Improving resectable gastric cancer prognosis prediction: A machine learning analysis combining clinical features and body composition radiomics by Gianni S.S. Liveraro, Maria E.S. Takahashi, Fabiana Lascala, Luiz R. Lopes, Nelson A. Andreollo, Maria C.S. Mendes, Jun Takahashi, José B.C. Carvalheira

“…Body composition radiomics were integrated with clinicopathological factors using machine learning (ML) algorithms trained for patient outcome prediction. We compared results using Random Forest, Logistic Regression and Boosted Decision Tree algorithms. …”
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Automated Quality Control of Cleaning Processes in Automotive Components Using Blob Analysis by Simone Mari, Giovanni Bucci, Fabrizio Ciancetta, Edoardo Fiorucci, Andrea Fioravanti

“…The LoG and DoG methods were more prone to spurious detections, while DoH demonstrated intermediate performance but struggled with reflective surfaces. …”
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Research on Mobile Agent Path Planning Based on Deep Reinforcement Learning by Shengwei Jin, Xizheng Zhang, Ying Hu, Ruoyuan Liu, Qing Wang, Haihua He, Junyu Liao, Lijing Zeng

“…For mobile agent path planning, traditional path planning algorithms frequently induce abrupt variations in path curvature and steering angles, increasing the risk of lateral tire slippage and undermining operational safety. …”
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Remote monitoring of Tai Chi balance training interventions in older adults using wearable sensors and machine learning by Giulia Corniani, Stefano Sapienza, Gloria Vergara-Diaz, Andrea Valerio, Ashkan Vaziri, Paolo Bonato, Peter M. Wayne

“…Data were collected from 32 participants with inertial measurement units (IMUs) while performing six Tai Chi movements evaluated and scored for adherence and proficiency by experts. …”
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A novel hybrid deep learning approach for super-resolution and objects detection in remote sensing by Muhammad Asif, Mohammad Abrar, Faizan Ullah, Abdu Salam, Farhan Amin, Isabel de la Torre, Mónica Gracia Villar, Helena Garay, Gyu Sang Choi

“…Advanced StyleGAN enhances image resolution, facilitating the detection of small and occluded objects, while Swin Transformer employs hierarchical attention mechanisms for effective feature extraction. …”
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Advanced Hydroponic Nutrient Management Systems for Vertical Farming Efficiency with IoT and Model Predictive Control to Enhance Sustainable Crop Growth by Almusawi Muntather, Hussein Abbas Hameed Abdul, Raju V. Siva Prasada

“…In the quest to advance vertical farming efficiency, optimizing hydroponic nutrient management systems is essential for achieving high productivity and sustainability. …”
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Review of Self-Powered Wireless Sensors by Triboelectric Breakdown Discharge by Shuzhe Liu, Jixin Yi, Guyu Jiang, Jiaxun Hou, Yin Yang, Guangli Li, Xuhui Sun, Zhen Wen

“…Key research directions are synthesized to enhance TENG-based sensing capabilities, including novel device architectures, the optimization of RLC circuit models, the integration of machine learning algorithms, and power management strategies. …”
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Data-driven prediction of critical diameter for deterministic lateral displacement devices: an integrated DPD-ML approach by Shuai Liu, Peng Zhang, Anbin Wang, Keke Tang, Shuo Chen, Chensen Lin

“…This leads to significant economic and time costs, while the complexity of instruments and algorithms further raises the barrier for DLD design and optimization. …”
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Niche Overlap Between Two Sympatric Steppe Birds in Inner Mongolia: Habitat Selection and Insights for Conservation by Zheng Han, Xi Yang, Lishi Zhang, Frédéric Jiguet, Piotr Tryjanowski, Haitao Wang

“…Jankowski's Bunting favors areas with higher vegetation cover and height, while Meadow Bunting prefers sites with greater edge density. …”
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Review and prospect of floating car data research in transportation by Chi Zhang, Yuming Zhou, Min Zhang, Bo Wang, Yuhan Nie

“…The three major research clusters include traffic flow state, traffic safety, and route planning. The optimal investment proportion for floating cars is determined to be 3%–8%, and the sampling frequency significantly affects the accuracy of vehicle speed and heading angle information, while having a weaker impact on positional parameters. …”
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Hierarchical Sensing Framework for Polymer Degradation Monitoring: A Physics-Constrained Reinforcement Learning Framework for Programmable Material Discovery by Xiaoyu Hu, Xiuyuan Zhao, Wenhe Liu

“…Our method combines three key innovations: (1) a dual-channel sensing architecture that fuses spectroscopic signatures from Graph Isomorphism Networks with temporal degradation patterns captured by transformer-based models, enabling comprehensive molecular state detection across multiple scales; (2) a physics-constrained policy network that ensures sensor measurements adhere to thermodynamic principles while optimizing the exploration of degradation pathways; and (3) a hierarchical signal processing system that balances multiple sensing modalities through adaptive weighting schemes learned from experimental feedback. …”
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PENC: a predictive-estimative nonlinear control framework for robust target tracking of fixed-wing UAVs in complex urban environments by Shiji Hai, Xitai Na, Zhihui Feng, Jinshuo Shi, Qingbin Sun

“…To address this, this paper proposes a Predictive-Estimative Nonlinear Control (PENC) framework. This framework optimizes the UAV-gimbal system’s control inputs in real-time to ensure the target remains within the camera’s field of view (FOV) despite obstacles, while simultaneously using historical target state measurements to accurately estimate its current state. …”
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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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