Molecular and metabolic insights into muscle development and feed efficiency in beef cattle by Sophia M. Ascolese, Brynn H. Voy, Jonathan E. Beever, Jonathan E. Beever, Laney M. Stephens, Phillip R. Myer

“…Feed efficiency, often quantified through residual feed intake (RFI), is a complex trait influenced by genetic, physiological, and environmental factors. …”
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Application of Hardware and Software Complex for Individualisation of Students’ Sport and Recreational Physical Activities by O. N. Moskovchenko, L. V. Zakharova, N. V. Tretyakova, N. V. Lyulina, O. A. Kattsin, G. S. Savolaynen

“…The survey sampling and processing of experimental data were carried out by means of the hardware and software complex (HSC).Results and scientific novelty. The authors studied and documented the interconnection of students’ heart rate variability, taking into account their age and sex peculiarities, motion behaviour and medical groups. …”
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Contextual Vulnerability Should Guide Fair Subject Selection in Xenotransplantation Clinical Trials by Gianna Strand

“…Xenografts are typically sourced from porcine animals (domestic pigs) or non-human primates (baboons) and range from simple tissues like corneas to complex vital organs like hearts, lungs, or kidneys. …”
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INVESTMENT PROGRAM OF POWER GRID COM PANIES: CHECK ALL CAN NOT BE SELECTED by V. A. Karle, LYU. Zolotova, S. A. Kechin

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Outage probability based power allocation and relay selection algorithm in cooperative communication by Li-yue SUN, Xiao-hui ZHAO, Ming GUO

“…The relay selection and power optimization of multi-relay cooperative communication network under a joint sum power constraint was considered.A low complexity lay selection and power allocation algorithm was also pro-posed in amplify-and-forward cooperative network aiming at minimizing the probability of system outage.In this scheme,optimal power allocation among source and relay nodes was conducted.According to the SNR,an optimal relay node set was selected and a power allocation factor leading to lower system outage probability was obtained by steepest descent method.This algorithm did not need large quantity of l statistical information and equal power condition.It can obtain the best set of relay nodes under optimal power allocation only by solving the arranged matrix on the basis of Sig-nal to Noise Ratio.Simulation results show that the proposed relay select and power allocation algorithm,under the same conditions,compared in the outage probability in erent relay node set among several algorithms,achieves better performance in outage probability and power efficiency.…”
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A Generalized Multi-Layer Framework for Video Coding to Select Prediction Parameters by Muhammad Asif, Maaz Bin Ahmad, Imtiaz A. Taj, Muhammad Tahir

“…The exploitation of the RDO technique contributes significantly to increase the computational complexity of the coding process. In this paper, a generalized multi-layer framework is presented, which provides a hierarchical optimized way to select MB prediction parameters. …”
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Evaluating the Nuclear Reaction Optimization (NRO) Algorithm for Gene Selection in Cancer Classification by Shahad Alkamli, Hala Alshamlan

“…<b>Background/Objectives</b>: Cancer classification using microarray datasets presents a significant challenge due to their extremely high dimensionality. This complexity necessitates advanced optimization methods for effective gene selection. …”
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Model predictive control for energy efficient AC motor drives: An overview by Muhammad Bilal Shahid, Weidong Jin, Muhammad Abbas Abbasi, Abdul Rashid Bin Husain, Hafiz Mudassir Munir, Mannan Hassan, Aymen Flah, Ahmed Saad Eddine Souissi, Thamer A. H. Alghamdi

“…Then, the important challenges in MPC implementation, such as computational complexity reduction and delay compensation, weighting factor selection for multi‐objective cost functions, steady state performance and ripple reduction, parameter variations/model mismatching and achieving extended prediction horizons, are surveyed and most relevant solutions are reviewed. …”
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Efficient structure learning of gene regulatory networks with Bayesian active learning by Dániel Sándor, Péter Antal

“…Abstract Background Gene regulatory network modeling is a complex structure learning problem that involves both observational data analysis and experimental interventions. …”
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Design and performance investigation for substrate filler in protected horticulture by WEI Yuyong, LU Jun, SHENG Kuichuan, QIAN Xiangqun, SHEN Junfeng

“…Furthermore, automatic feeding device is complex and expensive in the fierce competition in the growing market. …”
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Productivity of corn hybrids, economic and energy efficiency of their cultivation in the Krasnodar Territory by A. A. Makarenko, S. V. Kokovikhin, T. V. Logoyda

“…The development of modern technologies for growing corn grain is a complex task that requires the use of adaptive approaches and highly productive, stress-resistant hybrids with individually selected sets of agrotechnical techniques. …”
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Integrating decision tools for efficient operations management through innovative approaches by Weidong Liu, Xuewu Lai

“…This study redefines the future of operations management by addressing efficiency and sustainability goals, offering a practical roadmap for organizations facing complex operational challenges.…”
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Multifunctional Magnetic Ionic Liquid‐Carbon Nanohorn Complexes for Targeted Cancer Theranostics by Yun Qi, Eijiro Miyako

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Complex Dynamics and Intelligent Control: Advances, Challenges, and Applications in Mining and Industrial Processes by Luis Rojas, Víctor Yepes, José Garcia

“…Complex dynamics and nonlinear systems play a critical role in industrial processes, where complex interactions, high uncertainty, and external disturbances can significantly impact efficiency, stability, and safety. …”
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SCIENTIFIC APPROACH TO A COMPLEX ASSESSMENT OF DETERMINANTS OF THE INSURANCE MARKET DEVELOPMENT OF UKRAINE by L. V. Popova, N. O. Kovalchuk, D. D. Polagnyn

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LLMAGENTNET: A COLLABORATIVE NETWORK OF AUTONOMOUS AI AGENTS FOR COMPLEX TASK EXECUTION by А. Р. Бідочко, Я. І. Виклюк

“… Recent advancements in Large Language Models (LLMs) have opened new horizons for building autonomous AI agents capable of executing complex, multi-step tasks across a wide range of domains. …”
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Analysis of Pharmaceutical Active Compounds in Complex Water Samples: Sample Filtration as an Option by Sofia Silva, João Rodrigues, Vitor V. Cardoso, Rui N. Carneiro, Cristina M. M. Almeida

“…This can be especially difficult when working with complex matrices such as natural waters and wastewater. …”
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Energy efficient resource allocation scheme for AF relay downlink system by Yu CHEN, Xu-ming FANG, Bo HUANG

“…In order to maximize the total energy efficiency of amplify-and-forward relay downlink system,a joint scheme of relay selection and power allocation was proposed with the circuit power of the system.For reducing the computa-tional complexity,a step-by-step suboptimal allocation scheme was provided.Firstly,the virtual direct channel gains were adopted to select appropriate transmission link.Meanwhile,relay system was converted to the single hop system.Then,the power allocation could be solved by convex optimization.Besides,in order to accommodate different user distribu-tions,a resource allocation scheme based on cell zooming was also proposed.Simulations demonstrated that the solution of the proposed suboptimal scheme approaches the optimal solution.Additionally,the scheme with cell zooming is adaptable to different user distributions and further improves the total system energy efficiency.…”
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A Hybrid Seed Node Selection and No-Retracing Random Walk in Page Rank Algorithm by Azam Bastanfard, Ali Kheradbeygi Moghadam, Ali Fallahi RahmatAbadi

“…The random walk technique, which has a reputation for excellent performance, is one method for complex networks sampling. However, reducing the input data size is still a considerable topic to increase the efficiency and speed of this algorithm. …”
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Computationally Efficient Hybrid Downscaling of Surf Zone Hydrodynamics: Methodology and Evaluation by E. R. Echevarria, S. Contardo, B. Pérez‐Díaz, R. K. Hoeke, B. Leighton, C. Trenham, L. Cagigal, F. J. Méndez

“…Abstract We present a hybrid surf‐zone model that combines numerical simulations and statistical/machine learning techniques, enabling accurate calculations of nearshore wave and hydrodynamic parameters with high computational efficiency. The approach involves defining representative forcing conditions, carrying out numerical model (XBeach) simulations for these cases, and training machine learning models capable of predicting selected model output variables. …”
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