Correlation and path analysis of interaction between snap beans yield and its components with crop management by N. Shaban

“…Results showed that fresh weight of pod/studied variant (+++0.99), fresh weight of one pod (+++0.77), fresh weight of pods/ plant (+++0.67), calcium content in bean pods (++0.57), pods number /plant (++0.51), pollen fertility (++0.44) had positive impact on yield. The partial function of the studied parameters on variability of bean yield is 98.9%. …”
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Genetic and molecular basis of abnormal BOLD signaling variability in patients with major depressive disorder after electroconvulsive therapy by Siyu Fan, Yulin Zhang, Rui Qian, Jie Hu, Hao Zheng, Wentao Dai, Yang Ji, Yue Wu, Xiaohui Xie, Si Xu, Gong-Jun Ji, Yanghua Tian, Kai Wang

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An Efficient Coupled Genetic Algorithm-NLP Method for Heat Exchanger Network Synthesis

“…Solving such problems leads to difficulties in the optimization of continuous and binary variables. This paper presents a new efficient and robust method in which structural parameters are optimized by genetic algorithm (G.A.) and continuous variables are handled due to a modified objective function for maximum energy recovery (MER). …”
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The Role of Profitability and Liquidity in Meeting the Feasibility Standards of Sharia Banking with Capital Adequacy as A Moderating Variable in Indonesia by Padli Pawaid Yahya, Joko Setyono

“…Control variables include Net Profit Margin (NPM), Operational Efficiency (BOPO), and Loan to Deposit Ratio (LDR). …”
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On a geometric approach to the estimation of interpolation projectors by Mikhail V. Nevskii, Alexey Y. Ukhalov

“…Here $\sigma S$ is the result of homothety of $S$ with respect to the center of gravity with coefficient $\sigma$. Let $d\geqslant n+1,$ $\varphi_1(x),\ldots,\varphi_d(x)$ be linearly independent monomials in $n$ variables, and $\varphi_1(x)\equiv 1,$ $\varphi_2(x)=x_1,\ \ldots, \varphi_{n+1}(x)=x_n.$ Put $\Pi:=$lin$(\varphi_1,\ldots,\varphi_d).$ The interpolation projector $P: C(\Omega)\to \Pi$ with a set of nodes $x^{(1)},\ldots, x^{(d)} \in \Omega$ is defined by equalities $Pf\left(x^{(j)}\right)=f\left(x^{(j)}\right).$ Denote by $\|P\|_{\Omega}$ the norm of $P$ as an operator from $C(\Omega)$ to $C(\Omega)$ . …”
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A domain free of the zeros of the partial theta function by V. Kostov

“…For each $q$ fixed, $\theta$ is an entire function of order $0$ in the variable~$x$. When $q$ is real and $q\in (0,0.3092\ldots )$, $\theta (q,.)$ is a function of the Laguerre-P\'olya class $\mathcal{L-P}I$. …”
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Evaluation of the Efficiency of Metaheuristic Algorithms in the Optimal Design of Pile Wall Retaining Systems by Farshad Taiyari

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Optimization of non-smooth functions via differentiable surrogates. by Shikun Chen, Zebin Huang, Wenlong Zheng

“…These models are commonly used to predict outputs based on a combination of fixed parameters and adjustable variables. A key transition in optimization involves moving beyond simple prediction to determine optimal variable values. …”
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Scalable Processing of Glass with Multi‐Functional Cu Coating by Dan Wang, Xuelu Zhang, Yan Xing, Guanghua Liu, Hui Wu, Wei Pan

“…Abstract Functional glass has been intensively studied as a future material with improved comfort, safety, and practicality across a variety of settings, including industrial, and residential environments. …”
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Weighted average ensemble for Cholesky-based covariance matrix estimation by Xiaoning Kang, Zhenguo Gao, Xi Liang, Xinwei Deng

“…Our key idea is to obtain different weights for different candidate estimates by minimizing an appropriate risk function with respect to the Frobenius norm. Different from the existing ensemble estimation based on the MCD, the proposed method provides a sparse weighting scheme such that one can distinguish which variable orderings employed in the MCD are useful for the ensemble matrix estimate. …”
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Beyond Global Metrics: The U-Smile Method for Explainable, Interpretable, and Transparent Variable Selection in Risk Prediction Models by Katarzyna B. Kubiak, Agata Konieczna, Anna Tyranska-Fobke, Barbara Więckowska

“…Variable selection (VS) is a critical step in developing predictive binary classification (BC) models. …”
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Investigating Attitudes towards Refugee Students based on Several Variables: Revised Version of Refugee Student Attitude Scale by Ahmet Göçen, Ragıp Terzi, Bilal Altun

“…At this stage, the contribution of hosting teachers andschool administrators to attitudes towards migrants and inclusive educationpolicies is a key to the efficient functioning of the process. In this study,attitudes towards refugee students of teachers from Sanliurfa, one of Turkey'smost populated-refugee cities, is investigated based on several variables. …”
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Model-Based Control Allocation During State Transitions of a Variable Recruitment Fluidic Artificial Muscle Bundle by Jeong Yong Kim, Matthew Bryant

“…FAMs can be bundled together in parallel to exhibit variable recruitment functionality, which is an activation strategy inspired by how motor units (MUs) in skeletal muscle are recruited. …”
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An efficient eigenvector-based crossover for differential evolution: Simplifying with rank-one updates by Tae Jong Choi

“…We propose a new approach to enhancing the efficiency of the differential evolution (DE) algorithm, specifically targeting rotational invariance. …”
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Photocatalytic Efficiency of TiO2-Biomass Loaded Mixture for Wastewater Treatment by Devagi Kanakaraju, Soon Pang Wong

“…Surface morphology, functional groups, and elemental analysis supported observations of the ability of TiO2/MSB mixture to remove COD. …”
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Modeling fin efficiency considering transverse temperature gradients in rocket engine cooling channels by Volodymyr Sliusariev, Valerii Bucharskyi

“…This study aims to improve the accuracy of methods for determining fin efficiency. Its goal is to derive calculation relationships for finning coefficients that account for transverse temperature non-uniformity within the fin cross-section. …”
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Enhancing CAR T‐cell therapy manufacturing efficiency through semi‐automated bioprocessing by Jason Isaacson, Prajakta Bhanap, Nicholas Putnam, Jasmine Padilla, Nujhat Fatima, Max Dotson, Danny Hayoun, Moloud Ahmadi, Gertrude Nonterah, Yongchang Ji

“…Automated CAR T‐cell manufacturing methods that use software to control the equipment used in the process can help overcome the roadblocks associated with manual manufacturing, ultimately enabling a reduction in variability, increased efficiency, improved product quality and better data management. …”
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Analysis of Bulk Queueing Model with Load Balancing and Vacation by Subramani Palani Niranjan, Suthanthiraraj Devi Latha, Sorin Vlase, Maria Luminita Scutaru

“…Cloud computing using power BI can be analyzed based on server load balancing. The function that determines the probability of the queue size at any given time is derived for the specified queueing model using the supplementary variable technique with the remaining time as the supplementary variable. …”
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How Can We Manage Repairing a Broken Finite Vibrating String? Solutions to the Problem I by Vladimir L. Borsch

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Global change in the trophic functioning of marine food webs. by Aurore Maureaud, Didier Gascuel, Mathieu Colléter, Maria L D Palomares, Hubert Du Pontavice, Daniel Pauly, William W L Cheung

“…The development of fisheries in the oceans, and other human drivers such as climate warming, have led to changes in species abundance, assemblages, trophic interactions, and ultimately in the functioning of marine food webs. Here, using a trophodynamic approach and global databases of catches and life history traits of marine species, we tested the hypothesis that anthropogenic ecological impacts may have led to changes in the global parameters defining the transfers of biomass within the food web. …”
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