (Random Forest, LASSO regression, SVM, and XGBoost). immune cell distribution showed that the key genes correlated with multiple immune cell infiltrations. …”
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