Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…The development of this model contributes to improving the integrity management of oil and gas pipelines and provides decision support for the intelligent management of defective pipelines in oil and gas fields.…”
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Higher-order aberrations and spherical aberration in various age groups after LASIK and cataract surgery by Robert Edward T. Ang, Patricia L. Lee, Ryan S. Torres, Michelle Marie Q. Araneta, Emerson M. Cruz, Maria Socorro M. Torno

“…In Lasik surgery, manipulating spherical aberration in the corneal periphery improves overall vision while in the central cornea provides presbyopic treatment. …”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…By reducing the technical burden of coding, iMESc allows researchers to focus on scientific inquiry, improving both the efficiency and depth of their analyses.…”
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AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration by Tiffany I Leung, Andrew J Coristine, Arriel Benis

“…One consistently reported benefit is the improvement in the patient-physician interaction, as physicians feel more present during a clinical encounter. …”
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Sustainable power solutions for next-generation medical devices by Ye Liang, Chi Zhang, Rubing Lin, Junqing Lin, Jishizhan Chen

“…Next-generation medical devices include implantable medical devices (IMDs) and wearables, exemplified by devices such as pacemakers for heart regulation and deep brain stimulators for neurological disorders, which have significantly advanced healthcare by offering critical treatments and improving patient outcomes. However, conventional battery technologies for these devices remain prevalent, and their constraints on longevity, size, and necessity for periodic replacement or recharging pose significant challenges, especially in implantable scenarios, presenting concerns regarding patient safety, healthcare costs, and device reliability. …”
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IoT Device Identification Techniques: A Comparative Analysis for Security Practitioners by Ashley Andrews, George Oikonomou, Simon Armour, Paul Thomas, Thomas Cattermole

“…By using methods to quickly and easily identify IoT devices on a network, vulnerable devices can be identified, improving network security. Although there have been publications that survey this research, they are typically broad, discussing IoT device identification only in passing, and do not provide a methodology to clearly compare existing (or future) research. …”
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Multi-crop plant counting and geolocation using a YOLO-Powered GUI System by Renato Herrig Furlanetto, Nathan Schawn Boyd, Ana Claudia Buzanini

“…Crop counting has traditionally relied on manual field assessments or complex machine learning algorithms, which often struggle to identify small objects or underestimate the total count of objects present in the field. …”
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End-to-end multiple object tracking in high-resolution optical sensors of drones with transformer models by Yubin Yuan, Yiquan Wu, Langyue Zhao, Yuqi Liu, Yaxuan Pang

“…By utilizing end-to-end training, our approach simplifies the tracking pipeline, leading to significant performance improvements. A key innovation in our system is the introduction of a trajectory detection label matching technique. …”
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Clinical applications of photon-counting CT in neuroimaging by LÜ Haiying, LU Yong, HE Naying

“…Photon-counting computed tomography (PCCT) is a next-generation CT imaging technology that markedly improves image quality while reducing radiation dose and image noise through single-photon detection and energy discrimination by photon detectors. …”
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Grey Wolf Optimization- and Particle Swarm Optimization-Based PD/I Controllers and DC/DC Buck Converters Designed for PEM Fuel Cell-Powered Quadrotor by Habibe Gursoy Demir

“…This shows that the full systems optimized with both GWO and PSO algorithms significantly increase their energy efficiency and provide maximum route-following performance.…”
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Development and laboratory validation of an LVDC back-to-back system with residential inverter, PV, and battery-based power generation by Zaid Ali, David Raisz

“…Additional technical improvements have been made by fine-tuning the DC-link based on the number of IGBT-legs incorporated in the converter setup. …”
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Detection of Mycotoxin Contamination in Foods Using Artificial Intelligence: A Review by Ashish Aggarwal, Akanksha Mishra, Nazia Tabassum, Young-Mog Kim, Fazlurrahman Khan

“…Ultimately, the use of AI could revolutionize systems monitoring mycotoxins, improving food safety and safeguarding global public health.…”
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Ensemble Transformer–Based Detection of Fake and AI–Generated News by Md. Ishraquzzaman, Mohammed Ashraful Islam Chowdhury, Shahreen Rahman, Riasat Khan

“…This work leverages advanced natural language processing, machine learning, and deep learning algorithms to effectively detect fake and AI–generated content. …”
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Duck Egg Crack Detection Using an Adaptive CNN Ensemble with Multi-Light Channels and Image Processing by Vasutorn Chaowalittawin, Woranidtha Krungseanmuang, Posathip Sathaporn, Boonchana Purahong

“…In current practice, human inspectors use standard white light for crack detection, and many researchers have focused primarily on improving detection algorithms without addressing lighting limitations. …”
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The unwell patient with advanced chronic liver disease: when to use each score? by Oliver Moore, Wai-See Ma, Scott Read, Jacob George, Golo Ahlenstiel

“…Understanding of ACLF presentation of advanced liver disease remains in the preliminary stages. Improving collective understanding is important to optimise prognostication. …”
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A synergistic approach using digital twins and statistical machine learning for intelligent residential energy modelling by Ahmad Almadhor, Shtwai Alsubai, Natalia Kryvinska, Nejib Ghazouani, Belgacem Bouallegue, Abdullah Al Hejaili, Gabriel Avelino Sampedro

“…Abstract The growing need for energy efficiency in buildings has driven significant improvements in digitalisation and intelligent energy management. …”
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Enhancing placental pathology detection with GAMatrix-YOLOv8 model by Weirui Wu, Zhifa Jiang, Jingwen Liu, Jiahui Ji, Xiaoyan Wei, Xiangyun Ye, Zhen Zhang

“…Methods: Embedding GAM attention into the YOLOv8 backbone network and incorporating critical preprocessing steps like image enhancement and normalization enable the model's middle layer to focus more effectively on essential image features, improving computational efficiency and accuracy. Results: This study developed a new model,GAMatrix-YOLOv8,which enhances object detection accuracy and efficiency while offering superior generalization capabilities. …”
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Electricity Losses in Focus: Detection and Reduction Strategies—State of the Art by Daniela F. Niste, Radu Tîrnovan, Sorin Pavel, Horia Beleiu, Cziker Andrei, Marius Misaroș

“…In conclusion, this paper emphasizes the importance of the in-depth study of the energy domain to achieve performance and contribute to the improvement of power grids. Future research directions are based on the implementation of artificial intelligence (AI) algorithms to achieve this goal.…”
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Case Report: Myelodysplastic/myeloproliferative neoplasm with concurrent SF3B1, ASXL1, JAK2 and CBL mutations and <15% bone marrow ringed sideroblasts by Yifan Wang, Shengyu Jin

“…Our findings necessitate revision of therapeutic algorithms for molecularly complex, treatment-naive elderly patients, particularly in resource-limited settings where socioeconomic factors critically influence management strategies.…”
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Sedimentary microfacies prediction based on multi-point geostatistics under the constraint of INPEFA curve by Xudong Wang, Zicheng Yang, Xibao Liu, Chengyuan Yuan

“…The method predicts sedimentary microfacies under INPEFA curve constraints, which makes sequence interface identification more intuitive and improves cycle division and correlation precision. …”
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