Investigating Interaction Dynamics among Nonoil Economic Growth and Its Most Important Determinants: Evidence from Saudi Arabia by Badr Saleh Al-Abdi, Abdallah M. M. Badr, Faisal A. M. Ali, Tawfik M. A. Jabbar, Fahmy Al–Salwi

“…Overall, the findings of this study provide significant insights, empirical recommendations, and implications for policymakers striving to achieve sustainable nonoil trade economic growth in Saudi Arabia and the region.…”
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Financial technology and economic growth nexus in the East African community states by Chi Aloysius Ngong, Kesuh Jude Thaddeus, Josaphat Uchechukwu Joe Onwumere

“…Research limitations/implications – The governments should effectively enact and implement policies that protect investments in financial technologies to boost economic growth in the East African Community countries. …”
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Analyzing the interplay of urbanization, economic development, and seaborne trade: Revealing their connection to urban resilience in Saudi Arabia by AHM Mehbub Anwar, Nourah Alhosain, Yagyavalk Bhatt

“…Subsequently, it employs the Autoregressive Distributed Lag (ARDL) and Error Correction Model (ECM) techniques to unravel short-term and long-term causal dynamics. …”
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Urban Canopy Parameters’ Computation and Evaluation in an Indian Context Using Multi-Platform Remote Sensing Data by Kshama Gupta, Bhoomika Ghale, Ashutosh Bhardwaj, Anshika Varshney, Shweta Khatriker, Vinay Kumar, Prasun Kumar Gupta, Pramod Kumar

“…Performance evaluation of computed UCPs against a 3D reference geodatabase showed high prediction accuracy for most UCPs, with overall biases, mean absolute error, and root-mean-square error values significantly better than 1 m, with strong correlation (0.8–0.9). …”
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Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

“…Results demonstrate that the Transformer-GWO and Transformer-WOA models outperform conventional models such as GARCH by 70–90% across standard evaluation metrics like Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). By bridging state-of-the-art deep learning architectures with robust optimization strategies, this study contributes a scalable and interpretable solution for agricultural price forecasting. …”
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Enhanced Forecasting of Global Ionospheric Vertical Total Electron Content Maps Using Deep Learning Methods by Yang Lin, Hanxian Fang, Die Duan, Hongtao Huang, Chao Xiao, Ganming Ren

“…The ionospheric state holds significant implications for satellite navigation, radio communication, and space weather; however, precise forecasting of the ionosphere remains a formidable challenge. …”
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NSA-CHG: An Intelligent Prediction Framework for Real-Time TBM Parameter Optimization in Complex Geological Conditions by Youliang Chen, Wencan Guan, Rafig Azzam, Siyu Chen

“…Validation experiments employing field data from the Pujiang Town Plot 125-2 Tunnel Project demonstrated superior performance metrics, including 92.4% ± 1.8% warning accuracy for fractured zones, ≤28 ms optimization response time, and ≤4.7% relative error in energy dissipation analysis. Comparative analysis revealed a 32.7% reduction in root mean square error (<i>p</i> < 0.01) and 4.8-fold inference speed acceleration relative to conventional methods, establishing a novel data–physics fusion paradigm for TBM control with substantial implications for intelligent tunnelling in complex geological formations.…”
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Enhancing Time Series Product Demand Forecasting With Hybrid Attention-Based Deep Learning Models by Xuguang Zhang, Pan Li, Xu Han, Yongbin Yang, Yiwen Cui

“…Experimental results show that the HA-LSTM outperforms state-of-the-art baselines, including ARIMA, Prophet, and vanilla LSTM models, achieving a 15% improvement in Mean Absolute Percentage Error (MAPE) and a 12% reduction in Root Mean Square Error (RMSE). …”
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Comparison of the Effectiveness of Gamification, Tracking Patterns, and Visual Gauges in Improving Hand Motor Performance Through Biofeedback by Ayda Ebrahimi, Amir Salar Jafarpishe, Mohsen Vahedi, Marzieh Izadi Laybidi, Somayeh Mohammadi

“…Statistical analysis was conducted using the paired t-test to compare the root mean square error between groups. Results: The pattern-tracking group demonstrated significant motor performance improvement, with a statistically significant difference in root mean square error (P<0.001). …”
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Solar-Blind Ultraviolet Four-Quadrant Detector and Spot Positioning System Based on AlGaN Diodes by Longfei Peng, Shangqing Li, Yong Huang, Yang Yang

“…Utilizing a third-order polynomial least-squares fitting algorithm without introducing complex filtering techniques, the system achieves a maximum positioning error of 0.0101 mm and a root-mean-square error (RMSE) of 0.0057 mm, among of one the best-performing solar-blind UV 4QDs. …”
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Physicochemical profiling and ranking of parkinson’s disease drugs through QSPR and Fuzzy TOPSIS analysis by YuLan Chen, Abdul Rauf, Aqsa Shafique, Fairouz Tchier, Adnan Aslam, Keneni Abera Tola

“…Validation metrics, including coefficient of determination, mean squared error , and mean absolute error, confirmed model robustness. …”
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SubFoveal Choroidal Imaging in High Myopic Nepalese Cohort by Parash Gyawali, Ashutosh Jnawali, Anish Kharal, Manish Subedi, Sandeep Kandel, Prajjol Raj Puri, Nabin Paudel

“…However, choroidal thickness varies with the refractive error, age, axial length, and ethnicity. The purpose of this study was to determine the subfoveal choroidal thickness (SFCT) in high myopic Nepalese subjects and to investigate its association with the mean spherical equivalent refractive error (MSE), axial length, and age. …”
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A WebGL Serious Game for Practicing English Conversations in Public Places Using Speech Recognition by Rickman Roedavan, Iis Kunia Nurhayati, Kemas Muslim Lhaksmana, Muhammad Yudhi Rezaldi, Esa Prakasa, Sritenaya Geovani Putri

“…The methodology includes system analysis using Word Error Rate (WER) and Average Word Error Rate per Sentence (Avg WER) to evaluate speech recognition accuracy. …”
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Future declines of coronary heart disease mortality in England and Wales could counter the burden of population ageing. by Maria Guzman Castillo, Duncan O S Gillespie, Kirk Allen, Piotr Bandosz, Volker Schmid, Simon Capewell, Martin O'Flaherty

“…In scenario B, assuming recent declines continued, the BAPC model (the model with lowest error) suggests the number of deaths will decrease by 56%, representing approximately 36,200 fewer deaths by 2030.…”
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Construction of a Surface Roughness and Burr Size Prediction Model Through the Ensemble Learning Regression Method by Ali Khosrozadeh, Seyed Ali Niknam, Fatemeh Hajizadeh

“…The model was trained using cutting parameters as inputs and evaluated with performance metrics such as mean absolute error (<i>MAE</i>), mean squared error (<i>MSE</i>), and the coefficient of determination (<i>R</i>²). …”
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Addressing Spatial Variability in Estimating Cover Management Factor of Soil Erosion Models using Geoinformatics: A Case Study of Netravati Catchment, Karnataka, India by Waleed Makhdumi, Shwetha H. R., G. S. Dwarakish, Jagadeesha B. Pai

“…The model’s performance was evaluated using statistical metrics, including a correlation coefficient of 0.984, mean absolute error of 0.048, root mean square error of 0.058, and Kling-Gupta efficiency of 0.921, indicating superior accuracy compared to existing methods. …”
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Leveraging machine learning techniques to analyze nutritional content in processed foods by K. A. Muthukumar, Soumya Gupta, Doli Saikia

“…Model performance was evaluated using Normalized Mean Squared Error (NMSE) as the evaluation metric. The results indicated that the RF model achieved an NMSE of approximately 0.35, reflecting a moderate level of prediction error relative to data variance. …”
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Chemometric and computational modeling of polysaccharide coated drugs for colonic drug delivery by Ahmad Khaleel AlOmari, Khaled Almansour

“…Assessment metrics, such as the coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE), emphasize the MLP model’s exceptional performance. …”
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Test-retest reliability of the twenty-five-hole peg test in patients who had a stroke by Fredrik Granström, Mattias Hedlund, Britta Lindström, Staffan Eriksson

“…The use of an average of three trials compared with a single trial substantially reduces the measurement error.Trial registration number ISRCTN registry, reference number ISRCTN24868616.…”
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Acute rhabdomyolysis by Pascale de Lonlay, Asmaa Mamoune, Yamina Hamel, Michel Bahuau, Sabrina Vergnaud, Moniqu Piraud, Lætitia Lallemand, Marie-Ange Nguyen More, Mai Thao Vio, Norma Beatriz Romero

“…Some other diseases involved in rhabdomyolysis may implicate pro-inflammatory cytokines and may be proinflammatory diseases.…”
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