The impact of digital economy on urban-rural income gap under government intervention by LE Yang, GAO Dongxi, ZHANG Yi, GUO Wei, CHEN Yi

“…Ordinary least squares (OLS) and instrumental variables-two stage least squares (IV-2SLS) estimation methods are used to empirically test the above mentioned-theoretical inferences from the empirical level based on the mediation effect model. …”
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Optimization of Adaptive I²H ∞ Control Method Based on Multiple Input Sensors by Yu Gu, Hanyang Li, Zeting Mei, Hao Wen, Yuanxiong Jin, Wenxuan Dong

“…The core contributions of this study include: 1) Designing a multi-sensor current reference estimator to dynamically generate the optimal electromagnetic torque through state variables such as wheel speed, acceleration, slope, and human factor database (heart rate, subjective score, fatigue index) to achieve real-time prediction of rider demand; 2) Proposing an adaptive current reference value estimation algorithm that integrates feedforward compensation and error feedback to ensure smooth switching of assistance modes and suppress sensor noise; 3) Developing an intention-induced H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> robust current tracking controller that significantly enhances the system&#x2019;s robustness to parameter fluctuations and external disturbances by optimizing the H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> norm of the closed-loop transfer function, while supporting personalized riding assistance.…”
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Pulley ring suture increases shoulder stability after biceps tendon transposition by Duzheng Zhang, Jiezhou Wu, Liyun Zhang, Qiyun Chen, Chao Wang, Ming Cai, Ruijun Cong

“…These statistically significant variables and their coefficients were used to build a generalized linear equation and selected to build the final model including Grouping information (OR:1.61E + 01;95% CI:5.8854–52.5200), Mean T value of bone mineral density (OR:6.95E + 00;95% CI:2.4695–25.6797) and 3 Months post operation UCLA score (OR:1.77E + 00;95% CI:1.4810–2.2539).ConclusionsCompared with the traditional MDBT, the modified MDBT is more effective in improving the long-term function of the glenohumeral joint and better restoring the biological state of the glenohumeral joint.…”
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基于modeFRONTIER的离合器碟形弹簧多目标优化设计 by 潘金坤

“…Based on the analysis of the working characters of disc springs in clutch,the mathematical model of multi-objective optimal design of disc springs is established with unified objective function method,which regards the minimization of the disc spring volume and its average variable quantity of working compress force within the scope of friction lining wear as optimal objectives.The optimization calculation is presented by using the software modeFRONTIER.The results indicate that the relevant performance of disc springs is significantly improved after optimal design,with the objective function values reduced by 36% and 6% respectively.The software modeFRONTIER,with its simplicity and efficient algorithm,solves optimization problems and improves design efficiency.…”
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Calibration of Low-Cost Capacitive Soil Moisture Sensors for Irrigation Management Applications by Ahmed A. Abdelmoneim, Christa M. Al Kalaany, Roula Khadra, Bilal Derardja, Giovanna Dragonetti

“…The results showed that with higher soil moisture contents (above 30%), the sensor-to-sensor variability becomes significant, with a coefficient of variation (CV) ranging between 10 and 16%; meanwhile, in lower soil moisture contents, the CV ranged between 6.5 and 10.3%, implying that it is more consistent in lower moisture content within this soil condition. …”
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APPLICATION AND PERFORMANCE COMPARISON OF MULTI-OUTPUT MACHINE LEARNING FOR NUMERICAL-NUMERICAL AND NUMERICAL-CATEGORICAL OUTPUTS by Karin Joan, Robyn Irawan, Benny Yong

“…Multi-Output Machine Learning is an advancement of traditional machine learning, designed to predict multiple output variables simultaneously while considering the relationships between these output variables. …”
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On the development of a practical Bayesian optimization algorithm for expensive experiments and simulations with changing environmental conditions by Mike Diessner, Kevin J. Wilson, Richard D. Whalley

“…The method is validated on two synthetic test functions, and the effects of the noise level, the number of environmental parameters, the parameter fluctuation, the variability of the uncontrollable parameters, and the effective domain size are investigated. …”
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Predicting the Cetane Number of Biodiesel using two AI-Models: the Gradient-based ANN and ANN Optimized by Genetic Algorithm by Hadis Tanha, Fatemeh Bashipour

“…The learning function, transfer function, number of hidden layers, and number of neurons in the hidden layers are some of the optimized parameters in the current AI-models. …”
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Assessment of soil fertility and nutrient distribution for enhanced soil health and field management through an innovative approach by Amir Bostani, Amin Mohebbi Tafreshi, Mohammad Hosein Bijeh Keshavarzi

“…Total nitrogen ranged from 0.02% to 0.82%. Highly variable macronutrient variation coefficient. Thus, the critical limits for elements and physicochemical characteristics were 4.5, 6, 0.7, and 0.8 mg/kg. …”
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A Study of Some Properties of Fuzzy Laplace Transform with Their Applications in Solving the Second-Order Fuzzy Linear Partial Differential Equations by Elhassan Eljaoui, Said Melliani

“…Then, some properties dealing with the partial derivatives of fuzzy Laplace transform for a fuzzy function of two real variables have been proved. Afterwards, an algorithm of fuzzy Laplace transform for solving second-order fuzzy partial differential equations has been proposed. …”
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Incorporating stand parameters in nonlinear height-diameter mixed-effects model for uneven-aged Larix gmelinii forests by Muhammad Junaid Ismail, Tika Ram Poudel, Akber Ali, Lingbo Dong

“…Model performance was assessed using root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R2). Results identified the Ratkowsky model (M8) as the best performer, achieving the highest R2 (0.74), the lowest RMSE (16.47%) and MAE (12.50%), at statistically significant regression coefficients (p &lt; 0.05). …”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Under the BIA, an alpha coefficient (α) of 15% is applied, whereas in the SA, each business line has a specific beta coefficient (β) ranging between 12% and 18%. …”
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A secondary analysis of gait after a 4-week postural intervention for older adults with hyperkyphosis by L. C. Hughes, A. L. Ellis, H. L. Rogers, M. Hadley, R. V. Galloway

“…Pearson correlation coefficients were utilized to investigate correlations between all variables at baseline and in pre- and post intervention change values. …”
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Elastic Stress and Plastic Zone Distributions around a Deeply Buried Tunnel under the Nonhydrostatic Pressure by Shuhong Liu, Jinlu Fan, Chenhao Wu, Yongquan Zhu

“…Based on Muskhelishvili’s complex variable function, the analytical solution for the elastic stress around a deeply buried noncircular tunnel under the nonhydrostatic pressure is firstly derived. …”
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Fuzzy Goal Programming Procedure to Bilevel Multiobjective Linear Fractional Programming Problems by Mahmoud A. Abo-Sinna, Ibrahim A. Baky

“…In the proposed procedure, the membership functions for the defined fuzzy goals of the decision makers (DMs) objective functions at both levels as well as the membership functions for vector of fuzzy goals of the decision variables controlled by first-level decision maker are developed first in the model formulation of the problem. …”
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Inverse problem of life cycle assessment (LCA): its application in designing for environment (DfE) by Rybaczewska-Błażejowska Magdalena, Masternak-Janus Aneta, Gierulski Wacław

“…The dependencies between input and output signals were defined by nonlinear functions of several variables. Next, linearization was used and coefficient aki was calculated. …”
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Machine learning-based model for acute asthma exacerbation detection using routine blood parameters by Youpeng Chen, Junquan Sun, Yabang Chen, Enzhong Li, Jiancai Lu, Huanhua Tang, Yifei Xie, Jiana Zhang, Lesi Peng, Haojie Wu, Zhangkai J. Cheng, Baoqing Sun

“…Background: Acute asthma exacerbations (AAEs) are a leading cause of asthma-related morbidity and mortality, especially in resource-limited settings where pulmonary function tests are unavailable or when patients are unable to cooperate with testing. …”
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An Analytical Solution for Natural Frequencies of Elastically Supported Stepped Beams with Rigid Segments by Ferid Kostekci

“…After deriving the transverse displacement functions by means of using the separation-of-variables technique, the frequency equation was found by setting the determinant of the coefficient matrix to zero. …”
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An evolutionary-based optimization algorithm for truss sizing design by Pham Hoang Anh

“…Here, the constraints and objective function are treated separately so that both function and constraint evaluations can be saved. …”
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Optimum Design of RC Beams Strengthened with Externally Bonded FRP Using Pattern Search by Noor Mohammed Sheet, Baraa J. M. AL-Eliwi, Rabi M. Najem

“…The design process involved an objective function that represents the cost function of the optimum solution and design variables that define the optimum dimensions of the beam and FRP material, such as beam width, effective beam depth, FRP strip thickness, FRP strips spacing, and FRP strip width, according to the design constraints of the ACI 440-2R-17 code. …”
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