Combating Antimicrobial Resistance: Spectroscopy Meets Machine Learning by Dimple Saikia, Ritam Dadhara, Cebajel Tanan, Prajwal Avati, Tushar Verma, Rishikesh Pandey, Surya Pratap Singh

“…The combination of ML algorithms with advanced spectroscopic techniques delivers faster and deeper insights into the different mechanisms of bacterial resistance, delivering novel solutions.…”
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Data stewardship and curation practices in AI-based genomics and automated microscopy image analysis for high-throughput screening studies: promoting robust and ethical AI applicat... by Asefa Adimasu Taddese, Assefa Chekole Addis, Bjorn T. Tam

“…The study also examined specific AI considerations, such as algorithmic bias, model explainability, and the application of advanced cryptographic techniques. …”
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ATTRN: Acoustic Information Encoder and Temperature Field Reconstruction Decoder Network for Boiler Temperature Field Reconstruction by Kunyu Wu, Keqi Ni, Liwei Chen, Hengyuan Xu, Junqiao Wang, Jingyi Zhou, Xinzhi Zhou

“…Traditional temperature field reconstruction algorithms, while effective, often suffer from accumulated errors, difficulty in solving ill-posed problems, low accuracy, and poor generalization. …”
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Thermal-Aware Test Schedule and TAM Co-Optimization for Three-Dimensional IC by Chi-Jih Shih, Chih-Yao Hsu, Chun-Yi Kuo, James Li, Jiann-Chyi Rau, Krishnendu Chakrabarty

“…The former assumes that the DfT of dies cannot be changed, while the latter assumes that the DfT of dies can be adjusted. …”
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Few-shot segmentation based on multi-level and cross-scale clustering by Shuai Yuan, Junhai Qiu, Hongxia Xu, Yan Zhang, Jiaxing Zhang

“…The proposed method is evaluated on Pascal and COCO datasets, and it is shown that it outperforms the state-of-the-art algorithms in both one-shot and k-shot segmentation scenarios.…”
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On the electron agyrotropy during rapid asymmetric magnetic island coalescence in presence of a guide field by E. Cazzola, M. E. Innocenti, M. V. Goldman, D. L. Newman, S. Markidis, G. Lapenta

“…We study the departure from isotropic and gyrotropic behavior by means of different robust detection algorithms proposed in the literature. While in the case without guide field these metrics show an overall agreement, when the guide field is present, a discrepancy in the agyrotropy within some relevant regions is observed, such as at the separatrices and inside magnetic islands. …”
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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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Automatic extraction of 3d building meshes from LiDAR data by Jan Voříšek, Bořek Patzák, Daniel Rypl

“…Terrestrial laser scanning and drone-based scanning are often combined to gain a complete picture of the external envelopes of buildings. While the resulting data sets are easy to understand for humans, extracting any semantical information from the data is a challenging task. …”
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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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