Embedded solar adaptive optics telescope: achieving compact integration for high-efficiency solar observations by Naiting Gu, Hao Chen, Ao Tang, Xinlong Fan, Carlos Quintero Noda, Yawei Xiao, Libo Zhong, Xiaosong Wu, Zhenyu Zhang, Yanrong Yang, Zao Yi, Xiaohu Wu, Linhai Huang, Changhui Rao

“…Validations including turbulence simulations, optical bench testing, and practical observations at the Lijiang observatory collectively confirm the system's capability to maintain about λ/10 wavefront error during active region tracking. This architectural breakthrough of the ESAOT addresses long-standing SAO integration challenges in solar astronomy and provides scalability analyses confirming direct applicability to the existing and future large solar observation facilities.…”
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Bridging experiments and models, towards a new paradigm: DROP-PINN, a physics-informed neural network to predict droplet rupture in multiphase systems by Grégory Bana, Fabrice Lamadie, Sophie Charton, Didier Lucor, Nida Sheibat-Othman

“…These kernels contain parameters that are tailored to specific fluid properties and operating conditions, thus limiting their general applicability (i.e. transposition to other operating conditions or processes than those used during model development). …”
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Development of an Efficient and Generalized MTSCAM Model to Predict Liquid Chromatography Retention Times of Organic Compounds by Mengdie Fan, Chenhui Sang, Hua Li, Yue Wei, Bin Zhang, Yang Xing, Jing Zhang, Jie Yin, Wei An, Bing Shao

“…The results demonstrate that this model achieves an R2 of 0.98 and an average prediction error of 23 s, outperforming currently published models. …”
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Optimizing Backbone Networks Through Hybrid–Modal Fusion: A New Strategy for Waste Classification by Houkui Zhou, Qifeng Ding, Chang Chen, Qinqin Liao, Qun Wang, Huimin Yu, Haoji Hu, Guangqun Zhang, Junguo Hu, Tao He

“…Traditional manual methods are time-consuming, labor-intensive, costly, and error-prone, resulting in reduced accuracy. Deep learning has revolutionized this field. …”
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Hydrological insights: Comparative analysis of gridded potential evapotranspiration products for hydrological simulations and drought assessment by Mohammed Abdallah, Ke Zhang, Sudhir Kumar Singh, Mukhtar Jibril Abdi, Ayman M. Elameen, Almutaz A.A. Mohammed, Hussam Eldin Elzain

“…Seasonally, GLEAM PET exhibits the highest accuracy and lowest error in streamflow simulation across all three regions. …”
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AI-driven diagnosis and health management of autonomous electric vehicle powertrains: An empirical data-driven approach by Hicham El hadraoui, Adila El maghraoui, Oussama Laayati, Erroumayssae Sabani, Mourad Zegrari, Ahmed Chebak

“…To address this challenge, this paper proposes a novel and integrated data-driven methodology for fault diagnosis of induction motors (IMs) in EV powertrain applications. The approach leverages vibration signals acquired from accelerometers and employs a hybrid machine learning (ML) framework. …”
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AI-Powered Dental Forensics in Transforming Age Estimation Techniques: A Narrative Review by Parul Khare, Kalyani Bhargava, M Siddharth, Deepak Bhargava, Anoushka Chauhan

“…This review highlights how combining AI with different imaging techniques can enhance accuracy, reduce human error and address population-specific variations in forensic age estimation.…”
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Large-Scale Completion of Ionospheric TEC Maps Using Machine Learning Models With Constraints Conditions by Qingfeng Li, Hanxian Fang, Chao Xiao, Die Duan, Hongtao Huang, Ganming Ren

“…The CGVAE-label model provides a reliable solution for TEC gap-filling, with implications for broader applications in remote sensing and space weather studies.…”
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Bayesian Model Averaging for Satellite Precipitation Data Fusion: From Accuracy Estimation to Runoff Simulation by Shaowei Ning, Yang Cheng, Yuliang Zhou, Jie Wang, Yuliang Zhang, Juliang Jin, Bhesh Raj Thapa

“…Evaluation metrics included the correlation coefficient (CC), root mean square error (RMSE), and Kling–Gupta efficiency (KGE). The Variable Infiltration Capacity (VIC) hydrological model was further applied to assess how these datasets affect runoff simulations. …”
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Adaptive control strategies for button motor actuated insect scale flapping wing MAV mechanisms by Spoorthi Singh, Meet Hitesh Jain, Kanishk Kaushal, Mohammad Zuber, Ernnie Illyani Basri, Kamarul Arifin Ahmad, Sharul Sham Dol, Vishnu G. Nair

“…This study underscores the potential of SRFFC-driven designs and modular motor configurations to enhance the performance, control, and applicability of FWMAVs for advanced micro-aerial systems.…”
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Novel Mathematical Modeling Parameters of PEMFC Based on Newton–Raphson Iterative Method by Ahmed A. Zaki Diab, Ahmed Hamdy Ali, Hamdy M. Sultan, Mohamed A. Ismeil, Montaser Abdelsattar

“…A Proton Exchange Membrane Fuel Cell (PEMFC) is an electrochemical generator used for various applications in modern life. In recent years, it has become a promising Renewable Energy Source (RES) technology that uses natural gases such as oxygen and hydrogen for electrical generation. …”
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Research on a New Method of Macro–Micro Platform Linkage Processing for Large-Format Laser Precision Machining by Longjie Xiong, Haifeng Ma, Zheng Sun, Xintian Wang, Yukui Cai, Qinghua Song, Zhanqiang Liu

“…In summary, the proposed method adeptly balances efficiency and quality, rendering it particularly suitable for laser precision machining applications.…”
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From Stationary to Nonstationary UAVs: Deep-Learning-Based Method for Vehicle Speed Estimation by Muhammad Waqas Ahmed, Muhammad Adnan, Muhammad Ahmed, Davy Janssens, Geert Wets, Afzal Ahmed, Wim Ectors

“…Unmanned aerial vehicles (UAVs) and deep learning (DL) models are examples of such disruptive technologies with diverse industrial applications that are gaining traction. When it comes to road traffic monitoring systems (RTMs), the combination of UAVs and vision-based methods has shown great potential. …”
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Nomogram for predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids based on oxytocin experimentation and ultrasonographic features: a retrospec... by Sheng Chen, Danling Zhang, Guisheng Ding, Mengqi Chen, Songsong Wu, Jianzhong Zou

“…The calibration curve of the nomogram demonstrated good consistency between actual observations and nomogram predictions, with an absolute error of 0.066. The model’s discriminative ability was evaluated by the area under the curve, which was 0.887 (95% CI: 0.818–0.955). …”
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Golden eagle optimized CONV-LSTM and non-negativity-constrained autoencoder to support spatial and temporal features in cancer drug response prediction by Wesam Ibrahim Hajim, Suhaila Zainudin, Kauthar Mohd Daud, Khattab Alheeti

“…Evaluations are conducted on two large datasets from the Genomics of Drug Sensitivity in Cancer (GDSC) repository, and the proposed NNCAE-GEO-Conv-LSTM-based approach has achieved 96.99% and 97.79% accuracies, respectively, with reduced processing time and error rate for the DRP problem.…”
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Experimental modal identification of a pedestrian bridge through drive-by monitoring integrated with shared-mobility vehicles by Kun Feng, David Hester, Su Taylor, Connor O'Higgins, Alan Ferguson, Zuo Zhu, Guang Zou, Myra Lydon, Juliana Early

“…However, their effectiveness has predominantly been investigated in ideal scenarios, with actual real-world applications being quite scarce. The research presented in this paper explores the feasibility of combining two routes: (1) fleet emissions reduction and (2) transport resilience enhancement, through drive-by monitoring integrated with shared mobility, including electric mobility scooter and bicycle. …”
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An AI-Enabled Framework for <i>Cacopsylla chinensis</i> Monitoring and Population Dynamics Prediction by Ruijun Jing, Deyan Peng, Jingtong Xu, Zhengjie Zhao, Xinyi Yang, Yihai Yu, Liu Yang, Ruiyan Ma, Zhiguo Zhao

“…Furthermore, the population dynamics model yields a mean absolute error of 1.94% for the test dataset. These performance indicators fully meet the requirements of practical agricultural applications.…”
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Analysis of the Characteristics and Contribution Rate of Base Flow in Typical Basins of the Loess Plateau by ZHANG Jiyuan, YU Kunxia, LI Zhanbin, LI Peng, LIU Yonggang, MO Shuhong, ZHAO Binhua, YANG Jianhong, JIA Lu, LI Xue

“…[Results] The F4 digital filtering method exhibited superior performance in terms of stability, dispersion, and error metrics, making it the most suitable method for the typical watersheds of the Loess Plateau. …”
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Research on Missing Data Estimation Method for UPFC Submodules Based on Bayesian Multiple Imputation and Support Vector Machines by Xiaoming Yu, Jun Wang, Ke Zhang, Zhijun Chen, Ming Tong, Sibo Sun, Jiapeng Shen, Li Zhang, Chuyang Wang

“…Future research will explore dynamic weight optimization and extend the framework to multi-source heterogeneous data applications.…”
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Back Propagation Neural Network model for analysis of hyperspectral images to predict apple firmness by Shuiping Li, Yueyue Chen, Xiaobo Zhang, Junbo Wang, Xuanxiang Gao, Yunhong Jiang, Zhaojun Ban, Cunkun Chen

“…The coefficient of determination (R2) and root mean square error (RMSE) of Partial Least Squares (PLS) models are contrasted using various inputs. …”
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