Research on the Combined Load-Bearing Mechanism of Deeply Buried Pressure Pipelines Under High Internal Water Pressure by LIU Yijie, ZHANG Xuhui, HUANG Bensheng, YANG Fengjie, YUAN Mingdao, XU Yunqian

“…To enhance the surrounding rock’s contribution, reinforcement measures such as grouting may be necessary.ConclusionsAiming at the calculation problem of load transfer and distribution in deep-buried pressure pipelines under high internal water pressure conditions, a power series solution method based on complex variable functions was proposed. By solving the potential functions for the steel liner and surrounding rock as well as the contact stress between the bearing bodies, the stress, deformation at any position of the bearing structure and surrounding rock sharing rate can be accurately determined. …”
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UNFOLDING FACTORS INFLUENCING PINEAPPLE PRODUCTION: EMPIRICAL EVIDENCE FROM BAGAMOYO IN TANZANIA by Isaka Kasyupa, Bahati Ilembo

“…The coefficient of determination 𝑅 ଶ = 0.81 showed that the explanatory variables were fit for the model as 81% of the variation in the production of pineapples is explained by the selected seven factors. …”
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Intelligent wearable devices with audio collection capabilities to assess chronic obstructive pulmonary disease severity by Chunbo Zhang, Kunyao Yu, Zhe Jin, Yingcong Bao, Cheng Zhang, Jiping Liao, Guangfa Wang

“…A logistic regression model using the RR and blowing sounds as key predictors achieved accuracies of 0.77–0.89 in determining the GOLD grade, with a Cohen's kappa coefficient of 0.6757. Conclusions Audio data were more strongly correlated with lung function in COPD patients than were physiological parameters. …”
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Fractional Dynamics of Laser-Induced Heat Transfer in Metallic Thin Films: Analytical Approach by M. A. I. Essawy, Reham A. Rezk, Ayman M. Mostafa

“…Dynamic profiles demonstrate the responsiveness of heat transfer to thermal and optical variables. The innovation resides in the meticulous analytical formulation utilizing a realistic laser source, the clear significance of the absorption parameter that enhances the temperature amplitude, the incorporation of the Mittag–Leffler function, and a comprehensive investigation of fractional photothermal effects in metallic nano-systems. …”
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DC Performance Variations of SOI FinFETs with Different Silicide Thickness by Jun-Sik Yoon

“…DC parameters including threshold voltage, low-field-mobility-related coefficient, and parasitic resistance are extracted from Y-function method for the comparison of DC performance and variability, and the correlation analysis. …”
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Binary composite crossover genetic algorithm for locating critical slip surface by Wei Qin, Jiancheng Zhao

“…A reasonable combination of parameters for the binary composite crossover (BCC) operator in the RGA-BCC is determined through six benchmark function experiments. On this basis, the stability of five soil slopes from the literature was analysed using the RGA-BCC in combination with the Morgenstern and Price method, and the results obtained were compared with those in the published literature to demonstrate that the RGA-BCC is able to efficiently determine the CSSs of slopes and their minimum factors of safety. …”
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Algorithm for Dynamic Reactive Power Optimization of Regional Power Grid Based on Interior Point Method and Neighborhood Search Decoupling Dynamic Programming Method by Jie ZHANG, Hengfeng WANG, Shengchun LIU, Huabiao WANG, Canghai WANG, Yao RAN, Xianmin WANG, Yongfei MA, Wei YAN

“…The two-stage method could not only ensure the quality of the optimal solution, but also avoid solving the state combination explosion problem with discrete variables, which greatly improves the computational efficiency. …”
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Multi-objective optimal scheduling of cascade reservoirs in complex basin systems: Case study of the Jinsha River-Yalong River confluence basin in China by Zhaocai Wang, Zhihua Zhu, Hualong Luan, Tunhua Wu

“…Benchmark function tests demonstrate that IMOSSA outperforms others in terms of optimization capability and stability. …”
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Shunt active power filter using model predictive control with stability guarantee by Jhon Pérez-Ramírez, Diego Montoya-Acevedo, Walter Gil-González, Oscar Danilo Montoya, Carlos Restrepo

“…The cost function exhibits convex characteristics, ensuring a unique control law. …”
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Numerical Investigation and Optimization of Transpiration Cooling Plate Structures with Combined Particle Diameter by Dan Wang, Yaxin Liu, Xiang Zhang, Mingliang Kong, Hanchao Liu

“…An optimization analysis of CPD−PS is conducted using response surface methodology (RSM), and the influence of design variables on the objective function (<i>η</i>_ave and <i>p</i>) is analyzed. …”
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Sustainable PV-hydrogen-storage microgrid energy management using a hierarchical economic model predictive control framework by Xinyu Guo, Faying Gu, Hongxu Liu, Yongcheng Yu, Runjie Li, Juan Wang

“…First, a precise nonlinear model of the PHS microgrid is established and the logic variables are introduced to capture the hydrogen devices’ short-term properties, i.e., the start-up/shut-down of electrolyzers and fuel cells. …”
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Safety Assessment of Loop Closing in Active Distribution Networks Based on Probabilistic Power Flow by Wenchao Cai, Yuan Gao, Xiping Zhang, Qin Si, Jiaoxin Jia, Bingzhen Li

“…By modeling DGs and loads as random variables, their cumulants are efficiently obtained through LHS. …”
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A non-dominated sorting based multi-objective neural network algorithm of ethylene glycol hydrogenation reactor in energy reduction by Fakhrony Sholahudin Rohman, Sharifah Rafidah Wan Alwi, Dinie Muhammad, Muhamad Nazri Murat, Ashraf Azmi

“…Artificial intelligence (AI) can be applied to various ethylene glycol (EG) production aspects to improve efficiency, quality, and overall process optimization. …”
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Solving 0-1 Knapsack and Bin Packing Problem Using Logical Social Group Optimization by Rhiddhi Prasad Das, Junali Jasmine Jena, Suresh Chandra Satapathy, Naeem M. S. Hannoon

“…This prominent research gap has been addressed in this paper by introducing Logical Social Group Optimization (LSGO), a logic-based binarized variant of Social Group Optimization (SGO) that leverages Boolean logic for improved efficiency. In LSGO, after the binarization by replacing the arithmetic operators with logical operators, one of the variables gets cancelled out. …”
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ABOUT SOME FEATURES OF TRANSMISSION MODE FOR ACTIVE POWER OF ELECTRICAL LINE by Paţiuc V., Berzan V.P., Anisimov V., Cabac S., Postotonca S.

“…It enteritis that for the active character load of the active power input and power output of the line, so functions , and functions that characterize developments efficiency , power factor at the input line and the load power factor when the variable z. …”
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Application of artificial neural network in deoxygenation of water by glucoseoxidase immobilized in calcium alginate/MnO2 composite by A. Abdi, M.Sh Izadkhah, A. Karimi, M. Razzaghi, H. Moradkhani

“…The linear regression between the network outputs and the corresponding targets were proven to be satisfactory with a correlation coefficient of 0.995 for three model variables used in this study.…”
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Techno-economic assessment of low-carbon ammonia as fuel for the maritime sector by Wouter Schreuder, J. Chris Slootweg, Bob van der Zwaan

“…We incorporate three different cost levels for ammonia and a variable engine efficiency ranging from 35 % to 55 %. …”
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Parameter Sensitivity Analysis and Algorithm Improvement of Optimization Scheduling Model for Cascade Pumping Stations by LIU Xiaolian, LI Zhenrong, WANG Xue-ni, ZHAI Yu, ZHANG Lei-ke, GUO Weiwei, TIAN Yu

“…Additionally, a Tent boundary mapping strategy was employed to regenerate the boundary value, resulting in improved the optimization efficiency of RUN. Six benchmark functions, including unimodal, multimodal and fixed dimension, were used to verify the performance and improvement strategies of TRUN. …”
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Analysis of Surface Roughness and Machine Learning-Based Modeling in Dry Turning of Super Duplex Stainless Steel Using Textured Tools by Shailendra Pawanr, Kapil Gupta

“…One of the most critical aspects of turning, and machining in general, is the surface roughness of the finished product, which directly influences the performance, functionality, and longevity of machined components. …”
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Impact of Low-dose Imaging on PET Quantitative Accuracy and Image Quality by SU Xuesong, GENG Jianhua, ZHENG Rong, WANG Xuejuan

“…Subsequently, the recovery coefficient (RC), contrast recovery coefficient (CRC), contrast-to-noise ratio (CNR), percent background variability (PBV), background coefficient of variation (BCV), and residual error (RE) of the lung insert at different image planes were calculated within the phantom. …”