Artificial Intelligence in Wind Turbine Fault Detection and Diagnosis: Advances and Perspectives by Nejad Alagha, Anis Salwa Mohd Khairuddin, Zineddine N. Haitaamar, Obada Al-Khatib, Jeevan Kanesan

“…The global shift toward renewable energy, particularly wind power, underscores the critical need for advanced fault diagnosis systems to optimize wind turbine reliability and efficiency. While traditional diagnostic methods remain foundational, their limitations in addressing the nonlinear dynamics and operational complexity of modern turbines have accelerated the adoption of Artificial Intelligence (AI)-driven approaches. …”
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Thematic Analysis of Clinician Documentation Surrounding Treatment Discussions and Decision‐Making in Patients With Desmoid Tumors by Victoria Wytiaz, Tianyi Wang, Scott Schuetze, Nina J. Francis‐Levin, Rashmi Chugh

“…ABSTRACT Background Desmoid tumors are benign tumors without metastatic potential. While progression is rarely life‐threatening, it is often life‐affecting with significant morbidity. …”
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A comprehensive review of energy harvesting and routing strategies for IoT sensors sustainability and communication technology by Hesam Nejati Sharif Aldin, Mostafa Razavi Ghods, Farnoush Nayebipour, Masoud Niazi Torshiz

“…Furthermore, the study explores routing algorithms within the IoT network context, recognizing their crucial role in addressing challenges related to sensor battery lifespan and energy conservation. …”
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IoT Based Health Monitoring with Diet, Exercise and Calories recommendation Using Machine Learning by Muhammad Hassaan Naveed, Omar Bin Samin, Muhammad Bilal, Mustehsum Waseem

“…Additionally, machine learning algorithms recommend tailored exercise, diet type, Basal Metabolic Rate (BMR), and daily caloric intake based on individual member data. …”
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Robust zero-watermarking for color images using hybrid deep learning models and encryption by Hager A. Gharib, Noha M. M. Abdelnapi, Khalid M. Hosny

“…Traditional zero-watermarking techniques often struggle to maintain resilience against geometric and signal processing attacks while ensuring high security and imperceptibility. …”
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Deep reinforcement learning for conservation decisions by Marcus Lapeyrolerie, Melissa S. Chapman, Kari E. A. Norman, Carl Boettiger

“…We show that a deep RL agent is able to learn a nearly optimal solution for the fisheries management problem. …”
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Studies on in-flight aircraft rerouting by M. A. Kiselev, Yu. S. Kalyuzhny, A. V. Karpov, S. F. Borodkin

“…The methodology and the algorithms, proposed by the authors, make it possible to assess the safety of an original route, estimate options for alternatives to avoid around obstacles detected in-flight, check them for feasibility, taking into account aircraft performance, flight envelope, and also select the optimal route from the  view of some criterion, for example, based on minimizing the route length increase, reducing additional fuel consumption, the time required to implement a new route of flight, etc.…”
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Application of artificial intelligence in triage in emergencies and disasters: a systematic review by Azadeh Tahernejad, Ali Sahebi, Ali Salehi Sahl Abadi, Mehdi Safari

“…AI algorithms like OpenPose and YOLO enhanced efficiency in mass casualty incidents, while e-triage systems allowed for continuous vital sign monitoring and faster triaging. …”
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Lightweight Brain Tumor Segmentation Through Wavelet-Guided Iterative Axial Factorization Attention by Yueyang Zhong, Shuyi Wang, Yuqing Miao, Tao Zhang, Haoliang Li

“…Conclusions: This study underscores the advantages of integrating frequency-domain analysis with optimized attention mechanisms, paving the way for scalable, high-performance medical image segmentation algorithms with broader clinical diagnostic applications.…”
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Application of machine learning and temporal response function modeling of EEG data for differential diagnosis in primary progressive aphasia by Heather Dial, Lokesha S. Pugalenthi, G. Nike Gnanateja, Junyi Jessy Li, Maya L. Henry

“…Early diagnosis is essential for optimal provision of care but differential diagnosis by PPA subtype can be difficult and time consuming. …”
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Molecular biomarkers in salivary diagnostic materials: Point-of-Care solutions — PoC-Diagnostics and -Testing by Ziyad S. Haidar

“…Recent advancements in nanomaterials and fabrication techniques, coupled with emerging computational approaches such as artificial intelligence (AI), machine learning, and deep learning, have revolutionized high-throughput screening and laboratory automation. AI-driven algorithms now process and analyze salivary proteomic data with remarkable accuracy, identifying patterns and biomarkers associated with diseases such as oral cancer at an early stage. …”
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Urban Resilience and Energy Demand in Tropical Climates: A Functional Zoning Approach for Emerging Cities by Javier Urquizo, Hugo Rivera-Torres

“…The system’s capacity to adjust and optimize power distribution would be strengthened provided the algorithms were given the freedom to react dynamically to changes or disruptions brought about by distributed generation sources.…”
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Opportunities and Challenges of Brain-on-a-Chip Interfaces by Wenwei Shao, Weiwei Meng, Jiachen Zuo, Xiaohong Li, Dong Ming

“…Addressing these limitations could offer insights into emergent intelligence while enabling next-generation biocomputing solutions.…”
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Artificial Intelligence and Smart Technologies in Safety Management: A Comprehensive Analysis Across Multiple Industries by Jiyoung Park, Dongheon Kang

“…AI-driven solutions, such as predictive analytics, machine learning algorithms, IoT sensor integration, and digital twin models, are shown to proactively identify and mitigate potential hazards, optimize energy consumption, and enhance operational efficiency. …”
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Radiology AI and sustainability paradox: environmental, economic, and social dimensions by Burak Kocak, Andrea Ponsiglione, Valeria Romeo, Lorenzo Ugga, Merel Huisman, Renato Cuocolo

“…Socially, AI risks perpetuating healthcare disparities through biases in algorithms and unequal access to technology. On the other hand, AI has the potential to improve sustainability in healthcare by reducing low-value imaging, optimizing resource allocation, and improving energy efficiency in radiology departments. …”
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Advancing Alzheimer’s disease detection: a novel convolutional neural network based framework leveraging EEG data and segment length analysis by Md Nurul Ahad Tawhid, Siuly Siuly, Enamul Kabir, Yan Li

“…Abstract Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that primarily affects memory, thinking, and behavior, leading to dementia, a severe cognitive decline. While no cure currently exists, recent advancements in preventive drug trials and therapeutic management have increased interest in developing clinical algorithms for early detection and biomarker identification. …”
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Predicting anemia management in dialysis patients using open-source machine learning libraries by Takahiro Inoue, Norio Hanafusa, Yuki Kawaguchi, Ken Tsuchiya

“…It requires precise hemoglobin (Hb) control while minimizing erythropoiesis-stimulating agent (ESA) dosages to reduce cost and side effects. …”
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A Study on Spatial and Temporal Changes and Synergies/Trade-Offs of the Production-Living-Ecological Functions in Mountainous Areas Based on the Niche Width Model by Yaling Li, Ruoying Song, Ping Ren

“…Based on this, spatial clustering patterns were further analyzed using Maxwell’s triangle and K-means algorithms to delineate functional zones. Key findings include: (1) Production function (PF) and living function (LF) exhibit a “core-periphery” spatial pattern (high-value clusters in the south, low-value contiguous areas in the north), while ecological function (EF) displays a “high-low-high” ring-shaped pattern (high values in the northwest and southeast, declining in the central region due to development pressure); (2) synergy and trade-off relationships coexist in the study area. …”
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The Role of Pharmacometrics in Advancing the Therapies for Autoimmune Diseases by Artur Świerczek, Dominika Batko, Elżbieta Wyska

“…PBPK and PK/PD models have been instrumental in personalizing treatments, while DisP and QSP models provide insights into disease evolution and pathophysiological mechanisms in AIDs. …”
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Incidence, Pathogenesis, Risk Factors, and Treatment of Cystoid Macula Oedema Following Cataract Surgery: A Systematic Review by Lorenzo Ferro Desideri, Kirupakaran Arun, Enrico Bernardi, Nicola Sagurski, Rodrigo Anguita

“…Further research is needed to establish optimal treatment algorithms and improve outcomes for patients with post-operative CMO…”
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