Analysis of Surface Roughness and Machine Learning-Based Modeling in Dry Turning of Super Duplex Stainless Steel Using Textured Tools by Shailendra Pawanr, Kapil Gupta

“…One of the most critical aspects of turning, and machining in general, is the surface roughness of the finished product, which directly influences the performance, functionality, and longevity of machined components. …”
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A secondary analysis of gait after a 4-week postural intervention for older adults with hyperkyphosis by L. C. Hughes, A. L. Ellis, H. L. Rogers, M. Hadley, R. V. Galloway

“…Pearson correlation coefficients were utilized to investigate correlations between all variables at baseline and in pre- and post intervention change values. …”
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Predicting and Mapping of Soil Organic Matter with Machine Learning in the Black Soil Region of the Southern Northeast Plain of China by Yiyang Li, Gang Yao, Shuangyi Li, Xiuru Dong

“…The estimation of soil organic matter (SOM) content is essential for understanding the chemical, physical, and biological functions of soil. It is also an important attribute reflecting the quality of black soil. …”
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Preference set-based design method for qualitative assessments using dominance-based rough set approach by Shotaro OYAMA, Takeo KATO

“…The preference set-based design (PSD) method enhances design efficiency by providing an adjustment range that reflects the preferences of the designer in the quantitative design variables and performance. …”
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Dynamic Stability of a Circular Pre-Stressed Elastic Orthotropic Plate Subjected to Shock Excitation by Yuriy A. Rossikhin, Marina V. Shitikova

“…Behind the fronts of these waves, the solution is constructed in terms of ray series, which coefficients are the different order discontinuities in partial time-derivatives of the desired functions, and a variable is the time elapsed after the wave arrival at the plate’s point under consideration. …”
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A Gradient Grating Period Guided-Mode Resonance Spectrometer by Hsin-Yun Hsu, Yi-Hsuan Lan, Cheng-Sheng Huang

“…The GMR is specially designed to exhibit gradient grating periods (GPPs) laterally to ensure that the GMR functions as a linear-variable bandstop filter. Each period corresponds to a resonant wavelength such that this wavelength is reflected back at its corresponding resonant period and transmitted to all other periods. …”
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The IoT Technologies Acceptance in Education by the Students From the Economic Studies in Romania by Liliana Ionescu-Feleaga, Bogdan-Ștefan Ionescu, Mariana Bunea

“…The study included 1,179 students from four university centers from Romania and the included factors from the acceptance of IoT technologies model (Internet of Things) were analyzed using the quantitative statistical methods in SPSS, applying a series of tests processed to highlight the research results, respectively the reliability test, the validity test, the chi-square test and the Person's correlation coefficient. The results of the study show the existence of a positive correlation between the research variables and indicate that the students from the economic studies, are ready to accept the new technological advances in IoT and to implement them in their future jobs…”
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The impact of energy poverty on the health capital of middle-aged and older adult residents in rural China by Cuiting Yu, Tianrun Li, Qin Wan

“…Endogeneity was addressed using instrumental variables and propensity score matching.ResultsThe findings indicate that energy poverty has a significant negative impact on health capital, with a regression coefficient of −0.221(p<0.01), lowering self-rated health levels. …”
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ETHNOPEDAGOGICAL COMPONENT OF PHYSICAL TRAINING OF SCHOOLCHILDREN by M. M. Kolokoltsev

“…The inclusion of elements of the Buryat national sports into the program of variable school physical education classes at schools of Baikal region is proved. …”
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Adaptive Exploration Artificial Bee Colony for Mathematical Optimization by Shaymaa Alsamia, Edina Koch, Hazim Albedran, Richard Ray

“…The performance of AEABC was evaluated against 33 state-of-the-art metaheuristics across twenty-five benchmark functions and an engineering application. AEABC consistently outperformed its counterparts, demonstrating superior efficiency and accuracy. …”
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VHR Multispectral Satellite Image Classification with Kolmogorov-Arnold Networks for Urban Applications by M. Fawzy, M. Fawzy, Á. Barsi

“…The Kolmogorov-Arnold Network (KAN) is a computational framework rooted in the Kolmogorov-Arnold representation theorem, which states that any continuous function of multiple variables can be expressed as a superposition of univariate functions. …”
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Explanation of factors affecting the sense of place in religious places of Iran (case examples of historical mosques in Tabriz by Lida Akhlaghi, Asadollah Shafizadeh

“…Spss and Amos software were used for these analyses.The results showed that perceptual and physical factors have the greatest effect in inducing a sense of place in the historical mosques of Tabriz, and social and functional factors have less effect. Among the investigated variables, vitality has the highest correlation coefficient and impact on the sense of place. …”
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Vibration Response and Evaluation Method of High-Speed Tracked Vehicles Driving Off-Road by Xin-yong Qiao, Ying Jin, Cheng Gu

“…Three fitting methods, namely polynomial response surface, Kriging method, and radial basis function neural network, were used to establish approximate models between the design variables and the objective function, respectively. …”
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Adsorption of Cd (II) Using Chemically Modified Rice Husk: Characterization, Equilibrium, and Kinetic Studies by Javier Montalvo-Andía, Warren Reátegui-Romero, Alexis D. Peña-Contreras, Walter F. Zaldivar Alvarez, María E. King-Santos, Víctor Fernández-Guzmán, José Luis Guerrero-Guevara, Jhon E. Puris-Naupay

“…In optimal experimental conditions, the maximum adsorption efficiency was 92.65%. Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM) were used allowing the identification of the main functional groups and morphology of rice husk and treated rice husk, and the results showed an improvement of adsorption characteristics after rice husk treatment with NaOH. …”
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Manufacturing of Rotational Toroidal Shells in Coin Minting by Luís M. Alves, Paulo Alexandrino, Sónia Pereira

“…Through finite element modeling and experimentation, key process variables were identified, ensuring sound hollow toroidal shells with efficient rotation.…”
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Road Permeability Index as a tool for mitigation planning of road impacts on wildlife in Colombia: a case study using mammals by Fabio Leonardo Meza-Joya

“…The influence of 12 landscape variables on the permeability of each functional group was assessed at 30 locations along the road. …”
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An algorithm for independent component analysis using a general class of copula-based dependence criteria by Fatemeh Asadi, Hamzeh Torabi, Hossein Nadeb

“…The efficiency of Independent Component Analysis ($\rm ICA$) algorithms relies heavily on the choice of objective function and optimization algorithms. …”
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Expression variation and covariation impair analog and enable binary signaling control by Kyle M Kovary, Brooks Taylor, Michael L Zhao, Mary N Teruel

“…Such high variation is beneficial for population‐level regulation of cell functions but abolishes accurate single‐cell signal transmission. …”
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Dynamics of Nepalese Stock Market Performance: An Analysis of Macro-economic, Firm-specific, Size, and Event Factors by Rajesh Gurung

“…The ARDL bounds test (F-statistic = 8.378, df = 6, I(0) = 2.88, I(1) = 2.88, α = 1%) indicates the presence of long-run interrelationships among the variables of interest. Additionally, the significant negative coefficient of the error correction term (etc. (-1) = -0.527, p < 0.01) suggests a long-run convergence towards equilibrium. …”
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Physically-based constitutive model and dynamic recrystallization behavior of AISI 4330V mod. Alloy steel under hot working conditions by Jungmin Lee, Sungryul Kim, Byoungkoo Kim, Donghwan Kim

“…To enhance prediction accuracy, key variables such as characteristic stresses, strains, and material constants used in the model were expressed not only as functions of the Zener–Hollomon parameter (Z), but also as functions of forming temperature and strain rate. …”
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