Thermoelastic damping in piezothermoelastic nanobeam resonators under the strain gradient theory with micro-inertia and non-fourier heat conduction by Olha Hrytsyna, Maryan Hrytsyna

“…To account for small-scale effects, the Helmholtz free energy density is defined as a function of the strain tensor, strain gradient tensor, electric field vector, and temperature field, considering these parameters as independent state variables. …”
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Analysis of factors influencing the increase of extracellular water ratio in tumor patients without edema signs by Heling Zhu, Panpan Gan, Hao Jiang, Liangliang Bao, Chengjiang Liu, Jiawen Yu, Jiawen Yu

“…PA was the most influential factor among all independent variables affecting ECW/TBW (B = −1.006, p < 0.001). …”
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Torsional Vibration Suppression During Mode Transition Process in a Parallel Hybrid Electric Vehicle Based on Multiple Model Predictive Control by Cheng Huang, Changqing Du, Longjian Li, Xiangyu Gongye, Yifan Zhao

“…At the same time, the influence of the cost function, the weight coefficient, and the predictive time domain on the torsional vibration suppression effect during the mode transition process are explored in the mMPC strategy design, and the solution time is controlled within 10ms, which meet the real-time requirements. …”
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Improved basal drag of the West Antarctic Ice Sheet from L-curve analysis of inverse models utilizing subglacial hydrology simulations by L.-S. Höyns, L.-S. Höyns, L.-S. Höyns, T. Kleiner, A. Rademacher, M. Rückamp, M. Wolovick, M. Wolovick, A. Humbert, A. Humbert

“…Since we cannot directly measure basal properties on a large scale, inverse models can be used to infer the basal drag coefficient by minimizing a cost function that depends on a velocity misfit and a regularization term.…”
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Correlation of the FIB-4 Liver Biomarker Score with the Severity of Heart Failure by Roxana Buzas, Paul Ciubotaru, Alexandra Corina Faur, Marius Preda, Melania Ardelean, Doina Georgescu, Patrick Dumitrescu, Daniel Florin Lighezan, Mihaela-Diana Popa

“…Statistical analysis was based on ANOVA one-way tests for continuous variables and Chi-square tests for categorical variables. …”
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Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…In the end, using an attention function, Vision Transformer-based models classify vehicles seen from above. …”
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Flexible Reconfiguration for Optimal Operation of Distribution Network Under Renewable Generation and Load Uncertainty by Behzad Esmaeilnezhad, Hossein Amini, Reza Noroozian, Saeid Jalilzadeh

“…Minimizing the operational costs is difficult when there is a high penetration of renewable resources and variability of loads, which introduces uncertainty. …”
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Load frequency control in isolated island city microgrids using deep graph reinforcement learning considering extensive scenarios by Ping He, Xiongwei Huang, Ruobing He, Linkun Yuan

“…Demonstrated effectively in China Southern Grid’s island microgrid setup, LE-LFC emerges as an advanced solution for modern grid variability, offering superior robustness, adaptability, and learning speed, thus enabling flexible and efficient energy system management.…”
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A robust optimization model for allocation-routing problems under uncertain conditions. by Tingting Zhang, Yanqiu Liu

“…The findings show that data variability and the uncertainty budget play a critical role in determining hospital locations and casualty transportation plans. …”
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DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…The HC algorithm dynamically optimizes the fitness threshold, enabling adaptive decision-making that accommodates environmental variability. Simulation results confirm that the DTHC method achieves a spectrum hole detection accuracy of 99%, with a miss-detection probability below 0.9%, demonstrating its effectiveness in enhancing CRN performance while maintaining low complexity.…”
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Modeling and Regulation of Dynamic Temperature for Layer Houses Under Combined Positive- and Negative-Pressure Ventilation by Lihua Li, Min Li, Yao Yu, Yuchen Jia, Zhengkai Qian, Zongkui Xie

“…Additionally, a temperature control method for a layer house is designed using a variable universe fuzzy PID control algorithm (VFPID). …”
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Elastostatic analysis of tapered FGM beams with spatially varying material properties by Justín Murín, Stephan Kugler, Juraj Paulech, Juraj Hrabovský, Vladimír Kutiš, Herbert Mang, Mehdi Aminbaghai

“…In this article an effective method for elastostatic analysis of tapered beams made of functionally-graded material (FGM) is presented. The spatially variable stiffness of the beam is the consequence of the continuous longitudinal variability of the cross-sectional dimension, accompanied by the variability of the material properties in three orthogonal directions. …”
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The Effect of Hydraulic Partitioning on Prediction the Rate of Bed Load Transport in Gravel-bed Rivers using Support Vector Machine by Kiyoumars Roushangar, Mohammad Hosseini, Saman Shahnazi

“…After optimization of parameters for kernel function, the bed load transport rate was predicted and obtained results from different models were investigated in terms of correlation coefficient (R), Root mean square error (RMSE) and Nash-Sutcliffe (NSE). in order to assess the capability of SVM in quantification of bed load under varied hydraulic conditions, Froude number (Fr) and bed slope of channel (S0) were selected as a parameters describing the hydraulic conditions and median diameter of the sediment particles (D50) and shear Reynolds number (Re*) were considered as a representative of sediment characteristic. …”
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Commercial Vehicle Ride Comfort Optimization Based on Intelligent Algorithms and Nonlinear Damping by Shuilong He, Keren Chen, Enyong Xu, Wei Wang, Zhansi Jiang

“…The sum of the frequency-weighted RMS of the driver seat acceleration, the RMS of dynamic tyre load, and suspension working space is taken as the objective function in this article, using nonlinear damping coefficients and stiffness of suspension as design variables. …”
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Feasibility and psychometric quality of smartphone administered cognitive ecological momentary assessments in women with metastatic breast cancer by Ashley M Henneghan, Emily W Paolillo, Kathleen M Van Dyk, Oscar Y Franco-Rocha, Soyeong Bang, Rebecca Tasker, Tara Kaufmann, Darren Haywood, Nicolas H Hart, Raeanne C Moore

“…Test-retest reliability was examined using intraclass correlation coefficients (ICCs) for each EMA, and Pearson's correlation were used to evaluate convergent validity between cognitive EMAs and baseline clinical cognitive and psychosocial variables. …”
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Effects of Different Irrigation Regimes on Root Growth and Physiological Characteristics of Mulch-Free Cotton in Southern Xinjiang by Feiyan Su, Ziyang Guo, Bingrong Wu, Jichuan Wang, Shuangrong Chen

“…It can be concluded that no mulching has a certain impact on cotton root distribution and leaf physiological function. When the irrigation amount is 450–525 mm and irrigation times is 10–12, it is beneficial for promoting root growth and plays a role in leaf physiological function, and the water use efficiency (WUE) is high, which can provide reference for the scientific water management of mulch-free cotton in production practice.…”
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Energy‐maximising moment‐based constrained optimal control of ocean wave energy farms by Nicolás Faedo, Giordano Scarciotti, Alessandro Astolfi, John V. Ringwood

“…The authors develop a framework under which the objective function (and system variables) can be mapped to a finite‐dimensional tractable quadratic program (QP), which can be efficiently solved using state‐of‐the‐art solvers. …”
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Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. Among the ML methods explored, a backpropagation neural network (BPNN) model with a sigmoid activation function exhibited superior predictive accuracy compared to other algorithms. …”
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Forecasting Electricity Production in a Small Hydropower Plant (SHP) Using Artificial Intelligence (AI) by Dawid Maciejewski, Krzysztof Mudryk, Maciej Sporysz

“…Renewable Energy Sources (RESs) are difficult to predict due to weather variability. Electricity production by a run-of-river SHP is marked by the variability related to the access to instantaneous flow in the river and weather conditions. …”
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Spatial pattern of Trees in the Riparian Forests (Case Study: Wildlife Refuge of Karkhe) by Shaieste Gholami

“…This result showed that there was the small-scale variability and important proportion of unexplained variance. …”
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