Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0 by A. Lauer, L. Bock, B. Hassler, P. Jöckel, L. Ruhe, M. Schlund

“…While the examples shown here focus on atmospheric variables, the new functionality can be applied to any other ESM component such as land, ocean, sea ice, or land ice. …”
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Correlation Between Hallux Valgus Severity, Abductor Hallucis Muscle Properties, and Plantar Pressure Distribution by Kyeong-Ah Moon, Ye Jin Kim, Hye-Seon Jeon

“…Objects: This study aimed to explore how changes in skeletal, muscular, and functional variables correlate with HV severity and to provide evidence for more integrated treatment approaches. …”

Incorporating Traffic Flow Model into A Deep Learning Method for Traffic State Estimation: A Hybrid Stepwise Modeling Framework by Yuyan Annie Pan, Jifu Guo, Yanyan Chen, Siyang Li, Wenhao Li

“…Traffic state estimation (TSE), which reconstructs the traffic variables (e.g., speed, flow) on road segments using partially observed data, plays an essential role in intelligent transportation systems. …”
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Encapsulation Based Method for Natural Frequency Identification of Deployable Solar Arrays with Multiple Plates by Chunjuan Zhao, Xiangyu Zhao, Shanbo Chen, Jisong Yu, Lei Zhang

“…However, for the batch production of small satellites, the accuracy and efficiency of traditional ground modal testing methods are limited. …”
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A De-Nesting Hybrid Reliability Analysis Method and Its Application in Marine Structure by Chenfeng Li, Tenglong Jin, Zequan Chen, Guanchen Wei

“…Traditional methods for hybrid reliability analysis usually require a nested optimization framework, which will lead to too many calls to the limit state function (LSF) and result in poor computational efficiency. …”
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Feasibility Assessment of Novel Multi-Mode Camshaft Design Through Modal Analysis by Merve Üngör, Osman Taha Sen, Akif Yavuz, Cemal Baykara

“…Camshafts in internal combustion engines are critical components not only for mechanical functionality but also for dynamic performance and vibration characteristics. …”
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Revisiting the Group Classification of the General Nonlinear Heat Equation <i>u_t</i> = (<i>K</i>(<i>u</i>)<i>u_x</i>)<i>_x</i> by Winter Sinkala

“…In this paper, we revisit the group classification of the general nonlinear heat (or diffusion) equation <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>u</mi><mi>t</mi></msub><mo>=</mo><msub><mfenced separators="" open="(" close=")"><mi>K</mi><mrow><mo>(</mo><mi>u</mi><mo>)</mo></mrow><mspace width="0.166667em"></mspace><msub><mi>u</mi><mi>x</mi></msub></mfenced><mi>x</mi></msub><mo>,</mo></mrow></semantics></math></inline-formula> where <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>K</mi><mo>(</mo><mi>u</mi><mo>)</mo></mrow></semantics></math></inline-formula> is a non-constant function of the dependent variable. We present the group classification framework, derive the determining equations for the coefficients of the infinitesimal generators of the admitted symmetry groups, and systematically solve for admissible forms of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>K</mi><mo>(</mo><mi>u</mi><mo>)</mo></mrow></semantics></math></inline-formula>. …”
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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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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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Developing CGMap: Characterizing Continuous Glucose Monitoring Data in Patients with Type 2 Diabetes by Shuzhen Bai, Chu Lin, Xiaoling Cai, Suiyuan Hu, Jing Wu, Ling Chen, Wenjia Yang, Linong Ji

“…However, glucose variability decreased with increased BMI. Meanwhile, greater glycemic variability was associated with worse islet function, higher baseline glucose level, and higher hemoglobin.…”
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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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Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology by Lin Qi, Chaoran Chen, Jun Dong

“…A five-dimensional objective system—comprising energy efficiency, spatial quality, economic cost, ecological benefits, and cultural expression—was established, alongside the identification and standardization of 29 key variables to construct mapping relationships among objective functions. …”
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Semantic ECG hash similarity graph by Yixian Fang, Shilin Zhang, Yuwei Ren

“…Abstract Graph-based methods have made significant progress in addressing the dependent correlations among ECG time series variables. However, most existing graph structures primarily focus on local similarity while overlooking global semantic correlation. …”
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Structural strength analysis and optimization of converter lug based on Kriging model by HE Guanqiang, LIU Yongjiang, LI Hua, CHEN Liming

“…In this paper, machine learning methods were considered to approximate the functional relationships between design variables and responses. …”
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An Optimization Model for Shell Plate Seam Landing Using Minimum Manufacturing Cost and a Solution by Genetic Algorithm by Ho Rim Pae, Min Hyok Jon, Chol Jun Pak

“…In this paper, a new optimization model and its solution method for the landing of seams and butts (for convenience, seam and butt are simply called seam) on the ship hull surface are proposed in order to improve the shipbuilding efficiency. The minimum manufacturing cost of ship hull shell plates (SHSPs) is the objective function, the rules and requirements for the seam position and the size of a single shell plate are the constraints, and the position and shape of the seam are the design variables. …”
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