Comprehensive review on single-atom catalysts in electrochemical hydrogen-evolution reaction: computational modelling and experimental investigation by Fares Chabira, Sajjad Ali, Abbas Khan, Muhammad Humayun, Mohamed Bououdina

“…Single Atom Catalysts (SACs) have been recognised as promising catalysts for exceptional HER activities owing to their unique electronic and geometrical features. This comprehensive review highlights the effective correlation between computational modelling and experimental research in fabricating new SACs and better understanding their catalytic mechanisms in the HER. …”
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Enhancing the prediction of vitamin D deficiency levels using an integrated approach of deep learning and evolutionary computing by Ahmed Alzahrani, Muhammad Zubair Asghar

“…To improve the models effectiveness and guarantee the optimal choice of the features and hyper-parameters, we incorporate evolutionary computing methods, particularly genetic algorithms (GA). …”
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SpecTE: Parameter Estimation for LAMOST Low-resolution Stellar Spectra Based on Denoising Pretraining by Xirong Zhao, Xiangru Li, Hui Li, Xianqi Liu

“…SpecTE enhances its sensitivity to spectral features and improves its parameter estimation accuracy by prelearning a mapping from low-quality spectra to high-quality spectra. …”
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Evaluation of connection pool <i>PgBouncer</i> efficiency for optimizing relational database computing resources by A. S. Boronnikov, P. S. Tsyngalev, V. G. Ilyin, T. A. Demenkova

“…The research utilized methods of experimentation, induction, testing, and statistical analysis.Results. The main features, architecture and modes of operation of the PgBouncer service are considered. …”
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Unreliable communication in high-performance distributed multi-agent systems: A ingenious scheme in high computing by Ali Mustafa, Muhammad Najam ul Islam, Salman Ahmed, Muhammad Ahsan Tufail

“…Designing of distributed consensus algorithms featuring accuracy, robustness, reliability, and speed of convergence is in high demand for various multi-agent applications. …”
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A Quantitative Evaluation of UAV Flight Parameters for SfM-Based 3D Reconstruction of Buildings by Inho Jo, Yunku Lee, Namhyuk Ham, Juhyung Kim, Jae-Jun Kim

“…Quantitative evaluation results using various analytical methodologies (multiple regression analysis, Kruskal–Wallis test, random forest feature importance, principal component analysis including K-means clustering, response surface methodology (RSM), preference ranking technique based on similarity to the ideal solution (TOPSIS), and Pareto optimization) revealed that the basic shooting pattern ‘type’ has a significant and statistically significant influence on all major SfM performance metrics (reprojection error, final point count, computation time, reconstruction completeness; Kruskal–Wallis <i>p</i> < 0.001). …”
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Research on High-Resolution Modeling of Satellite-Derived Marine Environmental Parameters Based on Adaptive Global Attention by Ruochu Cui, Liwen Ma, Yaning Hu, Jiaji Wu, Haiying Li

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A Computationally Efficient Model Predictive Control Energy Management Strategy for Hybrid Vehicles Considering Driving Style by Yalian Yang, Yuqi Chen, Changdong Liu

“…Driving data were collected through driver-in-the-loop simulation experiments, a certain number of feature parameters related to driving styles were analyzed, and the final feature parameters were determined through two screenings. …”
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Using a Bodily Weight-Fat Scale for Cuffless Blood Pressure Measurement Based on the Edge Computing System by Shing-Hong Liu, Bo-Yan Wu, Xin Zhu, Chiun-Li Chin

“…The feature included two calibration-based parameters and one calibration-free parameter was used to estimate BP with XGBoost. …”
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Estimating Tea Plant Physiological Parameters Using Unmanned Aerial Vehicle Imagery and Machine Learning Algorithms by Zhong-Han Zhuang, Hui-Ping Tsai, Chung-I Chen

“…Among regression models, MIs provided greater stability for tea plant physiological parameters, whereas feature ranking methods had minimal impact on accuracy. …”
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Optimizing energy and latency in edge computing through a Boltzmann driven Bayesian framework for adaptive resource scheduling by Dinesh Sahu, Nidhi, Rajnish Chaturvedi, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Idrees Alsolbi

“…Abstract This paper presents a new approach based on Boltzmann Distribution and Bayesian Optimization to solve the energy-efficient resource allocation in edge computing. It employs Bayesian Optimization to optimize the parameters iteratively for the minimum energy consumption and latency. …”
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Dependence of energy-speed characteristics of pneumatic drive on initial parameters of additional volume under counterpressure braking by Andrey N. Sirotenko, Svetlana A. Partko, Bakir Ala Saed

“…But considerable inertia of the output link of the pneumatic drive and compressibility of the operating environment affect the drive performance and a shock-free stop block. This feature has caused existence of a large number of ways of braking of the output link of the pneumatic drive. …”
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NSA-CHG: An Intelligent Prediction Framework for Real-Time TBM Parameter Optimization in Complex Geological Conditions by Youliang Chen, Wencan Guan, Rafig Azzam, Siyu Chen

“…The framework resolves critical limitations of conventional experience-driven approaches that inadequately address the nonlinear coupling between the spatial heterogeneity of rock mass parameters and mechanical system responses. Three principal innovations are introduced: (1) a hardware-compatible sparse attention architecture achieving O(n) computational complexity while preserving high-fidelity geological feature extraction capabilities; (2) an adaptive kernel function optimization mechanism that reduces confidence interval width by 41.3% through synergistic integration of boundary likelihood-driven kernel selection with Chebyshev inequality-based posterior estimation; and (3) a physics-enhanced modelling methodology combining non-Hertzian contact mechanics with eddy field evolution equations. …”
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Adaptive Real-Time Channel Estimation and Parameter Adjustment for LoRa Networks in Dynamic IoT Environments by Fatimah Alghamdi, Fuad Bajaber

“…This innovative framework provides significant improvements in channel state estimation, communication reliability, adaptive parameter control, and computational efficiency, thereby ensuring robust performance in IoT environments at the same time.…”
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Parameter regionalization of large-scale distributed rainfall–runoff models using a conditional probability method by Takahiro Sayama, Masafumi Yamada, Ayato Yamakita, Yoshito Sugawara

“…The key feature of this method is that the calibration phase calculation assumes spatially uniform parameter sets within the calibrating basins, significantly reducing computational costs. …”
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Study of distribution and morphological characteristics of the trabecular bone in the uncinate process of the cervical spine using micro-computed tomography. by Yunteng Hao, Yuan Ma, Shaojie Zhang, Chaoqun Wang, Wei Wang, Xiaohe Li, Shang Gao, Kun Li, Jie Chen, Haiyan Wang, Yang Yang, Mingjie Gao, Jian Wang, Zhijun Li, Jun Shi, Xing Wang

“…This study aimed to observe the distribution of cancellous bone in the cervical uncinate process and its morphological features using micro-computed tomography (Micro-CT) to gain a deeper understanding of the morphological characteristics of the uncinate microstructure. …”
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A Bayesian vector-autoregressive application with time-varying parameters on the monetary shocks–production network nexus by Mihaela Simionescu, Nicolas Schneider, Beata Gavurova

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Extension to the Jiles–Atherton Hysteresis Model Using Gaussian Distributed Parameters for Quenched and Tempered Engineering Steels by Alasdair Regan, John Wilson, Anthony J. Peyton

“…The Jiles–Atherton (J–A) model has seen extensive use for modelling the hysteresis behaviour of ferromagnetic materials due to its computational efficiency, simplicity of use, and small number of physically related parameters. …”
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Computed tomography angiography in the diagnosis of non-ST-elevation myocardial infarction: redefining our first line of defense by Yvonne J.M. van Cauteren, Marie-Julie D.K. Lemmens, Sebastiaan C.A.M. Bekkers, Bas L.J.H. Kietselaer, Jordi Heijman, Ralph A.L.J. Theunissen, Braim Rahel, Talitha Voorn, Sander M.J. van Kuijk, Robin Nijveldt, Kevin Vernooy, Joachim E. Wildberger, Casper Mihl, Martijn W. Smulders

“…Combining all CTA parameters (CAD-RADS ≥ 3, Agatston score >1.000 and ≥2 HRP features) did not improve the diagnostic accuracy compared with CAD-RADS alone. …”
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Joint contribution of adaptation and neuronal population recruitment to response level in visual area MT: a computational model by Maria Inês Cravo, Rui Bernardes, Miguel Castelo-Branco

“…Abstract Adaptation is a form of short-term plasticity triggered by prolonged stimulus exposure, altering perceptual sensitivity to stimulus features through reduced neuronal firing rates. Our previous studies investigated adaptation to bistable stimuli, specifically inward-moving gratings perceived either as a plaid moving coherently downward or two gratings moving incoherently. …”
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