Navigating the Handover: Reviewing Takeover Requests in Level 3 Autonomous Vehicles by Joel Andrew Miller, Soodeh Nikan, Mohamed H. Zaki

“…Autonomous vehicles (AVs) represent a transformative advance in automotive technology, promising increased safety and efficiency by reducing human error. However, integrating human factors remains a critical challenge, especially during takeover scenarios where the human driver must re-assume control of the vehicle. …”
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A clustering-based federated deep learning approach for enhancing diabetes management with privacy-preserving edge artificial intelligence by Xinyi Yang, Juan Li

“…The results show that the Clu-FDL approach achieves high precision (0.93), recall (0.96), and F1 scores (0.95), along with low Root Mean Square Error (RMSE) values (11.08 ± 1.77 mg/dL). Additionally, for new patients with different data durations, analysis based on 0.25–3 days of data indicates that Clu-FDL models exhibit greater stability, with smaller RMSE and higher precision, recall, and F1 scores compared to non-clustering models. …”
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Reproduction of experimental data for stacked caffeine dimers using various computational methods by Maria Patricia Sanchez Gutierrez, Eduardo Gonzalez Jimenez, Alexandra Deriabina, Juan Carlos Sanchez Perez, Valeri Poltev

“…These methods are: the MP2 with Basis Set Superposition Error correction (MP2/CP), Poltev force field, along with PBE0-DH, SCAN and PBE-D3 functionals of DFT. …”
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Neural Network-Based Lower Limb Prostheses Control Using Super Twisting Sliding Mode Control by Adisu Tadese Demora, Chala Merga Abdissa

“…Simulation results show that training the neural network with processed data increases regression value and decreases trajectory tracking mean squared error (MSE). The controller’s robustness against internal parameter change and external environmental changes is demonstrated through parameter variation and disturbance analysis.…”
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Phase-Field Simulation of the Creep Mechanism in the AZ31 Magnesium Alloy Under Discontinuous Dynamic Recrystallization Dominance by Alireza Rezvani, Ramin Ebrahimi, Ebad Bagherpour

“…The model accurately predicts recrystallization kinetics and microstructural evolution, exhibiting a strong correlation with experimental results, with an error of approximately 5%. This research provides a robust and efficient approach for predicting creep behavior in high-temperature applications, vital for optimizing material selection and predicting component lifespan in industries. …”
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Analytical Solutions for Girder Distribution Factor in Steel-Concrete Composite Girders with the Effect of Parapets by Zejun Zhang, Yongjian Liu, Bowen Feng, Yinping Ma, Guojing Zhang

“…As the effect of the continuous layer on each girder was relatively uniform, the simplified method was optimized only considering the effect of the parapet. …”
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Contagious disease outbreaks: Distinguishing between constant and variable order using the SEIAR model by S.Sepehr Tabatabaei, Mohammadreza Dehghan

“…The proposed framework can be generalized to other diseases and regions, offering a robust tool for epidemic analysis and decision-making.…”
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An Innovation Machine Learning Approach for Ship Fuel-Consumption Prediction Under Climate-Change Scenarios and IMO Standards by Bassam M. Aljahdali, Yazeed Alsubhi, Ayman F. Alghanmi, Hussain T. Sulaimani, Ahmad E. Samman

“…For bulk carriers, the EANN achieved a Root Mean Squared Error (RMSE) of 5.71 tons/day during testing, compared to 9.91 tons/day for the FFNN model. …”
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Application of Proper Orthogonal Decomposition in Spatiotemporal Characterization and Reduced-Order Modeling of Rotor–Stator Interaction Flow Field by Yongkang Lin, Weijian Yang, Hu Wang, Fazhong Wang, Jie Hu, Jianyao Yao

“…Therefore, analyzing the excitation characteristics of RSI flow fields under multi-parameter conditions is essential for vibration analysis and optimization in fluid–structure interaction. …”
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Identification of Distribution Network Topology and Line Parameter Based on Smart Meter Measurements by Chong Wang, Zheng Lou, Ming Li, Chaoyang Zhu, Dongsheng Jing

“…Accurate line parameters are the basis for the optimal control and safety analysis of distribution networks. …”
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Self-driving lab for the photochemical synthesis of plasmonic nanoparticles with targeted structural and optical properties by Tianyi Wu, Sina Kheiri, Riley J. Hickman, Huachen Tao, Tony C. Wu, Zhi-Bo Yang, Xin Ge, Wei Zhang, Milad Abolhasani, Kun Liu, Alan Aspuru-Guzik, Eugenia Kumacheva

“…Here, we introduce the Autonomous Fluidic Identification and Optimization Nanochemistry (AFION) self-driving lab that integrates a microfluidic reactor, in-flow spectroscopic nanoparticle characterization, and machine learning for the exploration and optimization of the multidimensional chemical space for the photochemical synthesis of plasmonic nanoparticles. …”
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Advanced generalized machine learning models for predicting hydrogen–brine interfacial tension in underground hydrogen storage systems by Ahmed Farid Ibrahim

“…These top models achieved RMSE values below 1.3 mN/m and MAPE values under 1.5%, confirming their high predictive accuracy. Residual frequency analysis and APRE results further confirmed these ensemble models’ low bias and high reliability, with error distributions centered near zero. …”
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A Robust Stability Control Method Integrating Linear Quadratic Regulator and Proportional Integral for Islanded AC Microgrid by Muhammad Nauman Malik, Qianyu Zhao, Shouxiang Wang

“…The proposed hybrid LQR-PI control technique minimizes the quadratic value of power error and control inputs during transients while also optimizing robustness margins by including an adaptive tuning mechanism. …”
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Features of project activity in professional education by Yury Pavlovich Vetrov

“…Main difficulties and mistakes in the implementation of students' project activities in the educational process of vocational education institutions have been presented on the basis of the analysis of theoretical data. The author defines the conditions under which the organization of students' project activities in the educational process of vocational education organizations will be the most optimal. …”
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A Hybrid RBF-PSO Framework for Real-Time Temperature Field Prediction and Hydration Heat Parameter Inversion in Mass Concrete Structures by Shi Zheng, Lifen Lin, Wufeng Mao, Yanhong Wang, Jinsong Liu, Yili Yuan

“…This study proposes an RBF-PSO hybrid framework for efficient inversion analysis of hydration heat parameters in mass concrete temperature fields, addressing the computational inefficiency and accuracy limitations of traditional methods. …”
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A single-snapshot inverse solver for two-species graph model of tau pathology spreading in human Alzheimer’s disease by Zheyu Wen, Ali Ghafouri, George Biros, the Alzheimer’s Disease Neuroimaging Initiative (ADNI)

“…This optimization problem is solved with a projection-based quasi-Newton algorithm. …”
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Laor Initialization: A New Weight Initialization Method for the Backpropagation of Deep Learning by Laor Boongasame, Jirapond Muangprathub, Karanrat Thammarak

“…This paper presents Laor Initialization, an innovative weight initialization technique for deep neural networks that utilizes forward-pass error feedback in conjunction with k-means clustering to optimize the initial weights. …”
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Enhancing cardiovascular monitoring: a non-linear model for characterizing RR interval fluctuations in exercise and recovery by Matías Castillo-Aguilar, Diego Mabe-Castro, David Medina, Cristian Núñez-Espinosa

“…Validation against real-world RRi data demonstrated robust model performance (R 2 = 0.868, CI95%[0.834, 0.895] and Root Mean Square Error [RMSE] = 32.6 ms, CI95%[30.01, 35.77]), accurately reflecting autonomic recovery and exercise-induced fluctuations. …”
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Conversion to Variable Flow Rate—Advanced Control of a District Heating (DH) System with a Focus on Operational Data by Stanislav Chicherin

“…The results show a significant reduction in excess heat supply during warm days, with improvements in heat demand prediction accuracy (17.3% average error) compared to standard models. Notably, the optimized configuration led to a 21% reduction in total greenhouse gas (GHG) emissions (including 6537 tons of CO₂ annually), a 55.3% decrease in annualized operational costs, and a positive net present value (NPV) by year nine, with an internal rate of return (IRR) of 25.4%. …”
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Genderly: a data-centric gender bias detection system by Wael Khreich, Jad Doughman

“…Error analysis further explored top-performing model strengths and limitations. …”
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