Integrating data from unmanned aerial vehicles and Sentinel-2 with PROSAIL-5D-driven machine learning for fuel moisture content estimation in agroecosystems by Jinlong Liu, Jia Jin, Jing Huang, Mengjuan Wu, Shaozheng Hao, Haoyi Jia, Tengda Qin, Yuqing Huang, Dan Chen, Nathsuda Pumijumnong

“…To address the challenge of sparse ground observations, a calibrated PROSAIL-5D radiative transfer model was used to simulate diverse spectral responses, augmenting the training dataset. A genetic algorithm-optimized backpropagation neural network was then applied to assess the effectiveness of the fused remote sensing data and PROSAIL-5D simulation in improving FMC retrieval accuracy. …”
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The role of nanomedicine and artificial intelligence in cancer health care: individual applications and emerging integrations—a narrative review by Prasanthi Samathoti, Rajasekhar Komarla Kumarachari, Sarad Pawar Naik Bukke, Eashwar Sai Komarla Rajasekhar, Ashish Ashokkumar Jaiswal, Zohre Eftekhari

“…Nanomedicine leverages nanoparticles for targeted drug delivery, enhancing therapeutic efficacy while minimizing adverse effects. Concurrently, AI algorithms facilitate early cancer detection, personalized treatment planning, and predictive analytics, thereby optimizing clinical outcomes. …”
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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

“…These technologies are integrated, whereby the aim is to achieve multiple key objectives, such as optimizing nutrient delivery for improved yield, enhancing environmental control for optimal growing conditions, and encouraging sustainable growing practices. …”
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A Comprehensive Review of Blockchain and Machine Learning Integration for Peer-to-Peer Energy Trading in Smart Grids by Sameen Fatima, Muhammad Junaid Arshad

“…Blockchain enhances energy transactions by making them safer, more transparent, and tamper-proof, while ML optimizes grid performance by improving predictions, fault detection, and anomaly identification. …”
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SDGTrack: A Multi-Target Tracking Method for Pigs in Multiple Farming Scenarios by Tao Liu, Dengfei Jie, Junwei Zhuang, Dehui Zhang, Jincheng He

“…Compared to the original CSTrack method, SDGTrack improved the MOTA and IDF1 scores by 16.7% and 33.3%, respectively, while significantly reducing the number of ID switches by 94.6%. …”
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The role of artificial intelligence in enhancing personalized learning pathways and clinical training in dental education by Chengchen Hu, Fang Li, Shengguo Wang, Zhi Gao, Shan Pan, Maofeng Qing

“…Moreover, AI-driven innovations in dental biomaterials are optimizing material selection and prosthetic design, while robotic-assisted systems are enhancing precision in clinical training and treatment procedures. …”
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Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices? by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith

“…Key predictors included spatially lagged spectral bands (e.g., Green_lag, NIR_lag, RedEdge_lag) and VIs (e.g., CREI, GCI, NCPI, ARI, CCCI), highlighting the value of integrating neighborhood data for improved corn yield prediction. This study underscores the importance of spatial context in corn yield prediction and lays the foundation for future research across diverse agricultural settings, focusing on optimizing neighborhood size, integrating spatial and spectral data, and refining spatial dependencies through localized search algorithms.…”
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Fault Diagnosis in a Four-Arm Delta Robot Based on Wavelet Scattering Networks and Artificial Intelligence Techniques by Claudio Urrea, Carlos Domínguez

“…Results indicate that a WNN, using wavelet scattering features ranked by one-way anova, is optimal due to its consistency and reliability, while these features enhance computational efficiency by reducing classifier size. …”
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Blockchain based solid waste classification with AI powered tracking and IoT integration by Aliaa M. Alabdali

“…IoT-connected bins transmit data to a central server, which uses blockchain to ensure secure, transparent data storage. AI algorithms, including machine learning (ML) and deep learning (DL), classify waste in real-time, optimizing waste collection and recycling. …”
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Precise application of water and fertilizer to crops: challenges and opportunities by Yingying Xing, Xiukang Wang

“…Advanced irrigation methods, such as subsurface drip irrigation and micro-sprinkling, improve water-use efficiency and reduce salinity levels, while precision fertilization techniques optimize nutrient uptake and minimize leaching. …”
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Biosynthesis, applications, and mathematical modeling dynamics of lactic acid bacteria exopolysaccharides: A review by Ankit Barot, Kalyan Das, Yogesh Patel, et al.

“…White-box models, utilize comprehensive system knowledge, forecast performance, and optimize processes such as EPS biosynthesis while employing algorithms like fuzzy patterns, rule-based systems, and decision trees to increase productivity and identify bottlenecks. …”
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Double‐row suture‐bridge technique does not yield better clinical and radiological results than single‐row technique in patients older than 55 years at 2 years minimum follow‐up: A... by Vito Gaetano Rinaldi, Sassoli Iacopo, Federico Coliva, Antongiulio Favero, Alberto Bazzocchi, Marco Miceli, Stefano Di Paolo, Stefano Zaffagnini, Giulio Maria Marcheggiani Muccioli

“…Further research, including randomized controlled trials with long‐term follow‐up, is needed to refine treatment algorithms and improve patient outcomes in rotator cuff surgery. …”
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The potential role of next-generation sequencing in identifying MET amplification and disclosing resistance mechanisms in NSCLC patients with osimertinib resistance by Xiao Xiao, Xiao Xiao, Ren Xu, Ren Xu, Jun Lu, Beibei Xin, Chenyang Wang, Kexin Zhu, Hao Zhang, Xinyu Chen

“…With FISH results as gold standard, enumeration algorithm was applied to establish the optimal model for identifying MET amplification using gene copy number (GCN) data.ResultsThe optimal model for identifying MET amplification was constructed based on the GCN of MET, BRAF, CDK6 and CYP3A4, which achieved a 74.0% overall agreement with FISH and performed well in identifying MET amplification except polysomy with a sensitivity of 85.7% and a specificity of 93.9%. …”
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Effect of tool angle in nanocutting of single crystal GaN using diamond cutter by Yongqiang WANG, Hao XIA, Zhihang HU, Shuaiyang ZHANG, Shaohui YIN

“…This promotes more efficient and continuous chip formation while effectively suppressing undesirable lateral atomic flow and material pile-up at the groove sides, leading to improved groove definition. …”
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A novel method for soil organic carbon prediction using integrated ‘ground-air-space’ multimodal remote sensing data by Yilin Bao, Xiangtian Meng, Huanjun Liu, Mengyuan Xu, Mingchang Wang

“…Regarding model performance in SOC content prediction, GNN is more suitable for Model (i) and Model (iii), while CNN is more appropriate for Model (ii). In conclusion, ResoCroS-Net achieved collaborative optimization of spatial-spectral features across scales, provided a significant advantage in improving the accuracy of quantitative remote sensing, offers an efficient and accurate SOC monitoring tool, providing a practical basis for the integrated remote sensing theory of ‘ground-air-space’.…”
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Electrophysiological changes in the acute phase after deep brain stimulation surgery by Lucia K. Feldmann, Diogo Coutinho Soriano, Jeroen Habets, Valentina D'Onofrio, Jonathan Kaplan, Varvara Mathiopoulou, Katharina Faust, Gerd-Helge Schneider, Doreen Gruber, Georg Ebersbach, Hayriye Cagnan, Andrea A. Kühn

“…Background: With the introduction of sensing-enabled deep brain stimulation devices, characterization of long-term biomarker dynamics is of growing importance for treatment optimization. The microlesion effect is a well-known phenomenon of transient clinical improvement in the acute post-operative phase. …”
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Group twirling and noise tailoring for multiqubit controlled phase gates by Guoding Liu, Ziyi Xie, Zitai Xu, Xiongfeng Ma

“…Specifically, for multiqubit controlled phase gates, which are essential in quantum algorithms and directly implementable in practice, we determine optimal twirling groups within the realm of classically replaceable unitary operations. …”
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Automated Recognition of Abnormalities in Gastrointestinal Endoscopic Images – Evaluation of an AI Tool for Identifying Polyps and Other Irregularities by Weronika Jarych, Elżbieta Tokarczyk, Patryk Iglewski, Daria Ziemińska, Karina Motolko, Rafał Burczyk, Konrad Duszyński, Michał Kociński, Jan Reinald Wendt

“…Key advantages of AI integration in endoscopy include improved sensitivity, minimized detection errors, and the potential to optimize clinical workflow efficiency. …”
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Essay Answer Detection System Uses Cosine Similarity and Similarity Scoring in Sentences by Siti Yuliyanti, Diah Hidayatul Ula

“…This study highlights the importance of automated grading systems for optimizing essay scoring in educational settings while maintaining scalability and reliability. …”
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Quantum Edge Detection and Convolution Using Paired Transform-Based Image Representation by Artyom Grigoryan, Alexis Gomez, Sos Agaian, Karen Panetta

“…We demonstrate that our approach achieves improved processing speed compared to classical methods while maintaining comparable accuracy. …”
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