Analyzing Post-fire Vegetation Dynamics with Ultra-high Resolution Remote Sensing Data by O. Petrov, O. Petrov, A. Medvedev

“…Co-alignment was applied to multi-temporal UAV datasets, and tree segmentation was performed using the algorithms developed for Airborne Laser Scanning (ASL) forest point clouds. …”
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M3S-GRPred: a novel ensemble learning approach for the interpretable prediction of glucocorticoid receptor antagonists using a multi-step stacking strategy by Nalini Schaduangrat, Hathaichanok Chuntakaruk, Thanyada Rungrotmongkol, Pakpoom Mookdarsanit, Watshara Shoombuatong

“…Abstract Accelerating drug discovery for glucocorticoid receptor (GR)-related disorders, including innovative machine learning (ML)-based approaches, holds promise in advancing therapeutic development, optimizing treatment efficacy, and mitigating adverse effects. …”
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Urban Heat Island Effect: Remote Sensing Monitoring and Assessment—Methods, Applications, and Future Directions by Lili Zhao, Xuncheng Fan, Tao Hong

“…In terms of applications, the paper elaborates on the practical value of remote sensing technology in identifying thermally vulnerable areas, green space planning, urban material optimization, and decision support for UHI mitigation. …”
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SARS-COV-2 PREVALENCE IN INDIA COMPARED TO THE REST OF THE GLOBE AND ASCERTAINS EPIDEMIOLOGICAL CHARACTERISTICS ASSOCIATED WITH THE COVID-19 PANDEMIC DURING 2020 IN INDIA by M. Rajesh Kumar Rao, Rabindra N. Padhy, Manoj Kumar Das

“…We ascertain the pandemic burden of COVID-19 disease between India and the rest of the world; monitor the burden of COVID-19 disease in Indian states and union territories compared to other countries with nearly equivalent population sizes, and study the epidemiological characteristics.Material and Methods: A population-based comparative optimization algorithms study was conducted on all COVID positive cases reported by 31st December 2020.Results: Confirmed cases resulted in India with a ratio of 1:7.2 to the rest of the world, with a lower mortality rate with a ratio of 1:12 (CMR per 100,000 people) than other countries. …”
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Combined Use of Spectral and Structural Features for Improved Early Detection of Pine Shoot Beetle Attacks in Yunnan Pines by Yujie Liu, Youqing Luo, Run Yu, Lili Ren, Qi Jiang, Shaoshun He, Xinqiang Chen, Guangzhao Yang

“…Random forest (RF) was employed to determine the optimal detection model as well as to clarify the contributions of the candidate variables. …”
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Satellite-based detection of deep-convective clouds: the sensitivity of infrared methods and implications for cloud climatology by A. Z. Kotarba, I. Wojciechowska

“…Global accuracy ranged from 56.6 % (for TROPO) to 72.8 % (for BTD) using an optimal threshold of <span class="inline-formula">−</span>2 K. …”
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The Application of Artificial Intelligence in Medical Diagnostics: Implications for Sports Medicine by Michał Bolek, Dominika Musialska, Aleksandra Kędzia, Bartosz Jagieła, Monika Fidyk, Magda Minkiewicz, Maciej Dyda

“…Recent advancements allow AI systems to analyze physiological, biomechanical, and behavioral data, leading to improved injury prevention and performance optimization in athletes. These AI-driven tools can predict injury risks by evaluating training loads, biomechanics, and real-time physiological signals. …”
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YOLO11-ARAF: An Accurate and Lightweight Method for Apple Detection in Real-World Complex Orchard Environments by Yangtian Lin, Yujun Xia, Pengcheng Xia, Zhengyang Liu, Haodi Wang, Chengjin Qin, Liang Gong, Chengliang Liu

“…Third, we applied knowledge distillation to transfer the enhanced model to a compact YOLO11n framework, maintaining high detection efficiency while reducing computational cost, and optimizing it for deployment on devices with limited computational resources. …”
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Artificial intelligence in vaccine research and development: an umbrella review by Rabie Adel El Arab, May Alkhunaizi, May Alkhunaizi, Yousef N. Alhashem, Alissar Al Khatib, Munirah Bubsheet, Salwa Hassanein, Salwa Hassanein

“…AI‑driven multi‑omic integration accelerated epitope mapping, shrinking discovery timelines by months, while predictive analytics optimized manufacturing workflows and supply‑chain operations (including temperature‑controlled, “cold‑chain” logistics). …”
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Intelligent recognition of tobacco leaves states during curing with deep neural network by Qiang Xu, Yanling Zhang, Aiguo Wang, Guangqing Chen, Xianjie Cai, Shuoye Zhou, Junying Li, Baofeng Jin, Ding Yan, Jiajie Huang, Zuxiao Chen, Heng Zhang, Jianwei Wang, Weimin Guo, Jianjun Liu

“…IntroductionThe state monitoring of tobacco leaves during the curing process is crucial for process control and automation of tobacco agricultural production. While most of the existing research on tobacco leaves state recognition focused on the temporal state of the leaves, the morphological state was often neglected. …”
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Control of multi-level quadratic DC-DC boost converter for photovoltaic systems using type-2 fuzzy logic technique-based MPPT approaches by Souheyb Mohammed Belhadj, Bouziane Meliani, Habib Benbouhenni, Sarra Zaidi, Z.M.S. Elbarbary, Mohammed M. Alammer

“…These results highlight the significant potential of the MPPT-T2FLC in optimizing energy extraction and improving the reliability of PV systems operating under dynamic environmental conditions.…”
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BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification by Anderson P. Avila Santos, Breno L. S. de Almeida, Robson P. Bonidia, Peter F. Stadler, Polonca Stefanic, Ines Mandic-Mulec, Ulisses Rocha, Danilo S. Sanches, André C.P.L.F. de Carvalho

“…Recently, deep learning algorithms have provided advancements in ncRNA classification. …”
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Unmanned Aerial Vehicle Remote Sensing for Monitoring Fractional Vegetation Cover in Creeping Plants: A Case Study of <i>Thymus mongolicus</i> Ronniger by Hao Zheng, Wentao Mi, Kaiyan Cao, Weibo Ren, Yuan Chi, Feng Yuan, Yaling Liu

“…The SVR model achieved optimal performance during the green-up (R² = 0.87) and early flowering stages (R² = 0.91), while the ANN model excelled during budding (R² = 0.93), peak flowering (R² = 0.95), and fruiting (R² = 0.77). …”
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Deep learning-based detection and classification of acute lymphoblastic leukemia with explainable AI techniques by Debendra Muduli, Sourav Parija, Suhani Kumari, Asmaul Hassan, Harendra S. Jangwan, Abu Taha Zamani, Sk. Mohammed Gouse, Banshidhar Majhi, Nikhat Parveen

“…A detailed comparative analysis was conducted, examining key parameters such as learning rate, optimization algorithms, and the number of training epochs to determine the most effective approach. …”
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The future of critical care: AI-powered mortality prediction for acute variceal gastrointestinal bleeding and acute non-variceal gastrointestinal bleeding patients by Zhou Liu, Guijun Jiang, Liang Zhang, Palpasa Shrestha, Yugang Hu, Yi Zhu, Guang Li, Yuanguo Xiong, Liying Zhan

“…In case of ANGIB patients, gradient boosting model proven to be the optimal machine learning models, with the AUC of 0.985 ± 0.002, accuracy of 0.948 ± 0.009, precision of 0.949 ± 0.009, recall of 0.968 ± 0.009, and F1 score of 0.959 ± 0.007. …”
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Alpine Meadow Fractional Vegetation Cover Estimation Using UAV-Aided Sentinel-2 Imagery by Kai Du, Yi Shao, Naixin Yao, Hongyan Yu, Shaozhong Ma, Xufeng Mao, Litao Wang, Jianjun Wang

“…Subsequently, four machine learning models were employed for an accurate FVC inversion, using the estimated FVC values and UAV-derived reference FVC as inputs, following feature importance ranking and model parameter optimization. The results showed that: (1) Machine learning algorithms based on Sentinel-2 and UAV imagery effectively improved the accuracy of FVC estimation in alpine meadows. …”
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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

“…Conclusion This study suggests that both SR and DRSB techniques offer comparable clinical outcomes and tendon healing rates for rotator cuff tears in patients over 55 at 24 months minimum follow‐up. While limitations exist, our findings contribute to understanding optimal surgical approaches, emphasizing individualized treatment based on patient characteristics and surgeon expertise. …”
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Dynamic Dwell Time Adjustment in Wire Arc-Directed Energy Deposition: A Thermal Feedback Control Approach by Md Munim Rayhan, Abderrachid Hamrani, Fuad Hasan, Tyler Dolmetsch, Arvind Agarwal, Dwayne McDaniel

“…Experimental validation demonstrated improvements in thermal management, with the dynamic control system maintaining an average temperature undershoot of 1.38% while achieving 96.29% optimal temperature window compliance. …”
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NeuroRF FarmSense: IoT-fueled precision agriculture transformed for superior crop care by Tarun Vats, Shrey Mehra, Uday Madan, Amit Chhabra, Akashdeep Sharma, Kunal Chhabra, Sarabjeet Singh, Utkarsh Chauhan

“…In light of the ongoing global hunger crisis, it is imperative to improve food production in accordance with Sustainable Development Goal 2.0, which aims to eliminate hunger while promoting sustainable agricultural practices. …”
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Beam Scanning with Ultra‐Low Sidelobes and In‐Band Ultra‐Low Scattering Characteristics Empowered by Single Space‐Time‐Coding Radiation‐Scattering Metasurface by Lixin Jiang, Yongfeng Li, Hao Yang, Mingbao Yan, Jinming Jiang, Yunwei Zhang, Zhe Qin, Wanwan Yang, Hongya Chen, Yongqiang Pang, Zhihao Guo, Lin Zheng, Jiafu Wang, Shaobo Qu

“…Furthermore, the proposed strategy does not necessitate the utilization of optimization algorithms and exhibits low SLLs and low SBLs, which will make it flourish in RF stealth applications, such as covert communication systems.…”
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