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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The association between age and long-term quality of life after curative treatment for prostate cancer: a cross-sectional study by Reidun Sletten, Ola Berger Christiansen, Line Merethe Oldervoll, Lennart Åstrøm, Håvard Kjesbu Skjellegrind, Jūratė Šaltytė Benth, Øyvind Kirkevold, Sverre Bergh, Bjørn Henning Grønberg, Siri Rostoft, Asta Bye, Paul Jarle Mork, Marit Slaaen

“…We found no statistically significant independent association between age at treatment and global QoL, PF or side effects, except for sexual function (regression coefficient [RC] −0.77; p < 0.001) and hormonal/vitality (RC 0.30; p = 0.006) function. …”
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Animal welfare and biosecurity correlation in buffalo farm evaluated by ClassyFarm system by Domenico Vecchio

“…The statistical analysis was performed by Spearman Rank correlation coefficient using GraphPad Prism 8.0.1. (GraphPad Software, San Diego, CA, USA). …”
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Enhanced Dung Beetle Optimizer-Optimized KELM for Pile Bearing Capacity Prediction by Bohang Chen, Mingwei Hai, Gaojian Di, Bin Zhou, Qi Zhang, Miao Wang, Yanxiu Guo

“…The model utilizes the pile length, pile diameter, average effective vertical stress, and undrained shear strength as input variables, with the bearing capacity serving as the output variable. …”
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Combined Surfactant and Enzyme-Assisted Extraction of Pectin from Hawthorn (Crataegus monogyna Jacq.) Fruits by Anastasia E. Novikova, Liubov N. Skrypnik

“…The hawthorn pectin can be used to develop new functional products.…”
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Developing a novel layer network structure for a LSTM model to predict mean monthly river streamflow by Amin Gharehbaghi, Redvan Ghasemlounia, Shahaboddin Daneshvar, Farshad Ahmadi

“…For doing so, to select the most effective parameters on MRSF m , the Pearson’s correlation coefficient (PCC) and Cosine amplitude sensitivity (CAS) as features selection process are carried out for potential meteorological variables in the study area (i.e., average monthly temperature (T m ), evaporation (ET m ), and precipitation (P m )) and target (MRSF m ). …”
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A Low-Complexity Direction-of-Arrival Estimation Algorithm for Noncircular Signals via Subspace Rotation Technique by Wei Wang, Ming Zhang, Bobin Yao, Tongxing Zheng, Xiaojiao Fan

“…Then, utilizing the separation of variables and the orthogonality between the reduced-dimension noise subspace and the space spanned by the columns of the extended manifold matrix, a new one-dimensional spectral search function is derived to estimate DoAs. …”
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VARIATION OF EMBRYO WEIGHT IN BREEDING ACCESSIONS OF CARROT by A. F. Bukharov, D. N. Baleev, M. I. Ivanova

“…The least embryo weight 14.0 μg was observed in breeding lines. The coefficient of variation for embryo weight varied in the  range  from  10.4  to  14.2  and  reached  25.1  %  in ‘Rogneda’. …”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Under the BIA, an alpha coefficient (α) of 15% is applied, whereas in the SA, each business line has a specific beta coefficient (β) ranging between 12% and 18%. …”
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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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A novel unified variational finite difference (VFD) solution method for optimal control problems by Amir Norouzzadeh, Nader Nariman-zadeh, Reza Ansari

“…To do so, the general form of quadratic performance index function and nonlinear state equations are considered first. …”
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Pedestrian detection method based on improved YOLOv5 by Shangtao You, Zhenchao Gu, Kai Zhu

“…We optimize the regression prediction of the anchor using the Efficient IOU Loss (EIOU) function. Experimental data show that the mean average precision (mAP) of the HOD-YOLOv5 model achieves 83.5%, compared to YOLOv5, which is 4.4% higher than original YOLOv5, and the recognition speed of the HOD-YOLOV5 reaches 106.7 frames per second (FPS). …”
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Mechanical and Civil Engineering Optimization with a Very Simple Hybrid Grey Wolf—JAYA Metaheuristic Optimizer by Chiara Furio, Luciano Lamberti, Catalin I. Pruncu

“…The proposed SHGWJA was tested very successfully in seven “real-world” engineering optimization problems taken from various fields, such as civil engineering, aeronautical engineering, mechanical engineering (included in the CEC 2020 test suite on real-world constrained optimization problems) and robotics; these problems include up to 14 optimization variables and 721 nonlinear constraints. Two representative mathematical optimization problems (i.e., Rosenbrock and Rastrigin functions) including up to 1000 variables were also solved. …”
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Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost by Ji XU, Zicheng XIN, Mo LAN, Wenhui LIN, Bo ZHANG, Qing LIU

“…The MM–BO–XGBoost model demonstrates excellent training efficiency and prediction performance.Conclusion The analysis of the mechanism of the VD furnace refining process and Pearson correlation analysis are conducted, and the input variables for the prediction model of VD furnace endpoint liquid steel temperature are identified. …”
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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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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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Decomposed Linear Dynamical Systems (dLDS) models reveal instantaneous, context-dependent dynamic connectivity in C. elegans by Eva Yezerets, Noga Mudrik, Adam S. Charles

“…Abstract Mounting evidence indicates that neural “tuning” can be highly variable within an individual across time and across individuals. …”
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Order assignment mechanism based on hierarchical decomposition and element matching by ZHANG Xinyue, LYU Weimin, WEI Dingjiang, YANG Dongsheng

“…This integrates and coordinates operational tasks, ensures no resource conflicts, and provides alternatives for responding to battlefield variables. The approach employs a planning network model to illustrate the logical interrelationships among operations. …”
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Exploring the Impact of School-Based Physical and Perceived Environments on Students’ Physical Activity During Recess: A Case Study of Four Schools in Xi’an, China by Qing Wang, Yan Wang, Lan Zhou, Yong Nan

“…The study’s results confirmed previous findings from a social–ecological perspective and provide a comprehensive assessment framework that includes the spatial organization/spatial quality of the school and the perceived variables of safety, comfort, aesthetics, accessibility and functionality. …”
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IrrigApp: An Online Tool for Determining Crop Water Use and Evaluating Irrigation Scheduling Options by José O. Payero

“…., county, crop, soil type, start date, end date, irrigation applications, and irrigation efficiency). IrrigApp calculates daily crop evapotranspiration (ETc) and conducts a daily soil water balance to estimate several daily and seasonal variables, such as ETc under dryland and irrigated conditions, soil water content in the crop root zone, and water losses by runoff and deep percolation. …”
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