What Can DKIST/DL-NIRSP Tell Us about Quiet-Sun Magnetism? by Jiayi Liu, Xudong Sun, Peter W. Schuck, Sarah A. Jaeggli

“…We discuss the implications for DKIST observations.…”
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Prediction of Pilot Performance During Startle Events Based on Neuropsychophysiological Features of Stress Resilience and Cognitive Task Scores by Mate Gambiraza, Sinisa Popovic, Matej Kurtak, Tanja Jovanovic, Seth Norrholm, Kresimir Cosic

“…These findings may improve the accuracy of predicting pilot performance during startle events, with implications for pilot selection and training.…”
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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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Spatiotemporal Dynamics and Future Projections of Carbon Use Efficiency on the Mongolian Plateau: A Remote Sensing and Machine Learning Approach by Xinyu Yang, Qiang Yu, Buyanbaatar Avirmed, Yu Wang, Jikai Zhao, Weijie Sun, Huanjia Cui, Bowen Chi, Ji Long

“…This research offers valuable insights for improving carbon sequestration and climate resilience in arid ecosystems, with significant implications for carbon management under high-emission scenarios.…”
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Machine Learning Model for Predicting Global Ionospheric TEC Maps Based on Constraint Conditions by Qingfeng Li, Hanxian Fang, Chao Xiao, Die Duan, Hongtao Huang, Ganming Ren

“…The prediction and modeling of ionospheric total electron content (TEC) have consistently been a focal point for researchers, as it holds significant implications for satellite positioning, navigation, telemetry, control, and radio wave propagation. …”
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An AI-Based Deep Learning with K-Mean Approach for Enhancing Altitude Estimation Accuracy in Unmanned Aerial Vehicles by Prot Piyakawanich, Pattarapong Phasukkit

“…The outcomes of our study are particularly noteworthy, with the model demonstrating remarkably low Mean Squared Error (MSE) values across all data clusters, ranging from 0.011 to 0.072. …”
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A machine learning-based recommendation framework for material extrusion fabricated triply periodic minimal surface lattice structures by Sajjad Hussain, Carman Ka Man Lee, Yung Po Tsang, Saad Waqar

“…This study not only contributes to a better understanding of automated TPMS lattice structures but also has significant implications for sustainable design and innovation, particularly in enhancing efficient and environmentally friendly 3D printing technologies.…”
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Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone by Yuyu Sun, Yuchen Zhang, Zhiguo Zhao

“…Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years. Practical implications – The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. …”
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Optimizing demulsifier selection for crude oil dehydration: a fuzzy TOPSIS-based multi-criteria decision-making approach by Jianyong Yu, Merwa Alhadrawi, Farag M. A. Altalbawy, Ahmed Rasol Hasson, M. Mehdi Shafieezadeh

“…These findings have significant practical implications for the petroleum industry, as they enable more data-driven and sustainable selection processes, reducing operational costs and improving crude oil dehydration efficiency. …”
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Long-term trends and chemometric analysis of atmospheric air quality matrices in Nigeria (2003–2023) using NASA GIOVANNI satellite data by Daniel Omeodisemi Omokpariola, John Kanayochukwu Nduka, Martin Osita Anagboso, Patrick Leonard Omokpariola

“…Statistical analysis including mean, range, standard error of the mean (SEM), variance, coefficient of variance, standard deviation, median, skewness, kurtosis, regression plot, correlation, Pearson Correlation, Dendrogram Clustering, and Scatter Plot were conducted to determine the trends and relationships between atmospheric parameters. …”
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The combined impact of AI and VR on interdisciplinary learning and patient safety in healthcare education: a narrative review by Emmanuel Aoudi Chance

“…Strategic implementation can contribute to error reduction, improved patient outcomes, and a culture of safety. …”
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Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds by Vittoria Asti, Michela Ablondi, Arnaud Molle, Andrea Zanotti, Matteo Vasini, Alberto Sabbioni

“…Overall, the GBM model exhibits the highest accuracy and the lowest error. In conclusion, integrating IMU technology into horse performance evaluation offers valuable insights, with implications for breeding and training.…”
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Efficient and Accurate Calibration of Discrete Element Method Parameters for Black Beans by Xuezhen Wang, Qinghang Zhai, Shihao Zhang, Qianwen Li, Hanmi Zhou

“…The results from this study can provide implications for investigating interactions of BLBs and various BLB processing machines and for the efficient and accurate determination of DEM parameters of crop grains.…”
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COVID-19 pandemic, oil prices and Saudi stock market: empirical evidence from ARDL modeling and Bayer–Hanck cointegration approach by Jamel Boukhatem, Ali M. Alhazmi

“…Our findings have some prominent implications for asset managers and policymakers to improve stock market efficiency and boost global economic activity. …”
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Physical Model Research on the Impact of Bridge Piers on River Flow in Parallel Bridge Construction Projects by Yu Zhang, Bo Chen, Shuo Wang, Xin Zhang

“…This research methodology can serve as a reference for studying flow characteristics in similar parallel bridge construction projects in river sections, and the findings hold significant implications for practical engineering.…”
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Neurocomputational Mechanisms of Sense of Agency: Literature Review for Integrating Predictive Coding and Adaptive Control in Human–Machine Interfaces by Anirban Dutta

“…Understanding how the SoA arises and is disrupted in neuropsychiatric disorders has significant implications for human–machine interface (HMI) design for neurorehabilitation. …”
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Binding Affinity Prediction for Pancreatic Ductal Adenocarcinoma Using Drug-Target Descriptors and Artificial Intelligence by Pragya, A. Amalin Prince, Jac Fredo Agastinose Ronickom

“…We achieved a mean square error (MSE) value of 1.5 using Morgan-RDKit-PubChem-Conjoint descriptors and 1D-CNN on the PDAC dataset. …”
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DFN-YOLO: Detecting Narrowband Signals in Broadband Spectrum by Kun Jiang, Kexiao Peng, Yuan Feng, Xia Guo, Zuping Tang

“…These findings underscore the strong potential of DFN-YOLO for blind signal detection in broadband environments, with significant implications for both civilian and military applications.…”
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Understanding the determinants of domestic food availability: Evidence from a Caribbean Small Island Developing State by David Forgenie, Meera Mahase-Forgenie, Sunshine De Caires, Wendy Ann P. Isaac, Karambir Singh Dhayal

“…Using an Autoregressive Distributed Lag (ARDL) model with an Error-correction Mechanism (ECM) and annual data spanning 1983 to2022, this study investigates both short- and long-run dynamics. …”
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Design of an Iterative Method for Time Series Forecasting Using Temporal Attention and Hybrid Deep Learning Architectures by Yuvaraja Boddu, A. Manimaran

“…This method improves the focus on relevant information and achieves a 10% average reduction in mean absolute error (MAE) compared to models devoid of such mechanisms. …”
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