Jointed rock slope stability evaluation based on PEM-JFEM method by XIAO Shu, WU Shun-chuan, GAO Yong-tao, HAN Guang, ZHOU Yu, CHENG Ai-ping

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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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Multi-objective trajectory planning for connected and autonomous vehicles in mixed traffic flow by Hui Li, Yunfei Ge, Yahui Guo, Yu Guan, Xu Zhang

“…The reward function integrates multiple objectives, including safety, fuel consumption, and traffic efficiency. …”
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Predicting the onset of chronic kidney disease (CKD) for diabetic patients with aggregated longitudinal EMR data. by Neda Aminnejad, Michelle Greiver, Huaxiong Huang

“…This research contributes valuable insights for healthcare practitioners seeking efficient tools for early CKD detection in diabetic populations.…”
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Multiobjective optimization of suspension bridges via coupled modeling and dual population multiobjective particle swarm optimization by Peiling Yang, Jianhua Deng, Anli Wang

“…The Lasso function is used for elastic net regression analysis to evaluate the impact of design variables on the objective functions. …”
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Does charcoal act as a protective agent in fish nutrition to increase growth and physiological performance? A meta-analysis by Aliati Iswantari, Vitas Atmadi Prakoso, Nunak Nafiqoh, Rendy Ginanjar, Henti Hendalastuti Rachmat, Agung Irawan, Kurniawan Kurniawan, Mochammad Zamroni, Fathur Rochman, Danung Nur Adli, Mohammad Miftakhus Sholikin, Arif Wibowo, Anuraga Jayanegara

“…Charcoal notably reduced aspartate aminotransferase and increased immunoglobulin levels, suggesting benefits for liver function and immunity. Meta-regression revealed dose-dependent improvements with wood charcoal, whereas responses to bamboo and activated charcoal were variable. …”
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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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Vibration Response and Evaluation Method of High-Speed Tracked Vehicles Driving Off-Road by Xin-yong Qiao, Ying Jin, Cheng Gu

“…Three fitting methods, namely polynomial response surface, Kriging method, and radial basis function neural network, were used to establish approximate models between the design variables and the objective function, respectively. …”
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Decomposed Linear Dynamical Systems (dLDS) models reveal instantaneous, context-dependent dynamic connectivity in C. elegans by Eva Yezerets, Noga Mudrik, Adam S. Charles

“…Abstract Mounting evidence indicates that neural “tuning” can be highly variable within an individual across time and across individuals. …”
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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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Production of Cyanobacterial Microscale Adsorbent by Hydrothermal Method for Pre-concentration of Cadmium from Water by T. Mohammadi Arian, G. Rahimi, R. Khavari Farid

“…Solid-phase extraction using carbon adsorbents is the most efficient and common method of pre-concentration of heavy metals from environmental samples. …”
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Machine learning-based prediction of pervaporation permeation using physicochemical properties of permeant-membrane and process conditions by Muhammad Mujiburohman, Marwen Elkamel, Farzad Hourfar, Ali Elkamel

“…Two types of inputs were evaluated: regular variables (Type I) and dimensionless groups derived from these regular variables (Type II). …”
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Exploring the Future Energy Value of Long-Duration Energy Storage by Anna H. Schleifer, Stuart M. Cohen, Wesley Cole, Paul Denholm, Nate Blair

“…The negative effect of lower roundtrip efficiency on value is also found to be scenario-dependent, with the energy value in higher VRE scenarios being less sensitive to roundtrip efficiency and more supportive of longer storage durations. …”
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Possibilities of Using Artificial Intelligence in Security Analysis by Maciej Norbert Ciesielski

“…In total, out of twelve features/variables that make up analytical imagination, artificial intelligence already functions efficiently (or will function efficiently soon) in practically all of them.…”
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An Analysis of Influential Factors in the Use of Public Bicycles in Tehran by Ehsan Faghihi, Mojtaba Rafieian

“…So far, many researches have been conducted on the components affecting the functional stability of the shared bicycles system, for example Si et al. in 2020 found that factors of efficiency, economic benefits, environmental awareness, and infrastructure incentives influence the willingness to use the shared bicycle system. …”
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Research on Side Lobe Suppression of Time-Modulated Sparse Linear Array Based on Particle Swarm Optimization by Lei Liang, Jie Sun, Hailin Li, Jialing Liu, Yachao Jiang, Jianjiang Zhou

“…An efficient pattern synthesis approach is proposed for the synthesis of a time-modulated sparse linear array (TMSLA) in this paper. …”
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Physics-augmented deep learning models for improving evapotranspiration estimation in global land regions by Binrui Liu, Xinguang He, Wenkai Lyu, Lizhi Tao

“…A Physics-Data Learning (PDL) model is first formed by adding a complementary physical variable generated by Penman–Monteith (PM) equation to a deep learning (DL) model along with driving variables to regress latent heat flux. …”
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Market orientation and corporate performance of small and medium-sized enterprises in Saudi Arabia by Nabil Mohamed Abdo Alabsy

“…Corporate performance is a dependent variable, whereas business orientation, competitor orientation and inter-functional orientation are used as independent variables. …”
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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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Determinants of growth differentiation factor 15 plasma levels in outpatients with peripheral arterial disease by Emma Skau, Philippe Wagner, Jerzy Leppert, Johan Ärnlöv, Pär Hedberg

“…Results: The multivariable analysis identified independent relations of GDF-15 with several of the included variables (adjusted R2 = 0.48). Diabetes (beta coefficient [β] of 0.37, 95% confidence interval [95% CI] 0.25 to 0.50), low-density lipoprotein (LDL) cholesterol (β = −0.22, 95% confidence interval [CI]: −0.34 to −0.09), and physical activity (β = −0.16, 95% CI: −0.25 to −0.06) had the strongest associations. …”
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