Is tourism expansion the key to economic growth in India? An aggregate-level time series analysis by Deepti Singh, Qamar Alam

“…Johansen's cointegration and error correction model results support the long-run relationship among the variables. …”
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Dynamic relationships between energy use economic growth foreign investment and environmental pollution in South Korea from 1990 to 2023 by Vu Ngoc Xuan

“…Abstract This study investigates the dynamic interplay between energy consumption (ECO), fossil fuel (FFU) use, renewable energy (RE), foreign direct investment (FDI), population growth (PG), economic growth (EG), and environmental pollution in South Korea from 1990 to 2023. Using a Vector Error Correction Model (VECM) model and Granger causality framework, the analysis identifies FFU use and electricity consumption as key drivers of CO₂ emissions. …”
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The Challenges of AI in Administrative Law and the Need for Specific Legal Remedies: Analysis of Polish Regulations and Practice by Jowanka Jakubek-Lalik

“…However, these trends should be carefully monitored, especially from the perspective of citizens’ rights and potential errors that may differ from the classical, non-automated administrative proceedings. …”
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Revisiting the effect of point defects on the decay of the longitudinal optical mode in semiconductors by Julian Anaya

“…In re-examining the derivation of these results, a critical error in the evaluation of an integral has been found, which is central to the main finding of the model. …”
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From Anaxagoras to Albert the Great: The Latency of Forms and the Active Power of Matter in the Middle Ages by Nadia Bray

“…Albert reworks this doctrine, correcting the immanentist and paradoxical implications attributed to Anaxagoras’ error, and proposes an interpretation in which matter, while potentially active, receives the perfection of forms from an external causal principle. …”
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CREDIT AND HOUSING MARKETS IN VIETNAM: EVIDENCE FROM VECM ANALYSIS by Ngoc Toan Bui

“…By employing the Vector Error Correction Model (VECM) method, the findings reveal that bank credit has a positive impact on housing prices in the long term, a result observed in both of Vietnam's largest cities - Ho Chi Minh City and Hanoi City. …”
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Classical and Bayesian Estimation of the Inverse Weibull Distribution: Using Progressive Type-I Censoring Scheme by Ali Algarni, Mohammed Elgarhy, Abdullah M Almarashi, Aisha Fayomi, Ahmed R El-Saeed

“…Focusing on the censoring schemes, maximum likelihood estimators (MLEs) and asymptotic confidence intervals (ACI) for unknown parameters are constructed. Under the squared error (SEr) loss function, Bayes estimates (BEs) and concomitant maximum posterior density credible interval estimations are also produced. …”
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Peer learning in first grade: Do children communicate with each other during learning activities? by Elisabeth A. Mlawski

“…Four mechanisms were observed: Organization/Engagement, Scaffolding/Error Management,Communication, and Affect. The mechanism of Affect was found to be used the most by the dyads. …”
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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

“…Compared to the original forecasting models, the overall model error was reduced by approximately 15–17% on the test dataset. …”
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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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