A novel canopy water indicator for UAV imaging to monitor winter wheat water status by Meiyan Shu, Zhenghang Ge, Yang Li, Jibo Yue, Wei Guo, Yuanyuan Fu, Ping Dong, Hongbo Qiao, Xiaohe Gu

“…However, the complexity involved in acquiring LAI data and the associated high costs limit the practical application of FMCc in crop water monitoring. …”
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Emerging trends in sustainable energy system assessments: integration of machine learning with techno-economic analysis and lifecycle assessment by Ebrahimpourboura Zahra, Mosalpuri Manish, Jonas Baltrusaitis, Dubey Pallavi, Mba Wright Mark

“…Key case studies demonstrate the transformative potential of ML in improving economic viability and environmental sustainability, highlighting its role in predicting system performance, optimizing configurations, and reducing costs and impacts. …”
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Histopathological Image Analysis Using Machine Learning to Evaluate Cisplatin and Exosome Effects on Ovarian Tissue in Cancer Patients by Tuğba Şentürk, Fatma Latifoğlu, Çiğdem Gülüzar Altıntop, Arzu Yay, Zeynep Burçin Gönen, Gözde Özge Önder, Özge Cengiz Mat, Yusuf Özkul

“…Exosome treatments, particularly when administered post-cisplatin, significantly improve ovarian tissue recovery. …”
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A novel biochemical analysis for ApoE4 quantification in plasma and discrimination of homozygous and heterozygous APOE ε4 carriers by Andrés Rodríguez, Olga Calero, Sergio Veiga, Miriam Menacho-Román, Ignacio Arribas, Lluís Cano, Guillermo García-Ribas, Miguel Calero

“…Discussion The e4Quant assay offers a rapid, cost-effective, and highly accurate biochemical alternative to APOE genotyping, suitable for clinical and research settings, particularly in assessing AD risk and optimizing anti-amyloid therapeutic strategies. …”
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The Analysis of the Possibility to Conduct Orbital Manoeuvres of Nanosatellites in the Context of the Maximisation of a Specific Operational Task by Magdalena Lewinska, Michal Kedzierski

“…For example, slight adjustments to the altitude of the orbit with the use of Hohmann transfer proved to be optimal in terms of fuel costs. On the other hand, changes in inclination, although they are definitely energy-consuming, may significantly improve the coverage of the defined area. …”
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Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

“…Model performance was evaluated using metrics including the mean absolute error (MAE) and root mean squared error (RMSE) for regression models, while accuracy, F1-score, and area under the curve (AUC) were used for classification models. …”
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A bayesian network model for neurocognitive disorders digital screening in Chinese population: development and validation study by Yifan Yu, Shuaijie Zhang, Hongkai Li, Fuzhong Xue

“…Early screening for neurocognitive disorders is conducive to improving patients’ quality of life and reducing healthcare costs. …”
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Digital Land Suitability Assessment for Irrigated Cultivation of Some Agricultural Crops Using Machine Learning Approaches (Case Study: Qazvin-Abyek) by F. Jannati, F. Sarmadian

“…The utilization of modern mapping techniques such as digital soil mapping and machine learning algorithms can significantly improve the accuracy of land suitability assessment and crop performance prediction. …”
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Research Progress on Selective Depolymerization of Waste Plastics to High-Quality Liquid Fuels by Xinze LI, Zhicheng LUO, Rui XIAO

“…Real-time monitoring of temperature gradients and microwave power enabled dynamic adjustments, improving diesel-range hydrocarbon selectivity by 25%. …”
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Reinforcement Learning-driven Mechanism Study of Ecological Compensation to Suppress Carbon Lock-in by Yongxin Zhou

“…Experiment results demonstrate that RL-MEC-CL not only improves the efficiency of ecological compensation strategies but also exhibits strong robustness and adaptability, offering valuable insights for optimizing ecological governance pathways.…”
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Screening and Risk Analysis of Atrial Fibrillation After Radiotherapy for Breast Cancer: Protocol for the Cross-Sectional Cohort Study “Watch Your Heart (WATCH)” by Laura Saint-Lary, Baptiste Pinel, Loic Panh, Gaelle Jimenez, Julien Geffrelot, Youlia Kirova, Jeremy Camilleri, David Broggio, Marie-Odile Bernier, Corinne Mandin, Christelle Levy, Serge Boveda, Juliette Thariat, Sophie Jacob

“…Identifying the dose-risk associations would improve RT delivery protocols to limit the occurrence of different forms of AF and, if necessary, initiate appropriate treatment. …”
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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

“…This necessitates tracking algorithms capable of both target state estimation and prediction. …”
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The Potential of Artificial Intelligence in Pharmaceutical Innovation: From Drug Discovery to Clinical Trials by Vera Malheiro, Beatriz Santos, Ana Figueiras, Filipa Mascarenhas-Melo

“…AI has revolutionized drug discovery and development by enabling rapid and effective analysis of vast volumes of biological and chemical data during the identification of new therapeutic compounds. The algorithms developed can predict the efficacy, toxicity, and possible adverse effects of new drugs, optimize the steps involved in clinical trials, reduce associated time and costs, and facilitate the implementation of innovative drugs in the market, making it easier to develop precise therapies tailored to the individual genetic profile of patients. …”
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Developing advanced datadriven framework to predict the bearing capacity of piles on rock by Kennedy C. Onyelowe, Shadi Hanandeh, Viroon Kamchoom, Ahmed M. Ebid, Fabián Danilo Reyes Silva, José Luis Allauca Palta, José Luis Llamuca Llamuca, Siva Avudaiappan

“…The developed framework provides engineers and practitioners with a powerful tool for improving pile design accuracy, reducing uncertainties, and optimizing construction practices. …”
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Innovative approach for gauge-based QPE in arid climates: comparing neural networks and traditional methods by Bayan Banimfreg, Ernesto Damiani, Vesta Afzali Gorooh, Duncan Axisa, Luca Delle Monache, Youssef Wehbe

“…The superior performance of the neural network approach suggests significant potential for improving water resource management practices, optimizing cloud seeding interventions, and informing policy decisions. …”
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Application of artificial intelligence in electrochemical diagnostics for human health by Koushlesh Ranjan, Basanti Barar, Minakshi Prasad, Gaya Prasad

“…AI also assists in optimizing sensor design, manages large datasets, and improves the performance and reliability of electrochemical diagnostics (ED) devices. …”
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Electricity nowcasting and forecasting efficiency in blockchain-integrated energy trading platforms by Ameni Boumaiza

“…Our methodology integrates real-time nowcasting algorithms and machine learning-based forecasting models to optimize electricity distribution, battery storage utilization, and cost efficiency within the marketplace. …”
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Predicting Subcontractor Performance Using Web-Based Evolutionary Fuzzy Neural Networks by Chien-Ho Ko

“…The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. …”
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Experimental and machine learning based analysis of pervious concrete enhanced with fly ash and silica fume by Siva Shanmukha Anjaneya Babu Padavala, Siva Avudaiappan, Venkatesh Noolu

“…Pervious concrete (PC) has quickly gained attention as an eco-friendly solution to urban stormwater management, offering improved drainage performance while decreasing environmental impact. …”
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Cluster-based RSU deployment strategy for vehicular ad hoc networks with integration of communication, sensing and computing by Xinrui Gu, Shengfeng Wang, Zhiqing Wei, Zhiyong Feng

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