Symmetric physically unclonable functions of the arbiter type by V. N. Yarmolik, A. A. Ivaniuk

“…It has been established that classical APUF uses a standard basic element that performs three functions, namely, the function of generating two random variables Generate, the function of choosing a pair of paths Select and the function of switching paths Switch, which are specified by one bit of the challenge. …”
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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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Demonstrating Efficient and Robust Bosonic State Reconstruction via Optimized Excitation Counting by Tanjung Krisnanda, Clara Yun Fontaine, Adrian Copetudo, Pengtao Song, Kai Xiang Lee, Ni-Ni Huang, Fernando Valadares, Timothy C.H. Liew, Yvonne Y. Gao

“…In this work, we introduce an efficient and robust technique of optimized reconstruction with excitation-number sampling (ORENS) based on the idea of the generalized Q function. …”
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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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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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THE PROBLEM OF ENERGY EFFICIENCY OF SYSTEMS BASED ON ARTIFICIAL INTELLIGENCE OF THE INTERNET OF THINGS (AIOT) by С. В. Войтко

“…The emphasis is on allocating conventionally fixed and conventionally variable costs for AIoT. It was determined that integrating artificial intelligence functionality into the IoT infrastructure provides the opportunity to store big data for processing using artificial intelligence elements capable of conducting predictive analysis to make informed management decisions. …”
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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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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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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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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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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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Machine learning-based smart irrigation controller for runoff minimization in turfgrass irrigation by Sambandh Dhal, Jorge Alvarado, Ulisses Braga-Neto, Benjamin Wherley

“…The synthetic data were derived from observations collected from irrigation plots at the Texas A&M University Turfgrass Laboratory in Texas, United States, with Soil Wetting Efficiency Index (SWEI) serving as the target variable. …”
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Efficient Solar Cell Design through Grey Wolf Optimization: Multi-Layer Thickness Optimization for Enhanced Short-Circuit Current Density by Hamed Kargaran, Hassan Alipour, Maryam Amirhoseiny, Ghasem Alahyarizadeh

“…Optimization problems can be classified as discrete or continuous, depending on the nature of the decision variables. Using continuous algorithms for problems that are inher-ently discrete can pose challenges in achieving optimal efficiency. …”
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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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Gene function revealed at the moment of stochastic gene silencing by Shreyan Gupta, James J. Cai

“…In this study, we introduce the single-cell Stochastic Gene Silencing (scSGS) method, which leverages the natural variability in single-cell gene expression to decipher gene function. …”
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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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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

“…Global trends were identified and cluster analyses were used to characterize the variability of trends between ecosystems. Results showed that the most common pattern over the study period is a global decrease in TCI, while the ECI indicator tends to increase. …”
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Microbiological dimensions and functions in constructed wetlands: A review by Anju Rani, Mansi Chauhan, Pradeep Kumar Sharma, Mansi Kumari, Debasis Mitra, Samiksha Joshi

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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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Acute effects of resistance exercise intensity and repetition at a predetermined volume on inhibitory control: a randomized controlled trial by Ying-Chu Chen, Yan-Ho Lo, Chen-Sin Hung, Yi-Ting Cheng, Ruei-Hong Li, Feng-Tzu Chen, Yu-Kai Chang, Yu-Kai Chang

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