Validation of the Virtual Reality Stroop Room: Effects of inhibiting interfering information under time-pressure and task-switching demands by Veronika Ringgold, Luca Abel, Bjoern M. Eskofier, Nicolas Rohleder

“…The Stroop Effect, reflected in prolonged processing times and increased errors in the incongruent phase, was observed. Participants reported heightened Distress and Engagement post-experiment, alongside lower Worry, assessed via the Short Stress State Questionnaire. …”
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Prediction of barite scale formation and inhibition in hydrocarbon reservoirs using AI modeling: Focus on different optimization algorithms by Ouafa Belkacem, Ahmed Rezrazi, Kamel Aizi, Lokmane Abdelouahed, Maamar Laidi, Abdelhafid Touil, Leila Cherifi, Salah Hanini

“…The performance of the models was rigorously evaluated using statistical criteria and graphical tools, demonstrating exceptional accuracy with minimal errors. The ELM model emerged as the most precise (RMSE = 0.0005, R² = 0.999), closely followed by the SVR-PSO model (RMSE = 0.0008, R² = 0.999). …”
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Universal machine learning interatomic potentials poised to supplant DFT in modeling general defects in metals and random alloys by Fei Shuang, Zixiong Wei, Kai Liu, Wei Gao, Poulumi Dey

“…Remarkably, the latest EquiformerV2 models achieve DFT-level accuracy on comprehensive defect datasets, with root mean square errors below 5 meV atom ^−1 for energies and 100 meV Å ^−1 for forces, outperforming specialized machine learning potentials such as moment tensor potential and atomic cluster expansion. …”
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A quantum-resilient lattice-based security framework for internet of medical things in healthcare systems by Zeyad Ghaleb Al-Mekhlaf, Murtaja Ali Saare, Jalal Mohammed Hachim Altmemi, Mahmood A. Al-Shareeda, Badiea Abdulkarem Mohammed, Gharbi Alshammari, Reem alrashdi, Yasser A. Alkhabra, Ibrahim Alreshidi

“…This paper proposes a quantum-resistant healthcare security framework based on lattice-based cryptographic primitives such as Learning With Errors (LWE), Ring-LWE (RLWE), and Short Integer Solution (SIS). …”
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PolyBuild: An End-to-End Method for Polygonal Building Contour Extraction From High-Resolution Remote Sensing Images by Yaoteng Zhang, Julin Zhang, Guangshuai Wang, Jiwei Deng, Hui Sheng, Yasir Muhammad, Shiqing Wei

“…Mainstream approaches for building extraction often rely on pixel-level segmentation followed by multiple postprocessing steps to produce building contour, which can be computationally intensive and prone to errors. In this paper, we propose an end-to-end method named PolyBuild, which can directly extract building vector polygons from high-resolution remote sensing images without the need for any postprocessing operations. …”
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Large-area OLED substrate printing path planning method based on multi-head GAT imitation learning to solve partitioned integer programming by Jiacong Xiong, Jiankui Chen, Yiqun Li, Xiao Yue, Yu Fu, Zhouping Yin

“…The difficulty intensifies in large-area OLED production, where angular alignment errors in the substrate are magnified. This results in an exponential increase in pixels requiring planning, with the total pixel pit count reaching hundreds of millions. …”
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Real-time monitoring of soil moisture in cotton fields using electromagnetic induction technology by Yang Gao, Quanze Hu, Jiaojiao Hui, Lin Chang, Mei Zeng, Qingsong Jiang

“…Currently, electromagnetic induction technology provides a non-destructive alternative, using the inversion simulation of soil apparent electrical conductivity (ECa) to construct an empirical θg model, but the prediction accuracy of the constructed model is questioned when dealing with dynamic or highly uncertain data, resulting in large errors in the prediction results and cannot meet the needs of practical applications. …”
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Exploration of machine learning approaches for automated crop disease detection by Annu Singla, Ashima Nehra, Kamaldeep Joshi, Ajit Kumar, Narendra Tuteja, Rajeev K. Varshney, Sarvajeet Singh Gill, Ritu Gill

“…Conventional methods exclusively rely on human expertise, and are often labor-intensive, time-consuming, and prone to errors. Recent advancements in machine learning (ML) offer promising alternatives by automating the disease detection processes with high precision and efficiency. …”
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Buried PE Pipeline Location Method Based on Double-Tree Complex Wavelet Cross-Correlation Delay by Yang Li, Hanyu Zhang, Zhuo Xu, Ao Zhang, Xianfa Liu, Pengyao Sun, Xianchao Sun

“…The results indicate that the maximum error is 4.6% for asymmetric arrangements and less than 1% for symmetric arrangements. …”
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Accelerated commercial battery electrode-level degradation diagnosis via only 11-point charging segments by Yu Tian, Cheng Lin, Xiangfeng Meng, Xiao Yu, Hailong Li, Rui Xiong

“…Results demonstrates that 11 points collected at any starting state-of-charge (SOC) in a minimum of 2.5 ​minutes are sufficient to obtain reliable ICA curves with a mean root mean square error (RMSE) of 0.2774 Ah/V. Accordingly, battery status can be accurately elevated based on their degradation at both macro and electrode levels. …”
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Empirical Study of Magnet Distance on Magneto-Mechanical Resonance Frequency by Knopp Tobias, Mohn Fabian, Foerger Fynn, Thieben Florian, Hackelberg Niklas, Faltinath Jonas, Tsanda Artyom, Boberg Marija, Möddel Martin

“…Experimental analysis of the resonance frequency and comparison with the model values show both qualitative and quantitative agreement with an average relative error of only 0.8 %. This validates the implemented model and shows the suitability of our magneticmechanical resonator made from cylindrical permanent magnets for sensing applications.…”
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A neural network-based synthetic diagnostic of laser-accelerated proton energy spectra by Christopher J. G. McQueen, Robbie Wilson, Timothy P. Frazer, Martin King, Matthew Alderton, Ewan F. J. Bacon, Ewan J. Dolier, Thomas Dzelzainis, Jesel K. Patel, Maia P. Peat, Ben C. Torrance, Ross J. Gray, Paul McKenna

“…Trained on data from fewer than 700 laser-plasma interactions, the model achieves an error level of 13.5%, and improves with more data. …”
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Research on Flame Temperature Measurement Technique Combining Spectral Analysis and Two-Color Pyrometry by Pan Pei, Xiaojian Hao, Shenxiang Feng, Tong Wei, Chenyang Xu

“…In comparison to traditional two-color infrared thermometers and Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology, the maximum relative temperature measurement error was 2.1%. This work provides technical insights into the development of high-resolution, low-cost flame temperature imaging technology applicable across a wide range of fields.…”
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Li-Ion Battery State of Health Estimation Based on Short Random Charging Segment and Improved Long Short-Term Memory by Aina Tian, Zhe Chen, Zhuangzhuang Pan, Chen Yang, Yuqin Wang, Kailang Dong, Yang Gao, Jiuchun Jiang

“…Lithium-ion batteries have been used in a wide range of applications, including electrochemical energy storage and electrical transportation. …”
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A model to simulate human cardio-respiratory responses to different fluid resuscitation treatments after hemorrhagic injury by Varghese Kurian, Varghese Kurian, Xin Jin, Xin Jin, Sridevi Nagaraja, Sridevi Nagaraja, Anders Wallqvist, Jaques Reifman

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SIP-IFVM: A Time-evolving Coronal Model with an Extended Magnetic Field Decomposition Strategy by Haopeng Wang, Liping Yang, Stefaan Poedts, Andrea Lani, Yuhao Zhou, Yuhang Gao, Luis Linan, Jiakun Lv, Tinatin Baratashvili, Jinhan Guo, Rong Lin, Zhan Su, Caixia Li, Man Zhang, Wenwen Wei, Yun Yang, Yucong Li, Xinyi Ma, Edin Husidic, Hyun-Jin Jeong, Mahdi Najafi-Ziyazi, Juan Wang, Brigitte Schmieder

“…However, when the inner-boundary magnetic field evolves, ∣ B _1 ∣ can grow significantly, and its discretization errors often lead to nonphysical negative thermal pressure, ultimately causing the simulation to crash. …”
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Bionic Compass Method Based on Atmospheric Polarization Optimization in Non-Ideal Clear Condition by Yuyang Li, Xia Wang, Min Zhang, Ruiqiang Li, Qiyang Sun

“…The results demonstrate that the proposed algorithm effectively mitigates the impact of scattering from aerosols and other particles, reducing the heading angle error to within 2° under sunny, cloudy, overcast and sandy conditions.…”
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Deep Learning Method for Breakdown Voltage and Forward <i>I-V</i> Characteristic Prediction of Silicon Carbide Schottky Barrier Diodes by Hao Zhou, Xiang Wang, Shulong Wang, Chenyu Liu, Dongliang Chen, Jiarui Li, Lan Ma, Guohao Zhang

“…After training for 1000 epochs, the deep learning-based model could predict not only point values like <i>V</i>_br but also curves, such as forward <i>I-V</i> characteristics, with a mean squared error (MSE) of less than 10⁻³. Our research shows the applicability and high efficiency of introducing deep learning into device characteristic prediction.…”
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Evaluation of Clipping Based Iterative PAPR Reduction Techniques for FBMC Systems by Zsolt Kollár, Lajos Varga, Bálint Horváth, Péter Bakki, János Bitó

“…An overview is presented on transmitter oriented techniques employing baseband clipping, which can maintain the system performance with a desired bit error rate (BER).…”
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Active learning framework to optimize process parameters for additive-manufactured Ti-6Al-4V with high strength and ductility by Jeong Ah Lee, Jaejung Park, Man Jae Sagong, Soung Yeoul Ahn, Jung-Wook Cho, Seungchul Lee, Hyoung Seop Kim

“…Abstract Optimizing process and heat-treatment parameters of laser powder bed fusion for producing Ti-6Al-4V alloys with high strength and ductility is crucial to meet performance demands in various applications. Nevertheless, inherent trade-offs between strength and ductility render traditional trial-and-error methods inefficient. …”
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