Age-Related Changes in Corneal Deformation Dynamics Utilizing Scheimpflug Imaging. by Marta E Rogowska, D Robert Iskander

“…Raw Scheimpflug images were used to extract changes in anterior and posterior corneal profiles, which were further modelled by an orthogonal series of Chebyshev polynomial functions. Time series of the polynomial coefficients of even order exhibited a dynamic behavior in which three distinct stages were recognized. …”
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How Does Digital Banking-Driven Financial Inclusion Affect Income Inequality in Türkiye? by Ahmet Usta

“…As for the empirical evidence, the study employs the dynamic ordinary least squares method to obtain long-run coefficients, a vector autoregressive model to obtain short-run dynamics through impulse response functions with biascorrected bootstrap confidence intervals that account for the bias and skewness of the small sample, and a causality analysis. …”
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A New Four‐Component L*‐Dependent Model for Radial Diffusion Based on Solar Wind and Magnetospheric Drivers of ULF Waves by Kyle R. Murphy, Jasmine Sandhu, I. Jonathan Rae, Thomas Daggitt, Sarah Glauert, Richard B. Horne, Clare E. J. Watt, Sarah Bentley, Adam Kellerman, Louis Ozeke, Alexa J. Halford, Sheng Tian, Aaron Breneman, Leonid Olifer, Ian R. Mann, Vassilis Angelopoulos, John Wygant

“…We investigate the performance of the new models by characterizing the model residuals as a function of each independent variable and by comparing to existing radial diffusion models during a quiet geomagnetic period and through a geomagnetic storm. …”
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A 3D mixed frame element with multi-axial coupling for thin-walled structures with damage by D. Addessi, P. Di Re

“…The beam formulation is derived on the basis of the Hu-Washizu variational principle, expressed as function of four independent fields: the standard displacements, strains and stresses and the additional warping displacement. …”
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Shell and tube heat exchanger optimization: A critical literature assessment and fairness-based comparative performance analysis of meta-heuristic algorithms by Samet Gürgen

“…In order to make comparisons, the objective function, decision variables and their boundary values were taken as the same. …”
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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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Impacts of early postpartum behavioral patterns on the fertility and milk production of tropical dairy cows by Aqeel Raza, Kumail Abbas, Theerawat Swangchan-Uthai, Henk Hogeveen, Chaidate Inchaisri

“…Reproductive performance was analyzed using Cox proportional hazard models, while lactation dynamics were modeled using the Wood function to estimate peak yield, peak time, and persistency. …”
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Non-Similar Analysis of Boundary Layer Flow and Heat Transfer in Non-Newtonian Hybrid Nanofluid over a Cylinder with Viscous Dissipation Effects by Ahmed Zeeshan, Majeed Ahmad Yousif, Muhammad Imran Khan, Muhammad Amer Latif, Syed Shahzad Ali, Pshtiwan Othman Mohammed

“…Non-similar system of PDEs are obtained with efficient conversion variables. The dimensionless PDEs are truncated using a local non-similarity approach up to third level and numerical solution is evaluated using MATLAB built-in-function bvp4c. …”
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Market orientation and corporate performance of small and medium-sized enterprises in Saudi Arabia by Nabil Mohamed Abdo Alabsy

“…Corporate performance is a dependent variable, whereas business orientation, competitor orientation and inter-functional orientation are used as independent variables. …”
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Decarbonisation pathways for industrial clusters through multi-energy systems by Ugochukwu Ngwaka, Yousaf Khalid, Janie Ling-Chin, John Counsell, Ruben Pinedo-Cuenca, Huda Dawood, Andrew J. Smallbone, Nashwan Dawood, Anthony P. Roskilly

“…Given the complex and nonlinear interconnections among systems within a multi-energy cluster, this study extends the dynamic multi-vector methodology to multi-energy system clusters, representing variables as nodes and converting them into transfer functions for system integration. …”
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Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

“…The results revealed a significant negative correlation between SWHC and the smoothed leaf spectral reflectance, with the best correlation coefficient was r = − 0.59. The use of third-order derivatives and logarithmic second-order derivatives further enhanced this correlation, yielding optimal coefficients of r = − 0.78 and r = − 0.72, respectively. …”
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Explainable AI-driven assessment of hydro climatic interactions shaping river discharge dynamics in a monsoonal basin by Prashant Parasar, Akhouri Pramod Krishna

“…The main findings of this study are (1) KAN demonstrated high predictive performance with root mean squared error (RMSE) values ranging from 42.7 to 58.3 m3/s, Nash–Sutcliffe efficiency (NSE) between 0.80 and 0.87, mean absolute error (MAE) between 28.9 to 52.7 and R2 values between 0.84 and 0.90 across stations. (2) SHAP based feature contribution analysis identified Relative humidity (hurs), specific humidity (huss), and temperature (tas) as key predictors, while (pr) showed limited contribution due to spatial inherent inconsistencies in GCM precipitation data. (3) The bootstrapped SHAP distributions highlighted substantial variability in feature importance, particularly for humidity variables, revealing station specific uncertainty patterns in model interpretation. (4) The KAN framework results indicate strong temporal alignment and physical realism, confirming KAN’s robustness in capturing seasonal discharge dynamics and extreme flow events under monsoon influence environments. (5) In this study KAN with SHAP (SHapley additive exPlanations) is implemented for hydrological modeling under monsoon-influenced and data-limited regions such as SRB, offering improved accuracy, functional precision and efficiency compared to traditional models. …”
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Building electrical consumption patterns forecasting based on a novel hybrid deep learning model by Nasser Shahsavari-Pour, Azim Heydari, Farshid Keynia, Afef Fekih, Aylar Shahsavari-Pour

“…Specifically, the proposed model comprises three key components: (i) a mutual information-based feature selection method to identify the most significant input variables influencing energy consumption; (ii) a variational mode decomposition (VMD) approach to decompose the original energy consumption signal into intrinsic mode functions (IMFs), capturing relevant trends and eliminating noise; and (iii) a long short-term memory (LSTM) neural network to perform time-series forecasting of the target energy consumption values. …”
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Production of Cyanobacterial Microscale Adsorbent by Hydrothermal Method for Pre-concentration of Cadmium from Water by T. Mohammadi Arian, G. Rahimi, R. Khavari Farid

“…The absorbent surface was rich in oxygen and nitrogen functional groups, such as hydroxyl, isothiocyanate, and carbonyl. …”
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The Relationship between the Reorganization of Higher Education Institutions' Operations in Poland During the COVID-19 Pandemic and Student Loyalty by Sojkin Bogdan, Bartkowiak Paweł, Michalak Szymon

“…Using exploratory factor analysis (EFA), the main components were identified for various variables pertaining to the functioning, organization, and delivery of online classes, as well as for aspects associated with university operations during the COVID-19 pandemic. …”
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Why is Multi-Business Forestry Needed to Overcome the Low Performance of Forestry Governance and Food Security in Indonesia? by Suryanto Suryanto, Dodik Ridho Nurrochmat, Suria Darma Tarigan, Iskandar Zulkarnaen Siregar, Ishak Yassir, Mangarah Silalahi, Irdika Mansur, Rhett D. Harisson, Agus Wahyudi, Lutfy Abdulah

“…Results showed that CLD formulated in 280 sub-models in a total of 4,764 decision variables with an error deviation of 6.4%. The SM Mb-F simulation on two sample concession units produces a projected increase in wood supply, employment, and state revenue, plus the provision of new functions such as food, NTFP, and environmental services. …”
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Possibilities of Using Artificial Intelligence in Security Analysis by Maciej Norbert Ciesielski

“…In total, out of twelve features/variables that make up analytical imagination, artificial intelligence already functions efficiently (or will function efficiently soon) in practically all of them.…”
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Optimization of the Screw Conveyor Device Based on a GA-BP Neural Network by Qiang Guo, Yunpeng Zhuang, Houzhuo Xu, Wei Li, Haitao Li, Zhidong Wu

“…In this paper, we analyze the force and velocity components acting on the straw, give the design principles for the screw’s conveying parameters under the premise of ensuring maximum conveying capacity and minimum power consumption, and determine the optimal design variables, objective functions, and constraints according to the specific optimization problem; we establish a specific mathematical model, and introduce algorithm optimization for nonlinear problems with many variables and large amounts of calculations. …”
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Investigating wave solutions in coupled nonlinear Schrödinger equation: insights into bifurcation, chaos, and sensitivity by Adil Jhangeer, Abdallah M. Talafha, Ariana Abdul Rahimzai, Lubomír Říha

“…The transformation of the coupled partial differential equation into ordinary differential equation is achieved by utilizing a complex wave variable. Exponential function combinations are applied to construct the wave solutions. …”
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Structural network topologies are associated with deep brain stimulation outcomes in Meige syndrome by Bin Liu, Zhiqi Mao, Xinyuan Yan, Hang Yang, Junpeng Xu, Zhebin Feng, Yanyang Zhang, Xinguang Yu

“…The results indicated that HIG showed a higher clustering coefficient, longer characteristic path length, lower small-world index, and lower global efficiency compared with LIG. …”
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