Deep Learning Autoencoders for Fast Fourier Transform-Based Clustering and Temporal Damage Evolution in Acoustic Emission Data from Composite Materials by Serafeim Moustakidis, Konstantinos Stergiou, Matthew Gee, Sanaz Roshanmanesh, Farzad Hayati, Patrik Karlsson, Mayorkinos Papaelias

“…The proposed method achieves a reconstruction error of 0.0017 and a high R-squared value of 0.95, indicating the autoencoder’s effectiveness in learning compact representations while minimizing information loss. …”
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Unlocking the therapeutic potential of unexplored phytocompounds as hepatoprotective agents through integration of network pharmacology and in-silico analysis by Pranali A. Jadhav, Asha B. Thomas, Mohsin K. Pathan, Somdatta Y. Chaudhari, Ravindra D. Wavhale, Sohan S. Chitlange

“…Our findings demonstrate the utility of this integrated approach which transits beyond traditional trial-and-error methods. …”
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Enhanced power sharing and voltage regulation for islanded nano-satellite DC microgrids in spinning flight scenarios by Khalil Louassaa, Josep M. Guerrero, Baseem Khan, Muhammad Zain Yousaf, Mohamed Ali Zdiri, Liu Zhang, Rajkumar Sivanraju

“…Comprehensive validation through stability analysis, simulations, and experimental testing demonstrates superior performance versus conventional methods, with significant improvements in transient response speed, steady-state error reduction, and disturbance rejection capability. …”
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Transient Stability Analysis of Wind-Integrated Power Systems via a Kuramoto-like Model Incorporating Node Importance by Min Cheng, Jiawei Yu, Mingkang Wu, Yayao Zhang, Yihua Zhu, Yuanfu Zhu

“…As the global energy structure transitions towards cleaner sources, large-scale integration of wind power has become a trend for modern power systems. …”
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Keys to Achieving Target First Medical Contact to Balloon Times and Bypassing Emergency Department More Important Than Distance by Saad Ezad, Allan J. Davies, Hooria Cheema, Trent Williams, James Leitch

“…Using a cutoff distance of 50 km may reduce human error in estimating travel time to our PCI centre and thereby identifying patients who should receive prehospital thrombolysis.…”
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Statistical analysis of the formation mechanism of concepts-representations in organizational and technical systems by Alexander A. Solodov

“…The asymptotic relations for the number of corrections are obtained, and the error of the approximate asymptotic relations is estimated.Thus, the paper formulates a very general model of the random process of formation of sensual images and their transformation into concepts-representations. …”
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Individually addressed entangling gates in a two-dimensional ion crystal by Y.-H. Hou, Y.-J. Yi, Y.-K. Wu, Y.-Y. Chen, L. Zhang, Y. Wang, Y.-L. Xu, C. Zhang, Q.-X. Mei, H.-X. Yang, J.-Y. Ma, S.-A. Guo, J. Ye, B.-X. Qi, Z.-C. Zhou, P.-Y. Hou, L.-M. Duan

“…We use symmetrically placed crossed acousto-optic deflectors (AODs) to drive Raman transitions and achieve an addressing crosstalk error below 0.1%. …”
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Performance of wind assessment datasets in United States coastal areas by L. M. Sheridan, J. Wang, C. Draxl, N. Bodini, C. Phillips, D. Duplyakin, H. Tinnesand, R. K. Rai, J. E. Flaherty, L. K. Berg, C. Jung, E. Young, R. Kotamarthi

“…GWA3 produces the smallest annual average wind speed relative errors, whereas WTK-LED Climate is in best agreement in terms of representing diurnal wind speed cycles. …”
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Robust confinement state classification with uncertainty quantification through ensembled data-driven methods by Yoeri Poels, Cristina Venturini, Alessandro Pau, Olivier Sauter, Vlado Menkovski, the TCV Team, the WPTE Team

“…We evaluate our method quantitatively using Cohen’s kappa coefficient for predictive performance and the expected calibration error for the uncertainty calibration. Furthermore, we discuss performance using a variety of common and alternative scenarios, the performance of individual components, out-of-distribution performance, cases of broken or missing signals, and evaluate conditionally-averaged behavior around different state transitions. …”
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Modeling of critical sand-carrying flow rate of gas-liquid-solid three-phase flow in an inclined pipe by Guowei Wang, Yong Zhang, Junwei Sun, Qi Xia, Manlai Zhang, Ruiquan Liao

“…Compared with models proposed by previous scholars, the new model significantly improves computational accuracy (error within 9 %) and expands the applicability range by introducing the particle specific surface area and slip factor to quantify the morphological characteristics of non-spherical particles and the slip effects between multiphase fluids, respectively.…”
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A Refined Fuzzy MARCOS Approach with Quasi-D-Overlap Functions for Intuitive, Consistent, and Flexible Sensor Selection in IoT-Based Healthcare Systems by Mahmut Baydaş, Safiye Turgay, Mert Kadem Ömeroğlu, Abdulkadir Aydin, Gıyasettin Baydaş, Željko Stević, Enes Emre Başar, Murat İnci, Mehmet Selçuk

“…Furthermore, it effectively supports decision-makers in identifying optimal sensor alternatives by balancing critical factors such as accuracy, energy consumption, latency, and error tolerance. Overall, the study fills a significant methodological gap in fuzzy MCDM literature and introduces a robust fuzzy aggregation strategy that facilitates interpretable, consistent, and reliable decision making in dynamic and uncertain healthcare environments.…”
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V˙O2 linear-onset kinetics spanning steady- and non-steady-state exercise by Robert Robergs, Robert Robergs, Robert Robergs, Bridgette O’Malley, Bridgette O’Malley, Anais Dewilde, Shaun D’Auria, Ales Krouzecky

“…IntroductionThe traditional method for quantifying the kinetics of the increase in the body’s consumption of oxygen (V˙O2) during exercise transitions to steady state involves application of a mono-exponential function. …”
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Magnetic Activities of Wolf 359: Starspot Distribution and Quasiperiodic Pulsation Using TESS Data by Diya Ram, Soumen Mondal, Samrat Ghosh, Rajib Kumbhakar

“…The rotation period from TESS is estimated to be 2.69 days with negligible error, which matches well with the previous literature values. …”
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Improved lightweight DeepLabV3+ for bare rock extraction from high-resolution UAV imagery by Pengde Lai, Chao Lv, Lv Zhou, Shengxiong Yang, Jiao Xu, Qiulin Dong, Meilin He

“…Results show the following: (1) When MobileNetV2 is used as the backbone of DeepLabV3+, the Accuracy, F1 score, and MIoU reach 97.39 %, 78.91 %, and 82.11 %, respectively, outperforming VGG16, Xception, SqueezeNet, and traditional segmentation models. (2) Applying the lightweight DeepLabV3+ model to bare rock identification in orthophoto imagery of the study area results in a bare rock rate error of approximately 5 %, demonstrating the practical applicability of the model. (3) After the introduction of the attention mechanism, the model's Recall, F1 score, and MIoU increased by 14.00 %, 8.37 %, and 5.62 %, respectively, remarkably enhancing identification completeness and boundary accuracy. …”
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A Modified Nonlinear Mohr–Coulomb Failure Criterion for Rocks Under High-Temperature and High-Pressure Conditions by Zhuzheng Li, Hongxi Li, Qiangui Zhang, Jiahui Wang, Cheng Meng, Xiangyu Fan, Pengfei Zhao

“…In deep, geologically complex environments characterized by high in situ stress and elevated formation temperatures, the mechanical behavior of rocks often transitions from brittle to ductile, differing significantly from that of shallow formations. …”
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Review of radiolarian microfossils as a tool for reconstructing sea surface temperature of the past in the Northwest Pacific by Kenji M. Matsuzaki, Takuya Itaki, Yoshimi Kubota, Kyung Eun Lee, Isao Motoyama, Takuya Sagawa, Keiji Horikawa, Masafumi Murayama, Hajime Obata

“…Applying weighted averaging partial least squares transfer function on selected radiolarian species showing strong affinities with changes in summer SST, we re-evaluated past summer SSTs at IODP Site U1429 in the northern East China Sea with high accuracy (R2 = 0.97, error margin ± 1.4 °C). Our radiolarian-based summer SST reconstruction is similar to Globigerinoides ruber Mg/Ca-based summer SSTs, though showing minor disparities during glacial periods, while constant disparities were observed with alkenone-based SST estimates at the same site, which is likely due to seasonal biases. …”
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A Refined Model for Ablation Through Cavitation Bubbles with Ultrashort Pulse Lasers by Shwetabh Verma, Samuel Arba Mosquera

“…Taking a photodisruption model coefficient commonly used in the literature, the root mean square error between the two interaction models was minimized using the generalized reduced gradient fitting method to calculate the optimum scaling factors for the plasma model. …”
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Evaluation of the LI-710 evapotranspiration sensor in comparison to full eddy covariance for monitoring energy fluxes in perennial and annual crops by Srinivasa Rao Peddinti, Isaya Kisekka

“…Corresponding reductions in root mean square error (RMSE) confirmed that EBR-corrected LI-710 measurements closely aligned with EC observations, effectively capturing seasonal peaks and phenological transitions. …”
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Dynamic Simulation of Ground Braking Force Control Based on Fuzzy Adaptive PID for Integrated ABS-RBS System with Slip Ratio Consideration by Pinjia Shi, Yongjun Min, Hui Wang, Liya Lv

“…The proposed control strategy achieves remarkable precision improvements, reducing integral time absolute error (<i>ITAE</i>) by 8.3–52.8% compared to conventional methods. …”
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FEN-MRMGCN: A Frontend-Enhanced Network Based on Multi-Relational Modeling GCN for Bus Arrival Time Prediction by Ting Qiu, Chan-Tong Lam, Bowie Liu, Benjamin K. Ng, Xiaochen Yuan, Sio Kei Im

“…Experimental results demonstrate that our frontend-enhanced network achieves a reduction in the Mean Absolute Percentage Error (MAPE) by 15.36%, 13.44%, and 19.07% compared to traditional time series forecasting models like CNN, LSTM, and Transformer, respectively. …”
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