Incorporating Neutrosophic Uncertainty in Data Envelopment Analysis by A.Almutairi, Hamiden Abd El- Wahed Khalifa, Basma E. El- Demerdash

“…In the realm of Data Envelopment Analysis (DEA), the assessment of relative efficiency has historically relied on deterministic variables. …”
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Jump around: Selecting Markov Chain Monte Carlo parameters and diagnostics for improved food web model quality and ecosystem representation by Gemma Gerber, Ursula M. Scharler

“…However, little information exists on how each LIM-MCMC algorithm parameter affects the degree of empirical data variability introduced into the ensemble. Further, post hoc algorithm quality diagnostics with commonly used trace plots and the coefficient of variation (CoV) rarely address critical aspects of algorithm quality, such as (1) if the returned ensemble successfully targeted the solution space distribution (stationarity), (2) correlation between ensemble solutions (mixing), and (3) if the ensemble contains enough solutions to adequately capture input data variability (sampling efficiency). …”
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A study on the effect of spatially variation rainfall on urban flooding by Jinping Zhang, Ruyu Wang, Xuechun Li, Zhiwei Li, Yao Wang, Xi Zhang

“…A three-dimensional probabilistic model, incorporating the variation coefficient, total rainfall, and flooding risk, was constructed using the Copula function. …”
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Heart Rate Variability Time-Domain Analysis Across Glaucoma Subtypes by Yuto Yoshida, Hinako Takei, Misaki Ukisu, Keigo Takagi, Masaki Tanito

“…This study aimed to investigate the association between different glaucoma subtypes and the following time-domain heart rate variability (HRV) parameters: the standard deviation of normal-to-normal intervals (SDNN), the square root of the mean of the sum of the squared differences between adjacent normal-to-normal intervals (RMSSD), and the coefficient of variation of R-R intervals (CVRR). …”
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Factors associated with high glucose variability in patients with type 1 diabetes by V. V. Klimontov, Ju. F. Semenova, A. I. Korbut

“…BACKGROUND: High glucose variability (GV) is recognized as a risk factor for vascular diabetic complications and hypoglycemia. …”
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An Improved Adaptive Car-Following Model Based on the Unscented Kalman Filter for Vehicle Platoons’ Speed Control by Caixia Huang, Wu Tang, Jiande Wang, Zhiyong Zhang

“…Traditional models generally assume a fixed maximum speed within the optimal velocity function, which constrains effective platoon speed regulation across road segments with varying speed limits and lacks adaptability to dynamic scenarios such as changes in the platoon leader’s speed or substitution of the lead vehicle. …”
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Research on Small-Target Detection of Flax Pests and Diseases in Natural Environment by Integrating Similarity-Aware Activation Module and Bidirectional Feature Pyramid Network Mod... by Manxi Zhong, Yue Li, Yuhong Gao

“…Additionally, this paper adopts the EIOU loss function to further optimize the model’s bounding box regression, reducing the distortion of bounding boxes caused by high sample variability. …”
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A metaheuristic optimization framework inspired by virus mutations and its ability to optimize the structural design of 2D and 3D steel frames compared to other methods by Mehdi Ghasri, Hamid Reza Karimi, Abdolhamid Salarnia

“…MVPO integrates population-based exploration, simulating viral spread through intra-community interactions (guided by wavelet functions to model transmission variability) and inter-community propagation, with a two-phase mutation strategy: the first phase enhances global exploration via elongated search steps during accelerated spread, while the second phase introduces structural perturbations to escape local optima. …”
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Mathematical modeling describing the performance of open loop multivariable vapor compression chiller model: implications for sustainable HVAC in social housing development by Basim Touqan, Basim Touqan, Muna Salameh

“…IntroductionThis study introduces a simplified multi-variable state-space model of a vapour compression chiller system, focusing on key components such as the condenser and evaporator.MethodsThe model is based on a previously validated state-space framework and has been further developed to generate a transfer function matrix with two inputs (refrigerant and cold carrier flow rates) and two outputs (cooling capacity and outlet temperature). …”
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Effects of stand age and soil microbial communities on soil respiration throughout the growth cycle of poplar plantations in northeastern China by Xiangrong Liu, Xiangrong Liu, Lingyu Hou, Lingyu Hou, Changjun Ding, Changjun Ding, Xiaohua Su, Xiaohua Su, Weixi Zhang, Weixi Zhang, Zhongyi Pang, Yanlin Zhang, Yanlin Zhang, Qiwu Sun, Qiwu Sun

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Forecasting Industrial Electricity Consumption in Iran: A Novel Hybrid Approach for Sustainable Energy Management by Mohsen Rezaei

“…Accurately predicting industrial electricity consumption is essential for optimizing energy efficiency, and reducing costs in industrial operations. …”
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Modified GIC Estimation Using 3‐D Earth Conductivity by Anna Kelbert, Greg M. Lucas

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Stochastic Characteristics and Optimal Control for a Stochastic Chemostat Model with Variable Yield by Rong Yan, Shulin Sun

“…In this paper, a stochastic chemostat model with variable yield and Contois growth function is investigated. …”
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Frequency function and damping function in assessment of dynamic processes in mechanical oscillatory systems with symmetry by A. V. Eliseev

“…The study objective is to develop a method forevaluating properties of the mechanical oscillatory systems with account for viscous friction forces based on frequency functions and damping functions that depend on the so-called coefficient of connection forms, which is the ratio of characteristics of generalized coordinates.Materials and Methods. …”
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A POSSIBILISTIC APPROACH TO CALCULATING THE INTERNAL RATE OF RETURN FOR INVESTMENT PROJECTS WITH FUZZY CASH FLOWS by E. S. Volkova, V. B. Gisin

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Interannual variability in thermal state of the upper mixed layer in the Bering Sea in winter by V. A. Luchin

“…Series of annual mean fields of the mixed layer temperature in December-March were decomposed by applying the empirical orthogonal function (EOF); dynamics of the first two components of decomposition (described in sum 50.4 % of the initial fields variability) are analyzed. …”
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A Novel Method for Inverting Deep-Sea Sound-Speed Profiles Based on Hybrid Data Fusion Combined with Surface Sound Speed by Qiang Yuan, Weiming Xu, Shaohua Jin, Xiaohan Yu, Xiaodong Ma, Tong Sun

“…By constructing a high-resolution regional sound speed field through WOA23 and historical SSP fusion, this method effectively mitigates spatiotemporal heterogeneity and seasonal variability. The artificial lemming algorithm (ALA) is introduced to optimize the inversion of empirical orthogonal function (EOF) coefficients, enhancing global search efficiency while avoiding local optimization. …”
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Influence of Emergent Vegetation Layout on Flow Pattern in a Rectangular Shallow Basin by Junnan LYU, Yuxuan JIANG, Zhidong YAO, Chen YE, Xufeng YAN

“…The hydrodynamics within a shallow basin dictate its efficiency in treatment, water exchange rate, and the ratio of stagnant water areas. …”
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Sparsity‐optimised farrow structure variable fractional delay filter for wideband array by Wenjing Zhou, Mingwei Shen, Min Xu, Guodong Han, Yudong Zhang

“…The established cost function is formulated as a parametric minimisation problem with multiple regularisation constraints, and solved by the modified three‐block alternating direction multiplier method (MTB‐ADMM), which is improved by introducing core variable correction items to ensure stable and fast convergence. …”
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Morpho‐Physiological Traits and Dehydration Tolerance of High‐Altitude Andean Wetland Vegetation in the Chilean Atacama Region by Dariel López, Patricia L. Sáez, Lohengrin A. Cavieres, Fernanda C. Beveridge, Felipe Saavedra‐Mella, León A. Bravo

“…In this study, we characterized the functional trait spectrum of dominant plant species within the Salar de Pedernales, Quebrada Leoncito (Leoncito) and Río Negro HAWAs and explored the relationships between these traits and key environmental variables. …”
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