The impact of weightlifting training methods on strength development and perceived exertion: a comparative study of fixed-repetition and AMRAP (as many repetitions as possible) pro... by Omar Saad Ahmed Saad Ahmed, Saif Saad Ahmed, Maher Abdulateef Arif, Oday Abdulhussein Kareem Alsubaih

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Reviewing the complexity of endogenous technological learning for energy system modeling by Johannes Behrens, Elisabeth Zeyen, Maximilian Hoffmann, Detlef Stolten, Jann M. Weinand

“…While iterative solution methods tend to find future energy system designs that rely on suboptimal technology mixes, exact solutions leading to global optimality are computationally demanding. …”
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Treatment of metastatic ALK-positive non-small cell lung cancer: indirect comparison of different ALK inhibitors using reconstructed patient data by Vera Damuzzo, Vera Damuzzo, Lorenzo Gasperoni, Luna Del Bono, Andrea Ossato, Andrea Ossato, Alessandro Inno, Andrea Messori, Andrea Messori

“…However, due to the lack of direct head-to-head comparisons among these agents, the optimal treatment for metastatic ALK-positive NSCLC remains unclear.MethodsThis study used the IPDfromKM (Individual Patient Data from Kaplan-Meier) method to reconstruct patient-level data from Kaplan-Meier curves of seven randomized phase III trials, involving a total of 3,850 patients. …”
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Decentralized Nonstationary Fuzzy Neural Network with Meta-Learning-Net by Zhen Zhang, Meiling Yu, Hui Jia

“…The nonstationary fuzzy neural network (NFNN) has proven to be an effective and interpretable tool in machine learning, capable of addressing uncertainty problems similarly to type-2 fuzzy neural networks, while offering reduced computational complexity. …”
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Physics-Informed Decoupled Calibration for Fourier Ptychographic Microscopy by Mingdi Liu, Junzhao Liang, Yanxiong Wu, Zicong Luo, Rui Xie, Jiaxiong Luo, Lisong Yan

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The trunk segmental motion complexity and balance performance in challenging seated perturbation among individuals with spinal cord injury by Mianjia Shan, Chenhao Li, Jiayi Sun, Haixia Xie, Yan Qi, Wenxin Niu, Ming Zhang

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Hybrid Population-Based Hill Climbing Algorithm for Generating Highly Nonlinear S-boxes by Oleksandr Kuznetsov, Nikolay Poluyanenko, Kateryna Kuznetsova, Emanuele Frontoni, Marco Arnesano

“…This paper introduces the hybrid population-based hill-climbing (HPHC) algorithm, a novel approach for generating cryptographically strong S-boxes that combines the efficiency of hill climbing with the exploration capabilities of population-based methods. The algorithm achieves consistent generation of 8-bit S-boxes with a nonlinearity of 104, a critical threshold for cryptographic applications. …”
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A hybrid two stage Taguchi-regression-NSGA II-AHP-GRA, multi-objective optimization framework for sustainable straight slot milling of AZ31 magnesium alloy by M. Atif Saeed, Faraz Junejo, Imran Amin, Irfan Khan Tanoli, Abeer D. Algarni, Sadique Ahmad, Abdelhamied A. Ateya

“…By integrating Taguchi's method, stepwise regression, NSGA-II, AHP, and Grey Relational Analysis (GRA), the framework systematically optimizes machining parameters. …”
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The potential of combined robust model predictive control and deep learning in enhancing control performance and adaptability in energy systems by Xiaowen Lv, Ali Basem, Mohammadtaher Hasani, Ping Sun, Jingyu Zhang

“…Extensive simulations indicate that the integrated RMPC-Deep Learning system improves control accuracy by 8.02% compared to conventional methods, while also reducing energy consumption by 12.14%. …”
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Efficient Hybrid-Robust Approach for Cancer Biomarker Discovery Using Omics Data by Karima Sid, Soumia Zertal, Mohamed Batouche, Soumeya Zerabi

“…Comparison with related work demonstrates the efficacy of this approach, which enhances classification accuracy and stability while reducing the number of selected genes.…”
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Is there a competitive advantage to using multivariate statistical or machine learning methods over the Bross formula in the hdPS framework for bias and variance estimation? by Mohammad Ehsanul Karim, Yang Lei

“…While advanced machine learning methods such as XGBoost can enhance precision, simpler methods such as forward selection or backward elimination may offer similar performance in terms of bias and coverage with fewer computational demands. …”
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Digital Transformation in Water Utilities: Status, Challenges, and Prospects by Neil S. Grigg

“…Their digital transformation journeys are evident in business practices, operations, and asset management, including methods like decision support systems, SCADA systems, digital twins, and process optimization. …”
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Numerical illustration using finite difference method for the transient flow through porous microchannel and statistical interpretation of entropy using response surface methodolog... by Pradeep Kumar, A Felicita, Ajaykumar AR, Qasem Al-Mdallal

“…The modeled problem gives rise to partial differential equations, which are computed by finite difference method. Response surface methodology, an optimization technique, is used to attain the optimal conditions for entropy generated for the flow of fluid. …”
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Generating a Set of Reference Images for Reliable Condition Monitoring of Critical Infrastructure using Mobile Robots by Sotnikov O., Tymochko O., Bondarchuk S., Dzhuma L., Rudenko V., Mandryk Ya., Surkov K., Palonyi A., Olizarenko S.

“…This reduces the amount of computation and extends the operating time of mobile robots while maintaining accuracy. The significance of the obtained results consists in the possibility of solving a complex task of forming a set of reference images, depending on the information content and stochastic conditions of sighting of critical infrastructure objects. …”
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A Framework for Sustainability Performance Measurement Through Process Mining: Integration of GRI Metrics in Operational Processes by Ourania Areta Hiziroglu, Onur Dogan

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Model for evaluation of technical and economic indicators of offshore wind farms by D. Y. Davydov, S. G. Obukhov

“…The solution to this problem is possible by increasing efficiency while reducing costs as much as possible, which requires optimal design of offshore wind farms.GOAL. …”
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Application of Mixed-Integer Linear Programming Models for the Sustainable Management of Vine Pruning Residual Biomass: An Integrated Theoretical Approach by Leonel J. R. Nunes

“…Efficient biomass logistics play a key role in supporting circular bioeconomy principles by improving resource utilization and reducing operational costs. <i>Methods</i>: Two optimization approaches are evaluated: a base MILP model designed for scenarios with single processing points and an advanced model that incorporates intermediate processing steps to enhance logistical efficiency. …”
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The Impacts of Water Policies and Hydrological Uncertainty on the Future Energy Transition of the Power Sector in Shanxi Province, China by Xingtong Chen, Jijian Lian, Qizhong Guo

“…Hydrological time series analysis methods are employed to project future water resource variations in Shanxi Province and evaluate their implications for power system optimization. …”
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AutoML: A systematic review on automated machine learning with neural architecture search by Imrus Salehin, Md. Shamiul Islam, Pritom Saha, S.M. Noman, Azra Tuni, Md. Mehedi Hasan, Md. Abu Baten

“…Additionally, we delve into several noteworthy research directions in NAS methods including one/two-stage NAS, one-shot NAS and joint hyperparameter with architecture optimization. …”
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Production, characterization and antioxidant analysis on the Undaria-based alcoholic beverages using response surface method and HS-SPME-GC × GC-TOF-MS by Fangru Nan, Xinyi Li, Jia Feng, Junping Lv, Qi Liu, Xudong Liu, Yang Liu, Ruikai Zhang, Baoqing Bai, Shulian Xie

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