Numerical Simulation of Diversion Tunnel Excavation Using GPU-Accelerated Anisotropic Random Fields by Guo-jin Zhu, Yu Ning, Zhi-hao Cui, Nanxiang Hu, Qing-xiang Meng, Chun Zhu

“…In this study, a combined anisotropic random field and GPU-accelerated Cholesky decomposition algorithm is proposed for diversion tunnel excavation. …”
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Evaluating time-lagged relationships between groundwater storage and river discharge using GRACE-based data: insights from the Potomac Basin by AJ Villaruel, Alimatou Seck, Cherie Schultz

“…Vector Autoregressive (VAR) Models and Forecast Error Variance Decomposition (FEVD) highlighted the variable contributions of precipitation and temperature to the GWS-Q relationship, revealing a strong autoregressive component of Q, but also reveal that GWS plays an important role, and this role increases with time. …”
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Dimensions-Reduced Volterra Digital Pre-Distortion Based On Orthogonal Basis for Band-Limited Nonlinear Opto-Electronic Components by Hananel Faig, Yaron Yoffe, Eyal Wohlgemuth, Dan Sadot

“…In addition to the analytical modeling approach, a nonparametric method is developed by applying eigenvalue decomposition on the correlation matrix, which is required for the case of dependent random variables, or for the case of unknown probability distribution functions. …”
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Dynamics of Foreign Exchange Futures Trading Volumes in Thailand by Woradee Jongadsayakul

“…The analysis of variance decomposition shows that the variability of the USD/JPY futures trading volume and USD/THB futures trading volume, apart from its own shock, is explained by other FX futures trading volume shocks. …”
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Islamic Finance-Growth Nexus: Evidence from Malaysia by Hasan Kazak, Osman Okka

“…To analyze the relationship of the variables within the framework of the VAR model, the Johansen cointegration test, impulse-response functions, and variance decomposition was used. …”
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Gender Difference in the Trend and Forecast Analysis of Changes in the Burden of Disease of Pancreatic Cancer Attributable to Smoking in China, 1990-2021 by Haodi Wang MM, Wenhao Sun MM, Jiaqian Zuo MM, Gang Wang MD, Zhengming Deng MD, Zhiwei Jiang MD

“…The age-period-cohort model was applied to explain the epidemiological trends of the disease by controlling for variables associated with age, period, and birth cohort. …”
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Transient Horizontal Response of a Pipe Pile in Saturated Soil with a Flexible Support at the Pile Head by Ao Su, Min Zhang, Wei Shang, Qiqi Wang

“…The potential function is introduced, and the three-dimensional wave equation for saturated soils is decoupled using operator decomposition and the method of separation of variables. …”
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Optimizing winner determination for sustainability and timeliness in fresh agricultural product logistics service procurement auctions: insights from a fourth-party logistics persp... by Yi Zhou, Mingqiang Yin, Qiang Liu, Xiaohu Qian, Delong Jin, Xianming Lang

“…Based on Latin hypercube sampling approach, this paper reconstructs the traditional SAA algorithm framework, and combines the dual decomposition and Lagrangian relaxation algorithm to develop a sampling-based approximate algorithm to solve the proposed model. …”
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The Relationship Between Economic Growth and Foreign Aid: The Case of Afghanistan by Muhammad Akbar Farahmand

“…The Granger causality test based on the error correction model was conducted to investigate the causality relationship between these two variables. …”
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Computationally Efficient Hybrid Downscaling of Surf Zone Hydrodynamics: Methodology and Evaluation by E. R. Echevarria, S. Contardo, B. Pérez‐Díaz, R. K. Hoeke, B. Leighton, C. Trenham, L. Cagigal, F. J. Méndez

“…The approach involves defining representative forcing conditions, carrying out numerical model (XBeach) simulations for these cases, and training machine learning models capable of predicting selected model output variables. …”
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A time series analysis of mineral revenue and economic growth in Ghana by Frank Boateng, Gomashie Edem Wisdom, Sulaiman Olusegun Atiku

“…The study employed techniques such as the Vector Error Correction Model, Granger Causality, variance decomposition, and VAR for time series data analysis. …”
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Interpretable Machine Learning for Multi-Crop Yield Prediction in Semi-Arid Regions: A Hierarchical Approach to Handle Climate Data Sparsity by Rachid Ed-daoudi, M’barek El Haloui

“…Missing weather data (gaps of 8.3–45.2%) are addressed via Multiple Imputation by Chained Equations (MICE), incorporating climatological constraints to preserve physical consistency. Model interpretability is achieved through SHapley Additive exPlanations (SHAP) analysis and uncertainty decomposition, quantifying the contributions of data variability, temporal dynamics, and model ensembles. …”
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Dynamic Nonlinear Connectedness between the Financial Inclusion, Economic Growth, and China’s Poverty Alleviation: Evidence from a Panel VAR Analysis by Zhenhuan Chen, Hongge Zhu, Wencheng Zhao, Bo Cao, Yingli Cai

“…By building a panel vector autoregression model (PVAR), the comparison analyses of national, eastern, central, and western sample groups verify the existence of dynamic nonlinear connectedness among the four variables. …”
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Optimizing calcination for low-grade calcined kaolinite clay: Reactivity and energy consumption by Hao Sui, Bin Wang, Ziyu Chen, Yanming Liu, Kwesi Sagoe-Crentsil, Wenhui Duan

“…The proposed model demonstrates a robust correlation coefficient of approximately 0.97, providing reliable energy consumption predictions across various calcination scenarios. …”
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State Identification of Charging Module Based on SN‐EMD‐SSEE and DBO‐HKELM by Bingyu Li, Xianhai Pang, Xuhao Du, Ziwen Cai

“…In data pre‐processing, SN‐EMD‐SSEE is developed to extract state characteristics values for high adaptability to full working condition and high significance for easy identification. In modeling, DBO‐HKELM identification model is constructed by improving ELM (Extreme Learning Machine) and optimizing parameters based on DBO 60 state characteristics values and 24 states including normal state, which are, respectively, used as the input and output of the identification model. …”
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Autonomous nervous system responses to environmental‐level exposure to 5G's first deployed band (3.5 GHz) in healthy human volunteers by Layla Jamal, Lisa Michelant, Stéphane Delanaud, Laurent Hugueville, Paul Mazet, Philippe Lévêque, Tamara Baz, Véronique Bach, Brahim Selmaoui

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Bidirectional relationship between corruption and economic performance in Tanzania by Lucas Salati, Maurice Mbago, Dimpna Mosha

“…The study applied Vector Autoregression approach to analyze and model bidirectional relationship between corruption perceptions index and three macroeconomic variables, namely; unemployment, inflation, and Gross Domestic Product growth rate which measure economic performance in Tanzania. …”
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The Efficiency of The Interest Channel in The Context of Monetary Policy in Developed Countries by Taner Taş, Kubilay Çağrı Yılmaz

“…Within the framework of the panel VAR model established in line with the results obtained from these tests, the efficiency of the interest channel was investigated with the impulse-response functions and variance decomposition methods. …”
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Multi-Modal Joint Pulsed Eddy Current Sensor Signal Denoising Method Integrating Inductive Disturbance Mechanism by Yun Zuo, Gebiao Hu, Fan Gan, Zhiwu Zeng, Zhichi Lin, Xinxun Wang, Ruiqing Xu, Liang Wen, Shubing Hu, Haihong Le, Runze Wu, Jingang Wang

“…This method constructs the Improved Whale Optimization -Variational Mode Decomposition-Singular Value Decomposition-Wavelet Threshold Denoising (IWOA-VMD-SVD-WTD) fourth-order processing architecture: IWOA adaptively optimizes the VMD essential variables (K, α) and employs the optimized VMD to decompose the perception coefficient (IMF) of the PEC signal. …”
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Circular Economy Innovation in Built Environments: Mapping Policy Thresholds and Resonant Resilience via DEMATEL–TAISM by Zhuo Su, Junlong Peng, Mengyu Wang, Guyue Gui, Qian Meng, Yuntao Su, Zhenlin Xiao, Sisi Zhang

“…This study couples the Decision-Making Trial and Evaluation Laboratory (DEMATEL) with Total Adversarial Interpretive Structural Modeling (TAISM) to build a weighted, multi-layer model of the policy–market–organization–technology chain. …”
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