Potential of Multi-Source Multispectral vs. Hyperspectral Remote Sensing for Winter Wheat Nitrogen Monitoring by Xiaokai Chen, Yuxin Miao, Krzysztof Kusnierek, Fenling Li, Chao Wang, Botai Shi, Fei Wu, Qingrui Chang, Kang Yu

“…Results showed that, while hyperspectral data yielded slightly higher accuracy, optimized multispectral indices, particularly from PS and S2, achieved comparable performance. …”
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Bioinformatic Methodologies in Assessing Gut Microbiota by James Douglas Fox, Austin Sims, Morgan Ross, Jeffery Bettag, Alexandra Wilder, Dylan Natrop, Alison Borsotti, Sree Kolli, Shaurya Mehta, Hema Verma, Kento Kurashima, Chandrashekhara Manithody, Arun Verma, Ajay Jain

“…Bioinformatics tools and algorithms process these data to identify microbial taxa and quantify and elucidate their roles within the microbiome. …”
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Research on noninvasive electrophysiologic imaging based on cardiac electrophysiology simulation and deep learning methods for the inverse problem by Yi Chang, Ming Dong, Lihong Fan, Bochao Kang, Weikai Sun, Xiaofeng Li, Zhang Yang, Ming Ren

“…Abstract Background The risk stratification and prognosis of cardiac arrhythmia depend on the individual condition of patients, while invasive diagnostic methods may be risky to patient health, and current non-invasive diagnostic methods are applicable to few disease types without sensitivity and specificity. …”
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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

“…We evaluate the significance of body composition radiomics in predicting outcomes for resectable gastric cancer (GC) patients, as these parameters can enhance optimal surveillance strategies and risk-stratification models. …”
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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

“…These components are highly visible and require optimal surface conditions prior to painting, making the detection of residual contaminants critical for quality assurance. …”
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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

“…This study proposes a robust object detection framework integrating super-resolution techniques with advanced feature extraction algorithms for remote sensing images. The hybrid model combines Advanced StyleGAN and Swin Transformer. …”
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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

“…It is imperative to efficiently handle energy resources to fulfill computational requirements, ensuring optimal performance and continuous operation of IoT sensors across various applications. …”
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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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